A dynamic model and an algorithm for short-term supply chain scheduling in the smart factory industry 4.0. Issue 2 (17th January 2016)

• Record Type: Journal Article
• Authors: Ivanov, Dmitry; Dolgui, Alexandre; Sokolov, Boris; Werner, Frank; Ivanova, Marina
• Is Part Of: International journal of production research. Volume 54:Issue 2(2016)
• Page Start: 386
• Page End: 402
• Publication Date: 2016-01-17
• Subjects: supply chain scheduling -- smart factory -- structure dynamics -- flexible flow shop -- alternative machines -- optimal programme control; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2014.999958
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : Smart factories Industry 4.0 on the basis of collaborative cyber-physical systems represents a future form of industrial networks. Supply chains in such networks have dynamic structures which evolve over time. In these settings, short-term supply chain scheduling in smart factories Industry 4.0 is challenged by temporal machine structures, different processing speed at parallel machines and dynamic job arrivals. In this study, for the first time, a dynamic model and algorithm for short-term supply chain scheduling in smart factories Industry 4.0 is presented. The peculiarity of the considered problem is the simultaneous consideration of both machine structure selection and job assignments. The scheduling approach is based on a dynamic non-stationary interpretation of the execution of the jobs and a temporal decomposition of the scheduling problem. The algorithmic realisation is based on a modified form of the continuous maximum principle blended with mathematical optimisation. A detailed theoretical analysis of the temporal decomposition and computational complexity is performed. The optimality conditions as well as the structural properties of the model and the algorithm are investigated. Advantages and limitations of the proposed approach are discussed.