選擇供應商對於企業是一項重要決策，而供應商與企業之間若能配合得宜，則可創造最大的利潤；Dickson(1966)曾提出23項供應商評估準則，有品質、交期、過去績效、價格、產能與技術能力等等，其中以品質最為重要。而製程能力指標(Process capability index)就是一個簡單又易懂的整體衡量工具，提供企業對於供應商或是製造商評估產品或其品質水準，並提高其品質績效；本文以指標Spk為主軸，由於指標Spk與製程良率有一對一數學關係，因此在實務應用上較Cp、Cpk與Cpm更為合適。但在製程品質評估上，若以指標的點估計值評估製程品質優劣，會因為抽樣誤差的產生而導致對製程能力指標的誤判；信賴區間考慮了點估計的標準誤，並可藉由信賴下限判斷製程的優劣；但因為Spk估計式的分配函數相當的複雜，所以推導其信賴區間也相對的困難。本研究將指標Spk化為δ＝（μ－T）/d與γ＝σ/d的函數，並以δ與γ所構成的聯合信賴區間為可行解區域及Spk(δ, γ)為目標函數，求解出指標Spk的信賴區間。接著利用指標Spk的信賴區間建立一套客觀的供應商評選模式，藉此比較各供應商之指標Spk信賴區間並評選出最佳供應商與候補供應商，而且此評選模式可透過EXCEL運算即可完成，方便業者使用。最後本研究應用上述結果，針對縫紉機之重要零組件－上軸軸承供應商，提出一套品質完整評估與分析模式；藉此提升其生產之軸承之品質與良率，並可減少縫紉機之不良與降低縫紉機成本；由於上軸軸承之四個品質特性分別有望目與望小品質特性，因此利用製程能力指標發展出一套可同時評估單邊與雙邊規格的評估方法，可衡量各品質特性是否皆達到品質水準之要求；接著利用多品質製程能力分析圖(MPCAC)分析影響造成軸承品質不佳的因素，供製造商與供應商做為改善之依據，並可持續改善上軸軸承的品質，進而達到六標準差品質水準的目標。

Supplier selection is a significant decision for enterprises, in which if a supplier and the enterprise cooperate well, it makes possible the creation of greatest profits. Dickson proposed 23 criteria for evaluating suppliers, including quality, delivery, past performance, pricing, productivity and technical abilities, of which quality is most important. Process capability index is a simple and easy-to-know overall measuring tool that is provided for enterprises to evaluate a supplier in terms of product or its quality level and to upgrade its quality performance. This thesis focuses on the index Spk, which is more suitable to use in practice than Cp, Cpk and Cpm, as it has a one-to-one mathematical relation with process yield rate. But, in evaluating process quality, if the estimated value of index point is used to evaluate the process quality, sampling error may occur, which would result in misjudgment of process capability index. The confidence interval has taken the standard error of point estimation into account and it is possible to determine whether a process is good or poor by lower confidence bound. However, because the distribution function of estimating equation for Spk is very complex, the derivation of its confidence interval is thus difficult. The present research converts index Spk into the function of δ＝(μ－T)/d and γ＝σ/d, and sets the simultaneous confidence interval consisting of δ and γ as feasible region and Spk(δ, γ) as target function to solve the confidence interval of index Spk. the confidence interval of index Spk is then used to build an objective selecting mode of suppliers, whereby to compare such interval for various suppliers and obtain the best suppliers and standby suppliers. This selecting mode can be carried out by algorithm on EXCEL, a convenience to the industry. Lastly, applying the above results, the present research proposes a complete quality evaluation and analysis model in respect of the suppliers of upper shaft bearings, a key component of sewing machine, whereby to elevate the quality and yield rate of the bearing they produce and to decrease flaw rates and costs of sewing machine. Given that the four quality characteristics of the upper shaft bearing have nominal-the-best and smaller-the-better characteristics, the process capability index is employed to develop an evaluating method of unilateral and bilateral specifications, which is able to measure whether each of the quality characteristics meets the requirements of quality levels. A multi-process capability analysis chart (MPCAC) is further used to analyze the factors affecting the bearing quality to serve as basis for manufacturers and suppliers to improve. This also can continue to help improve the quality of the upper shaft bearing and further achieve the object of 6-sigma quality level.

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