A fuzzy rule-based industry 4.0 maturity model for operations and supply chain management

被引:187
作者
Gusmao Caiado, Rodrigo Goyannes [1 ]
Scavarda, Luiz Felipe [2 ]
Gaviao, Luiz Octavio [3 ]
Ivson, Paulo [1 ]
de Mattos Nascimento, Daniel Luiz [4 ]
Garza-Reyes, Jose Arturo [5 ]
机构
[1] Pontificia Univ Catolica Rio de Janeiro, Tecgraf PUC Rio, Inst Tech Sci Software Dev, Rua Marques Sao Vicente 225, Rio De Janeiro, RJ, Brazil
[2] Pontificia Univ Catolica Rio de Janeiro, Dept Ind Engn, Rua Marques Sao Vicente 225, Rio De Janeiro, RJ, Brazil
[3] Escola Super Guerra ESG, Av Joao Luiz Alves S-N, Rio De Janeiro, RJ, Brazil
[4] Univ Fed Santa Catarina, CERTI Fdn, Ctr Reference Innovat Technol, Campus Univ UFSC, Florianopolis, SC, Brazil
[5] Univ Derby, Ctr Supply Chain Improvement, Kedleston Rd Campus, Derby DE22 1GB, England
关键词
Industry; 4.0; Maturity model; Production and operations management; Supply chain; Fuzzy rule-based system; Monte Carlo simulation; MANUFACTURING-INDUSTRY; BIG DATA; FUTURE; TECHNOLOGIES; FRAMEWORK; SYSTEMS; LOGIC; DIGITIZATION; READINESS;
D O I
10.1016/j.ijpe.2020.107883
中图分类号
T [工业技术];
学科分类号
08 ;
摘要
Industry 4.0 (I4.0) aims to link disruptive technologies to manufacturing systems, combining smart operations and supply chain management (OSCM). Maturity models (MMs) are valuable methodologies to assist manufacturing organizations to track the progress of their I4.0 initiatives and guide digitalization. However, there is a lack of empirical work on the development of I4.0 MMs with clear guidelines for OSCM digitalization. There is no I4.0 MM with an assessment tool that addresses the imprecision brought by human judgment and the uncertainty and ambiguity inherent to OSCM evaluation. Here we develop a fuzzy logic-based I4.0 MM for OSCM, through a transparent and rigorous procedure, built on a multi-method approach comprising a literature review, interviews, focus groups and case study, from model design to model evaluation. To provide a more realistic evaluation, fuzzy logic and Monte Carlo simulation are incorporated into an I4.0 self-assessment readiness-tool, which is connected with the model architecture. The proposed model has been validated through a real application in a multinational manufacturing organization. The results indicate that the approach provides a robust and practical diagnostic tool, based on a set of OSCM indicators to measure digital readiness of manufacturing industries. It supports the transition towards I4.0 in OSCM domain, by holistically analyzing gaps and prescribing actions that can be taken to increase their OSCM4.0 maturity level.
引用
收藏
页数:21
相关论文
共 99 条
[81]   Conducting systematic literature review in operations management [J].
Tavares Thome, Antonio Marcio ;
Scavarda, Luiz Felipe ;
Scavarda, Annibal Jose .
PRODUCTION PLANNING & CONTROL, 2016, 27 (05) :408-420
[82]   Understanding the implications of digitisation and automation in the context of Industry 4.0: A triangulation approach and elements of a research agenda for the construction industry [J].
Thuy Duong Oesterreich ;
Teuteberg, Frank .
COMPUTERS IN INDUSTRY, 2016, 83 :121-139
[83]  
Tolk A., 2003, P FALL SIM INT WORKS, V7, P1
[84]  
Tortorella G., 2019, LEARN ORG
[85]  
Tremblay M.C., 2009, Communications of AIS, V2009, P599, DOI DOI 10.17705/1CAIS.02627
[86]  
Vose D., 2008, Risk analysis: a quantitative guide
[87]  
Voss C., 2010, Researching operations management, P176
[88]   A maturity model for blockchain adoption [J].
Wang, Huaiqing ;
Chen, Kun ;
Xu, Dongming .
FINANCIAL INNOVATION, 2016, 2 (01)
[89]   Making sense of blockchain technology: How will it transform supply chains? [J].
Wang, Yingli ;
Singgih, Meita ;
Wang, Jingyao ;
Rit, Mihaela .
INTERNATIONAL JOURNAL OF PRODUCTION ECONOMICS, 2019, 211 :221-236
[90]   M2DDM-A Maturity Model for Data-Driven Manufacturing [J].
Weber, Christian ;
Koenigsberger, Jan ;
Kassner, Laura ;
Mitschang, Bernhard .
MANUFACTURING SYSTEMS 4.0, 2017, 63 :173-178