研究目的 - 本研究的目的是應用比率測試統計和過程產量指數，為線性剖面的多個供應商選擇問題提出解決方案。
研究方法 - 在本研究中，應用比率測試統計和過程收益率指數，並考慮多個供應商。對於每個供應商，計算產量指數並按大小排序。其後，通過使用比率測試統計數據將每個供應商與具有最大值的供應商進行比較。此後應用Bonferroni方法作為調整以控制總體錯誤率。此外，計算臨界值，並進行功率分析。
研究結果 - 研究結果表明，對於給定的顯著水平α，隨著最小能力要求的增加，臨界α值增加。然而，對於給定的α值，隨著樣本大小的增加，臨界α值的大小減小。除此之外，隨著供應商的最低能力要求在給定水平上增加，所需的資料數量也會增加。
研究意義 - 所提出之方法的結果為製造商提供了有用的信息，使其面對兩個以上的供應商時，能夠選擇具有卓越工藝能力指數的最佳決策。
Purpose – The objective of this study is to apply ratio test statistics and process yield index for proposing a solution to multiple supplier selection problems for linear profiles.
Methodology – In this study, the ratio test statistic and process yield indices are applied and multiple suppliers are considered. For each supplier, a yield index was calculated and ranked by the magnitude. Then, each supplier was compared to the supplier with the maximum value by using ratio test statistics. Afterwards Bonferroni method was applied as an adjustment to control the overall error rate. Furthermore, the critical values were calculated, and power analysis was performed.
Findings - The result of the study showed that for a given significant level alpha, as the minimum capability requirement increases, the critical alpha value increases. Whereas, for a given α value, as sample size increases, the magnitude of critical alpha value decreases. In addition to this, as supplier’s minimum capability requirement increases at a given level, the number of profiles required increases.
Research Implications - The result of the proposed method provides useful information to manufacturers in making the best possible decision selecting among more than two suppliers with superior process capability index.
