由於半導體封裝測試產業位於全球半導體供應鏈之末端，因此深受長鞭效應之影響。各廠商因而無不極力於以提升生產效率為主要工具來降低生產成本提升競爭力以因應此產業現況。
文獻探討顯示以往研究中之生產成本模式並未將衡量生產效率之重要指標OEE (Overall Equipment Effectiveness)納入其成本模式之中。然而實務上不同產品製程作業特性將導致生產效率OEE有相當之差異，連帶的實際生產成本也有顯著的不同。因此本研究提出一個替代傳統半導體產業標準SEMI定義的OEE指標，並使之更能適切地反應產品製程特性造成之成本差異而應用於本研究提出之成本模式之中。在此模式實務運用於實際產業案例中，發現不同產品生產效率之差異的確影響生產成本甚鉅並驗證了此模式的可行性。
雖然前述成本模式之提出讓吾人知道生產效率的重要性，然而實際運用該模式之時資料的正確性將是一大問題。以往產業進行生產效率資料收集及分析之後往往會發現一大問題，亦即傳統的例行資料收集方式均需依賴作業者輸入一些資料，總會有不明原因歸屬的生產效率損失無法知悉其損失原因。此外傳統機台標準單位小時產出UPH (unit-per-hour machine rates) 是一種理論性的理想概念，實務上UPH是隨機台參數持續動態變化的，取得可靠數值並不容易。
因此，本研究延續成本模式之提出後，接著為了解決OEE損失之原因分析以及實際UPH取得問題提出了一個整合的IT技術，將半導體封裝瓶頸機台『打線機(wire bonder)』機台的資料傳輸藉由其KNetTM (K&S wire bonder製造商所發展)系統傳出與MES (Manufacturing Execution System) 連結構成一個自動化資料收集系統 ADC (Automated Data Collection) 。這個實例應用結果解決了動態UPH的取得問題並且原本未知的OEE損失高達6% 降至幾乎近於零。

The semiconductor assembly and testing industry is at the tail-end of the semiconductor supply chain and thus is deeply influenced by the bull-whip effect. Thus raising production efficiency as a means to reducing production cost is an important issue in this industry.
Previous literatures show that most researches do not include the OEE (Overall Equipment Effectiveness) effect in their cost models. However, depending on the product characteristics, each has its own OEE, therefore, the net profit for each product could well be significantly different. To develop the cost model with OEE, we propose an alternative OEE without idle time and integrate it into the cost model. The sensitive analysis for the proposed cost model is derived to analyze the net profit drew from OEE improvement. The data from a case study of a semiconductor assembly and testing company is used to substantiate the proposed model. The results show that the proposed cost model provides an alternative method to analyze cost and net profit for different product.
However, it is very hard to collect the reliable and accurate data. One will find the unknown differences between the recorded losses from their operational system and OEE losses once people implement OEE. Furthermore, how to obtain the theoretical unit throughput or standard UPH (unit-per-hour machine rates) to determine the average processing rates of a equipment is another issue to be conquered.
In this study, after cost model with OEE is proposed and demonstrated, we also develop an IT integrated system to record the time intervals of OEE losses for the bottleneck equipment “wire bonder” to improve data integrity in the semiconductor assembly industry. We integrate a KNetTM system (developed by the wire bonder supplier “K&S“) and MES (Manufacturing Execution System) into an ADC (Automated Data Collection) system for collecting useful data. The application of the ADC system has eliminated the unknown OEE losses from original 6% of manual recording system.

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