實施PDCA改善設備綜合產能效率(OEE)之研究-以封裝挑揀產線為例

A study of Applying PDCA on Improving Overall Equipment Production Efficiency (OEE)- A Case Study of Packaging picking production line

魏瑞慶(Wei Jui-Ching)

指導教授 ： 邱皓政

國立臺灣師範大學/管理學院/高階經理人企業管理碩士在職專班(EMBA)/碩士(2021年)

https://doi.org/10.6345/NTNU202100038

摘要

台灣半導體產業因同業競爭越來越激烈，製程及設備人員需做出有效的分析與規劃，徹底掌握生產設備及產品之生產效能需求降低時間成本，進而提升產品產能與公司的競爭力。故本研究針對製程及設備產能之需求加以全盤分析考量及改善，依據實際生產資料比較及製程改善進行設備修正幫助管理階層以綜觀全局的角度降低設備生產週期時間(cycle time)、維修時間、消除產能瓶頸、以提升設備產能利用率降低設備採購成本支出持續進行改善提高公司獲利及企業競爭優勢，並利用時間序列分析的方式，建立統計預測模型，以精進半導體製程機台生產效率。本研究透過2017年10月8日至2018年2月8日，共四個月16台封裝機檯實際產線資料為研究樣本。將Uph(每單位小時產能)、Totally time(完全生產時間)、Postplace(後位)、Wrong work state(工作狀態錯誤)、Down Time(設備停機時間)及MTTA(Max) (平均協助時間)等變數的變化圖像化，解讀各變數於PDCA管理模式下的變化情形，接著建構ARIMA 模型，進行時間序列分析。
研究發現PDCA管理模式控管相當有效，當Postplace時間周期變化時，Wrong work state則呈現平穩的狀態; 在本研究期間中UPH微幅上升，Totally time明顯下降趨勢;Down Time & MTTA(Max)呈現正相關係。根據本研究的結果，得到下列結論，第一，如能控管好製程過程中Postplace時間周期變化，將能夠減少Wrong work state的發生。第二，不斷的執行PDCA模式，可將錯誤持續反饋更正，使得錯誤訊息變少，且機台效能穩定成週期性，利於操作人員控管機台。第三，UPH在整體機台的控制下相對穩定，公司需更加著重於各機台Totally time的控管。公司需有效地降低MTTA(Max)時間，以降低Down Time。最後，公司可聘用專門負責處理統計數據的人才，以協助各機台的數據處理，並將處理好的資料提供給相關技術人員及管理階層。
綜上，後續可針對半導體產業統計分析人才作為主題，加以研究半討體業與資料分析兩者間關係；同時可加入更多管理學要素，探討如何控管以分配半導體管理階層、技術人員及分析人員，以達到半導體業產能效益的極大化。

關鍵字

PDCA ； 設備總合效率( OEE ) ； Pick & Place ； UPH ； ARIMA模型 ； 時間序列分析

並列摘要

Due to the increasingly fierce competition in the Taiwan semiconductor industry, process and equipment personnel need to make effective analysis and planning, thoroughly master the production equipment and product production efficiency requirements to reduce time costs, and thereby enhance product production capacity and the company's competitiveness. Therefore, this research aims at the overall analysis, consideration and improvement of the requirements of the production process and equipment capacity. Based on the above-mentioned data comparison and process improvement, equipment modification is carried out to help the management to reduce the equipment production cycle time (cycle time), maintenance time, and eliminate production capacity from an overall perspective. Bottlenecks, improve equipment capacity utilization, reduce equipment procurement costs and continue to improve the company’s profitability and corporate competitive advantage.From October 8, 2017 to February 8, 2018, a total of four months of packaging machine operation data, Uph (per unit hour capacity), Totally time (full production time), Postplace (postplace), Wrong The work state (work state error), Down Time (equipment down time) and MTTA (Max) (mean assist time) and other variables are visualized, and the changes of each variable under the PDCA management mode are interpreted, and then the ARIMA model is constructed. According to the results of this research, the following conclusions are drawn. First, if the Postplace time period change during the manufacturing process can be controlled, the occurrence of Wrong work state will be reduced. Second, the continuous implementation of PDCA mode can continuously feedback and correct errors, so that there are fewer error messages, and the machine performance is stabilized periodically, which is beneficial for the operator to control the machine. Third, UPH is relatively stable under the control of the overall machine, and the company needs to pay more attention to the total time control of each machine. The company needs to effectively reduce the MTTA (Max) time to reduce the Down Time. Finally, the company can hire talents who specialize in processing statistical data to assist in the data processing of each machine, and provide the processed data to relevant technical personnel and management.
Based on the results of this research, the following conclusions are drawn. First of all, if the Postplace time period change in the manufacturing process can be controlled, it will reduce the occurrence of erroneous working conditions. Secondly, the continuous execution of PDCA mode can continuously feedback and correct errors, thereby reducing error messages and stabilizing machine performance on a regular basis, which is very beneficial for the operator to control the machine. Third, UPH is relatively stable under the control of the entire machine, so the company needs to pay more attention to the total time control of each machine. Companies need to effectively reduce the MTTA (maximum) time to reduce downtime. Finally, the company can hire talents who specialize in processing statistical data to assist in the data processing of each machine, and provide the processed data to relevant technical personnel and management personnel.
To sum up, we can focus on the statistical analysis talents of the semiconductor industry as the theme, and study the relationship between the semi-discussive industry and data analysis; at the same time, we can add more management elements to discuss how to control and allocate semiconductor management, technical personnel and Analysts in order to maximize the efficiency of the semiconductor industry.

並列關鍵字

PDCA ； Total equipment efficiency (OEE) ； Pick & Place ； UPH ； ARIMA model ； Time series analysis

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