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http://dx.doi.org/10.11627/jkise.2020.43.2.137

A Case Study on the Improvement of Display FAB Production Capacity Prediction  

Ghil, Joonpil (Department of Industrial Engineering, Ajou University)
Choi, Jin Young (Department of Industrial Engineering, Ajou University)
Publication Information
Journal of Korean Society of Industrial and Systems Engineering / v.43, no.2, 2020 , pp. 137-145 More about this Journal
Abstract
Various elements of Fabrication (FAB), mass production of existing products, new product development and process improvement evaluation might increase the complexity of production process when products are produced at the same time. As a result, complex production operation makes it difficult to predict production capacity of facilities. In this environment, production forecasting is the basic information used for production plan, preventive maintenance, yield management, and new product development. In this paper, we tried to develop a multiple linear regression analysis model in order to improve the existing production capacity forecasting method, which is to estimate production capacity by using a simple trend analysis during short time periods. Specifically, we defined overall equipment effectiveness of facility as a performance measure to represent production capacity. Then, we considered the production capacities of interrelated facilities in the FAB production process during past several weeks as independent regression variables in order to reflect the impact of facility maintenance cycles and production sequences. By applying variable selection methods and selecting only some significant variables, we developed a multiple linear regression forecasting model. Through a numerical experiment, we showed the superiority of the proposed method by obtaining the mean residual error of 3.98%, and improving the previous one by 7.9%.
Keywords
Fabrication; Photolithography; Production Capacity Forecasting; Equipment Efficiency; Multiple Linear Regression Analysis;
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