Sustainable Scheduling of an Automatic Pallet Changer System by Multi-Objective Evolutionary Algorithm with First Piece Inspection

In this study, the machining center with the Automated Pallet Changer (APC) scheduling problem considering the disturbance of the first piece inspection is presented. The APC is frequently used in industry practice; it is useful in terms of sustainability and robustness because it increases the mach...

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Vydáno v:Sustainability Ročník 11; číslo 5; s. 1498
Hlavní autoři: Liao, Qingmiao, Yang, Jianjun, Zhou, Yong
Médium: Journal Article
Jazyk:angličtina
Vydáno: Basel MDPI AG 12.03.2019
Témata:
algorithms
Automation
genes
Genetic algorithms
Job shops
manufacturing
Preventive maintenance
Process planning
Production scheduling
risk
simulation models
Studies
Sustainable development
uncertainty
United States > US
China
ISSN:2071-1050, 2071-1050
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Shrnutí:In this study, the machining center with the Automated Pallet Changer (APC) scheduling problem considering the disturbance of the first piece inspection is presented. The APC is frequently used in industry practice; it is useful in terms of sustainability and robustness because it increases the machine utilization rate and enhances the responsiveness to uncertainties in dynamic environments. An enhanced evolutionary algorithm for APC scheduling (APCEA) is developed by combining the multi-objective evolutionary algorithm with APC simulation. The dynamic factors in the simulation model include the pass rate of the first piece inspection (FPI) and the adjusted time when the FPI is unpassed. The proposed APCEA defines the non-robust gene based on the risk combination of the first piece inspection, and screens the non-robust gene in the genetic operation, thus improving the solution quality under the same computation times. Compared with the other three multi-objective evolutionary algorithms (MOEAs), it is demonstrated that the proposed APCEA produces the best result among the four methods. The proposed APCEA has been embedded into the manufacturing execution system (MES) and successfully applied in a manufacturing plant. The application value of the proposed method is verified by a practical example.
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ISSN:2071-1050
2071-1050
DOI:10.3390/su11051498