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Francesco LOLLI

Professore Associato
Dipartimento di Scienze e Metodi dell'Ingegneria

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2024 - Enhancing Waste-to-Energy and Hydrogen Production through Urban–Industrial Symbiosis: A Multi-Objective Optimisation Model Incorporating a Bayesian Best-Worst Method [Articolo su rivista]
Neri, Alessandro; Butturi, Maria Angela; Lolli, Francesco; Gamberini, Rita

A surging demand for sustainable energy and the urgency to lower greenhouse gas emissions is driving industrial systems towards more eco-friendly and cost-effective models. Biogas from agricultural and municipal organic waste is gaining momentum as a renewable energy source. Concurrently, the European Hydrogen Strategy focuses on green hydrogen for decarbonising the industrial and transportation sectors. This paper presents a multi-objective network design model for urban-industrial symbiosis, incorporating anaerobic digestion, cogeneration, photovoltaic, and hydrogen production technologies. Additionally, a Bayesian best-worst method is used to evaluate the weights of the sustainability aspects by decision-makers, integrating these into the mathematical model. The model optimises industrial plant locations considering economic, environmental, and social parameters, including the net present value, energy consumption, and carbon footprint. The model's functionalities are demonstrated through a real-world case study based in Emilia Romagna, Italy. It is subject to sensitivity analysis to evaluate how changes in the inputs affect the outcomes and highlights feasible trade-offs through the exploration of the ϵ-constraint. The findings demonstrate that the model substantially boosts energy and hydrogen production. It is not only economically viable but also reduces the carbon footprint associated with fossil fuels and landfilling. Additionally, it contributes to job creation. This research has significant implications, with potential future studies intended to focus on system resilience, plant location optimisation, and sustainability assessment.

2024 - Exploring Industry 5.0 for Remanufacturing of Lithium-Ion Batteries in Electric Vehicles [Relazione in Atti di Convegno]
Neri, Alessandro; Butturi, Maria Angela; da Silva, Leandro Tomasin; Lolli, Francesco; Gamberini, Rita; Sellitto, Miguel Afonso

The growing demand for electric vehicles exacerbates concerns over the environmental implications of lithium-ion battery waste, which poses risks to both ecological systems and public health. While remanufacturing has been acknowledged as a viable, sustainable pathway for mitigating these issues, existing literature lacks a comprehensive investigation into the role of Industry 5.0 technologies in optimising this process. To achieve this goal, this study compares and evaluates the potential of different Industry 5.0 technologies and approaches to support the remanufacturing process of lithium-ion batteries. Specifically, we apply the AHP-PROMETHEE method to identify the most critical and influential Industry 5.0 prospects that should be prioritised for development and implementation. The novelty of our approach lies in the identification of critical Industry 5.0 imperatives that can enable efficient and effective remanufacturing processes. The analysis is supported by a comprehensive review of the relevant literature. The results of our study provide important implications for policymakers, battery manufacturers, and remanufacturing companies. By prioritising key Industry 5.0 technologies like digital twins, the Internet of Everything, and blockchain, this study shows that carmakers can significantly improve efficiency and sustainability in battery remanufacturing. This paper contributes to the emerging research on the integration of Industry 5.0 technologies in the remanufacturing process of lithium-ion batteries. Our next step is to explore the potential of the identified technologies in real-life applications and to evaluate their impact on the sustainability and efficiency of the remanufacturing process of lithium-ion batteries.

2024 - Set up a supply chain observatory through the comparison of multi-criteria parsimonious methods [Articolo su rivista]
Butturi, M. A.; Lolli, F.; Gamberini, R.

2023 - A PERT model based on the Dampster and Shafer's theory of evidence – application to product development [Articolo su rivista]
Lolli, Francesco; Coruzzolo, Antonio Maria; Zironi, Matteo

2023 - Empowering rural districts with Urban-Industrial Symbiosis: A multiobjective model for Waste-to-Energy cogeneration and hydrogen sustainable networks [Relazione in Atti di Convegno]
Neri, A.; Butturi, M. A.; Lolli, F.; Gamberini, R.

The growing demand for sustainable energy sources and the need to mitigate greenhouse gas emissions have led to increased interest in developing efficient, cost-effective, and environmentally friendly industrial systems. This paper presents a multi-echelon multi-objective network design model for urban-industrial symbiosis, combining biogas and hydrogen production plants with locally sourced organic waste as feedstock. The integrated biogas-hydrogen system utilizes locally sourced agricultural and organic waste as feedstock, enhancing rural processes sustainability and resource efficiency. The model optimizes the location of industrial plants based on environmental and economic parameters, including transportation emissions, energy consumption, and carbon footprint. A case study set in Emilia Romagna validates the model, and a sensitivity analysis examines the impact of varying input parameters on the designed industrial park. Results demonstrate that the novel combined biogas-hydrogen system not only reduces greenhouse gas emissions but also produces hydrogen at a lower cost due to the utilization of excess power from the biogas cogeneration plant. This research has significant implications, offering a sustainable and cost-effective hydrogen source while promoting efficient supply chain management and strategic decision-making in the renewable energy sector. Further study might investigate system robustness against disruptive events, plant design, and the integration of additional renewable sources.

2023 - Ergonomic Risk Reduction: A Height-Adjustable Mesh Truck for Picking Activities Evaluated With A Depth Camera [Abstract in Atti di Convegno]
Lolli, Francesco; Maria Coruzzolo, Antonio; Forgione, Chiara; Gonçalves Terra Neto, Platao

2023 - Exposure to Air Pollution in Transport Microenvironments [Articolo su rivista]
Marinello, S.; Lolli, F.; Coruzzolo, A. M.; Gamberini, R.

People spend approximately 90% of their day in confined spaces (at home, work, school or in transit). During these periods, exposure to high concentrations of atmospheric pollutants can pose serious health risks, particularly to the respiratory system. The objective of this paper is to define a framework of the existing literature on the assessment of air quality in various transport microenvironments. A total of 297 papers, published from 2002 to 2021, were analyzed with respect to the type of transport microenvironments, the pollutants monitored, the concentrations measured and the sampling methods adopted. The analysis emphasizes the increasing interest in this topic, particularly regarding the evaluation of exposure in moving cars and buses. It specifically focuses on the exposure of occupants to atmospheric particulate matter (PM) and total volatile organic compounds (TVOCs). Concentrations of these pollutants can reach several hundreds of µg/m3 in some cases, significantly exceeding the recommended levels. The findings presented in this paper serve as a valuable resource for urban planners and decision-makers in formulating effective urban policies.

2023 - Inter-firm exchanges, distributed renewable energy generation, and battery energy storage system integration via microgrids for energy symbiosis [Articolo su rivista]
Neri, Alessandro; Butturi, Maria Angela; Lolli, Francesco; Gamberini, Rita

2023 - Optimization of the logistic “fill rate” key performance indicator through the application of the DMAIC approach [Relazione in Atti di Convegno]
Marinello, Samuele; Zhao, Qian; Coruzzolo, ANTONIO MARIA; Balugani, Elia; Gamberini, Rita; Lolli, Francesco

Measuring and monitoring the performances of supply chains over time is a primary interest factor for companies. In this way, it is possible to determine the effectiveness and efficiency of strategies for being competitive in global markets, verify the achievement of the predetermined targets, and establish intervention and improvement measures. In this context, key performance indicators (KPIs) are widely used to measure the numerous activities performed across a supply chain. Numerous KPIs are available in the literature, and they are often customized by each user to make them more suitable for their reference context. This paper analyzes the logistic “fill rate” KPI that characterizes the shipping phase of goods by evaluating the fill rate of the transport unit used. A case study analyzes the fill rate indicator used by a multinational corporation that produces and markets food packaging. Through the DMAIC (Define, Measure, Analyze, Improve, and Control) approach, the criticalities of the current formulation of the index are highlighted, and a new model for calculating the index is proposed and applied experimentally at a plant in northern Italy.

2023 - Order Picking Problem: A Model for the Joint Optimisation of Order Batching, Batch Assignment Sequencing, and Picking Routing [Articolo su rivista]
Coruzzolo, A. M.; Lolli, F.; Balugani, E.; Magnani, E.; Sellitto, M. A.

Background: Order picking is a critical activity in end-product warehouses, particularly using the picker-to-part system, entail substantial manual labor, representing approximately 60% of warehouse work. Methods: This study develops a new linear model to perform batching, which allows for defining, assigning, and sequencing batches and determining the best routing strategy. Its goal is to minimise the completion time and the weighted sum of tardiness and earliness of orders. We developed a second linear model without the constraints related to the picking routing to reduce complexity. This model searches for the best routing using the closest neighbour approach. As both models were too complex to test, the earliest due date constructive heuristic algorithm was developed. To improve the solution, we implemented various algorithms, from multi-start with random ordering to more complex like iterated local search. Results: The proposed models were tested on a real case study where the picking time was reduced by 57% compared to single-order strategy. Conclusions: The results showed that the iterated local search multiple perturbation algorithms could successfully identify the minimum solution and significantly improve the solution initially obtained with the heuristic earliest due date algorithm.

2023 - Waste Plastic and Rubber in Concrete and Cement Mortar: A Tertiary Literature Review [Articolo su rivista]
Marinelli, S.; Marinello, S.; Lolli, F.; Gamberini, R.; Coruzzolo, A. M.

In recent years, the addition of plastic and rubber waste to construction materials has been widely studied by the research community. This great interest can mainly be attributed to the achievable potential environmental and economic benefits, mainly deriving from the reduction of incinerated or landfilled wastes and the decrease of used raw materials. Several reviews have been published on the addition of polymeric waste materials in concrete and cement mortar mixtures, discussing properties, environmental and cost implications. However, there are not available studies that organize and analyses the knowledge presented in this review. For the scope, in this paper we present a tertiary study of previous relevant review articles from peer-reviewed journals, with the aim to provide an overview of the state of the evidence related to this topic and to highlight the main critical aspects and open issues. The overview provides conclusions drawn from the 33 included reviews finding different open issues on the theme regarding environmental performance, cost savings and impacts on the supply chain as well as long term health problem related to the use of waste plastic and rubber in concrete and cement mortar. For each open issue further research proposals are also suggested.

2022 - A Bibliographic Analysis of Indoor Air Quality (IAQ) in Industrial Environments [Articolo su rivista]
Lolli, F.; Coruzzolo, A. M.; Marinello, S.; Traini, A.; Gamberini, R.

2022 - A Decision Support System for the Selection of Insulating Material in Energy Retrofit of Industrial Buildings: A New Robust Ordinal Regression Approach [Articolo su rivista]
Lolli, F.; Balugani, E.; Butturi, M. A.; Coruzzolo, A. M.; Ishizaka, A.; Marinelli, S.; Romano, V.

The criteria for selecting insulating materials in the energy retrofitting of industrial buildings can often be conflicting, leading to a multicriteria decision-making problem. This is the first study to take an indirect elicitation approach to solving this selection problem, which is particularly applicable in the preliminary phases of negotiation with all of the decision-makers involved. We introduce a nonlinear indirect elicitation approach for PROMETHEE II that uses Bézier curves as nonlinear preference curves to fit the decision-maker's preferences, i.e., indifference and/or strict preferences for insulating materials that are taken as references. In our approach, no parameters need to be initially set, and thus, it has the advantage of setting both the preference curves on the criteria and the criteria weights when the decision-maker is not confident. The set of Bézier curves and criteria weights that best fits the preferences given by the decision-maker may thus be achieved and visualized, which provides managerial insights as it makes explicit the preference structure of the decision-maker. We use a case study to validate our proposal in a real setting and confirm that linear preference curves would have achieved less clear relations between the insulating materials used as references respect to Bèzier curves.

2022 - A framework to assess the sustainability of additive manufacturing for spare parts [Relazione in Atti di Convegno]
Butturi, MARIA ANGELA; Marinelli, Simona; Lolli, Francesco

Additive manufacturing (AM) is a promising technology for the optimization of the spare parts supply chain. A complete evaluation of whether it is advantageous to switch to this technology for spare parts management should include a comprehensive assessment of its sustainability in addition to its techno-economic viability. General analyses of the economic, environmental, and social impacts of AM have been conducted, but assessments of the sustainability effects of AM in the spare parts field is limited to specific industries. Thus, based on the literature, we designed a framework that can support a life cycle evaluation of the emerging application of AM technology. It represents a methodological approach that covers all the stages of the spare parts life cycle and the three dimensions of sustainability. It has been designed to support both researchers and practitioners who are considering AM for the manufacturing of spare parts. Copyright (C) 2022 The Authors.

