Product quality for mixed model assembly system considering emotion

被引：0
作者：
Zhao X. [1 ]
Chen K. [1 ]
Zhang M. [1 ]
Liu N. [1 ]
机构：
[1] College of Management and Economics, Tianjin University, Tianjin
来源：
Jisuanji Jicheng Zhizao Xitong/Computer Integrated Manufacturing Systems, CIMS | 2023年 / 29卷 / 03期
基金：
中国国家自然科学基金;
关键词：
complexity; emotion; mixed model assembly system; product quality; quantum genetic algorithm;
D O I：
10.13196/j.cims.2023.03.010
中图分类号：
学科分类号：
摘要：
Aiming at the problem that operator's emotion state affected the product quality in production system, based on choice complexity and operator's emotion, an optimization model for product quality of the mixed-model assembly line was established by taking Rolled Throughput Yield (RTY) as the optimization objective. Quantum genetic algorithm was applied to solve the model, the segmental encoding was used to effectively deal with continuous and discrete variables, the mutation based on tabu search was used to enhance the global search ability of the algorithm. The effectiveness of the model and the improvement effect of the algorithm were verified by the example. The results showed that the emotion state of operators had a great influence on the rolled throughput yield of assembly system. Emotional factors could increase the RTY of assembly system by optimizing the operator's emotion type and arousal degree, which could further improve the product quality based on complexity optimization. © 2023 CIMS. All rights reserved.
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页码：801 / 810
页数：9
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共 36 条
  • [1] RADATZ H, SCHRODER H, BECKER C, Et al., Selection of equipment modules for a flexible modular production plant by a multi-objective evolutionary algorithm[j], Computers 6- Chemical Engineering, 123, pp. 196-221, (2019)
  • [2] DI-PASQUALE V, MIRANDA S., NEUMANN E P., Et al., Human reliability in manual assembly systems: A systematic literature review [J], IFAC-PapersOnLlne, 51, 11, pp. 675-680, (2018)
  • [3] INZLICHT M., BARTHOLOW B D, HIRSH J B., Emotional foundations of cognitive control[J], Trends in Cognitive Sciences, 19, 3, pp. 126-132, (2015)
  • [4] FALCK A C, ORTENGREN R, ROSENQVIST M, Et al., Basic complexity criteria and their impact on manual assembly quality in actual production[J], International Journal of Industrial Ergonomics, 58, pp. 117-128, (2017)
  • [5] DI-PASQUALE V, MIRANDA S, IANNONE R, Et al., A Simulator for Human Error Probability Analysis (SHERPA), Reliability Engineering & System Safety, 139, pp. 17-32, (2015)
  • [6] OTTO A, BATTAIA, Reducing physical ergonomic risks at assembly lines by line balancing and job rotation: A survey, Computers & Industrial Engineering, 111, pp. 467-480, (2017)
  • [7] ZHAO Xiaosong, ZHAO Shumeng, LIU Na, Et al., Balance problem of mixed flow assembly line considering fatigue and recovery[J], Journal of Systems Engineering, 35, 2, pp. 265-275, (2020)
  • [8] KOMBEIZ O, DIETL E., Light as a positive situational cue at work: Satisfaction with light relates to judgements of other s warmth and competence, Ergonomics, 62, 8, pp. 995-1007, (2019)
  • [9] BROUN A, THORVALD P, CASE K., Experimental study of cognitive aspects affecting human performance in manual assembly[J], Production & Manufacturing Research, 5, 1, pp. 141-163, (2017)
  • [10] ABDOUS M A, DELORME X, BATTINI D, Et al., Multi-objective optimization of assembly lines with workers fatigue considerationQ, IFAC-PapersOnLine, 51, 11, pp. 698-703, (2018)
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