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應用主成份田口法與灰關聯分析進行多重品質特性之最佳參數設計—以壓鑄品製程...
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國立高雄大學亞太工商管理學系碩士班
應用主成份田口法與灰關聯分析進行多重品質特性之最佳參數設計—以壓鑄品製程為例 = Application of Taguchi Method, Principal Component and Grey Relation Analysis in Multi-objective Quality Characterization Optimization-Take the Process of Casting as the Example
Record Type:
Language materials, printed : monographic
Paralel Title:
Application of Taguchi Method, Principal Component and Grey Relation Analysis in Multi-objective Quality Characterization Optimization-Take the Process of Casting as the Example
Author:
陳宏佳,
Secondary Intellectual Responsibility:
國立高雄大學
Place of Publication:
[高雄市]
Published:
撰者;
Year of Publication:
2009[民98]
Description:
70面圖、表 : 30公分;
Subject:
主成份分析
Subject:
Grey Relation Analysis
Online resource:
http://handle.ncl.edu.tw/11296/ndltd/20415743428031250227
Notes:
指導教授:盧昆宏
Notes:
參考書目:面
Summary:
田口博士提出二次損失函數的觀念,透過改善品質來降低生產成本,以達到產品之穩健性。但是,傳統田口方法大多僅針對單一品質特性探討,對於多品質特性最佳化問題,必須依賴工程師的經驗來主觀判斷最佳參數水準組合,然而在實務上產品往往是具有多個品質特性的,而且這些品質特性間均可能有極高的相關聯性。 因此,本研究應用灰關聯與主成份分析結合田口方法提出一個解決多重品質特性參數設計問題的三階段程序。首先,以田口損失函數來評估產品的品質特性,接著利用主成份分析程序,使得這些品質特性之損失函數轉換成無相關的主成份,透過灰關聯分析解決兩個以上的主成份,求得最佳參數組合;若是僅求得一個主成份,則透過權重主成份法求得最佳參數組合,並且所遭遇取捨與衝突問題將可大幅降低。 由於壓鑄品製程中若發生嚴重品質缺陷,常須以人工補銲方式加以修補,嚴重時無法補銲則需報廢,造成極高成本浪費且影響產品品質。因此,本文亦利用壓鑄品製程來實證本文所建構之最佳化程序。經兩實例的驗證結果令人滿意且可達節省實驗成本與縮短新產品由實驗階段導入生產階段之時程。 Dr. Taguchi developed the concept of loss function and used the Signal-to-Noise ratio to evaluate the performance of product quality. By finding the optimal combination levels of factors in the parameter design, the performance of product quality could be made insensitive to noise factor. However, the method only takes a single quality attribute into account. When the multi-response quality characteristics need to be considered and the optimal combined levels of factors for some quality characteristics are conflict, the optimal combined levels are usually decided based on the experiences of the individual engineer. Practically, we often have to deal with multi-response process or product and it is usually to optimize such case just by engineering experiences. The difficulty will become even more pronounced if these responses are highly correlated. We proposed a three-phased procedure that combines principal component analysis, grey relation, and Taguchi method to solve the problem in parameters design responses. The quality characteristics of a product are first evaluated through Taguchi’s quality loss function. The function relationship is then fed into the principal component analysis to transfer a set of responses into a set of uncorrelated principal components. Then this study uses grey relation analysis to obtain the optimal combination of over two principle components. If there is only a principal component, this study uses weighted principal component to obtain the optimal combination. Therefore, the conflict for determining the optimal combination of control factors in a multi-response problem can be greatly reduced. If there are any severe defects during the process of casting, manual soldering patch repair is often required. When the defect is too severe to repair, the entire cast must be abandoned. It not only causes an enormous waste in cost, but also affects quality of products. Therefore, this study used the cases of the process of casting to explain the optimization procedure and the pattern of numerical analysis. The confirmation experiment yields a satisfactory result that demonstrating the effectiveness and the usability of the research. This research helps the example company to reduce the experimental cost and to shorten the interval between the experimental stage and productive stage.