2022 - Additive or Conventional Manufacturing for Spare Parts: Effect of Failure Rate Uncertainty on the Sourcing Option Decision [Relazione in Atti di Convegno]
Peron, M.; Basten, R.; Knofius, N.; Lolli, F.; Sgarbossa, F.

2022 - Age-based preventive maintenance with multiple printing options [Articolo su rivista]
Lolli, F.; Coruzzolo, A. M.; Peron, M.; Sgarbossa, F.

In today's economic context, production systems must be readily available and machinery downtime kept to a minimum. Maintenance and spare parts inventory management play a vital role in achieving these goals, and preventive maintenance has increasingly been considered in maintenance policies. Additive manufacturing (AM) has recently been combined with preventive maintenance, and thus represents an emerging research direction. However, few studies have as yet been conducted in this research stream, and we intend to fill this gap. Our study makes three main contributions. First, we address the main limitations of two current models (i.e., assuming that no failure occurs during the replenishment lead time of the spare parts). Second, we propose a new maintenance policy that considers two printing options with different levels of reliability and unitary purchase costs. Third, we develop a decision support system (DSS) to assist managers in deciding whether to implement a preventive maintenance policy that includes AM or conventional manufacturing (CM) parts. We take an interdisciplinary approach to conducting a parametrical analysis where we consider real data on the reliability of CM and AM parts, in addition to the impact of post-processing operations and optimization routines. We find that AM-based preventive maintenance policies are favored when the MTTF and the backorder costs are low and when the failure and maintenance costs are high. These findings have been incorporated into the DSS, which provides thresholds for every parameter to guide practitioners in choosing between AM and CM parts for preventive maintenance, without requiring time-expensive calculations.

2022 - How the type of customer can influence the product attributes: Application of house of quality with multi-user information to improve the functions of a waste collection and treatment service management software [Relazione in Atti di Convegno]
Coruzzolo, A. M.; Marinello, S.; Lolli, F.; Gamberini, R.

2022 - Influence of dependence on social capital and operational performance: a study of the textile and clothing industry [Articolo su rivista]
Celestini, J.; Goecks, L. S.; Lolli, F.; Sellitto, M. A.

Purpose: The purpose of this study is to investigate empirically whether the presence of dependence influences the strength and direction of the relationship between social capital and operational performance. Design/methodology/approach: The authors tested two effects, moderator and mediator, of the dependence between social capital and operational performance in the buyer–supplier relationship in the supply chain. The authors use dependence as a dichotomous variable and empirically test the hypotheses using hierarchical linear regression from data collected from 117 industrial companies in Brazil. Findings: The results show that although dependence does not have a mediating effect on social capital shares in operational performance, it moderates the strength of trust actions in relation to cost, delivery, flexibility and innovativeness of the buyer. Practical implications: As for the practical implications, in a buyer–supplier relationship, managers may not be fully capable of decreasing dependence and thus increasing the effect of trust actions on operational performance. Originality/value: For management practices in the textile and clothing industry, social capital actions contribute to strategic objectives, increasing collaboration between supply chain partners, and for operations, offering more options in managing social ties.

2022 - On demand printing with Additive Manufacturing (AM) for spare parts: scenarios for the insourcing of a 3D Printer [Relazione in Atti di Convegno]
Coruzzolo, A. M.; Lolli, F.; Balugani, E.; Rimini, B.

Additive Manufacturing (AM) has become a promising technique for spare parts management. The reduced lead time of AM compared to Classical Manufacturing (CM) has attracted the interest of researchers and many applications of AM to spare parts management have been introduced in the literature. However, the high production and equipment costs obscure the advantages of AM to spare parts management to practitioners and academics. The recent literature on spare parts management with AM have two main limitations which we address in this work. The first is that AM spare parts are mistakenly assumed to be less reliable than CM ones, which has been refuted by the recent literature on the mechanical characteristics of AM parts. Secondly, the external supply of AM parts that excludes the investment cost of the equipment. Our model overcomes these limitations by taking into account a spare part installed on a fleet of systems which failures are based on failure data from recent literature. In addition, we consider an insourced 3D printer, and account for the purchasing cost. We propose several scenarios for the insourcing of a 3D printing, considering a future cost reduction and constrained stock systems, individuating constrained stock system with high lead times for the CM part, ideal for in-house printing. The work has been supported by the project SUPERCRAFT, funded by the Emilia-Romagna Region (Italy) with European funds (POR FESR).

2022 - On the suitability of insourced Additive Manufacturing for spare parts management [Relazione in Atti di Convegno]
Lolli, F; Coruzzolo, Am; Peron, M; Sgarbossa, F

Additive Manufacturing (AM) has recently emerged as a promising technique in spare parts manufacturing. Unlike conventional manufacturing (CM) techniques, AM can lead to a reduction in inventory levels, particularly when insourced, through manufacturing spare parts on demand. However, due to the high production costs, the economic benefits of manufacturing spare parts through AM are unclear to managers and practitioners. Recent studies aimed at assisting in this decision have two main limitations: (i) they assume that AM spare parts typically have higher failure rates than CM parts: and (ii) they do not consider the AM machinery investment costs and parts are assumed to be externally supplied. We have developed a model that overcomes these limitations, first by assessing the failure rates of AM spare parts through an interdisciplinary approach rather than making arbitrary assumptions, which enables a comparison with the failure rates through CM reported in the literature. Second, we considered that the manufacturing of AM spare parts can be insourced and thus the investment costs for AM printers are also included, while the manufacturing of CM spare parts is considered to be outsourced. The model was tested with unconstrained and constrained stock systems, and clearly demonstrates the advantages of an insourced 3D printer for on-demand printing under constrained stock systems. Neither is AM preferable under an unconstrained system, due to the high costs of purchasing the printer and of production. Copyright (C) 2022 The Authors.

2022 - Order Picking Systems: A Queue Model for Dimensioning the Storage Capacity, the Crew of Pickers, and the AGV Fleet [Articolo su rivista]
Lolli, F.; Lodi, F.; Giberti, C.; Coruzzolo, A. M.; Marinello, S.

Designing an order picking system can be very complex, as several interrelated control variables are involved. We address the sizing of the storage capacity of the picking bay, the crew of pickers, and the AGV fleet, which are the most important variables from a tactical viewpoint in a parts-to-pickers system. Although order picking is a widely explored topic in the literature, no analytical model that can simultaneously deal with these variables is currently available. To bridge this gap, we introduce a queue model for Markovian processes, which enables us to jointly optimise the aforementioned control variables. A discrete-event simulation is then used to validate our model, and we then test our proposal with real data under different operative scenarios, with the aim of assessing the usefulness of the proposal in real settings.

2022 - Performance Assessment of an Eco-Industrial Park: a Strategic Tool to Help Recovering Energy and Industrial Waste [Articolo su rivista]
Maurer Koch, Cristiane; Tomasin, Leandro; Lolli, Francesco; Butturi, MARIA ANGELA; Afonso Sellitto, Miguel

The purpose of this study is to propose and test a tree-like structure for assessing the operational performance of an eco-industrial park composed of a managerial, focal company, and five manufacturing companies that exchange, generate, or reuse energy, waste, and by-products from different sources. The top term is the EIP operational overall performance, supported by indicators retrieved from the literature and organized in four constructs: (i) internal relationships; (ii) external relations; (iii) energy recovery; and (iv) materials recovery. The first construct encompasses relationships between companies, leadership, mutual trust and technological exchange, communication, and integrated information systems. The second encompasses relations with government, stakeholder communication, compliance, and social responsibility. The third encompasses the reuse of biomass, refuse-derived fuels, heat, fluids (water, gases, steam), and the energy efficiency of facilities. The last encompasses reuse of waste, reuse of byproducts, efficiency in the logistical process, and efficiency in the manufacturing process. The structure embraces the three main pillars of sustainability, since the first and second constructs include social issues, whereas the third and fourth include economic and environmental ones. The research method is qualitative modeling. Managers employed a Likert scale of agreement [0 = strongly disagree ... 1 = strongly agree] to evaluate the importance and performance of indicators. The importance depends on the influence on the construct and the influence that the construct exerts on the top term. The performance depends on the contribution of the indicator to the overall operational result of the EIP. Results show that there is no need to reallocate or replace strategic resources among the constructs, but also show that the overall performance is only 59 % of the maximum possible. Two constructs, internal relationships, and energy recovery require control actions and further managerial improvement.

2022 - Post-Occupancy Evaluation’s (POE) Applications for Improving Indoor Environment Quality (IEQ) [Articolo su rivista]
Lolli, F.; Marinello, S.; Coruzzolo, A. M.; Butturi, M. A.

To improve buildings and their characteristics, the feedback provided directly by users is generally fundamental in order to be able to adapt the technical and structural functions to the well-being of users. The post-occupancy evaluation (POE) fits perfectly into this context. The POE, through qualitative and quantitative information on the interior environment, makes it possible to identify the differences between the performances modeled in the design phase and the real performances experienced by the occupants. This review of 234 articles, published between 2006 and 2022, aims to analyze and compare the recent literature on the application of the POE methodology. The aim was to provide both a qualitative and quantitative assessment of the main factors that comprise the indoor environmental quality (IEQ). The study highlighted the factors that comprise the quality of the indoor environment, as well as the variables that are usually analyzed to describe the well-being of the occupants. The results suggested which are the most common approaches in carrying out POE studies and will identify the factors that most influence the determination of the good quality of an indoor environment.

2022 - The Indoor Environmental Quality: A TOPSIS-based approach with indirect elicitation of criteria weights [Articolo su rivista]
Lolli, F.; Maria Coruzzolo, A.; Balugani, E.

The Indoor Environmental Quality (IEQ) assessment is a hot topic both for designers of industrial buildings and for academics since it has been proven to affect workers’ productivity. Despite the advantages of indirect eliciting approaches, only direct eliciting is used in the literature to assign weights to the main risks included in the IEQ assessment, i.e., those referring to the thermal comfort, visual comfort, acoustic comfort and indoor air quality. In order to bridge this gap and in line with the drivers of the human-centric industrial revolution, we have developed an indirect eliciting approach based on logistic regression and integer optimization that indirectly derives the aforementioned weights per worker (i.e., individual weighting) on the basis of the overall comfort perceived by him/her in different reference scenarios. These weights are then used to compute a TOPSIS-based risk measure that maps the aggregated, individual and dynamic risks to which the worker is subjected over time. A real case study is used to validate our proposal. The achieved results highlight the superiority of our indirect eliciting approach compared to the Analytical Hierarchic Process in reconstructing the overall comfort perceived by workers, as well as that age plays a crucial role to assign weights to the main risks included in the IEQ.

2021 - An open innovation B2B web platform design: Application of the QFD approach for the definition of its primary functions [Articolo su rivista]
Marinello, S.; Lolli, F.; Gamberini, R.

Global markets and the concept of innovation require modern companies to quickly adapt to two very relevant paradigms: digital innovation and open innovation. Therefore, the use of digital technologies and the development of open collaboration networks have radically changed the nature of the organisation of innovation and of the managerial approach and strategic choices. The objective of this paper is to describe the approach adopted to define the main functionalities of a digital Business to Business (B2B) platform for the development of new commercial collaborations between Small and Medium-sized Enterprises (SMEs). The approach of Quality Function Deployment and its House of Quality tool have been applied to support the combination of customer and technical needs. The prioritisation of the technical characteristics of the platform has identified in the ‘system for managing orders’ and ‘systems to speed up processes’ the main functions to be developed with greater attention within the platform.

2021 - Conventional or additive manufacturing for spare parts management: An extensive comparison for Poisson demand [Articolo su rivista]
Sgarbossa, Fabio; Peron, Mirco; Lolli, Francesco; Balugani, Elia

Due to the main peculiarities of spare parts, i.e. intermittent demands, long procurement lead times and high downtime costs when the parts are not available on time, it is often difficult to find the optimal inventory level. Recently, Additive Manufacturing (AM) has emerged as a promising technique to improve spare parts inventory management thanks to a ‘print on demand’ approach. So far, however, the impact of AM on spare parts inventory management has been little considered, and it is not yet clear when the use of AM for spare parts inventory management would provide benefits over Conventional Manufacturing (CM) techniques. With this paper we thus aim to contribute to the field of AM spare parts inventory management by developing decision trees that can be of support to managers and practitioners. To this aim, we considered a Poisson-based inventory management system and we carried out a parametrical analysis considering different part sizes and complexity, backorder costs and part consumption. Moreover, we evaluated scenarios where the order-up-to level is limited to resemble applications with a limited storage capacity. For the first time, the analysis was not limited to just one AM and one CM technique, but several AM and CM techniques were considered, also combined with different post-process treatments, for a total of nine different sourcing alternatives. In addition, the economic and technical performance of the different sourcing options were obtained thanks to an interdisciplinary approach, where experts from production economics and material science were brought together.

