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Qian ZHAO

Ricercatore t.d. art. 24 c. 3 lett. A
Dipartimento di Scienze e Metodi dell'Ingegneria

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Pubblicazioni

2024 - A novel framework for FMEA using evidential BWM and SMAA-MARCOS method [Articolo su rivista]
Ju, Y.; Zhao, Q.; Luis, M.; Liang, Y.; Dong, J.; Dong, P.; Giannakis, M.
abstract

This paper presents a novel failure mode and effect analysis (FMEA) framework as a formal design method to ensure safety and reliability. FMEA is used to identify potential failure modes (FMs), and it is crucial to determine the weights of risk factors and prioritize FMs. In this work, we propose a comprehensive framework that integrates the Dempster-Shafer theory, best-worst method (BWM), stochastic multi-objective acceptability analysis (SMAA), and measurement of alternatives and ranking according to compromise solution (MARCOS) to address this problem. To capture the uncertainty caused by the loss of information, the Dempster-Shafer theory is applied for dealing with the uncertainty about risk factors and FMs in terms of linguistic information. Based on the comprehensive evidential preference interval vectors of risk factors constructed by Dempster-Shafer theory, an evidential BWM combined with SMAA is proposed to determine the optimal set of risk factor weights. Meanwhile, based on the constructed interval belief interval decision matrix of FMs to risk factors constructed by Dempster-Shafer theory, an evidential SMAA-MARCOS method is proposed for determining the risk priority of FMs. Further, we conduct a case study to evaluate the risk of equipment in an automobile manufacturing enterprise. A sensitivity and comparative analysis are also conducted to demonstrate the effectiveness and superiority of the proposed framework.

2023 - A K-means Clustering and Triangulation-Based Scheme for Accurate Detection of Multiple Adjacent Through-the-Wall Human Targets [Articolo su rivista]
Shan, J.; Zhang, Y.; Zhao, Q.; Lin, J.
abstract

Through-the-wall (TTW) human targets' detection is extensively desired in civil and military applications. Most studies in this field have only focused on multiple human targets with large spacing, while the situation of short spacing has yet to be well-treated. To solve this problem, an accurate and robust postprocessing scheme is developed in this article for detecting multiple adjacent TTW human targets. First, we identify human targets in the range slow-time planes with a high detection rate. Second, according to the comparing result between different operating planes, two localization solutions based on K-means clustering and triangulation are proposed to extract the precise spatial positions of human targets. Third, using the designed radar system, the effectiveness of the proposed scheme is verified by two typical simulations and three field experiments. The results indicate that the proposed scheme can accurately detect multiple TTW human targets under conditions including large, short spacing, and different orientations with a localization accuracy of 20 cm.

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
abstract

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.

2022 - A hybrid decision making aided framework for multi-criteria decision making with R-numbers and preference models [Articolo su rivista]
Zhao, Q.; Ju, Y.; Dong, P.; Gonzalez, E. D. R. S.
abstract

As a risk modeling about fuzzy numbers, R-numbers have successfully extended to multi-criteria decision making (MCDM) methods for the real-life decision making problems involving the risk and uncertainties associated with fuzzy numbers. To obtain more reliable and robust multi-criteria ranking alternatives in these uncertain situations, a hybrid decision making aided framework involving stochastic multiobjective acceptability analysis (SMAA), robust ordinal regression (ROR), and multi-attributive border approximation area comparison (MABAC) is proposed for MCDM problems with risk factors and preference models. Firstly, some novel operations of the R-numbers associated with triangular fuzzy numbers are proposed to explore a broader application scope. Secondly, a novel MABAC method combined with the R-numbers is proposed for MCDM problems which focus on uncertainty and error of triangular fuzzy numbers. Thirdly, a hybrid decision making aided framework which applies SMAA and ROR into the novel MABAC method is proposed for obtaining robust multi-criteria ranking alternatives through two binary relations, and two measures complement each other. Moreover, a Monte Carlo simulation of the framework is performed. Lastly, an application of assessment of wind energy potential and comparative analysis is provided to illustrate the efficiency and superiority of the proposed framework.

2022 - SMAA-Bicapacity-Choquet-Regret Model for Heterogeneous Linguistic MCDM With Interactive Criteria With Bipolar Scale and 2-Tuple Aspirations [Articolo su rivista]
Zhao, Q.; Ju, Y.; Martinez, L.; Pedrycz, W.; Dong, P.; Wang, A.
abstract

