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首页> 外文期刊>International Journal of Production Research >Learning curve modelling of work assignment in mass customized assembly lines
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Learning curve modelling of work assignment in mass customized assembly lines

机译：在批量定制的装配线中学习工作分配的曲线建模

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In customized markets, a large variety of product models is demanded by customers. That requires fast set-up of production resources to comply with specifications of the next model to be produced. Such compliance, however, may cause considerable production and quality losses owing to workers' poor performance during the initial production runs of a new model. Therefore, modelling workers' learning upon exposure to each product model may help production managers to define the best assignment scheme for models and workers, such that losses in the initial stages of production are minimized. The current paper presents a method that uses learning curves to guide the best assignment of product models to teams of workers. Product models are first clustered into families based on their similarities, aiming at a smaller data collection to generate the learning curves. Allocation of product families to teams is then carried out, based on the analysis of their corresponding learning curves. Two courses of action are proposed for this, depending on whether the production batch will lead to longer or shorter production runs. The proposed methodology is illustrated in a case study from the shoe manufacturing industry.
机译：在定制市场中，客户需要各种各样的产品型号。这要求快速设置生产资源，以符合要生产的下一个型号的规格。但是，由于工人在新型号的首次生产过程中表现不佳，因此这种合规性可能会导致可观的生产和质量损失。因此，对工人在接触每种产品模型时的学习进行建模可以帮助生产经理为模型和工人定义最佳分配方案，从而将生产初期的损失降到最低。当前的论文提出了一种使用学习曲线来指导产品模型对工人团队的最佳分配的方法。首先基于产品模型的相似性将它们分为不同的系列，旨在通过较小的数据收集来生成学习曲线。然后根据对产品系列的相应学习曲线的分析，将产品系列分配给团队。为此提出了两个行动方案，这取决于生产批次将导致更长或更短的生产周期。鞋类制造业的案例研究说明了所提出的方法。

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