2021 - Dimensionality reduced robust ordinal regression applied to life cycle assessment [Articolo su rivista]
Balugani, E.; Lolli, F.; Pini, M.; Ferrari, A. M.; Neri, P.; Gamberini, R.; Rimini, B.

Life Cycle Assessment quantifies the multi-dimensional impact of goods and services and can be handled by Multi-Criteria Decision Analysis. In Multi-Criteria Decision Analysis, Robust Ordinal Regression manages all the compatible preference functions at once when assessing a set of alternatives and a group of preferences on reference alternatives. Robust Ordinal Regression is thus a versatile method of reducing the cognitive effort required by decision makers for eliciting their preference structures in Life Cycle Assessment, although it does not directly operate on noisy alternatives and requires Stochastic Multicriteria Acceptability Analysis to deal with such scenarios. We propose integrating a dimensionality reduction technique, Principal Component Analysis, and Robust Ordinal Regression methods, to reduce the problem dimensionality and ensure the actual problem features are considered. A generated dataset, a dataset from literature and a Life Cycle Assessment case study are used to test the effectiveness of the proposed methods.

Coruzzolo, A. M.; Lolli, F.; Gennari, F.; Marinello, S.; Gamberini, R.

An increasing freight demand is putting pressure on the freight transport network, forced to pay high costs to ensure compliance with the conditions and delivery times, as well as to grow towards environmental sustainability. The purpose of this paper is to analyse the main drivers for choosing the type of transport in the planning of distribution logistics through the application of the Multinomial Logit Model (MLN) under the objective of CO2 emission minimisation in order to identify the most sustainable transport solution as a function of distance along the same lines as Hoover’s diagrams. The approach has been applied to a real case study (the logistics department of an Italian manufacturing company) in order to define the mode of transport that minimises the quantity of carbon dioxide emitted and therefore to analyse the effect that this modal shift strategy has on the other selection drivers. The results were encouraging in guiding the application of a modal shift strategy and the change to more sustainable transport modes: 62.5% of the company’s transport shipments should be transferred from road to a different mode, with an overall reduction of 41% of CO2 emissions, without any impact on costs and delivery time.

2021 - Resizing the Workforce for Picking Activity: Application in the Fashion Sector [Relazione in Atti di Convegno]
Coruzzolo, A. M.; Lolli, F.; Montanari, V.; Ciampi, T.

Order picking is one of the most critical activities in warehouses as being the most labor intensive with costs that can be up to 55% of total warehouse expenses. In this context the right sizing of picking workforce is decisive and has to guarantee a satisfactory service level. In this paper, workforce resizing for warehouse picking activities, was investigated in the light of the growth of receptivity required by one of the commissioning firms. Given the high labour intensity in the picking activities, the first phase of our analytical framework for the workforce resizing incl udes a statistical validation of the law of diminishing returns, which can be viewed as an effect of the free-rider behaviour, and then (i.e., second phase) a fitting approach of the said law; the curve that best fits the historical data is used in the third phase to forecast the future productivity. The last phase is made of an analytical procedure to derive the average future required number of ordinary and overtime pickers. We applied our framework in a real warehouse for a firm in the fashion sector, results highlighted a necessity for workforce increase, compared to the “as-is” scenario; this will allow the firm to strategically identify future workforce size requirements, from a cost-based perspective.

2021 - The Dynamic, Individual and Integrated Risk Assessment: A Multi-criteria Approach Using Big Data [Relazione in Atti di Convegno]
Lolli, Francesco; Coruzzolo, ANTONIO MARIA; D'Alessandro, Giulia; Balugani, Elia; Butturi, MARIA ANGELA; Marinello, Samuele; Marinelli, Simona

Occupational Health and Safety Risk Assessment can undoubtedly benefit from enabling technologies of Industry 4.0, with the aim of collecting and analyzing the big data related to the occupational risk factors arising into workplaces. In this paper, the assessment of the occupational risk is addressed by means of a multi-criteria approach. Indeed, after the pre-treatment of the time series of the said risk factors by means of a segmentation algorithm, a TOPSIS approach is implemented to assess the dynamic, individual and integrated risk to which a worker is subjected over the time. Finally, a numerical example is reported to illustrate the proposed in practice.

2021 - The Impact of the COVID-19 Emergency on Local Vehicular Traffic and Its Consequences for the Environment: The Case of the City of Reggio Emilia (Italy) [Articolo su rivista]
Marinello, Samuele; Lolli, Francesco; Gamberini, Rita

first_pagesettings Open AccessArticle The Impact of the COVID-19 Emergency on Local Vehicular Traffic and Its Consequences for the Environment: The Case of the City of Reggio Emilia (Italy) by Samuele Marinello 1,*OrcID,Francesco Lolli 1,2 andRita Gamberini 1,2OrcID 1 En&Tech Interdepartmental Center, University of Modena and Reggio Emilia, 42124 Reggio Emilia, Italy 2 Department of Sciences and Methods for Engineering, University of Modena and Reggio Emilia, 42122 Reggio Emilia, Italy * Author to whom correspondence should be addressed. Sustainability 2021, 13(1), 118; Received: 3 December 2020 / Revised: 21 December 2020 / Accepted: 22 December 2020 / Published: 24 December 2020 (This article belongs to the Special Issue 8th World Sustainability Forum—Selected Papers) Download PDF Browse Figures Abstract The COVID-19 health emergency has imposed the need to limit and/or stop non-essential economic and commercial activities and movement of people. The objective of this work is to report an assessment of the change in vehicle flows and in air quality of a specific study area in the north of Italy, comparing the periods February–May 2020 and February–May 2019. Circulating vehicles have been measured at nine characteristic points of the local road network of the city of Reggio Emilia (Italy), while atmospheric pollutant concentrations have been analysed using data extracted from the regional air quality monitoring network. The results highlight a rapid decline in the number of vehicles circulating in 2020 (with values of up to −82%). This has contributed to a reduction in air concentrations of pollutants, in particular for NO2 and CO (over 30% and over 22%, respectively). On the other hand, O3 has increased (by about +13%), but this is expected. Finally, the particulate matter grew (about 30%), with a behaviour similar to the whole regional territory. The empirical findings of this study provide some indications and useful information to assist in understanding the effects of traffic blocking in urban areas on air quality.

2021 - Waste Management and Covid-19: What does the Scientific Literature Suggest? [Relazione in Atti di Convegno]
Marinello, Samuele; Lolli, Francesco; Gamberini, Rita

The studies conducted on the effects of the health emergency due to COVID-19 have shown heavy consequences on human activities (industrial production, economic activities, tourism), but also interesting improvements for the quality of different environmental matrices (water, air, soil). The waste management sector, which represents an essential public utility service, has suffered very negative consequences. In fact, the global change in the behavior and habits of citizens and the variations in industrial, production and economic processes in general have altered the consolidated dynamics that governed the production and treatment of waste, putting them in crisis. This review intends to provide a structured and critical evaluation of the recent scientific literature about the study of the effect of health emergency on the waste management sector. The results reported showed a general common trend towards a significant increase in the production of hazardous medical waste and packaging plastics, while the increasing or decreasing trend in household waste does not appear uniform. Industrial waste and those associated with public areas and events are decreasing. The recovery and recycling sector suffered a sharp slowdown. In the face of various gaps and criticalities highlighted by the analyzed authors, various possible solutions to improve waste management during emergency situations such as that of COVID-19 have been identified and reported in this review work.

2020 - A model for renewable energy symbiosis networks in eco-industrial parks [Relazione in Atti di Convegno]
Butturi, Maria Angela; Sellitto, Miguel A:; Lolli, Francesco; Balugani, Elia; Neri, Alessandro

Renewable energy technologies integration within industrial districts can boost carbon emissions reduction in the industry sector. The eco-industrial parks model promotes the sustainable use of energy and the application of energy synergies and energy exchanges that can include renewable sources of energy. This paper presents an optimization methodology based on a multi-stakeholder perspective to evaluate energy symbiosis including the integration of renewable energy sources within the parks. The study results in three scenarios providing to managers of single firms and parks relevant information for supporting decision making regarding the economic sustainability and the environmental impacts of the energy synergies. The results show that the optimization of the collective point of view ensures more efficient management of the energy supplied by renewables as well as by firms that can provide an energy surplus.

2020 - A second life for cigarette butts? A review of recycling solutions [Articolo su rivista]
Marinello, S.; Lolli, F.; Gamberini, R.; Rimini, B.

Trillions of cigarettes are smoked annually making cigarette butts one of the most common types of litter in the world. Due to the materials and toxic substances that they contain, this waste carries a very harmful risk for the environment and for living organisms (including humans). Only a few - barely sustainable - solutions have tried to tackle this waste and alternative solutions to landfilling and incineration are needed. Identifying the best methodological solutions and technologies for recycling this kind of waste in terms of results and applicability to real contexts would reduce the presence of dangerous materials in the environment and ecosystems and would promote the recovery of materials in line with the circular economy and sustainable development. The objective of this review was to collect and analyze the alternative solutions available in the literature for the recovery and recycling of the materials in cigarette butts, considering them as possible sources of secondary raw materials applicable to contexts of common interest. Several papers were selected and the results obtained by the authors are presented in terms of type of treatment process (physical, chemical or both), product derived (in solid, liquid or gaseous form) and its possible use in different sectors (e.g. construction, electronics, energy, chemistry and environmental protection). The main results, together with the advantages and disadvantages are highlighted and proposals for further research are outlined.

2020 - Application of the quality function deployment approach to the optimization of an enterprise resource planning software [Relazione in Atti di Convegno]
Marinello, S.; Berte, S.; Lolli, F.; Butturi, M. A.

Enterprise Resource Planning (ERP) software are essential tools for those business activities that want to be competitive on the market: their use allows to manage all the economic and organizational aspects of a company, optimizing the use of resources. For this reason, the structure and functions of this software must be able to manage countless heterogeneous business aspects and, often, characteristic for each individual company. Therefore, during the design and the development phases it is necessary to analyze and understand the interests and needs of the end users, combining them with technical and market aspects. An approach capable of combining these aspects is the House of Quality (HoQ), a tool of Quality Function Deployment. It, applicable to new products or to the optimization of existing ones, allows to effectively identify and order the technical specifications and functions of the software (HOWs) by evaluating the most important requests of user customers (WHATs). This study describes the application of HoQ to the optimization of an ERP software, identifying the main critical elements in the existing configuration and co-designing a new version through the direct involvement of users, evaluating the importance of their needs.

2020 - Balancing of Manual Reconfigurable Assembly Systems with Learning and Forgetting Effects. [Relazione in Atti di Convegno]
Butturi, Maria Angela; Lolli, Francesco; Menini, Chiara

2020 - Data on the environmental performance analysis of a dual-source heat pump system [Articolo su rivista]
Marinelli, S.; Butturi, M. A.; Lolli, F.; Rimini, B.; Gamberini, R.

This data article reports supplementary input and output data related to the research article “Environmental performance analysis of a dual-source heat pump system” on the life cycle assessment evaluation of an heat pump prototype, able to use alternatively the air and the ground as external heat sources. Primarily, the present article shows the life cycle inventory input data of the system under study and of the conventional air and ground heat pump systems, which were used for comparison. Secondly, complete numerical results are exposed, which are showed only graphically and in an aggregated form in the main article. Data include normalised and unaggregated environmental impacts of each investigated life cycle phase. The article also reports the complete results of the sensitivity analysis conducted using different assumptions on the energy mix and on the energy use.

2020 - Environmental benefits of the industrial energy symbiosis approach integrating renewable energy sources [Relazione in Atti di Convegno]
Marinelli, S; Butturi, M. A.; Balugani, E.; Lolli, F.; Rimini, B.

