Utilize este identificador para referenciar este registo: http://hdl.handle.net/10400.11/6063
Título: Simulation optimization: a new job release approach for Industry 4.0
Autor: Fernandes, N.O.G.
Thurer, Matthias
Pinho, Tatiana
Torres, Pedro
Carmo-Silva, Silvio
Palavras-chave: Controlled job release
Simulation
Optimization
Data: Fev-2018
Citação: Fernandes, N.O.G. [et al.] (2018) - Simulation optimization: a new job release approach for Industry 4.0. In International Working Seminar on Production Economics, 20, Innsbruck, 19-23 de Fevereiro. [S. l: s.n.]. p. 1-10
Resumo: The rise of Industry 4.0 has highlighted simulation optimisation as a decision-making tool for scheduling complex-manufacturing systems, specifically when resources are expensive and multiple jobs compete for the same resources. In this context, simulation optimisation provides an important mean to predict, evaluate and improve the short-term performance of the manufacturing system. An important scheduling function is controlled job release; jobs (or orders) are not released immediately to the shop floor, as they arrive to the production system, but release is controlled to stabilize work-in-process, reduce manufacturing lead times and meet customer delivery requirements. While there exists a broad literature on job release, reported release procedures typically use simple rules and greedy heuristics to determine which job to select for release. While this is justified by its simplicity, the advent of Industry 4.0 and its advanced scheduling techniques question its adequateness. In this study, an integer linear programming model is used to select jobs to be released to the shop floor. While there are some recent studies that use a similar procedure, these studies assume the release decision for a given set of jobs is optimized in discrete time intervals. In contrast, in this study, we analyse the impact of different triggering intervals. Experimental results for a pure flow shop support our contention that simulation optimisation as a decision-making tool for job release is likely to be too important to be overlooked
Peer review: yes
URI: http://hdl.handle.net/10400.11/6063
Aparece nas colecções:ESTCB - Comunicações em encontros científicos e técnicos

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