The Development of Customer Complaint Handling Mode for Printed Circuit Board Industries Using Data Mining Techniques
碩士 === 元智大學 === 工業工程與管理學系 === 91 === In today’s competitive manufacturing, a quick response to corrective action request (CAR) from customers is a very important issue. In the printed circuit board (PCB) industries, the defective issue from customers is recorded in CAR by the quality engineers and...
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| Format: | Others |
| Language: | zh-TW |
| Published: |
2003
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| Online Access: | http://ndltd.ncl.edu.tw/handle/28339593040338390074 |
| Summary: | 碩士 === 元智大學 === 工業工程與管理學系 === 91 === In today’s competitive manufacturing, a quick response to corrective action request (CAR) from customers is a very important issue. In the printed circuit board (PCB) industries, the defective issue from customers is recorded in CAR by the quality engineers and then the countermeasures are proposed for this issue immediately.
The focus of this research is on the development of a handling model of the customer complaint for the PCB industries. The handling model of the customer complaint based on data mining technology will be developed to address various types of defects described by customers. External CARs that record the descriptions of defects and correction procedures will be collected and clustered by workstations using SOM neural networks. A decision tree will be applied to build a diagnosis knowledge base to address the root causes of defective products. Data from a local PCB manufacturer demonstrate that the proposed approach is a useful tool in preparing a CAR report.
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