A new grey prediction model for the return material authorization process in the TFT-LCD industry

Der Chiang Li, Chun Wu Yeh, Chien Chih Chen, Yung Tai Wang

研究成果: Article

1 引文 斯高帕斯(Scopus)

摘要

In the era of the short product life cycle, the return materials authorization (RMA) process plays an important role in satisfying customers because sellers have to prepare a certain amount of stock for returning products. Hence, determining how to evaluate the trade-off between over-stock and under-stock to balance cost-cutting and customer satisfaction is worthy of study. In this paper, we reveal a case taken from a leading TFT-LCD (thin film transistor liquid crystal display) maker in Taiwan, where the prepared stock is very likely to go from being hoarded to futility because the life cycle of TFT-LCD products is very short. To overcome the issues of the RMA process in the case company, obtaining the precise sizes of returning defectives in the near future is considered as one of the key tasks. General grey models (GMs) are widely applied to make predictions for this kind of short-term time series data; nevertheless, there still has the possibility of improving its predictions. This study thus proposes a new GM model, called the MTD-GM model, where a mega-trend-diffusion technique is employed to improve estimating the background values in the traditional GM. The experimental results show that the proposed MTD-GM grey model outperforms four other grey models with eight products in the case company data.

原文English
頁(從 - 到)2149-2160
頁數12
期刊International Journal of Advanced Manufacturing Technology
96
發行號5-8
DOIs
出版狀態Published - 2018 五月 1

    指紋

All Science Journal Classification (ASJC) codes

  • Control and Systems Engineering
  • Software
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

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