Industry sector accounts for almost 40% of final energy demand and is responsible for one-fifth of global energy-related CO₂ emissions. A viable pathway to reduce the carbon footprint of the industry sector is represented by the industrial energy symbiosis, that promotes inter-firm energy exchanges and the sharing of energy-related resources. While a single firm comes across technical and financial barriers that often hamper the implementation of energy conservation projects, the cooperation between firms can enable energy saving measures and the use of renewable energy sources at industry level. Considering a case study involving an energy intensive industry, the study analyses the potential environmental benefits of the industrial energy symbiosis approach integrating renewable energy sources. The research suggests a methodology to design strategic energy symbiosis connections, advantageous for the involved firms, with the objective of reducing carbon emissions and economic costs. The methodology is based on the mathematical optimization through mixed integer linear programming. combined with the environmental analysis conducted with the life-cycle assessment method. The application of the methodology to the case study provides a scenario outlining all the potential energy flows, that are evaluated respect to the state-of-the-art (reference) scenario and alternative electrification strategies, showing the potential environmental benefits.

2020 - Environmental performance analysis of a dual- source heat pump system [Articolo su rivista]
Marinelli, S.; Lolli, F.; Butturi, Maria Angela; Rimini, B.; Gamberini, R.

Using all phases of a life cycle assessment (LCA), this paper analyses the environmental impact of a dualsource heat pump (DSHP) system that uses either the air or the ground as external heat sources. Data on the production were provided by the manufacturer of the heat pump prototype. The use phase was considered by evaluating the seasonal and annual energy performance of the system, using dynamic simulations. The system maintenance and end-of-life were modelled in accordance with the current regulations and statistical data in this sector. The Ecoinvent database was used as a reference for background data. The ReCiPe, CED and IPCC 100a impact methods were used to assess the environmental impact categories. The results were compared with those of conventional air and ground source heat pump systems. A sensitivity study on the influence of the energy in the use phase was carried out in terms of a variation in energy use and for different energy mixes, including photovoltaic energy. The results demonstrated the environmental validity of the technology in comparison with the two conventional heat pumps used for residential applications in different conditions. The results could be used by heat pump manufacturers to improve the design and performance of their products, by designers in the selection of thermal technologies, and by researchers involved in the study of similar emerging renewable energy technologies.

2020 - Logistic regression for criteria weight elicitation in PROMETHEE-based ranking methods [Relazione in Atti di Convegno]
Balugani, Elia; Lolli, Francesco; Butturi, MARIA ANGELA; Ishizaka, Alessio; Afonso Sellitto, Miguel

For a PROMETHEE II method used to rank concurrent alternatives both preference functions and weights are required, and if the weights are unknown, they can be elicited by leveraging present or past partial rankings. If the known partial ranking is incorrect, the eliciting methods are ineffective. In this paper a logistic regression method for weight elicitation is proposed to tackle this scenario. An experiment is carried out to compare the logistic regression method performance against a state-of-the-art linear weight elicitation method, proving the validity of the proposed methodology.

2020 - Roadway tunnels: A critical review of air pollutant concentrations and vehicular emissions [Articolo su rivista]
Marinello, S.; Lolli, F.; Gamberini, R.

Air quality is a widespread problem with the presence of pollutants in indoor and outdoor environments that generate significant consequences for the population, ecosystems and exposed materials. Vehicular traffic is one of the main sources of air pollutants and, therefore, needs to be studied and analysed in detail. This review reported the results of studies conducted on tunnels, in particular for the measurement of concentrations and the definition of emission factors. The characteristics of the tunnels, available ventilation systems, type of vehicular traffic, and geographical distribution, in addition to concentrations and emission factors, are discussed. Light-duty vehicles are the most frequent category in the case studies. Between the fuels used, gasoline is by far the most widespread. Pollutant concentrations concentrations can reach very high levels. For example, atmospheric particulates (with an aerodynamic diameter of 10 µm) and nitrogen dioxide have also reached levels of 1490 µg/m3 and 4982 µg/m3, respectively.

2020 - The application of a Quality Function Deployment approach for the design of a B2B web platform [Relazione in Atti di Convegno]
Marinello, Samuele; Gamberini, Rita; Lolli, Francesco

2020 - The Geolocation of an Industrial Plant by Means of a Multi-Criteria Fuzzy Approach [Relazione in Atti di Convegno]
Butturi, M. A.; Lolli, F.; Filippi, D.

An innovative company should be ready to take advantage of all the opportunities offered by the market as well as to face the market challenges, and particularly to meet customers' needs. Thus, when compiling a business plan, the use of decision support tools can improve the presented solutions. This paper presents a method for the geolocation of a new industrial plant, to become competitive in the customer mind-set. An innovative project in the E-mobility sector of a company based in Europe concerned a partnership with a corporation and required a new plant located in the US. The problem of the geolocation is solved using a fuzzy analytic hierarchy process approach. Ten key factors that could potentially affect the location of a newcomer in the US have been selected and analyzed, and the State for the optimal location identified.

2019 - A periodic inventory system of intermittent demand items with fixed lifetimes [Articolo su rivista]
Balugani, Elia; Lolli, Francesco; Gamberini, Rita; Rimini, Bianca; Babai, M. Z.

Perishable items with a limited lifespan and intermittent/erratic consumption are found in a variety of industrial settings: dealing with such items is challenging for inventory managers. In this study, a periodic inventory control system is analysed, in which items are characterised by intermittent demand and known expiration dates. We propose a new inventory management method, considering both perishability and intermittency constraints. The new method is a modification of a method proposed in the literature, which uses a periodic order-up-to-level inventory policy and a compound Bernoulli demand. We derive the analytical expression of the fill rate and propose a computational procedure to calculate the optimal solution. A comparative numerical analysis is conducted to evaluate the performance of the proposed solution against the standard inventory control method, which does not take into account perishability. The proposed method leads to a bias that is only affected by demand size, in contrast to the standard method which is impacted by more severe biases driven by intermittence and periods before expiration.

2019 - Complexity measurement in two supply chains with different competitive priorities [Relazione in Atti di Convegno]
Sellitto, M. A.; Lolli, F.; Rimini, B.; Balugani, E.

Complexity measurement based on the Shannon information entropy is widely used to evaluate variety and uncertainty in supply chains. However, how to use a complexity measurement to support control actions is still an open issue. This article presents a method to calculate the relative complexity, i.e., the relationship between the current and the maximum possible complexity in a Supply Chain. The method relies on unexpected information requirements to mitigate uncertainty. The article studies two real-world Supply Chains of the footwear industry, one competing by cost and quality, the other by flexibility, dependability, and innovation. The second is twice as complex as the first, showing that competitive priorities influence the complexity of the system and that lower complexity does not ensure competitivity.

2019 - Corrigendum to “Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation” (Journal of Cleaner Production (2019) 222 (77–89), (S0959652619306870), (10.1016/j.jclepro.2019.03.004)) [Articolo su rivista]
Pini, M.; Lolli, F.; Balugani, E.; Gamberini, R.; Neri, P.; Rimini, B.; Ferrari, A. M.

The authors regret some errors with the notation of decimals in tables 8, 11, 12, 13 and 14. Following, the authors report the correct number values per each of the above mentioned tables. Table 8 Repair time spent for preparing for reuse of WEEE.

2019 - Cost-benefit evaluation of investment in natural gas distribution [Relazione in Atti di Convegno]
Balugani, Elia; Butturi, MARIA ANGELA; Lolli, Francesco; Rimini, Bianca

Investment in the distribution of natural gas must be assessed by combining a technical analysis of the investment and an assessment of the social costs and benefits, to evaluate the impact of the project on social welfare in monetary terms. This paper describes how such an analysis can be conducted, by developing a methodology for the evaluation of investment in the distribution of natural gas. Once the net social benefit (NSB) of the investment has been evaluated, it is also important to assess the degree of reliability of such an estimate. This assessment can be conducted through two types of tests: sensitivity analysis and risk analysis. The critical variables are identified in sensitivity analysis as those that have a significant impact on the predicted outcome when they change. To address any uncertainties in the critical variables, a risk analysis quantifies the probability that the NSB is less than that estimated when using modal values for the critical variables. This type of analysis, combined with a technical evaluation, can be effectively used to assess the social consequences of an investment.

2019 - Life Cycle Thinking (LCT) applied to residential heat pump systems: A critical review [Articolo su rivista]
Marinelli, Simona; Lolli, Francesco; Gamberini, Rita; Rimini, Bianca

Heat pump technology is widely considered to be one of the promising opportunities for energy-efficient and low-carbon solutions for buildings and construction. However, sustainability is not always an intrinsic feature of all heat pumps. According to the Life Cycle Thinking approach, to assess the complete sustainability of a technology, a direct evaluation of the environmental, economic and social aspects over the entire life cycle is needed. Due to the growing interest in this technology, the present review summarizes the existing contributions on the sustainability of heat pump systems for residential heating and cooling using the Life Cycle environmental and Social Assessment and Life Cycle Costing. The main results are highlighted, then the data input, methodological assumptions and evaluation criteria are analyzed. The study reveals how to improve the sustainability of HP devices from a life cycle thinking approach.

2019 - Machine learning for multi-criteria inventory classification applied to intermittent demand [Articolo su rivista]
Lolli, F.; Balugani, E.; Ishizaka, A.; Gamberini, R.; Rimini, B.; Regattieri, A.

Multi-criteria inventory classification groups inventory items into classes, each of which is managed by a specific re-order policy according to its priority. However, the tasks of inventory classification and control are not carried out jointly if the classification criteria and the classification approach are not robustly established from an inventory-cost perspective. Exhaustive simulations at the single item level of the inventory system would directly solve this issue by searching for the best re-order policy per item, thus achieving the subsequent optimal classification without resorting to any multi-criteria classification method. However, this would be very time-consuming in real settings, where a large number of items need to be managed simultaneously. In this article, a reduction in simulation effort is achieved by extracting from the population of items a sample on which to perform an exhaustive search of best re-order policies per item; the lowest cost classification of in-sample items is, therefore, achieved. Then, in line with the increasing need for ICT tools in the production management of Industry 4.0 systems, supervised classifiers from the machine learning research field (i.e. support vector machines with a Gaussian kernel and deep neural networks) are trained on these in-sample items to learn to classify the out-of-sample items solely based on the values they show on the features (i.e. classification criteria). The inventory system adopted here is suitable for intermittent demands, but it may also suit non-intermittent demands, thus providing great flexibility. The experimental analysis of two large datasets showed an excellent accuracy, which suggests that machine learning classifiers could be implemented in advanced inventory classification systems.

2019 - On the elicitation of criteria weights in PROMETHEE-based ranking methods for a mobile application [Articolo su rivista]
Lolli, Francesco; Balugani, Elia; Ishizaka, Alessio; Gamberini, Rita; Butturi, Maria Angela; Marinello, Samuele; Rimini, Bianca

Today, almost everybody has a smartphone and applications have been developed to help users to take decisions (e.g. which hotel to choose, which museum to visit, etc). In order to improve the recommendations of the mobile application, it is crucial to elicit the preference structures of the user. As problems are often based on several criteria, multicriteria decision aiding methods are most adequate in these cases, and past works have proposed indirect eliciting approaches for multicriteria decision aiding methods. However, they often do not aim of reducing as much as possible the cognitive efforts required by the user. This is prerequisite of mobile applications as they are used by everybody. In this work, the weights to assign to the evaluation criteria in a PROMETHEE-based ranking approach are unknown, and therefore must be elicited indirectly either from a partial ranking provided by the user or from the selection of his/her most preferred alternative into a subset of reference alternatives. In the latter case, the cognitive effort required by the decision-maker is minimal. Starting from a linear optimisation model aimed at searching for the most discriminating vector of weights, three quadratic variants are proposed subsequently to overcome the issues arising from the linear model. An iterative quadratic optimisation model is proposed to fit the real setting in which the application should operate, where the eliciting procedure must be launched iteratively and converge over time to the vector of weights, which are the weights that the user implicitly assigns to the evaluation criteria. Finally, three experiments are performed to confirm the effectiveness and the differences between the proposed models.

