在人工智慧AI應用高速發展帶動伺服器、資料中心與能源儲存系統需求急遽攀升的背景下，電子製造產業面臨前所未有的產能擴張壓力。治工具作為DIP（Dual In-line Package）製程中維持焊接品質與製程穩定性的關鍵資產，其清洗頻率、保養策略與使用壽命對品質與成本皆具有顯著影響。然而目前對於治具清洗時機重視程度較低，缺乏以科學化數據為基礎的管理制度，易導致清洗不足造成品質不良，或過度清洗使治具壽命縮短並增加成本。因此，本研究以個案公司高使用頻率之過爐治具為研究對象，建立一套結合田口方法、變異數分析、反應曲面法以及品質成本模型的治具清洗參數最佳化方法。研究首先蒐集治具使用履歷、焊錫品質紀錄與清洗作業相關成本，並以部分因子實驗設計探討八項主要因子，包含使用次數、清洗時間、洗劑濃度、洗劑用量、水溫設定、手工清潔時間、烘烤時間與溫度，對焊錫良率的顯著性影響，再透過ANOVA驗證關鍵因子及其效應，建構治具清洗條件與品質變異之統計關聯。因此，本研究整合清洗成本、補焊工時、焊錫用量與品質失敗成本，建立總成本函數，整合反應曲面法、穩健式設計、POE誤差傳播分析及品質成本模型概念，進行實驗結果分析以求取同時具備高品質與最小成本的最佳清洗策略。研究結果可提供企業建立治具清洗週期、最佳保養頻率與壽命管理之量化依據，亦可提升焊錫品質穩定性、延長治具壽命並有效降低整體製造成本，預期可在未來可作為電子製造業在快速擴產情境下提升產能利用率、品質一致性與成本效率的重要管理策略。

The rapid advancement of artificial intelligence technologies has significantly accelerated the demand for servers, data centers and energy storage systems resulting in unprecedented production expansion within the electronics manufacturing industry. Under this trend, maintaining high manufacturing quality while minimizing operational costs has become a critical challenge. In the DIP assembly process, wave soldering fixtures are indispensable process assets that ensure soldering quality and process stability. Their cleaning frequency, maintenance strategy and service life directly influence product quality, production efficiency and manufacturing costs. In my case company, fixture cleaning practices are still largely experienced-driven, lacking a systematic and data-based decision-making mechanism. To address this issue, this study proposes an integrated optimization framework for fixture cleaning parameter design by combining the Taguchi method, ANOVA, RSM and COQ model. A case study is conducted using high utilization reflow fixtures in an electronics manufacturing company. A fractional factorial Design of DOE is first employed to evaluate the effects of eight process factors, including fixture usage count, cleaning time, detergent concentration, detergent dosage, water temperature, manual cleaning time, baking time and baking temperature. Furthermore, a comprehensive total cost model is developed by integrating cleaning cost, rework labor cost, solder consumption cost and quality failure cost. The proposed optimization model simultaneously considers product quality and manufacturing cost to determine the optimal fixture cleaning strategy. ANOVA is subsequently applied to identify statistically significant factors affecting soldering quality, while RSM is utilized to determine the optimal combination of cleaning parameters and to establish the quantitative relationships between process variables and quality performance. In the final experienced stage, POE as well as Taguchi Robust Design are used to evaluate the stability of the optimal results. The results show that the optimal robust process combination in this study is a cleaning time (X2) of 28.2 minutes and a baking temperature (X8) of 98°C The research findings provide quantitative guidelines for establishing fixture cleaning intervals, preventive maintenance schedules, and fixture life-cycle management.

丘東祥（2009）。反應曲面法於製程最佳化之應用。品質工程學刊。
林幸里（2013）。《實驗設計》。台北：華泰書局。
林嘉瑜（2002）。反應曲面法之改良研究－權重平滑搜尋方向與實驗區域改變規則之探討。國立成功大學工業管理研究所，台南市。
沈澤宏（2015）。探討表面貼裝技術之印刷治工具設計。崑山科技大學機械工程系碩士論文，台南市。
莊辰昱（2017）。以部分因子實驗設計提升車用面板網版印刷製程能力之研究。國立成功大學工業與資訊管理學系碩士在職專班，台南市。
許倍誠（2014）。運用田口方法於洗淨製程參數最佳化之研究。國立雲林科技大學工業工程與管理系工業工程組，雲林縣。
黃語潔（2017）。雙反應曲面法於產品製程改善之應用。國立虎尾科技大學工業工程與管理系碩士，雲林縣。
靳孟學（2007）。《混合實驗最佳化之研究》。國立交通大學工業工程與管理學系碩士，新竹市。
潘浙楠（2009）。品質管理理論與實務。台北市：華泰文化。
謝嘉興（2011）。應用直交表技術於背光模組之設計。國立高雄應用科技大學機械與精密工程研究所碩士，高雄市。
蘇朝敦（2005）。品質工程。台北市：中華民國品質學會。
蘇智強（2012）。以品質成本觀點對小型供應商評選之研究-以某設備製造公司為例。中華大學工業管理學系科技管理碩士，新竹市。
Box, G. E. P. （1954）. The exploration and exploitation of response surfaces: Some general considerations and examples. Biometrics, 10(1), 16-60.
