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http://dx.doi.org/10.11627/jkise.2016.39.1.123

A Study on the Design of Tolerance for Process Parameter using Decision Tree and Loss Function  

Kim, Yong-Jun (Department of Industrial and Management Engineering, Incheon National University)
Chung, Young-Bae (Department of Industrial and Management Engineering, Incheon National University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.39, no.1, 2016 , pp. 123-129 More about this Journal
Abstract
In the manufacturing industry fields, thousands of quality characteristics are measured in a day because the systems of process have been automated through the development of computer and improvement of techniques. Also, the process has been monitored in database in real time. Particularly, the data in the design step of the process have contributed to the product that customers have required through getting useful information from the data and reflecting them to the design of product. In this study, first, characteristics and variables affecting to them in the data of the design step of the process were analyzed by decision tree to find out the relation between explanatory and target variables. Second, the tolerance of continuous variables influencing on the target variable primarily was shown by the application of algorithm of decision tree, C4.5. Finally, the target variable, loss, was calculated by a loss function of Taguchi and analyzed. In this paper, the general method that the value of continuous explanatory variables has been used intactly not to be transformed to the discrete value and new method that the value of continuous explanatory variables was divided into 3 categories were compared. As a result, first, the tolerance obtained from the new method was more effective in decreasing the target variable, loss, than general method. In addition, the tolerance levels for the continuous explanatory variables to be chosen of the major variables were calculated. In further research, a systematic method using decision tree of data mining needs to be developed in order to categorize continuous variables under various scenarios of loss function.
Keywords
Continuous Variable; Decision Tree; Loss Function; Tolerance;
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