對晶圓代工產業而言：生產的彈性及穩定的高良率是競爭優勢之所在，為維持這兩項核心能力，企業必須持續改進製程以提高生產績效。Vadgama, Trybula (1996)曾對晶圓廠生產績效之改善提出建議方案：作者認為將模型工具與作業制成本制整合的管理方式，可辨認出對生產績效具有重大影響的生產區域，再以作業分析找出影響因素並提出相對應的解決方案，進而達到持續改善的目標。 本研究擬以個案公司作業制成本制為分析的基礎資訊系統，以「作業」的資訊進行生產績效影響因素的分析，期能分析出生產績效的影響因子，並找出其與生產績效之關係，管理當局即可根據策略目標，藉由持續改善影響因素來達成企業的生產績效目標。 本研究係以實地(Field)及實地實證(Field Empirical)研究的方式進行，以國內某積體電路製造公司為研究對象。並透過實地對個案公司進行觀察、訪談及書面閱讀的方式，瞭解個案公司特色，以形成本研究的研究假說。 本研究將晶圓廠內影響生產績效的因素分為排程因素、派工因素及監控因素三大類。 （一）排程因素對生產績效之影響 就排程因素來看，生產需求影響生產計畫，因此產品複雜性、生產控制活動可能都是生產排程必須考量的因素，而這些因素亦可能進一步對生產績效造成影響。 （二）派工因素對生產績效之影響 就生產現場而言，原料投入時點、機台派工規則、機台運用狀況及批量大小等因素都會綜合影響生產效率與效果，因此若能有系統的將這些因素組織起來，再進一步探討其對生產績效的影響程度高低，將有助管理者決定改善的重點及資源的調配。 （三）監控因素對生產績效之影響 晶圓製造過程要求之精密度、潔淨度相當高，也使得製程中常有許多無法預期的變異發生，因此「檢查」、「重製」與「廢棄」可視為晶圓製造過程中的必要支出。 透過迴歸分析，本研究之結果如下： （一）排程因素對生產績效之影響 排程因素之代理變數包括：製程技術、光罩層數、製程優先順序與製程配方種類數。 就成本、生產週期時間與良率而言：緊急批量制度之採用確實能達到縮短生產週期時間的效果，但是卻會增加該批量之生產成本且降低其良率表現。 就成本因素而言：製程技術愈複雜、光罩層數愈多、製程配方筆數愈多，生產成本自然較高。 就生產週期時間而言︰顯示光罩層數每多一層，約需多耗費一個工作天；製程技術複雜性與製程配方筆數並不會影響生產週期時間，這樣的訊息對於交期的評估將具有一定的參考價值。 就良率而言︰愈新世代製程、製程配方筆數愈多，其良率表現愈差。 （二）派工因素對生產績效之影響 派工因素之代理變數包括：批量大小、批次待機時間、保養維護時間與當機時間。 就成本、生產週期時間與良率而言：保養維護時間愈短將可反應出較低的成本、較短的生產週期時間與較高的良率表現。 就成本而言︰批量愈接近滿批（25片），該批之總成本愈低，顯示控片、擋片等間接物料之支出，在ABC制度下獲得充分反應，相當值得生產單位進行併單、拆單時之參考︰「批次待機時間」之結論並不合理，經訪談廠方工程師後發現：樣本選取期間之產能利用率達100%，此時之待機時間相當短（每批次之平均值為0.98秒），此變數之具體影響必須進一步研究，才能得到驗證。 就良率而言︰愈接近滿批，良率表現愈佳，這應該也是控片、擋片制度採用之原因︰就「批次待機時間」而言，樣本期間之待機時間相當短，無法據以判斷對良率之影響︰而「當機時間」未達顯著水準，意味著無法解釋良率之變化。 （三）監控因素對生產績效之影響 監控因素之代理變數為晶圓重製片數。 晶圓重製決策將具體影響生產成本；晶圓重製與否無法據以解釋生產週期時間之長短；就良率而言︰重製與良率之間並未具有解釋關係。 根據實地實證研究結論，針對個案公司與後續研究者之建議如下所述： （一）對個案公司之建議 本研究所選定之影響變數可分為幾類，包括：產品特性相關，如製程技術複雜性與光罩層數；作業動因相關，如待機時間、保養維護時間、當機時間；生產管理相關：緊急批量、批量大小、機台設定次數、晶圓重製。 1.產品特性相關 若能以ABC為骨幹，結合作業分析與上述實證結果，在市場導向與目標成本概念下，組成跨功能之產品開發團隊，不僅能縮短開發時間，降低技術移轉造成之誤差，並在短期內提升新製程技術的生產績效，保有生產高複雜性產品組合所應具備之彈性。 就「獲利分析」而言，透過ABC成本資訊，依顧客獲利分析、產品獲利分析之結論，作為客戶篩選與產品技術組合比重之參考。 2.作業動因 在ABC系統下，應可建立作業動因分析的機制，據以評估待機時間、保養維護時間與當機時間之影響及效益，若能藉此導入品質成本之概念，將過去品質管理之相關措施，以預防性支出、鑑定性支出、內部失敗成本、外部失敗成本等方式將品質作業具體數字化，透過定期的覆核與檢視，不僅能評估品質保證暨可靠性政策之成本效益，亦能滿足管理者進行例外管理之需求。 3.生產管理制度 依此模式建立一套生產績效影響因素之分析模型，透過統計方法，分析各變數對績效表現之具體影響為何？並排定解決上述問題之優先順序，進行專案管理，若再加上ABC所提供之作業分析資訊，將能使問題的焦點明確至作業(Activity)層級，自然能兼具"Do The Right Things"及"Do The Things Right"之效。 （二）對未來研究之建議 1.依生產區域，進行影響因素之分析，研究結果將更具管理價值。 2.透過實證模型發展出一套綜合生產績效指標，以滿足績效管理之需求。 3.以品質成本之概念，配合作業制成本制之作業屬性，分析預防性支出、鑑定性支出、內部失敗成本與外部失敗成本對生產績效表現之影響。

Manufacturing performance measures the extent to which the manufacturing plant has built capabilities like low cost, high quality, delivery, and flexibility. The importance of identifying drivers of these capabilities has been underscored by many scholars although limited evidence exists so far regarding this issue. The available evidence is also primarily based on data obtained from manufacturing firms operating in developed and emerging economies and not from firms in developing economies. This study, therefore, bridges this gap by exploring key internal and external drivers of manufacturing performance taking evidence from the manufacturing sector of a developing economy - Ethiopia. A quant-emphasis mixed method approach was used along with cross-sectional survey design to gather data and answer the research questions in the study. The unit of analysis is the manufacturing plant, and hence primary data was collected using multidimensional questionnaires at plant level from 197 medium and large scale firms from Addis Ababa and its periphery. Secondary data was obtained from census reports, the country’s Growth and Transformation Plan (GTP), and report on the performance of the Ethiopian economy, which were analyzed qualitatively and the implications to manufacturing performance drawn in the study. A series of scale checks and analyses were made to test unidimensionality, reliability, and validity of measures and then structural equation modeling (SEM) was used to analyze hypothesized relationships. The main finding is that environmental dynamism significantly influences competitive priorities and firm’s strategic orientation, which in turn significantly influence manufacturing decisions. Structural