2019 - Preparation for reuse activity of waste electrical and electronic equipment: Environmental performance, cost externality and job creation [Articolo su rivista]
Pini, Martina; Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Neri, Paolo; Rimini, Bianca; Ferrari, Anna Maria

The European Waste Electrical and Electronic Equipment system introduced measures to encourage both the reduction of the amount of electronic waste and its separation to prepare for reuse. The aim of this study is compare the environmental performance, cost externality and job creation of the whole life cycle of new and reconditioned electrical and electronic equipment by adopting Life Cycle Assessment methodology. Five electrical and electronic equipment categories were investigated and the data collection was made on an Italian context. The refurbishing of breakdown electrical and electronic equipment was assessed by considering different sets of faulty components (Scenario A and B) and a total of 25 scenarios were studied. Moreover, both attributional and consequential life cycle inventory modelling framework were adopted to represent the investigated scenarios. The outcomes highlighted that the preparation for reuse process leads to obtaining a sustainable electronic device than the new one, depending on which set of components are replaced. Adopting Scenario B with the attributional model, the environmental damage of reconditioned electrical and electronic equipment decreases compared to the new one. Conversely, the consequential approach determines an environmental credit for all repaired electronic devices except for one category; in particular, Scenario A produced the largest environmental advantage. The analyses of external costs and social aspects confirm that the preparation for reuse activity allows to obtain a more sustainable product than a new one. For these two latter aspects, the results showed a turnaround passing from attributional model to consequential one. Noting the variability in results adopting both different life cycle inventory modelling framework and set of replaced components, the Life Cycle Assessment practitioner, that conducted the study, should help the decision-makers to determine which scenario is more sustainable accomplishing an adequate choice.

2019 - P207 - VALETUDO project: VAlidation study of the LEarning machine Technique (neUral networks) for big Data in the breast tumor in ReggiO Emilia region, Italy [Poster]
Giovanardi, Filippo; Lolli, Francesco; Balugani, Elia; Pezzuolo, D.; Prati, G.; Degli Esposti, C.; Cerioli, D.

2019 - Quality cost-based allocation of training hours using learning-forgetting curves [Articolo su rivista]
Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca

The training of suppliers and inbound quality inspectors is a common strategy to increase the quality performance of the supply chain but, under budget constraints, these actors compete for a limited amount of training hours. The proposed model aims to allocate the available training hours so as to minimise a total quality cost function composed of prevention, appraisal, and failure costs; it also sets the inspection rates defining the inspection policies assigned to suppliers. The relationship between decision variables and costs is expressed through organisational and individual learning-forgetting curves, for suppliers and quality inspectors respectively, and the effect of the training hours on quality improvement is measured in terms of failure rates. To the best of our knowledge, a total quality cost model with such decision variables is new in the related literature, as it is a model including both organisational and individual learning-forgetting phenomena. A nonlinear optimisation approach was adopted to solve this complex problem. The experimental section includes a decision trees analysis of simplified scenarios in order to interpret the model functioning, as well as a complex numerical example to extrapolate managerial insights.

2019 - Renewable energy in eco-industrial parks and urban-industrial symbiosis: A literature review and a conceptual synthesis [Articolo su rivista]
Butturi, M. A.; Lolli, F.; Sellitto, M. A.; Balugani, E.; Gamberini, R.; Rimini, B.

Replacing fossil fuels with renewable energy sources is considered as an effective means to reduce carbon emissions at the industrial level and it is often supported by local authorities. However, individual firms still encounter technical and financial barriers that hinder the installation of renewables. The eco-industrial park approach aims to create synergies among firms thereby enabling them to share and efficiently use natural and economic resources. It also provides a suitable model to encourage the use of renewable energy sources in the industry sector. Synergies among eco-industrial parks and the adjacent urban areas can lead to the development of optimized energy production plants, so that the excess energy is available to cover some of the energy demands of nearby towns. This study thus provides an overview of the scientific literature on energy synergies within eco-industrial parks, which facilitate the uptake of renewable energy sources at the industrial level, potentially creating urban-industrial energy symbiosis. The literature analysis was conducted by arranging the energy-related content into thematic categories, aimed at exploring energy symbiosis options within eco-industrial parks. It focuses on the urban-industrial energy symbiosis solutions, in terms of design and optimization models, technologies used and organizational strategies. The study highlights four main pathways to implement energy synergies, and demonstrates viable solutions to improve renewable energy sources uptake at the industrial level. A number of research gaps are also identified, revealing that the energy symbiosis networks between industrial and urban areas integrating renewable energy systems, are under-investigated.

2018 - A human-machine learning curve for stochastic assembly line balancing problems [Relazione in Atti di Convegno]
Lolli, F.; Balugani, E.; Gamberini, R.; Rimini, B.; Rossi, V.

The Assembly Line Balancing Problem (ALBP) represents one of the most explored research topics in manufacturing. However, only a few contributions have investigated the effect of the combined abilities of humans and machines in order to reach a balancing solution. It is well-recognized that human beings learn to perform assembly tasks over time, with the effect of reducing the time needed for unitary tasks. This implies a need to re-balance assembly lines periodically, in accordance with the increased level of human experience. However, given an assembly task that is partially performed by automatic equipment, it could be argued that some subtasks are not subject to learning effects. Breaking up assembly tasks into human and automatic subtasks represents the first step towards more sophisticated approaches for ALBP. In this paper, a learning curve is introduced that captures this disaggregation, which is then applied to a stochastic ALBP. Finally, a numerical example is proposed to show how this learning curve affects balancing solutions.

2018 - Clustering for inventory control systems [Relazione in Atti di Convegno]
Balugani, E.; Lolli, F.; Gamberini, R.; Rimini, B.; Regattieri, A.

Inventory control is one of the main activities in industrial plant management. Both process owners and line workers interact daily with stocks of components and finite products, and an effective management of these inventory levels is a key factor in an efficient manufacturing process. In this paper the algorithms k-means and Ward's method are used to cluster items into homogenous groups to be managed with uniform inventory control policies. This unsupervised step reduces the need for computationally expensive inventory system control simulations. The performance of this methodology was found to be significant but was strongly impacted by the intermediate feature transformation processes.

2018 - DEASort: Assigning items with data envelopment analysis in ABC classes [Articolo su rivista]
Ishizaka, Alessio; Lolli, Francesco; Balugani, Elia; Cavallieri, Rita; Gamberini, Rita

Multi-criteria inventory classification groups similar items in order to facilitate their management. Data envelopment analysis (DEA) and its many variants have been used extensively for this purpose. However, DEA provides only a ranking and classes are often constructed arbitrarily with percentages. This paper introduces DEASort, a variant of DEA aimed at sorting problems. In order to avoid unrealistic classification, the expertise of decision-makers is incorporated, providing typical examples of items for each class and giving the weights of the criteria with the Analytic Hierarchy Process (AHP). This information bounds the possible weights and is added as a constraint in the model. DEASort is illustrated using a real case study of a company managing warehouses that stock spare parts.

2018 - Distributed renewable energy generation: a critical review based on the three pillars of sustainability [Relazione in Atti di Convegno]
Butturi, MARIA ANGELA; Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca

Reducing emissions responsible for the climate change is recognized as a strategic goal at European and global level. A higher deployment of renewable energy sources is considered as essential for a low-carbon transition, towards a more sustainable energy system. The 2030 Framework for Climate and Energy sets out the European Union target for 2030 of at least 27% for the share of renewable energy consumption. A high share of renewables requires a new flexible and integrated electricity system to ensure grid stability and match supply and demand. The advances in technologies for renewable electricity and heating production, efficient storage solutions, and advanced ICT allow flexible electrical infrastructures: distributed renewable energy generation is now widely recognized as the main pathway towards an effective integration of discontinuous sources into the energy system. The discussion on renewable energy sources introduction in the energy system has long been focused on technical, economic and policy issues, but the transition to a distributed renewable energy generation approach demands a change of perspective, considering a multi-sectoral sustainability view and the need for multi-stakeholder action. Purpose of this research is reviewing the more recent scientific papers on the distributed renewable energy generation approach, focusing on how all the three key sustainability dimensions, environmental, economic and social, are evaluated and managed in a multi-criteria perspective. The sustainability indicators suggested in literature are classified and discussed to build up an up-to-date and comprehensive set of sustainability related criteria, suitable for future research applications and for supporting decision making processes.

2018 - Economic order quantity and storage assignment policies [Relazione in Atti di Convegno]
D’Urso, Diego; Chiacchio, Ferdinando; Lucio Compagno, :; Lolli, Francesco; Balugani, Elia

The basic Harris’s lot size model dates back to 1913 (Harris, 1913), hence one century from its publication has been recently celebrated. Starting from the seminal work of Harris, a wide plethora of contributors has faced with the lot-sizing problem for fitting the basic model of the economic order quantity to several environments. In fact, the three key parameters constituting the basic model, i.e. the demand rate, the ordering costs, and the inventory holding costs, have been widely explored in order to relax the assumptions of the original model. However, to the best of the authors’ knowledge, the liaison between holding costs and warehouse management has not been completely addressed. The holding costs have been early considered for simplicity as primarily given by the cost of capital, and thus dependent solely on the average inventory on stock. Conversely, by including a more detailed supply chain costs contribution, the economic order quantity calculus appears depending on a recursive calculus process and on the storage assignment policy. In fact, different approaches of warehouse management, e.g. shared and dedicated storage, lead to highly variable distances to be covered for performing the missions. This leads to a total cost function, and consequently to optimum lot sizes, that are affected by the warehouse management. In this paper, this relationship has been made explicit in order to evaluate an optimal order quantity taking into account storage assignment policies.

2018 - New and Reconditioned Electrical and Electronic Equipment. How does change the environmental performance? [Abstract in Atti di Convegno]
Pini, Martina; Neri, Paolo; Gamberini, Rita; Rimini, Bianca; Lolli, Francesco; Ferrari, Anna Maria

The scope of this study, carried out within the LIFE12 ENV/IT001058 - "WEEENmodels" project, was to compare the environmental performance of the life cycle of new electrical and electronic equipment (EEE) and the reused one through the Life Cycle Assessment (LCA) methodology. Different set of replaced components have been evaluated in order to understand which determines the best solution. Finally, both attributional and consequential LCI (Life Cycle Inventory) modelling have been implemented. A representative product has been considered for each WEEE group, assuming that it generates the same environmental damage of the other products belonging to the same category. In particular, the following representative products have been selected: refrigerator (R1), washing machine (R2), cathode ray tube (CRT) (R3), laptop (R4) and fluorescent lamp (R5). In addition, in the use phase, lower performance of reconditioned EEE has been taken into account, e.g. higher energy consumptions. The lifespan of the reused product has been supposed to be equal to half-life time of an equivalent new product. This study evaluated different set of replaced components for each WEEE category in order to examine how the environmental performance can vary adopting different maintenance choices in the reconditioning step. In particular, Scenario A represents the set of replaced components, which damage more frequently; Scenario B is just an alternative set of replaced components. The environmental comparison between new and reused WEEE, adopting attributional LCI modelling, showed that Scenario B produces a damage decrease for all WEEE categories. Moving on the consequential LCI modelling, the environmental comparison highlighted for both scenarios a considerable damage reduction for the reused EEE respect the new one. In addition, Scenario B determined the best environmental performance. Furthermore, for the reused R1, R2, R3 the analysis of results carried out environmental credits. This is due to the avoided burdens associated to the manufacturing of the new EEE, since the system boundaries have been enlarged until to considering the avoided production of the new product. Attributional and consequential LCI modelling performed different LCIA results. Following the methodological guidance for the identification of the most adequate LCI modelling framework presented by Laurent et al., 2014, it would recommend to adopt consequential LCI modelling. But we suggest to LCA practitioner to focus also the attention on the request of who commissioned the project, which often in the waste field are local administrations. Generally, they wants a snapshot of the real effects that waste management policies provoke on human health and environment. For this reason, attributional LCI modelling would be the proper LCI modelling to achieve this scope. Considering this LCI modelling the Scenario B determines the best environmental performance.

2018 - Spare Parts Replacement Policy Based on Chaotic Models [Relazione in Atti di Convegno]
Sellitto, Miguel A.; Balugani, Elia; Lolli, Francesco

Poisson point processes are widely used to model the consumption of spare parts. However, when the items have very low consumption rates, the historical sample sizes are too small. This paper presents a modelling technique for spare parts policies in the case of items with a low consumption rate. We propose the use of chaotic models derived from the well-known chaotic processes logistic map and Hénon attractor to assess the behaviour of a set of five medium voltage motors supplying four drives in the rolling mill of a steelmaking plant. Supported by the chaotic models, we conclude that the company needs an additional motor to ensure full protection against shortages.

Gamberini, R.; Ruggerini, T.; Lolli, F.

