Hybrid system of artificial neural network, case based reasoning and fuzzy logic for QS9000 implementation
Advanced Product Quality Planning (APQP), which is one of QS9000 requirements applied to automotive industries, performs an important role in quality assurance activities. It’s aroutine job in most of the companies. A group of employees fulfill the job following designated procedures and produce a l...
Saved in:
| Main Author: | |
|---|---|
| Other Authors: | |
| Format: | Theses and Dissertations |
| Published: |
2008
|
| Subjects: | |
| Online Access: | http://hdl.handle.net/10356/6056 |
| Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
| Institution: | Nanyang Technological University |
| Summary: | Advanced Product Quality Planning (APQP), which is one of QS9000 requirements applied to automotive industries, performs an important role in quality assurance activities. It’s aroutine job in most of the companies. A group of employees fulfill the job following designated procedures and produce a lot of reports and forms. In this dissertation, one model of problem solving that involves choosing an action based on past experiments in similar situations is presented. The problem to be solved in actual business activities is the APQP implementation. This model realized the advantages of some Artificial Intelligence (AI) technologies; these AI technologies include Artificial Neural Network (ANN), Case-Based Reasoning (CBR) and Fuzzy Logic (FL). |
|---|