Journal
ENGINEERING APPLICATIONS OF ARTIFICIAL INTELLIGENCE
Volume 47, Issue -, Pages 140-146Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.engappai.2015.03.005
Keywords
Mixed-model assembly line; Mental workload; Rolled throughput yield (RTY); Efficiency; Genetic algorithm; Multi-objective optimization
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Funding
- National Natural Science Foundation of China [70931004]
- National Science Foundation for Distinguished Young Scholars of China [71225006]
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The increasing complexity of product varieties and productions leads to higher mental worldoad in the mixed-model assembly line (MMAL). Mental workload can improve product quality and guarantee the efficiency simultaneously. However, little research has been done on balancing the production quality and efficiency based on the effect of mental workload and complexity in the MMAL. This study aims to propose a mathematical model to formulate the multi-objective MMAL problem and the genetic algorithm is applied for problem solving due to the computational complexities. A numerical example is used to demonstrate the effectiveness of the proposed approach. The results show that incorporating the impact of mental workload on performance into account can make the rolled throughput yield (RTY) and efficiency balance when designing the MMAL. Moreover, we also verify that improving the experience of the operators can mitigate the impact of mental workload on the quality and efficiency. (C) 2015 Elsevier Ltd. All rights reserved.
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