Selecting risk response strategies to minimize human errors in a design project for factories of the future

被引:6
作者
Jin, Guangying [1 ]
Sperandio, Severine [2 ]
Girard, Philippe [2 ]
机构
[1] Dalian Maritime Univ, Sch Maritime Econ & Management, Dalian 116026, Peoples R China
[2] Univ Bordeaux, IMS, UMR 5218, 351 Cours Liberat, F-33405 Talence, France
关键词
Interdependent effect; Risk response strategy; Design risk; Optimization; Expected utility; EXPONENTIAL UTILITY;
D O I
10.1016/j.eswa.2023.120120
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Currently, the Internet of Things (IoT) and Industry 4.0 revolution in product design and development is changing the designer collaborative relationship structure, and communication between designers is becoming easier and more frequent. Meanwhile, risk response strategy, as an important part of risk management, has a significant impact on the effective execution of design projects, and it is becoming more difficult to choose in this new design organizational structure because not only the personal risk response effects need to be considered but also the risk response effects of interdependence caused by frequent communication between designers. Therefore, this research presents a new qualitative analysis and quantitative measurement risk response strategy selection method based on an optimization model integrated by Failure Mode and Effects Analysis (FMEA) and Matrix of Alliances and Conflicts: Tactics, Objectives and Recommendations (MACTOR) methodology to help design companies select optimal risk response strategies, minimize designer risk and allow design projects to be executed safely and effectively in the future design organizational structure. Here, the FMEA method is used to assess the risk for candidate errors depending on the (Risk Priority Number) RPN value, and consider the Severity, Detection and Occurrence property of risk. Meanwhile, the MACTOR method approaches the direct and indirect risk response effect between designers. The proposed method can provide valuable insights for design companies to improve risk management in product design and development.
引用
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页数:16
相关论文
共 57 条
[1]   Arctic shipping accident scenario analysis using Bayesian Network approach [J].
Afenyo, Mawuli ;
Khan, Faisal ;
Veitch, Brian ;
Yang, Ming .
OCEAN ENGINEERING, 2017, 133 :224-230
[2]  
Ali Hatefi M., 2007, INT J APPL MANAGEMEN, V385
[3]   A novel data-driven methodology for fault detection and dynamic risk assessment [J].
Amin, Md. Tanjin ;
Khan, Faisal ;
Ahmed, Salim ;
Imtiaz, Syed .
CANADIAN JOURNAL OF CHEMICAL ENGINEERING, 2020, 98 (11) :2397-2416
[4]  
[Anonymous], 2011, CHERN GALL WHAT CAUS
[5]  
[Anonymous], 310002018 ISO
[6]  
Arsenio A., 2014, Stud. Comput. Intell, V495, DOI [DOI 10.1007/978-3-642-35016-0_1, 10.1007/978-3-642-35016-0_1]
[7]   On the exact solution of the multi-period portfolio choice problem for an exponential utility under return predictability [J].
Bodnar, Taras ;
Parolya, Nestor ;
Schmid, Wolfgang .
EUROPEAN JOURNAL OF OPERATIONAL RESEARCH, 2015, 246 (02) :528-542
[8]   Emerging technologies and industrial leadership. A Wikipedia-based strategic analysis of Industry 4.0 [J].
Bonaccorsi, Andrea ;
Chiarello, Filippo ;
Fantoni, Gualtiero ;
Kammering, Hanna .
EXPERT SYSTEMS WITH APPLICATIONS, 2020, 160
[9]  
Dreyfus S.E., 2004, B SCI TECHNOL SOC, V24, P177, DOI [DOI 10.1177/0270467604264992, 10.1177/0270467604264992]
[10]   Generating project risk response strategies based on CBR: A case study [J].
Fan, Zhi-Ping ;
Li, Yong-Hai ;
Zhang, Yao .
EXPERT SYSTEMS WITH APPLICATIONS, 2015, 42 (06) :2870-2883