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Abstract：
In the production of air conditioners, there are various issues such as complex requirements, redundant stations, excessive man-hours, and low production line balance rate. This paper aims to address these problems by analyzing the historical data of H Company\'s commercial air conditioner production line. The data is categorized into five aspects: station, working hours, standard working hours, labor capacity, and presence of bottleneck processes. To optimize and improve the second production line, this paper applies the production line balance management method based on data mining. It utilizes the decision tree model in data mining and incorporates lean production knowledge from industrial engineering. The goal is to identify crucial factors that affect the balance of the production line and address the issues caused by these factors. The aim is to reduce and eliminate redundant working hours and enhance the balance rate of the production line. By implementing the approach outlined in this paper, the bottleneck time of the second production line was reduced from 96.67 s to 74.6 s, and the production line balance rate increased from 68% to 85%.
摘要：
在空调生产中,有各种问题，如复杂的要求，冗余站,过多的工时,和低生产线平衡率。本文旨在通过分析H公司商用空调生产线的历史数据来解决这些问题。数据分为五个方面：站，工作时间,标准工作时间,劳动能力,以及瓶颈过程的存在。优化和完善第二条生产线，本文应用了基于数据挖掘的生产线平衡管理方法。它利用数据挖掘中的决策树模型，并结合了工业工程中的精益生产知识。目标是确定影响生产线平衡的关键因素，并解决由这些因素引起的问题。目的是减少和消除多余的工作时间，提高生产线的平衡率。通过实施本文概述的方法，第二条生产线的瓶颈时间从96.67s减少到74.6s，生产线平衡率从68%提高到85%。
