Abstract
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.
| Original language | English |
|---|---|
| Pages (from-to) | 2149-2160 |
| Number of pages | 12 |
| Journal | International Journal of Advanced Manufacturing Technology |
| Volume | 96 |
| Issue number | 5-8 |
| DOIs | |
| Publication status | Published - 2018 May 1 |
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All Science Journal Classification (ASJC) codes
- Control and Systems Engineering
- Software
- Mechanical Engineering
- Computer Science Applications
- Industrial and Manufacturing Engineering
Cite this
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A new grey prediction model for the return material authorization process in the TFT-LCD industry. / Li, Der Chiang; Yeh, Chun Wu; Chen, Chien Chih; Wang, Yung Tai.
In: International Journal of Advanced Manufacturing Technology, Vol. 96, No. 5-8, 01.05.2018, p. 2149-2160.Research output: Contribution to journal › Article
TY - JOUR
T1 - A new grey prediction model for the return material authorization process in the TFT-LCD industry
AU - Li, Der Chiang
AU - Yeh, Chun Wu
AU - Chen, Chien Chih
AU - Wang, Yung Tai
PY - 2018/5/1
Y1 - 2018/5/1
N2 - 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.
AB - 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.
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UR - http://www.scopus.com/inward/citedby.url?scp=85042185295&partnerID=8YFLogxK
U2 - 10.1007/s00170-018-1754-y
DO - 10.1007/s00170-018-1754-y
M3 - Article
AN - SCOPUS:85042185295
VL - 96
SP - 2149
EP - 2160
JO - International Journal of Advanced Manufacturing Technology
JF - International Journal of Advanced Manufacturing Technology
SN - 0268-3768
IS - 5-8
ER -