在台灣由於近年來新車銷售量逐年遞減,影響後時期汽車維修、保養產業,各家廠商為鞏固自家車輛車口數的回流量,勢必提供更多元服務,因此競爭更加愈來愈激烈。 本研究針對中部M汽車修護廠顧客發放問卷,並利用因素分析對題項萃取出構面,再以基本資料之變項為因子,分別對各個構面認知做差異分析。此外,為提升M汽車修護廠經營績效,本研究採用PZB模式針對台中市M汽車修護廠設計問卷,並利用六標準差(DMAIC)改善流程,從問卷各題項期望重要度與實際滿意度之成對指標的認知差異,試圖以績效評估矩陣(含管制界限)找出M汽車修護廠在維修、保養營運時需改善題項。結果從問卷21個題項中有7個題項落在優先改善區(資源不足),本研究並提供改善策略給經營者作參考以擬定改善方案,並利用品質管制圖檢驗改善成效,執行過程中這7個異常題項在5個時段點均採3個標準誤範圍,其中有四個題項改善成功,而另三個題項改善失敗,且均呈現資源供給過度。本研究藉此實例分析作為相關產業在未來做企業診斷時對績效提升之參考。
In Taiwan in recent years by year new vehicle sales volume decrease, affecting the era automobile repair and maintenance industry,various manufacturers to consolidate their own vehicles for the return flow bound to provide more services,result more and more intense competition. In this study, against midland M automobile repair plants customer questionnaires, and using factor analysis on questions of extracted dimensions, then the basic information for the factor variables were done for each dimension of cognitive difference analysis. In addition, to enhance the M automobile repair plant operating performance, this study PZB model for the Taichung M automobile repair plant design questionnaires and using Six Sigma (DMAIC) to improve processes, each of the questions from the questionnaire and the actual satisfaction expectations importance degree of cognitive differences pairs indicators, trying to performance evaluation matrix (with control limits) to identify M automobile repair plant in the repair and maintenance operations required to improve the questions. The results from the questionnaire has 21 questions of the questions fall seven priority improvement areas (lack of resources), this study provides improved strategies for information to the operators to develop improvement programs and the use of quality control charts of improve the effectiveness of inspection, the implementation process in five time section, these seven abnormalities item were to adopt three sigma the standard error ranges, which have four item improvement success,the other three item improvement fails,and showed excessive supply of resources. In this study, related industries to improvement in the future when business diagnostic reference as a case study.