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目前在服装企业小批量生产中,工时定额通常只能作为静态指标,而不能反映工时的动态变化,应用学习曲线制定动态工时定额是解决这一问题的有效方法。该方法通过拟合流水线的学习曲线确定批量系数,根据不同的批量条件用批量系数对标准工时进行修正,从而满足了工时动态管理的需要。该方法通过实例验证可行,使企业能获得更精确的基础管理数据,应用于成本核算、生产计划编制和劳动报酬支付等工作环节。
At present, in the small-batch production of apparel enterprises, the working hour quota is usually only used as a static indicator, which can not reflect the dynamic changes of working hours. It is an effective way to solve this problem by using the learning curve to formulate dynamic working hours quota. The method determines the batch coefficient by fitting the learning curve of the pipeline, and modifies the standard man-hour with the batch coefficient according to different batch conditions so as to meet the requirement of dynamic management of working hours. The method is validated through examples, enabling enterprises to obtain more accurate basic management data and apply them to the work processes such as cost accounting, production planning and payment of labor remuneration.