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Assegnista di ricerca
INTERMECH Centro Interd. per la Ricerca Applicata e i Servizi nel settore della Meccanica Avanzata e della Motoristica
Docente a contratto
Dipartimento di Ingegneria "Enzo Ferrari"

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2022 - Digital Technologies to Redesign Automatic Machines with a Human-Centric Approach: Application in Industry [Relazione in Atti di Convegno]
Grandi, Fabio; Peruzzini, Margherita; Khamaisi, Riccardo Karim; Lettori, Jacopo; Pellicciari, Marcello

Human factors integration is definitely a transdisciplinary and urgent matter in modern factories. Despite the great surge in factory automation in recent years, human-machine interaction is still a crucial aspect and companies need to take care of the workers' wellbeing and performance to enhance the overall system quality and productivity. Nevertheless, ergonomics is poorly considered during the design of complex industrial systems, such as automatic machinery, especially for the lack of practical methodologies and guidelines to promote human factors from the early stages of design or redesign. To overcome this issue, this work proposes a transdisciplinary approach to redesign automatic machinery in compliance with factory ergonomics, using a combination of digital technologies (e.g., digital human simulation, human physiological data monitoring). The paper defines a structure method and related tools to apply a human-centric approach to industrial cases and their validation of a real case, concerning the redesign of a packaging automatic machine. Results show how the proposed approach is useful to detect possible ergonomic issues at the shop floor, identifying in advance risky situations for the operators during operating or maintenance tasks, and leading to an optimized machine able to enhance the workers’ wellbeing and factory productivity at the same time.

2021 - A Reference Framework to Combine Model-Based Design and AR to Improve Social Sustainability [Articolo su rivista]
Grandi, Fabio; Khamaisi, Riccardo Karim; Peruzzini, Margherita; Raffaeli, Roberto; Pellicciari, Marcello

Product and process digitalization is pervading numerous areas in the industry to improve quality and reduce costs. In particular, digital models enable virtual simulations to predict product and process performances, as well as to generate digital contents to improve the general workflow. Digital models can also contain additional contents (e.g., model-based design (MBD)) to provide online and on-time information about process operations and management, as well as to support operator activities. The recent developments in augmented reality (AR) offer new specific interfaces to promote the great diffusion of digital contents into industrial processes, thanks to flexible and robust applications, as well as cost-effective devices. However, the impact of AR applications on sustainability is still poorly explored in research. In this direction, this paper proposed an innovative approach to exploit MBD and introduce AR interfaces in the industry to support human intensive processes. Indeed, in those processes, the human contribution is still crucial to guaranteeing the expected product quality (e.g., quality inspection). The paper also analyzed how this new concept can benefit sustainability and define a set of metrics to assess the positive impact on sustainability, focusing on social aspects.

2021 - A preliminary experimental study on the workers’ workload assessment to design industrial products and processes [Articolo su rivista]
Brunzini, A.; Peruzzini, M.; Grandi, F.; Khamaisi, R. K.; Pellicciari, M.

The human‐centered design (HCD) approach places humans at the center of design in order to improve both products and processes, and to give users an effective, efficient and satisfy-ing interactive experience. In industrial design and engineering, HCD is very useful in helping to achieve the novel Industry 5.0 concept, based on improving workers’ wellbeing by providing prosperity beyond jobs and growth, while respecting the production limits of the planet as recently promoted by the European Commission. In this context, the paper proposes an ergonomic assessment method based on the analysis of the workers’ workload to support the design of industrial products and processes. This allows the simultaneous analysis of the physical and cognitive workload of operators while performing their tasks during their shift. The method uses a minimum set of non‐invasive wearable devices to monitor human activity and physiological parameters, in addition to questionnaires for subjective self‐assessment. The method has been preliminarily tested on a real industrial case in order to demonstrate how it can help companies to support the design of optimized products and processes promoting the workers’ wellbeing.

2021 - Preliminary validation of a low-cost motion analysis system based on rgb cameras to support the evaluation of postural risk assessment [Articolo su rivista]
Agostinelli, T.; Generosi, A.; Ceccacci, S.; Khamaisi, R. K.; Peruzzini, M.; Mengoni, M.

This paper introduces a low-cost and low computational marker-less motion capture system based on the acquisition of frame images through standard RGB cameras. It exploits the open-source deep learning model CMU, from the tf-pose-estimation project. Its numerical accuracy and its usefulness for ergonomic assessment are evaluated by a proper experiment, designed and per-formed to: (1) compare the data provided by it with those collected from a motion capture golden standard system; (2) compare the RULA scores obtained with data provided by it with those obtained with data provided by the Vicon Nexus system and those estimated through video analysis, by a team of three expert ergonomists. Tests have been conducted in standardized laboratory conditions and involved a total of six subjects. Results suggest that the proposed system can predict angles with good consistency and give evidence about the tool’s usefulness for ergonomist.

2021 - Ux in ar-supported industrial human–robot collaborative tasks: A systematic review [Articolo su rivista]
Khamaisi, R. K.; Prati, E.; Peruzzini, M.; Raffaeli, R.; Pellicciari, M.

The fourth industrial revolution is promoting the Operator 4.0 paradigm, originating from a renovated attention towards human factors, growingly involved in the design of modern, human-centered processes. New technologies, such as augmented reality or collaborative robotics are thus increasingly studied and progressively applied to solve the modern operators’ needs. Human-centered design approaches can help to identify user’s needs and functional requirements, solving usability issues, or reducing cognitive or physical stress. The paper reviews the recent literature on augmented reality-supported collaborative robotics from a human-centered perspective. To this end, the study analyzed 21 papers selected after a quality assessment procedure and remarks the poor adoption of user-centered approaches and methodologies to drive the development of human-centered augmented reality applications to promote an efficient collaboration between humans and robots. To remedy this deficiency, the paper ultimately proposes a structured framework driven by User eXperience approaches to design augmented reality interfaces by encompassing previous research works. Future developments are discussed, stimulating fruitful reflections and a decisive standardization process.