The problem of studying a plant layout is frequently tackled in literature. Nevertheless, approaches specifically dedicated to predefined market fields are rare. Usually, methodologies available for a wide variety of companies are studied and adopted, disregarding those details typical of each economical sector. On the contrary, in this paper, customized guidelines for the design of a plant layout of a foundry are proposed, in order to support such a critical productive environment where automated equipment, characteristic of Industry 4.0, are integrated with manual activities. Specifically, the casting area is studied. The long term design is supported by a medium term analysis, focused on the products turnover into the casting moulds. The application to a real life case study is finally described in order to assess the performance of the proposed approach.

2018 - The training of suppliers: A linear model for optimising the allocation of available hours [Articolo su rivista]
Lolli, Francesco; Gamberini, Rita; Gamberi, Mauro; Bortolini, Marco

The cost of quality represents a relevant item in total manufacturing costs. The learning process is incorporated into contemporary models because of its impact on unitary production costs through both autonomous (learning by doing) and induced (learning by means of proactive actions) learning processes. A learning model with time-varying learning rate is proposed in order to establish the relationship between quality improvements and training hours to allocate to suppliers. The performance indicator adopted is the rate of non-conforming units, rather than the more traditional process variance. This enables definition of a novel total cost function, which can be minimised for the best allocation of training hours to suppliers during a single learning cycle. A novel criterion also emerges for the evaluation of suppliers in terms of investment opportunity. Finally, a case study was carried out in order to verify the applicability of this model to real industrial settings.

2017 - A multicriteria framework for inventory classification and control with application to intermittent demand [Articolo su rivista]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca

Several papers have studied inventory classification in order to group items with a view to facilitating their management. The generated classes are then coupled with the specific reorder policies composing the overall inventory control system. However, the effectiveness of inventory classification and control system is strictly interrelated. That is to say, different classification approaches could show different performance if applied to a different set of reorder policies, and vice versa. Furthermore, when the cost structure is subjected to uncertainty, a pure cost-based analysis of the inventory control system could be corrupted. This paper presents a multicriteria framework for the concurrent selection of the item classification approach and the inventory control system through a discrete-event simulation approach. The key performance indicators provided by the simulator (i.e., average holding value, average number of backorders, and average number of emitted orders) are indicative of the multidimensional effectiveness of the adopted inventory control system when coupled with a specific classification approach. By this way, a multicriteria problem arises, where the alternatives are given by exhaustively coupling the item classes, which are generated by different classification approaches, with the reorder policies composing the inventory system. An analytical hierarchy process is then used for selecting the best alternative, as well as for evaluating the effect of the weights assigned to the key performance indicators through a sensitivity analysis. This approach has been validated in a real case study with a company operating in the field of electrical resistor manufacturing, with a view of facilitating the management of items showing intermittent demand.

2017 - AHP-K-GDSS: A new sorting method based on AHP for group decisions [Relazione in Atti di Convegno]
Ishizaka, Alessio; Lolli, Francesco; Gamberini, Rita; Rimini, Bianca; Balugani, Elia

Some public buildings need for energy requalification intervention as they are responsible for a significant share of energy consumption and other related CO2 emissions. With tight budget constraints choices have to be made. To solve this problem a group sorting decision support system based on the analytic hierarchy process, the Kmeans algorithm has been developed. The system aims at sorting alternatives into ordered classes of importance. A case study carried out in an Italian municipality allowed us to verify the validity of our new method in a real setting.

2017 - Decision Trees for Supervised Multi-criteria Inventory Classification [Relazione in Atti di Convegno]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Balugani, Elia; Rimini, Bianca

A multi-criteria inventory classification (MCIC) approach based on supervised classifiers (i.e. decision trees and random forests) is proposed, whose training is performed on a sample of items that has been previously classified by exhaustively simulating a predefined inventory control system. The goal is to classify automatically the whole set of items, in line with the fourth industrial revolution challenges of increased integration of ICT into production management. A case study referring to intermittent demand patterns has been used for validating our proposal, and a comparison with a recent unsupervised MCIC approach has shown promising results.

2017 - FMECA-based optimization approaches under an evidential reasoning framework [Relazione in Atti di Convegno]
Lolli, F.; Gamberini, R.; Balugani, E.; Rimini, B.; Mai, Francesco

One of the major shortcomings of traditional failure modes, effects and criticality analysis is the absence of any interconnection between failure ranking and a procedure for selecting the most critical maintenance/improvement tasks to be carried out. This limits the potential of FMECA for implementation in real environments. In order to bridge this gap, three different 0-1 knapsack models have been formulated. The first aims to select the failures in order to maximise cost savings. The second enriches the selection problem by also taking into account the probabilities of solving the failures with a set of maintenance tasks. The third aims to select the maintenance tasks to maximise the expected profit. In particular, the last two models make use of an evidential reasoning framework to deal with the epistemic uncertainty related to these probabilities. A dataset from a manufacturer of lift winches has been used to validate this proposal, as well as to comment on the need for group decision support systems that are capable of converting the FMECA ranking into maintenance tasks in real environments.

2017 - Inventory control system for intermittent items with perishability [Relazione in Atti di Convegno]
Balugani, E.; Lolli, F.; Gamberini, R.; Rimini, B.

Perishable items, with a limited lifespan and a known expiration date, are found in a variety of industrial settings. From the food to the pharmaceutical industries, the supply chains specialize their inventory control systems to handle the added complexity. These efforts are enhanced when the items present also an intermittent consumption, characterized by frequent periods without demand mixed to highly variable positive demand events. In this paper, a novel periodic inventory control system aims at bridging the gap between these two product features, managing intermittent items with expiration dates. The proposed system performs a combinatorial analysis evaluating all the demand scenarios before and after an expiration date to measure the expected fill rate. An optimization algorithm then sets the order quantity, using mathematical properties of the system to define efficient search boundaries.

2017 - On the Analysis of Effectiveness in a Manufacturing Cell: A Critical Implementation of Existing Approaches [Articolo su rivista]
Gamberini, Rita; Galloni, Luca; Lolli, Francesco; Rimini, Bianca

OEE (Overall Equipment Effectiveness) is a widely used indicator in the evaluation of effectiveness of manufacturing systems. However, several authors published alternative approaches for its computation, complicating the implementation step for practitioners. This study analyses the literature regarding OEE, selects four main methodologies for its evaluation and examines the underlying differences between them. A real life case study is analysed to illustrate problems arising during data collection and the differences in results obtained, together with traceable conclusions for improving the performance of production systems, both in traditional and in innovative industrial plants, following Industry 4.0 principles.

2017 - Requalifying public buildings and utilities using a group decision support system [Articolo su rivista]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca; Balugani, Elia; Prandini, Laura

Public buildings and utilities are responsible for a significant share of energy consumption and other related CO2 emissions. There is therefore an acute need for energy requalification interventions. Unfortunately, municipalities are under tight budget constraints, but decisions have to be made. A new hybrid group decision support system has been proposed in a bid to provide them with firm, transparent support. The system is based on a combination of the analytic hierarchy process, the K- means algorithm, and the 0-1 knapsack model. The first two methods aim at sorting alternatives into ordered classes of importance. To help in this task, the Bezier curve-fitting approach is used to construct the preference functions of decision-makers based on reference points. Then, the knapsack model selects the alternatives from the generated classes while complying with the budget constraints. A case study carried out in an Italian municipality allowed us to verify the validity of our new method in a real setting, and to highlight the advantages of an automatic sorting procedure in practice.

2017 - Single-hidden layer neural networks for forecasting intermittent demand [Articolo su rivista]
Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Balugani, Elia; Gatos, T.; Gucci, S.

Managing intermittent demand is a vital task in several industrial contexts, and good forecasting ability is a fundamental prerequisite for an efficient inventory control system in stochastic environments. In recent years, research has been conducted on single-hidden layer feedforward neural networks, with promising results. In particular, back-propagation has been adopted as a gradient descent-based algorithm for training networks. However, when managing a large number of items, it is not feasible to optimize networks at item level, due to the effort required for tuning the parameters during the training stage. A simpler and faster learning algorithm, called the extreme learning machine, has been therefore proposed in the literature to address this issue, but it has never been tried for forecasting intermittent demand. On the one hand, an extensive comparison of single-hidden layer networks trained by back-propagation is required to improve our understanding of them as predictors of intermittent demand. On the other hand, it is also worth testing extreme learning machines in this context, because of their lower computational complexity and good generalisation ability. In this paper, neural networks trained by back-propagation and extreme learning machines are compared with benchmark neural networks, as well as standard forecasting methods for intermittent demand on real-time series, by combining different input patterns and architectures. A statistical analysis is then conducted to validate the best performance through different aggregation levels. Finally, some insights for practitioners are presented to improve the potential of neural networks for implementation in real environments.

2017 - Stochastic assembly line balancing with learning effects [Relazione in Atti di Convegno]
Lolli, Francesco; Balugani, Elia; Gamberini, Rita; Rimini, Bianca

Human learning is nowadays taken into account in several research fields, including the assembly line balancing problem. Despite the plethora of contributions and different approaches to solving the problem, the autonomous learning phenomenon, that is to say, the time-dependent or position-dependent reduction of assembly task times due to repetition, should also be explored using stochastic models which, to the best of our knowledge, have been disregarded. In this paper, a well-established cost-based stochastic balancing heuristic has been coupled with a time-dependent learning curve in order to investigate the role of learning in the rebalancing of assembly lines with repetitive tasks. Finally, a real case study has been conducted with the aim of demonstrating the applicability of our proposal.

2016 - A learning model for the allocation of training hours in a multistage setting [Articolo su rivista]
Lolli, Francesco; Gamberini, Rita; Giberti, Claudio; Gamberi, Mauro; Bortolini, Marco; Bruini, Emanuele

In line with the continuous improvement theory, the learning phenomenon is often incorporated into models for predicting the evolution of the unitary quality costs. In this paper, the quality metric predicted is the rate of supplied non-conforming units through a learning process with autonomous and induced sources of experience. The former is simply learning by doing, i.e. supplying, whilst the latter is driven by the allocation of training hours to suppliers. A revised learning model with time-varying learning rates is proposed for embracing both these effects into a multistage assembly/production setting. A single-period prevention–appraisal–failure cost function is achieved, and the sample inspection rates adopted among suppliers are also considered in order to evaluate their effect. If these sample rates are given, the goal of allocating the training hours among suppliers is pursued by means of integer linear programming. Otherwise, a mixed-integer quadratic problem arises for the concurrent allocation of training hours and inspection sample rates among suppliers. A case study is finally carried out for demonstrating the applicability of the model, as well as for providing managerial insights.

Lolli, Francesco; Gamberini, Rita; Pulga, Francesco; Rimini, Bianca

This paper aims to present a modified failure mode and effects analysis (FMEA) in order to make the assignment of the scores for the occurrence factor more robust, and to link the FMEA chart directly to the maintenance activities. A well-known clustering algorithm (i.e. K-Means), along with a normalisation approach, are applied and compared for the assignment of the occurrence scores. Subsequently, the relationship between failures and maintenance operations is made explicit by a correlation matrix. Finally, the K-Means algorithm is applied to the maintenance operations again in order to sort them into priority classes. It is found that this revised FMEA approach improves the standard one due to its more rigorous mathematical formulation and lean applicability in real operating environments. A real case study is introduced in order to show the applicability of this approach to the quality control of a blow moulding process. It is found that this approach reveals a high potentiality for dealing with real issues. The paper provides a further step towards bridging the gap between theory and practical application of the FMEA approach.

2016 - A simulative approach for evaluating alternative feeding scenarios in a kanban system [Articolo su rivista]
Lolli, Francesco; Gamberini, Rita; Giberti, Claudio; Rimini, Bianca; Bondi, Federica

In accordance with the lean production philosophy, an assembly line may be supplied by means of a kanban system, which regulates and simplifies the flow of materials between the lines and the warehouses. This paper focuses on evaluation of feeding policies that differ from each other in term of the number of kanbans managed per feeding tour. A pure cost-based approach is thus proposed, which considers both inline inventories along with handling costs proportionate to the number of operators involved in the parts-feeding process. A multi-scenario simulative approach is applied in order to establish the number of operators required to avoid inline shortages. The scenario minimising total cost is then selected. The innovation introduced is a model for describing kanban arrivals and their requests for feeding, improving the potential of the simulation to describe real-life environments. Lastly, a case study from the automotive industry is presented in order to highlight the applicability of the proposed approach as well and the effects of alternative feeding policies on the total cost incurred.