and infrastructural manufacturing decisions eventually significantly influence manufacturing performance when firms place increased emphasis on quality or delivery. The competitive priorities also significantly influence external learning capability of the manufacturing plant, although the influence of strategic orientation on this variable was not significant even at the 0.1 level except in the delivery priority model. Both the competitive priorities and strategic orientation, however, play little role in guiding leadership practices of manufacturing managers. The study further indicates that government support directly influences manufacturing performance, though it does not significantly influence external learning capability. Based on the findings, it is suggested that manufacturing firms should give due attention to what is going on in their external environment and accordingly align their competitive priorities, strategic orientation, and investments in structural and infrastructural resources to enhance plant performance. They should exhaustively utilize the supports provided by government as well. / Business Management / DBL

Manufacturing performance measures the extent to which the manufacturing plant has built capabilities like low cost, high quality, delivery, and flexibility. The importance of identifying drivers of these capabilities has been underscored by many scholars although limited evidence exists so far regarding this issue. The available evidence is also primarily based on data obtained from manufacturing firms operating in developed and emerging economies and not from firms in developing economies. This study, therefore, bridges this gap by exploring key internal and external drivers of manufacturing performance taking evidence from the manufacturing sector of a developing economy - Ethiopia. A quant-emphasis mixed method approach was used along with cross-sectional survey design to gather data and answer the research questions in the study. The unit of analysis is the manufacturing plant, and hence primary data was collected using multidimensional questionnaires at plant level from 197 medium and large scale firms from Addis Ababa and its periphery. Secondary data was obtained from census reports, the country’s Growth and Transformation Plan (GTP), and report on the performance of the Ethiopian economy, which were analyzed qualitatively and the implications to manufacturing performance drawn in the study. A series of scale checks and analyses were made to test unidimensionality, reliability, and validity of measures and then structural equation modeling (SEM) was used to analyze hypothesized relationships. The main finding is that environmental dynamism significantly influences competitive priorities and firm’s strategic orientation, which in turn significantly influence manufacturing decisions. Structural and infrastructural manufacturing decisions eventually significantly influence manufacturing performance when firms place increased emphasis on quality or delivery. The competitive priorities also significantly influence external learning capability of the manufacturing plant, although the influence of strategic orientation on this variable was not significant even at the 0.1 level except in the delivery priority model. Both the competitive priorities and strategic orientation, however, play little role in guiding leadership practices of manufacturing managers. The study further indicates that government support directly influences manufacturing performance, though it does not significantly influence external learning capability. Based on the findings, it is suggested that manufacturing firms should give due attention to what is going on in their external environment and accordingly align their competitive priorities, strategic orientation, and investments in structural and infrastructural resources to enhance plant performance. They should exhaustively utilize the supports provided by government as well. / Business Management / D.B.L.