Box, G. E. P., & Draper, N. R.（1978）. Response surface methodology. Wiley.
Box, G. E. P., & Draper, N. R.（2007）. Response surfaces, mixtures, and ridge analyses (2nd ed.). Wiley.
Box, G. E. P., & Wilson, K. B.（1951）. On the experimental attainment of optimum conditions. Journal of the Royal Statistical Society： Series B (Methodological), 13(1), 1–45.
Brooks, S. H., & Mickey, M. R.（1961）. Optimum estimation of gradient direction in steepest ascent experiment. Biometrics, 17, 48-56.
Feigenbaum, A. V.（1956）. Total Quality Control. Harvard Business Review, 34(6), 93-101.
Feigenbaum, A. V.（1961）. Total Quality Control. NY：McGraw-Hill.
Fisher, R. A.（1925）. Statistical methods for research workers. Oliver & Boyd.
Fisher, R. A.（1935）. The design of experiments. Oliver & Boyd.
Giovanni, M. (1983). Response surface methodology and process optimization. Food Technology, 37(11), 41–45.
Juran, J. M.（1974）. Quality Control Handbook. 3rd Edition. NY：McGraw-Hill.
Khuri, A. I., & Mukhopadhyay, S.（2010）. Response surface methodology. Wiley Interdisciplinary Reviews：Computational Statistics, 2(2), 128–149.
Kleijnen, J. P. C. （2004）. Response surface methodology for optimization: All-next-step steepest ascent. International Journal of Simulation and Process Modelling, 1(1-2), 43-52.
Ku, H. H.（1966）. Notes on the use of propagation of error formulas. Journal of Research of the National Bureau of Standards, Section C: Engineering and Instrumentation, 70(4), 263–273.
Masser, W. J.（1957）. The quality manager and quality costs. Industrial Quality Contral, 14(6), 5-8.
Montgomery, D. C. （2020）. Design and analysis of experiments (10th ed.). John Wiley & Sons.
Myers, R. H., & Carter, W. H. （1973）. Response surface techniques for dual response systems. Techno metrics, 15(2), 301–317.
Myers, R. H., & Khuri, A. I.（1979）. A new procedure for steepest ascent. Communications in Statistics-Theory and Methods, A8, 1359-1376.
Myers, R. H., & Montgomery, D. C.（1995）. Response surface methodology： Process and product optimization using designed experiments. Wiley.
Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M.（2009）. Response surface methodology：Process and product optimization using designed experiments (3rd ed.). Wiley.
Myers, R. H., Montgomery, D. C., & Anderson-Cook, C. M. （2016）. Response Surface Methodology: Process and Product Optimization Using Designed Experiments (4th ed.). Wiley.
Neyman, J., & Pearson, E. S.（1933）. On the problem of the most efficient tests of statistical hypotheses. Philosophical Transactions of the Royal Society of London. Series A, Containing Papers of a Mathematical or Physical Character, 231(694–706), 289–337.
Phadke, M. S.（1989）. Quality engineering using robust design. Englewood Cliffs, NJ： Prentice Hall.
Taguchi, G.（1986）. Introduction to quality engineering：Designing quality into products and processes. Asian Productivity Organization.
Taguchi, G., & Wu, Y.（1980）. Introduction to off-line quality control. Central Japan Quality Control Association.
Vining, G. G., & Myers, R. H. （1990）. Combining Taguchi and response surface philosophies: A dual response approach. Journal of Quality Technology, 22(1), 38–45.
Wu, C. F. J., & Hamada, M.（2000）. Experiments： Planning, analysis, and parameter design optimization. Wiley.
Yeh, C. L., et al.（2014）. Optimization of reflow soldering parameters for solder joint strength using response surface methodology. Journal of Electronic Packaging, 136(2), Article 021005.
2025年下半年及2026年全球AI伺服器市場與供應鏈發展展望. （2025, August 5）. Trandforce. https：//www.trendforce.com.tw/research/download/RP250805AD
2025年電子產業需求總覽. （2025, August 5）. Trandforce. https：//www.trendforce.com.tw/research/download/RP250805JL
集邦TrendForce看2026科技趨勢：AI伺服器出貨年增逾20% AI晶片液冷滲透率達47%. （2025, November 28）. https：//news.cnyes.com/news/id/6254107
AI基建市場高速成長 AI伺服器夯、台ODM廠大補. （2025, November 3）https：//www.ctee.com.tw/news/20251103700072-439901