Decision making could be an extremely complicated process. Especially, in situations in which the diversity of backgrounds and experience of decision makers (DMs) may require various forms to model their opinions. DMs' rational choice even may be distorted by their judgements due to limitations of human cognitive competence. Generally, the interactions between criteria, the bipolar scale with negative values, and linguistic-valued aspirations on criteria are also needed to be addressed. In addition, several types of input information may be stochastic or uncertain, such as criteria evaluations, capacities, and preference coefficients. Our aim is to address all previous issues simultaneously by proposing a novel model that incorporates Choquet integral, bicapacity, regret theory, and stochastic multiobjective acceptability analysis (SMAA), i.e., SMAA-bicapacity-Choquet-regret for heterogeneous linguistic multiple criteria decision-making (MCDM) problems with interactive criteria with bipolar scale and 2-tuple aspirations. The heterogeneous linguistic information can offer a highly flexible way to express DMs' preference; a novel 2-tuple aspirations-based utility within regret can better reflect the subjective perceptions of DMs in MCDM problems with 2-tuple aspirations on criteria; bicapacity can weigh the criteria and their coalitions, and Choquet integral concerning bicapacity can aggregate interactive criteria with bipolar scale; and finally, an application to evaluate medical waste disposal technologies is given, and a comparative analysis is performed to verify the applicability and effectiveness of the proposed model.

2022 - The SMAA-TWD model: A novel stochastic multi-attribute three-way decision with interrelated attributes in triangular fuzzy information systems [Articolo su rivista]
Zhao, Q; Ju, Yb; Martinez, L; Dong, Pw; Shan, Jf
abstract

As a decision model to depict the human cognitive process, three-way decision (TWD) offers a reasonable semantic interpretation for solving practical multi-attribute decision -making (MADM) problems. Due to the complexity of the decision-making environment, uncertainties usually exist in multi-attribute three-way decision making problems. To stress these uncertainties simultaneously, a novel stochastic multi-attribute TWD model that incorporates TWD, epsilon-almost stochastic dominance, and stochastic multiobjective acceptability analysis (SMAA) is proposed for dealing with stochastic MADM problems with interrelated attributes in triangular fuzzy information systems. First, based on the epsilon-almost stochastic dominance, a novel epsilon-almost stochastic dominance degree is proposed for measuring the quantitative relationship of two triangular fuzzy numbers. Second, a novel stochastic TWD model is presented, in which the set of two states, conditional prob-ability, and relative loss, can be obtained according to an information system. Third, the Choquet integral with respect to bi-capacity is utilized to aggregate the expected losses of three actions to strengthen their interpretability. Fourth, a SMAA-TWD model is pro-posed for multi-attribute TWDs with interrelated attributes in triangular fuzzy information systems. Finally, an application to medical diagnosis is given, and a comparative analysis is performed to verify the applicability and effectiveness of the proposed model. (c) 2022 Published by Elsevier Inc.

2020 - A method based on bivariate almost stochastic dominance for multiple criteria group decision making with probabilistic dual hesitant fuzzy information [Articolo su rivista]
Zhao, Q.; Ju, Y.; Pedrycz, W.
abstract

Probabilistic dual hesitant fuzzy sets (PDHFSs) are sound information granules to describe decision maker's aleatory and epistemic uncertainty in multiple criteria group decision making (MCGDM) process. In this paper, a bivariate almost stochastic dominance-based PROMETHEE-II method is presented to solve probabilistic dual hesitant fuzzy MCGDM problems which consider correlation averse behavior of decision makers. First, probabilistic dual hesitant fuzzy power Bonferroni mean (PDHFPBM) operator and probabilistic dual hesitant fuzzy power geometric Bonferroni mean (PDHFPGBM) operator are proposed to acquire collective preference information of decision makers. Second, based on the defined bivariate almost stochastic dominance (BASD) and BASD degree, qualitative and quantitative relationships between two probabilistic dual hesitant fuzzy elements (PDHFEs) with corresponding to all criteria are obtained. Third, distance-based correlation coefficient method for computing combined weight with respect to all criteria is proposed. Finally, a BASD-based PROMETHEE-II method is developed to determine the ranking results. Three illustrative examples followed by comparative analysis are included to show the practicality and effectiveness of the proposed method.

2018 - Effect of travelling waves on stochastic seismic response and dynamic reliability of a long-span bridge on soft soil [Articolo su rivista]
Xiong, M.; Huang, Y.; Zhao, Q.
abstract

It is generally known that the variability of earthquake ground motion is mainly in time and space. To investigate the impact of this variability on the seismic performance of a long-span flexible structure, we discuss the seismic dynamic responses of a real bridge subjected to stochastic seismic ground motion. We incorporate the effect of wave passage by means of the method of probability density evolution based on dynamic time-history analysis from the perspective of stochastic dynamics. First, we introduce the theory of probability density evolution and a category of stochastic seismic model. We then conduct a series of deterministic seismic dynamic analyses of the bridge to establish the probability density equation. Eventually, we obtain the probability information at the level of the probability density function of the seismic response by solving the probability-density evolution equation. The results show that the impact of travelling waves on a long-span structure is related to the characteristics of the earthquake ground motion and the structure, and that travelling waves increase the variability of the seismic response.