Job shop schedules analysis in the context of industry 4.0
| Autor: | Maria Leonilde Rocha Varela, José Machado, Cláudio Alves, R. A. Sousa |
|---|---|
| Přispěvatelé: | Universidade do Minho |
| Jazyk: | angličtina |
| Rok vydání: | 2017 |
| Předmět: |
0209 industrial biotechnology
Science & Technology Job shop scheduling Operations research Industry 4.0 Job shop Computer science business.industry Tardiness makespan Context (language use) 02 engineering and technology heuristics 020901 industrial engineering & automation Shifting bottleneck heuristic tardiness 0202 electrical engineering electronic engineering information engineering job shop scheduling 020201 artificial intelligence & image processing dispatching rules business Enterprise resource planning Manufacturing execution system |
| Zdroj: | ICE/ITMC |
| Popis: | Industry 4.0 is announced as a fourth industrial revolution. The next level of evolution will comprehend the wide spread inclusion of machines sensors and big data analytics. Enterprise Resource Planning and Manufacturing Execution Systems will be the information management tools for the revolution. Different forms of optimization will be in the brink of development to answer this revolution needs. In this paper is proposed a model for solving a classical job shop scheduling problem, which is NP-hard in the strong sense. For accomplishing this, a test problem is run to evaluate the difference between the performance of Shifting Bottleneck Heuristic (SBH) and some dispatching rules, such as First Come First Served (FCFS), Earliest due Date (EDD), and Shortest Processing Time (SPT). The evaluation criteria used were the makespan (Cmax) and the total weighted tardiness (TWT). The results did show that the SBH outperforms the dispatching rules, although the computation time turns out to be considerable higher. This work has been supported by FCT- Fundacao para a Ciencia e Tecnologia of Portugal under the project PEst2015-2020: UID/CEC/00319/2013. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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