2016 - Analisi LCA di un possibile scenario di riuso delle apparecchiature elettriche ed elettroniche dismesse: il progetto WEEENMODELS [Relazione in Atti di Convegno]
Pini, Martina; Gamberini, Rita; Lolli, Francesco; Neri, Paolo; Rimini, Bianca; Signori, Alessandra; Ferrari, Anna Maria

Il sistema europeo di raccolta dei rifiuti da apparecchiature elettriche ed elettroniche (RAEE) ha introdotto misure volte a incentivare la separazione dei RAEE da preparare per il riutilizzo. Obiettivo dello studio, svolto nell’ambito del progetto LIFE12 ENV/IT001058 – “WEEENMODELS”, è la valutazione ambientale di un possibile scenario di riuso di apparecchiature elettriche ed elettroniche dismesse e l’elaborazione di un calcolo approssimato per valutare gli effetti locali e indoor delle emissioni da esso generate.

2016 - Modelling production cost with the effects of learning and forgetting [Relazione in Atti di Convegno]
Lolli, Francesco; Messori, Michael; Gamberini, Rita; Rimini, Bianca; Balugani, Elia

Defining a dynamic model for calculating production cost is a challenging goal that requires a good fitting ability with real data over time. A novel cost curve is proposed here with the aim of incorporating both the learning and the forgetting phenomenon during both the production phases and the reworking operations. A single-product cost model is thus obtained, and a procedure for fitting the curve with real data is also introduced. Finally, this proposal is validated on a benchmark dataset in terms of mean square error.

2016 - Solving the group sorting problem with an AHP-based approach [Relazione in Atti di Convegno]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca

Multi-criteria decision making represents an extended branch of decision sciences which is highly applicable to several real settings. In particular, the question of ranking has attracted wide attention from researchers in the last few decades, through approaches based on different multi-criteria methods. However, ranking alternatives does not solve the question of sorting them into priority classes. When alternatives need to be classified into ordered classes, a sorting method has to be applied, but much less attention has been paid to investigating this kind of problem, especially in the case of multiple decision-makers asked to give subjective scores to different alternatives based on qualitative criteria. In this paper, a new Analytic Hierarchy Process (AHP)-based group sorting method is defined, with the aim of achieving ordered classification without asking the decision-makers to provide limiting profiles. The resulting group sorting approach is validated with a numerical example.

2016 - Waste treatment: an environmental, economic and social analysis with a new group fuzzy PROMETHEE approach [Articolo su rivista]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca; Ferrari, Anna Maria; Marinelli, Simona; Savazza, Roberto

Most complex decisions involve several stakeholders and therefore need to be solved using a group multi-criteria decision method. However, stakeholders or decision-makers often have divergent views, especially in the environmental sector. In order to integrate this divergence, a new group fuzzy PROMETHEE approach is introduced to combine the traditional environmental criteria of life cycle assessments with social and economic criteria. The modelling of uncertainty within the group of decision-makers using a fuzzy approach makes this method unique. The proposed fuzzy approach differs significantly from the standard one. The decision-makers express their judgments in crisp forms. In order to take into account the intrinsic dispersion of judgments within the group, a posteriori fuzzification procedure is applied. The crisp values are not simply aggregated; they are converted into a triangular fuzzy number based on the given evaluations. As a consequence, the definition of fuzzy membership functions, as required in standard fuzzy logic, is not required, which simplifies the process and makes it more reliable. The new approach is illustrated with a real case study concerning the selection of the best waste treatment solution in a natural park from among a traditional incinerator and an innovative integrated plant.

2015 - A bi-objective heuristic for supporting fire stations to respond quickly and efficiently in case of micro calamities [Articolo su rivista]
Lolli, Francesco; Pergreffi, A.; Gamberini, Rita; Rimini, Bianca; Regattieri, A.

Among the wide set of requests of interventions sent to a fire station, the so called ‘micro calamities’ may play a significant role. They are characterized by simultaneous requests of low severity mark from a spread area. These events are completely comparable to those referring to the post-crisis humanitarian logistics. A pure cost-based approach does not fit with this operative issue, as well as a pure minimum latency approach, which is typically applied in the previous acute phases. Thereby, a bi-objective problem is formulated and solved by means of an ‘a priori’ scalarization heuristic. A case study shows the applicability of the proposed approach and indicates the opportunity of further investigations.

2015 - FlowSort-GDSS - A novel group multi-criteria decision support system for sorting problems with application to FMEA [Articolo su rivista]
Lolli, Francesco; Ishizaka, Alessio; Gamberini, Rita; Rimini, Bianca; Messori, Michael

Failure mode and effects analysis (FMEA) is a well-known approach for correlating the failure modes of a system to their effects, with the objective of assessing their criticality. The criticality of a failure mode is traditionally established by its risk priority number (RPN), which is the product of the scores assigned to the three risk factors, which are likeness of occurrence, the chance of being undetected and the severity of the effects. Taking a simple "unweighted" product has major shortcomings. One of them is to provide just a number, which does not sort failures modes into priority classes. Moreover, to make the decision more robust, the FMEA is better tackled by multiple decision-makers. Unfortunately, the literature lacks group decision support systems (GDSS) for sorting failures in the field of the FMEA. In this paper, a novel multi-criteria decision making (MCDM) method named FlowSort-GDSS is proposed to sort the failure modes into priority classes by involving multiple decision-makers. The essence of this method lies in the pair-wise comparison between the failure modes and the reference profiles established by the decision-makers on the risk factors. Finally a case study is presented to illustrate the advantages of this new robust method in sorting failures.

2015 - Retrofitting of R404a commercial refrigeration systems using R410a and R407f refrigerants [Articolo su rivista]
Bortolini, Marco; Gamberi, Mauro; Gamberini, Rita; Graziani, Alessandro; Lolli, Francesco; Regattieri, Alberto

This paper presents an experimental analysis about the retrofitting of two commercial stationary refrigeration systems marketed by an Italian leading company. Such systems operate both at medium temperature (MT), i.e. [-5; 10]°C, and low temperature (LT), i.e. [-25; -15]°C, and they are originally designed to work with hydrofluorocarbon (HFC) R404a, known as a high global warming potential (GWP) fluid (GWP = 3922). The goal is to investigate the performances of HFC R410a (GWP = 2088) and R407f (GWP = 1825), chosen as effective alternatives to HFC R404a. Such fluids are compatible with the refrigeration systems, non-flammable and easy-available. Furthermore, they meet the European Union (EU) restrictions in force in the next future, so that they are suitable to start the transition toward efficient and eco-friendly refrigeration systems. The experimental campaign shows the feasibility of adopting R407f and R410a for the MT refrigeration system and R407f fluid for the system operating at LT.

Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca

Managing intermittent demand represents a very critical task in term of forecasting and stock control due to the variability both of demand sizes and demand arrivals. In this pa-per the forecasting issue is tackled by comparing different extrapolative forecasting ap-proaches. In particular, the SARIMA model (Seasonal Autoregressive Integrated Moving Average) is applied on 60 real time series by means of the TRAMO-SEATS procedure, which is a versatile and automatic procedure allowing a quick identification of the best performing SARIMA model for each item. The forecasting performances are then compared with those obtained by the well-known methods of Croston and Syntetos-Boylan, which represent two modified versions of the simple exponential smoothing specifically introduced for estimating the mean demand per period in case of intermittent demand profiles. Furthermore, the aggre-gation of forecasts in lower-frequency ‘time buckets’ is implemented in order to evaluate how these methods behave on aggregated time horizons.

Gamberini, Rita; Lolli, Francesco; Regattieri, A.; Rimini, Bianca

Irregular and sporadic demand profiles frequently occur in different contexts characterised either by a large fragmentation of client requests within a broad product mix or when new products are introduced. Their optimal management often requires the definition of approaches based on Key Performance Indicators (KPI) other than costs, which in the aforementioned situations are characterised by uncertainty. Specifically, holding costs and stock-out costs are difficult to quantify. This paper examines 104 dynamic re-order policies in an environment where demand patterns with very low demand frequency and demand size equal to very few items are required by customers. Furthermore, the cost structure is uncertain. The aforementioned alternative management approaches are experimentally compared in terms of the average inventory level, average and maximum lost demand and average number of stock-out they can ensure.

Gamberini, Rita; Castagnetti, E.; Lolli, Francesco; Rimini, Bianca

In this paper the problem of allocating and scheduling jobs on parallel unrelated machines is studied. Jobs are grouped in families of similar items. A sequence dependent setup is required between batches of jobs belonging to the same and different families, even if in the first case lower time is required. The size of batches is not known a-priori, hence the problem is divided in two different sub-problems: a) the allocation of volumes of work on each machine and b) subsequently the scheduling of each item. The focus of the paper is on the first step and consequently on the pre-assignment problem. Three different solving approaches are implemented in several real-life case studies.

Lolli, Francesco; Ishizaka, A.; Gamberini, Rita

Multi-Criteria Inventory Classification (MCIC) groups inventory items with respect to several criteria, in order to facilitate their management. This paper introduces a new hybrid method based on AHP and the K-means algorithm. On benchmarking data, it provides a clearly higher clustering validity index than previous sorting methods. However, as with previous methods, it is a full compensatory method. This means that an item scoring badly on one or more key criteria may still be placed in the best class because these bad scores are compensated. In order to prevent these hidden bad scores, a new variant method is introduced: AHP-K-Veto. The sorting is performed on each single criterion, where a veto system prevents an item evaluated as high/bad on at least one criterion to be top/bottom ranked in the global aggregation. This veto system is an assurance against hidden problems but slightly worsens the clustering validity index.

Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca; Morsiani, M.

The liaison between forecasting and inventory control represents a promising research field even if they have been often considered as independent problems. Otherwise, this paper follows a recent set of works that proved the importance of simultaneously considering both aspects. As a consequence, the choice of the best-performing approach should not consider only the accuracy of forecasts, but also the effects of forecasting methods on re-order policies. In particular, this paper deals with different periodic inventory control methodologies, with different lead times and safety stocks. The application to intermittent demand patterns is studied. The best Seasonal Autoregressive Integrated Moving Average (SARIMA) forecasting models are initially automatically identified by the TRAMO-SEATS software and results obtained are subsequently used for tuning periodic review inventory control approaches. The experimental analysis is performed on a real data set of 40 time series. A discrete-event simulation finally shows the obtained effects. Two features of this paper are remarkable. The former is that the intermittent data set is not pseudo-random generated and thus assumptions on the best-fitting demand distribution are not required. The latter regards the full automation of the TRAMO-SEATS software, which indicates its ability of being applied also in real industrial environments.

Gamberini, Rita; Meli, M.; Galloni, Luca; Rimini, Bianca; Lolli, Francesco

Assembly lines managed by means of lean production philosophy are usually characterized by workstations with inline stock areas, supplied by means of items contained in a larger supermarket zone. Furthermore, inline components necessities are usually showed by means of the use of kanbans. In this work, the number of kanbans and the number of carriers serving the line are computed by means of Erlang-C approach, in order to minimize a total cost function obtained as the sum of an estimation of cost of inline stock and of cost of refilling operations. Specifically, the Erlang-C approach is adopted since assures fast re-design of the system when variations in input data occur. Finally, a real-life case study in a company manufacturing items for the automotive market field is presented in order to highlight the approach potentialities when alternative scenarios are studied.

Rimini, Bianca; Gamberini, Rita; Bianchi, M.; Lolli, Francesco

La progressiva diffusione delle logiche di gestione delle singole aziende o delle supply chain basate sui principi del Total Quality Management e del Lean Thinking hanno portato ad un cambio di prospettiva, non più focalizzato sul prodotto, ma sulla customer satisfaction e sulle caratteristiche dei processi (interni o esterni all’impresa, di stampo produttivo o organizzativo o legato alla gestione di servizi per il cliente) che permettono di perseguirla. Tale cambiamento è evidente anche analizzando le novità imposte dalla normativa UNI EN ISO 9001: 2000 e dai suoi successivi aggiornamenti. Obiettivo quindi di ogni sistema produttivo diventa la proposta sul mercato di prodotti e servizi con requisiti di qualità tali da soddisfare clienti sempre più esigenti. Risultato questo perseguibile solo con un forte orientamento ad esso di tutte le componenti aziendali e con un significativo monitoraggio delle componenti di costo legate alla non completa soddisfazione dei requisiti di qualità. Tali componenti di costo nel seguito verranno sinteticamente denominate Non-Conformity-Costs (NCCs). Il framework di riferimento per lo studio è la normativa ISO 10014:2006 Quality management – Guidelines for realizing financial and economic benefits e la pubblicazione proposta da Feigenbaum nel 1991, che suddivide NCCs mediante il modello PAF – Prevention Appraisal Failure, cioè in base alla loro pertinenza con azioni di prevenzione, controllo o conseguenti alla gestione di un guasto (o più in generale di un difetto). Il presente lavoro descrive i risultati conseguenti al monitoraggio dei NCCs all’interno della supply chain di una azienda manifatturiera operante sul territorio nazionale ed internazionale e l’effetto di una corretta formazione degli operatori coinvolti nel processo, al fine di ridurre la frequenza di presentazione dei guasti e dei difetti.

