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Assigning Unskilled Workers on the Production Line According to the Fuzzy C-Means Clustering Method

机译:根据模糊C-Means聚类方法在生产线上分配非熟练工人

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摘要

Based on the recent trend toward higher consumer demand for customized products, the possibility of mass customization has become a topic of great importance for companies. In order to deal with seasonal fluctuations in demand, most companies require flexible scheduling of the manpower involved in product assembly; one means of achieving this flexibility is by hiring dispatch laborers. Ensuring the productivity of new employees and their departments under conditions of continuous employee turnover on the production line has become an essential element of the modern manufacturing business. This research uses the fuzzy c-means clustering method to develop a new model for evaluating employees' ability to perform on the production line and identifying which operational capabilities are suitable for each employee. This study used a personal computer assembly process as an empirical analysis case. The results show that this evaluation model enables users to accurately determine what new employees are good at, which will inform them where each employee should be assigned so that the products can be assembled most efficiently. Our evaluation model can not only provide companies with a reference and judgment basis for more efficient staffing, but also help them reduce lead time when changing production lines or production line configurations and increase their production efficiency and profit.
机译:根据最近对定制产品的更高消费需求的趋势,大规模定制的可能性已成为对公司非常重要的话题。为了处理需求的季节性波动,大多数公司都需要灵活调度产品组装的人力;实现这种灵活性的一种方法是通过招聘派遣劳动者。确保新员工及其部门在生产线上持续员工营业额的条件下成为现代制造业业务的基本要素。该研究使用模糊的C-MEARELEARING方法开发用于评估员工在生产线上执行能力的新模型,并识别哪些操作能力适用于每个员工。本研究使用个人计算机组装过程作为经验分析案例。结果表明,该评估模型使用户能够准确地确定新的员工擅长哪些擅长,这将向他们通知他们,其中应该为每个员工分配,以便最有效地组装产品。我们的评估模型不仅可以为更高效的人员配置提供参考和判断基础,还可以帮助他们减少生产线或生产线配置并提高生产效率和利润时减少延长时间。

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