Job shop schedules analysis in the context of industry 4.0

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....

ver descrição completa

Detalhes bibliográficos
Autor principal: Sousa, R. A. (author)
Outros Autores: Varela, M.L.R. (author), Alves, Cláudio (author), Machado, José (author)
Formato: conferencePaper
Idioma:eng
Publicado em: 2017
Assuntos:
Texto completo:http://hdl.handle.net/1822/62963
País:Portugal
Oai:oai:repositorium.sdum.uminho.pt:1822/62963
Descrição
Resumo: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.