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  • 學位論文

以品質工具及實驗設計進行表面處理製程改善之研究

Surface Treatment Process Improvement Through Quality Tools and Design of Experiments

指導教授 : 陳育欣
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摘要


表面處理的對象非常廣泛,從傳統工業到精密的高科技工業,從金屬表面到非金屬的塑膠表面。它能使材料更耐腐蝕,更耐磨損、更耐熱,並使材料壽命延長,此外改善材料表面之特性、光澤美觀等提升產品之附加價值,所有這些改變材料表面之物理、機械及化學性質之加工技術統稱為表面處理。 本技術報告探討表面處理製程中所屬塗裝之溶劑式噴塗法,並針對該製程的生產線作業模式及其重點機台設備提出參數設定之優化方法,並以W公司案例說明。 個案公司初期產品開發階段,以往是以試誤法做參數優化,無法有效達到縮短生產前置時間及產品不良率管控目的。產品不良率高達44.2%,因此有必要提出一套科學且可提高良率的方法,遂針對個案公司表處製程,以客戶需求為出發點,並以降低產品開發階段不良率管控為目的,進行個案公司表處製程個案研究探討,於各階段中運用實驗設計工具及統計品管手法如特性要因圖、品質機能展開、因果矩陣及失效模式分析等,找出關鍵因子並進行分析,尋求最佳穩定參數。 經品質工具歸納後,可得四項改善因子分別是:(1)底漆段塗料黏度。(2)噴槍風壓。(3)清潔使用藥劑的藥液殘留。(4)產品操作SOP確認,其中(3)、(4)兩項因子為人為因素造成,但此兩項可藉由操作人員的教育訓練來進行改善,因此不在本技術報告改善方法的討論範圍。 據上述所提研究方法,發現底漆段製程的參數為改善重點,包含烘烤溫度、塗料黏度、噴槍壓力、溶劑種類等四項,經由實驗與分析結果發現塗料黏度及溶劑種類為顯著因子,其他兩項因子烘烤溫度及噴槍風壓為不顯著因子,因考量烘烤溫度較高,溶劑容易揮發,塗料與素材附著性表現較佳及風壓設定值調降可降低塗料成本支出,最後提出這四個因子的參數值組合。 本技術報告提出的參數值組合,針對個案公司進行小批量生產測試,檢驗結果進行改善成效分析,包含兩部分:(1)不良率分析及(2) X-bar及R管制圖分析。 經過個案實際驗證,順利將產品不良率由44.2%降為14.3%,符合客戶需求,改善後的X-bar及R管制圖幾乎都在管制界限內,表示製程穩定且製程中心接近規格值,驗證了統計品管結合實驗設計的成效與可行性,本個案亦可作為相關產業問題解決方案時的參考。

並列摘要


The object of the surface treatment is very extensive and widely be used. Not only from traditional industries to high-tech industrial precision but also from the metal surface to the non-metallic plastic surface. Officially, the major function of the surface treatment makes the material more proofed against corrosion and abrasive. Also it marks the material be more heated-resistant. The most important thing is extended to life time of the material. In sum up, there is no doubt the definition of the “surface treatment is all the changes in the physical surface of materials, mechanical and chemical properties of the processing in terms of improving the properties of the material surface, the gloss appearance and other value-added products. The main article of the technical report is illustrate the method of painting by solvent. Based on the case study of W company indicate and focus on how to best improving the production model of the operation in line and the excellent parameters setting of its equipment. In the early stage when the W company doing the product development. They do trial and error in order to optimize the best parameter of its production process. However, just could not effectively shorten the lead time of the production and could not control the low yield rate. To be more precise, the figures of the low yield rate reach to 44.2 %. Therefore, it is necessary to conduct the method which is could efficiently increase the yield and shorten the low yield rate when developing new products. Regarding to the case study of W company, Set up the target purpose of the W company, in order to figure out the key factors of how to implementing fit parameters successfully, The use of experimental design and statistical quality control techniques tools in various stages such as the characteristics to be a result of the whole maps, quality function deployment, causality matrix and failure mode analysis to identify and analyze these key factors to meet its purpose. In conclusion, There are four key factors of improving the quality as below : (1)Base coating viscometer.(2) Air pressure of spray gun.(3) The after treatment of the cleaner uses the pharmaceutical is residual.(4) The SOP of product operation. Regarding factors of item (3) and (4). These two factors are caused by human factors. However, these two factors might be gain the significantly improves after educating and training. Thus, it is not including to the report of the improvement methods. According to the studying, It is illustrate the base coating of the process is the most important key factor when improving the operation process. There are four ingredient of this method are contains baking temperature, coating viscosity, pressure spray guy and type of solvent. The result figure out the significant factors is the coating viscometer and the type of solvents. Conversely, there is no any meaning of the rest factors. Due to the baking temperature is high, volatile solvents, coatings and material adhesion performance is good. in sum up , it is come out the best combination of these four key factors. The combination of parameter values presented in the report, the cases against companies small batch test, the test results were analyzed to improve the effectiveness. It is consists of two parts : (1) Fail rate analysis (2) X-bar and R control chart analysis. After the actual experiment, it is successfully reduced the low yield rate from 44.2 % to the 14.3%. It is just meet the customer need indeed. After improving of X-bar and R control chart almost all within the control limits , it is also indicate that the process is stable and close to the center of the process specification values . This case may be used as reference solutions related to industries during problem solving.

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