統計製程管制(Statistical Process Control, SPC)是一種用來分析資料的科學方法,並且利用分析結果來解決實際的問題,是監控製程品質一個非常重要的方法。 實驗設計法(Design Of Experiment, DOE)是探討實驗應如何進行與分析的學問,它強調利用最少的資源在短的時間內,將產品或製程的最佳參數條件尋找出來,是開發企業Know How的一項重要工具。 本研究將運用實驗設計以及統計製程管制,以A公司之銲線能力改善為例,找出產生問題的重要製程參數並找出各因子之相關性,藉由評估多個操作變數對系統性能的影響效應,以及各變數間的交互影響效益;再透過實驗找出最佳的操作變數並利用實驗設計法來建立製程模型,以達到最佳的生產製程及生產條件的最佳化。 本研究所使用的方法、程序,可應用於各種產業製程,盼本研究之內容,可做業界的學習參考依據,面對快速激烈競爭的時代裡,能建構出一套優質的製程技術提升管理體系,才能增強公司企業的競爭力,藉此使其能不斷的創新與進步,而使公司企業能永續經營、基業長青。
Statistical Process Control is a scientific method used for data analysis. The analysis result is then used to solve specified problems. This is an important method for monitoring process quality. The design of experiments method probes into how the experiment should be conducted and analyzed. It places emphasis on utilizing the least resources in the shortest time to identify the best parameter levels for products or processes. DOE is an important tool for developing enterprise Know How. This study integrates the design of experiments and statistical process control techniques in identifying the crucial process parameters and further locating their inter-dependences. The multi-variable effects versus system performance and the interacted impact benefits among process parameters are assessed using the various settings. This study identifies the initial optimal operational variables via experiments to develop a process model using the design of experiment method to achieve the best production process. All methods and procedures used in this research can be applied to the manufacturing processes of different industries. Hopefully, the content in this research can be a reference for lessons learned in industry. Living in this era of rigorous and rapid competition, we need to build a set of superior process technologies to promote effective management systems. Thus, we will be able to increase our companies’ competitive ability. We can improve and progress continually and keep the companies’ operation moving.
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