應用主成份田口法與灰關聯分析進行多重品質特性之最佳參數設計—以壓鑄品製程為例 = Application of Taguchi Method, Principal Component and Grey Relation Analysis in Multi-objective Quality Characterization Optimization-Take the Process of Casting as the Example
陳, 宏佳
應用主成份田口法與灰關聯分析進行多重品質特性之最佳參數設計—以壓鑄品製程為例
= Application of Taguchi Method, Principal Component and Grey Relation Analysis in Multi-objective Quality Characterization Optimization-Take the Process of Casting as the Example / 陳宏佳撰 - [高雄市] : 撰者, 2009[民98]. - 70面 ; 圖、表 ; 30公分.
指導教授:盧昆宏參考書目:面.
主成份分析Grey Relation Analysis
應用主成份田口法與灰關聯分析進行多重品質特性之最佳參數設計—以壓鑄品製程為例 = Application of Taguchi Method, Principal Component and Grey Relation Analysis in Multi-objective Quality Characterization Optimization-Take the Process of Casting as the Example
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田口博士提出二次損失函數的觀念,透過改善品質來降低生產成本,以達到產品之穩健性。但是,傳統田口方法大多僅針對單一品質特性探討,對於多品質特性最佳化問題,必須依賴工程師的經驗來主觀判斷最佳參數水準組合,然而在實務上產品往往是具有多個品質特性的,而且這些品質特性間均可能有極高的相關聯性。 因此,本研究應用灰關聯與主成份分析結合田口方法提出一個解決多重品質特性參數設計問題的三階段程序。首先,以田口損失函數來評估產品的品質特性,接著利用主成份分析程序,使得這些品質特性之損失函數轉換成無相關的主成份,透過灰關聯分析解決兩個以上的主成份,求得最佳參數組合;若是僅求得一個主成份,則透過權重主成份法求得最佳參數組合,並且所遭遇取捨與衝突問題將可大幅降低。 由於壓鑄品製程中若發生嚴重品質缺陷,常須以人工補銲方式加以修補,嚴重時無法補銲則需報廢,造成極高成本浪費且影響產品品質。因此,本文亦利用壓鑄品製程來實證本文所建構之最佳化程序。經兩實例的驗證結果令人滿意且可達節省實驗成本與縮短新產品由實驗階段導入生產階段之時程。 Dr. Taguchi developed the concept of loss function and used the Signal-to-Noise ratio to evaluate the performance of product quality. By finding the optimal combination levels of factors in the parameter design, the performance of product quality could be made insensitive to noise factor. However, the method only takes a single quality attribute into account. When the multi-response quality characteristics need to be considered and the optimal combined levels of factors for some quality characteristics are conflict, the optimal combined levels are usually decided based on the experiences of the individual engineer. Practically, we often have to deal with multi-response process or product and it is usually to optimize such case just by engineering experiences. The difficulty will become even more pronounced if these responses are highly correlated. We proposed a three-phased procedure that combines principal component analysis, grey relation, and Taguchi method to solve the problem in parameters design responses. The quality characteristics of a product are first evaluated through Taguchi’s quality loss function. The function relationship is then fed into the principal component analysis to transfer a set of responses into a set of uncorrelated principal components. Then this study uses grey relation analysis to obtain the optimal combination of over two principle components. If there is only a principal component, this study uses weighted principal component to obtain the optimal combination. Therefore, the conflict for determining the optimal combination of control factors in a multi-response problem can be greatly reduced. If there are any severe defects during the process of casting, manual soldering patch repair is often required. When the defect is too severe to repair, the entire cast must be abandoned. It not only causes an enormous waste in cost, but also affects quality of products. Therefore, this study used the cases of the process of casting to explain the optimization procedure and the pattern of numerical analysis. The confirmation experiment yields a satisfactory result that demonstrating the effectiveness and the usability of the research. This research helps the example company to reduce the experimental cost and to shorten the interval between the experimental stage and productive stage.
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310001863623
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