Gamberini, Rita; DEL BUONO, D.; Lolli, Francesco; Rimini, Bianca

The definition and utilisation of engineering indexes in the field of Municipal Solid Waste Management (MSWM) is an issue of interest for technicians and scientists, which is widely discussed in literature. Specifically, the availability of consolidated engineering indexes is useful when new waste collection services are designed, along with when their performance is evaluated after a warm-up period. However, most published works in the field of MSWM complete their study with an analysis of isolated case studies. Conversely, decision makers require tools for information collection and exchange in order to trace the trends of these engineering indexes in large experiments. In this paper, common engineering indexes are presented and their values analysed in virtuous Italian communities, with the aim of contributing to the creation of a useful database whose data could be used during experiments, by indicating examples of MSWM demand profiles and the costs required to manage them.

Gamberini, Rita; Consoli, D.; Lolli, Francesco; Rimini, Bianca

For ceramic tile manufacturers, warehouse management represents an extremely critical issue due to the necessity of storing pallets in an open yard by stacking them according to specific storage rules. In particular, pallets belonging to the same production batch must be stored in adjacent bins because customer orders must be collected from the same batch. Hence, a high fragmentation of the yard must be avoided. In order to free the bins that are to be assigned to the batches, shuffling operations must be performed before the batches are delivered by the production lines. In this paper, a shuffling algorithm is presented with the aim of designing a useful and flexible tool that may be integrated into a Warehouse Management System.

Gamberini, Rita; Rimini, Bianca; Dell'Amico, Mauro; Lolli, Francesco; Bianchi, M.

Order picking related costs may account for up to 65% of the total expense of warehouse management. Hence, the implementation of robust design and optimization procedures for planning picking is addressed by researchers and practitioners.In this chapter the case of warehouses served by humans, in picker-to-parts systems, with a discrete picking organization is studied. Specifically, the case of orders including multiple different items, located in different aisles and requiring more than one forklift load to completely satisfy customer requests is analyzed, with the aim of minimizing the time for retrieving an order. Specifically, two aspects are studied:•the grouping of orders into a finite number of forklift missions, by assuring that each required item is picked in the required amount•the optimization of the routing to be followed by handling facilities in accordance with the objective of minimizing the total travelled distance and the computation of the number of handling facilities necessary for serving the warehouse aisles.

Gamberini, Rita; Bicchierini, E.; Lolli, Francesco; Rimini, Bianca; Regattieri, A.; Galloni, Luca

The Assembly Line Balancing Problem (ALBP) consists in assigning tasks to operators engaged on a line in such a way that the final item is produced according to a pre-determined production rate and by optimizing pre-defined objective functions. In the literature, a wide range of algorithms claiming to solve ALBP are found, however almost all of them consider this problem from a mathematical standpoint, thus disregarding details which are useful for ensuring the correct implementation of proposed solutions in real-life environments. Authors have gradually narrowed the gap between theory and practice by introducing stochastic operating times when manual operations are executed, or by describing more and more complex versions of the problem, usually known by the term GALBP (Generalized Assembly Line Balancing Problem), where a wide variety of objective functions and constraints are managed. By researching such an area, this paper will investigate the case of redesigning a manufacturing area dedicated to the production of heavy and voluminous items by highlighting the characteristics and peculiarities of the problem. Finally, a real-life case study is solved.

Gamberini, Rita; Lolli, Francesco; Rimini, Bianca; Torelli, M.; Castagnetti, E.

The problem of allocating jobs to a set of parallel unrelated machines in a make to stock manufacturingsystem is studied. The items are subdivided into families of similar products. Sequence-dependent setupsarise when products belonging both to the same family and to different families are sequenced. Restrictionson the number of available setups should be considered. The availability of planning batch production exists.Nevertheless, batch size is not known a priori. Hence, a solving approach considering both a preassignmentprocedure and a scheduling algorithm is proposed. Specifically, the focus of the paper is on thepre-assignment methodology: a pre-assignment model (solved by a commercial solver) and two heuristicsare presented and compared, in order to minimize the average idle residual capacity during the planninghorizon, while considering pejorative factors related with the split volumes of the same product on differentmachines, unsatisfied demand along with demand produced in advance in each time period. The applicationto a case study is finally described in order to assess the performance of the proposed approach.

Lolli, Francesco; Gamberini, Rita; Regattieri, A.; Rimini, Bianca; Grassi, Andrea; Belluti, P.

Managing sporadic and irregular demand patterns represents a relevant issue in several industrial contexts. Two main aspects have to be underlined due to their prominence: the former is the problem of forecasting future demand profiles, and the latter choosing and determining the best re-order policy to be applied, in accordance with information gained during the forecasting step. In this paper the former issue is discussed, by focusing on the management of items with sporadic and irregular demand patterns that also present a seasonality component. TRAMO-SEATS is a versatile procedure that allows quick identification of the best SARIMA forecasting model from an available set. Results obtained by its implementation are compared with those obtained by the Croston (1972) and Syntetos-Boylan (2005) methods, which represent two modified versions of simple exponential smoothing, introduced in literature for forecasting mean demand size per period specifically in case of irregular and sporadic demand profiles. In particular, two items are analysed, with the aim of demonstrating that when the strict hypothesis required by Croston’s and Syntetos-Boylan’s approaches fails, alternative forecasting methods could be required. TRAMO-SEATS represents a promising and user-friendly option.

Gamberini, Rita; Lolli, Francesco; Rimini, Bianca

Managing irregular and sporadic demand patterns is a fundamental task in several real life contexts, such as spare parts consumption, multi-echelon supply chains or start-up production. This work is a study of re-order policies and stock inventory management approaches aimed at optimizing pre-defined performance indexes. Specifically, given a firm operating in the field of electric resistance manufacturing, the focus is on the application of different item clustering methods, in order to define groups of items with similar behavior that require similar management approaches. The work offers a framework for the comparative evaluation of two different item clustering methods, by means of a simulative approach, available when product demand profiles are irregular and sporadic. In order to compare them, a multi-criteria technique is preferable because of the high uncertainty of the cost structure. Hence, after running the simulation, three Key Performance Indicators (KPI) are estimated: the average inventory level, the average number of backorders that occurred and the average number of emitted orders. Finally, some conclusions are drawn by defining a field of implementation for each clustering approach studied.

Rimini, Bianca; Grassi, Andrea; Gamberini, Rita; Gebennini, Elisa; Lolli, Francesco; Ferrara, A.

The paper describes a study of designing rack storage systems managed according to a Last-In Fist-Out (LIFO) policy. The system is supposed to house a number of cyclic items (i.e. characterized by batch production and continuous deliveries policies). This kind of behaviour is common for high-consumption products in the food industry, such as pasta and bakery products.The aim of the study is to define a static design solution by assigning each item to a number of LIFO racks so that the overall system performance results are satisfactory. The dynamic behaviour is kept under control by adopting automated material handling devices such as Automated Guided Vehicles (AGVs).This paper is an extension of a previous work by Ferrara et al. (2011), here named the single-allocation procedure, by allowing each item to be assigned to two different rack typologies (double-allocation solution).The convenience of the double-allocation solution in comparison with the single-allocation one is proven by a significant case study from the food industry.

Regattieri, A.; Gamberini, Rita; Lolli, Francesco; Manzini, R.

Queues of people, products and machines frequently occur in many production and service systems, resulting in significant inefficiencies. This paper discusses the significant impact on these problems of the queuing theory introduced by Erlang and Kendall. A methodology based on the M/M/m queuing model (including a validation phase through a goodness-of-fit test) is proposed. This methodology makes parametric analyses of system performance according to the different possible ranges of input parameters. It helps solve several typical problems found in production systems (e.g., resource design, traffic and logistics analysis) and services (e.g., optimal design and management). There is a good tradeoff between the robustness of the results, coherence with real industrial systems and mathematical complexity. A real-world application involving the design optimisation of a passenger security screening system in an international airport is presented. In particular, the optimal number of security gates in the design is discussed.

Gamberini, Rita; Lolli, Francesco; Rimini, Bianca; Sgarbossa, F.

Items with irregular and sporadic demand profiles are frequently tackled by companies, given the necessity of proposing wider and wider mix, along with characteristics of specific market fields (i.e. when spare parts are manufactured and sold). Furthermore, a new company entering into the market is featured by irregular customers orders. Hence, consistent efforts are spent with the aim of correctly forecasting and managing irregular and sporadic products demand. In this paper, the problem of correctly forecasting customers orders is analyzed by empirically comparing existing forecasting techniques. The case of items with irregular demand profiles, coupled with seasonality and trend components, is investigated. Specifically, forecasting methods (i.e. Holt-Winters approach and (S)ARIMA) available for items with seasonality and trend components are empirically analyzed and tested in the case of data coming from the industrial field and characterized by intermittence. Hence, in the conclusions section, well performing approaches are addressed.

Gamberini, Rita; Lolli, F.; Rimini, Bianca; Torelli, M.

The problem of allocating jobs to a set of parallel unrelated machines in a make to stock manufacturing system is studied. The items are subdivided into families of similar products. Sequence-dependent setups arise when products belonging both to the same family and a different family are sequenced. Restrictions on the number of available setups should be considered. The availability of planning batch production exists. Nevertheless, batch size is not known a priori. Hence, a solving approach considering both a pre-assignment procedure and a scheduling algorithm is proposed. Specifically, the focus of the paper is on the pre-assignment methodology: a pre-assignment model (solved by a commercial solver) and two heuristics are presented and compared, in order to minimize the average idle residual capacity during the planning horizon, while considering pejorative factors related with the split volumes of the same product on different machines, unsatisfied demand along with demand produced in advance in each time period. The application to a case study is finally described in order to asses the performance of the proposed approach.

Gamberini, Rita; Rimini, Bianca; Lolli, Francesco

In diversi settori della produzione industriale si sta sempre piùaffermando l’esigenza di progettare e produrre prestandoattenzione all’impatto ambientale. In questo contesto si collocala direttiva RoHS (Restriction of the use of HazardousSubstances), finalizzata a ridurre o eliminare l’utilizzo di alcunesostanze definite come genericamente pericolose. Questo articolo affronta l’analisi sperimentale dei costi di adeguamento alla suddetta direttiva in un’impresa di piccole-medie dimensioni che realizza cablaggi su commessa, nella quale la direttiva ha significativamente modificato i cicli tecnologici di saldatura, che tradizionalmente venivano effettuati con leghe di saldatura al piombo ora bandite dal mercato. In particolare, si è focalizzata l’attenzione sulle voci di costo di adeguamento alla direttiva che sono risultate più significative: costi di modifica dei cicli tecnologici e costi di stoccaggio. I risultati ottenuti confermano l’elevata incidenza sui costi di produzione che la direttiva RoHS genera nel caso di una piccola-media impresa.

Regattieri, A.; Gamberini, Rita; Lolli, F.; Manzini, R.

Queues of people, products, and machines frequently occur in many production systems (goods manufacturing and service supply) and result in significant inefficiencies. For example, machines waiting to be repaired may result in lost production, vehicles forced to wait before being unloaded may delay subsequent shipments, and people made to wait for a service (i.e. bank, hospital, supermarket) may become frustrated which could result in lost future business. This paper discusses the tremendous positive impact of queuing theory (introduced by Erlang and Kendall) on the problems typically found in production systems (e.g. optimal design, resources rationalization, traffic and logistics analysis). The fundamental models in this theory are discussed and then applied to the design and optimization of production systems. Finally, a real world application of M/M/n queuing theory is presented involving design optimization of a passenger security screening system in an international airport.