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A method of garment factory workers' performance monitoring using control chart based on RFID system

机译:一种基于RFID系统的控制图表的服装厂工人性能监控方法

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摘要

Massive production data of front-line workers are recorded every day by RFID system in garment factory, which are mainly in multiple variety and small batch production. To maintain productivity and consistency of front workers, a technique is proposed to monitor the mean and variance of front-line workers' production time based on the recorded data to avoid bottleneck operation. Results of monitoring can be used to schedule allocations and workers' performance assessment. Two front-line workers' SPC control charts are made as examples, and procedures are given simultaneously: changing batch data to daily data; finding critical point of the process, after the critical point, the process is stable; making SPC control charts to monitor both mean and variance of workers. The first 7 to 10 days data are utilized to build optimal hyperbolic curve models to find critical point for the process; mean of monitored variables are forecasted after about 10 days of production. Stable data after critical point are utilized to make control charts, to monitor both mean and variance of monitored variables.
机译:通过RFID系统在服装厂的每天都记录了前线工人的大规模生产数据,主要在多种品种和小批量生产中。为了维持前工人的生产力和一致性,提出了一种基于记录数据的前线工作人员生产时间的均值和方差,以避免瓶颈操作。监测结果可用于安排拨款和工人的绩效评估。两个前线工人的SPC控制图表是例子,并同时给出程序:将批量数据更改为日常数据;发现过程的关键点,临界点后,过程稳定;制作SPC控制图以监测工人的均值和方差。前7到10天数据用于构建最佳的双曲线曲线模型,以找到过程的关键点;在大约10天的生产后预测了监测变量的平均值。在关键点进行稳定数据以进行控制图,以监测监控变量的均值和方差。

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