Development of Scrap Cost Forecasting Model: A Case Study in Hard Disk Drive Company
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Creator 1. Phattarasaya Tantiwattanakul
2. Athakorn Kengpol
Title Development of Scrap Cost Forecasting Model: A Case Study in Hard Disk Drive Company
Publisher Faculty of Engineering, Khon Kaen Univeristy
Publication Year 2555
Journal Title KKU Engineering Journal
Journal Vol. 39
Journal No. 3
Page no. 281-289
Keyword Forecasting, Correlation analysis, Regression analysis, Artificial neural networks
ISSN 0125-8573
Abstract The objective of this research is to develop the optimized scrap cost forecasting model in the Hard Disk Drive manufacturing with more accuracy. Due to the current forecasting, calculated from the Key Performance Index (KPI) of all assembly processes, has error about 30% which means the production planning is imprecise and can not specify the cause of scrap due to some KPIs are irrelevant with scrap cost. This is the reason why this research aims to improve accuracy more than 10%. At first, the correlation analysis is used to identify the relationship between KPI and scrap cost. The time-series analysis of KPI is taken and forecasted value of KPI is used as independent variables in the scrap cost forecasting model formulation. Two techniques are applied to formulate forecasting models: regression analysis and artificial neural networks. The results from scrap cost forecasting of product A, B and C have showed that the artificial neural network model can forecast with more accurate than regression model. The forecasting errors of artificial neural network models are 11.48%, 11.43% and 18.86% for product A, B and C respectively.
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