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首页> 外文期刊>International Journal of Computer Integrated Manufacturing >Prediction and analysis impact of operational design of a manual assembly system with walking workers on performance
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Prediction and analysis impact of operational design of a manual assembly system with walking workers on performance

机译：预测和分析具有步行工人的手动装配系统的运营设计对性能的影响

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摘要

Manual assembly lines, with workers travelling with the work along the line to perform all required tasks, are an example of assembly systems which have greater flexibility over traditional systems due to an improved response to product demand variability. Implementing assembly systems in this way is difficult, especially when operational design reflects an incomplete understanding of how workers can best perform within the system. Different operational designs for such systems have a profound impact on the performance of the system in terms of productivity and ergonomics. This paper analyses the performance of walking worker assembly line (WWAL) in different operational designs. A mathematical model was developed, which considers the effects of a number of operational design variables. An industrial case study is presented here to demonstrate the effectiveness of the proposed model. The results indicate that WWAL can be designed to improve performance, flexibility and labour costs by approaching productivity and ergonomics collaboratively. The results obtained by the model prediction were compared with computer simulation results. Comparison validated the accuracy of the proposed model. The model provides partial characterisations of the optimal design of WWAL and can be used to develop heuristics for local or global optimisation.
机译：人工装配线，工人沿着生产线行进以执行所有必需的任务，是装配系统的一个示例，由于对产品需求可变性的改进响应，装配系统比传统系统具有更大的灵活性。以这种方式实施组装系统非常困难，尤其是当运营设计反映出对工人如何在系统中最佳执行情况的不完全理解时。在生产率和人体工程学方面，此类系统的不同操作设计对系统性能产生深远影响。本文分析了步行操作员装配线（WWAL）在不同运营设计中的性能。开发了一个数学模型，该模型考虑了许多操作设计变量的影响。这里提供了一个工业案例研究，以证明所提出模型的有效性。结果表明，WWAL可以设计为通过协同处理生产力和人体工程学来提高性能，灵活性和人工成本。通过模型预测获得的结果与计算机仿真结果进行了比较。比较验证了所提出模型的准确性。该模型提供了WWAL最佳设计的部分特征，可用于开发启发式算法以进行本地或全局优化。

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