A framework for designing supply chain disruptions management considering productive systems and carrier viewpoints. Issue 15 (3rd August 2018)

• Record Type: Journal Article
• Authors: Blos, Maurício Fontoura; da Silva, Robson Marinho; Wee, Hui-Ming
• Is Part Of: International journal of production research. Volume 56:Issue 15(2018)
• Page Start: 5045
• Page End: 5061
• Publication Date: 2018-08-03
• Subjects: supply chain risk management -- disruption management -- Petri nets -- agent-based systems -- supply chain design; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2018.1442943
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : With the advent of the global and digital world, the number of geographically dispersed firms throughout the world has increased and the problem of Supply Chain (SC) disruption appeared as a main concern to many industries. In such context, designing disruptions management strategies for a robust SC has become a critical worldwide issue that is still under-explored. Since its design phase, this class of robust and global SC must integrate technologies and agents of production. However, the existing works only consider the Productive Systems (PSs) and the carrier viewpoint must also be considered since goods should be produced and distributed at the right quantity, at the right place and at the right time. In this complex task of designing disruptions management, a formal method must be used to integrate technologies ensuring the compliance of certain requirements, such as: developing collaborative and autonomous models, allowing reuse templates, considering analysis/simulation abilities and facilitating the interaction among engineering practitioners. Therefore, this paper presents a framework to model, analyse, control and monitor the robust and global SC, designing and integrating models with Petri Net, agent-based model techniques for disruptions management and considering both PSs and carrier viewpoints. A case study is investigated and the findings demonstrated the proposed solution supports decisions making for solving problems of design, analysis and control.