Abstract
This paper proposes a two-stage fuzzy clustering engine by combining fuzzy clustering method and fuzzy inference method. In the first stage, the raw data during manufacturing process can be classified based on its own nature, and with the classification results, operation decision can be made in the second stage by running fuzzy inference engine without relying on highly skilled expert. The objective of the proposed method eliminates the human interference so that the decision can be much more impersonal and reliable. In addition, to improve the performance, fuzzy rules in this engine are mostly derived from the natural feature of the raw data rather than the tradition fuzzy rules formalization. Also, a case study of a company based in Singapore has been presented, and the results are promising and satisfied by the company.
| Original language | English |
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| Title of host publication | 5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010 |
| Pages | 1002-1007 |
| Number of pages | 6 |
| DOIs | |
| Publication status | Published - 30 Jul 2010 |
| Externally published | Yes |
| Event | 5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010 - Singapore, Singapore Duration: 2 Jun 2010 → 5 Jun 2010 |
Conference
| Conference | 5th IEEE International Conference on Management of Innovation and Technology, ICMIT2010 |
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| Country/Territory | Singapore |
| City | Singapore |
| Period | 2/06/10 → 5/06/10 |
Keywords
- Decision making
- Fuzzy clustering
- Fuzzy inference
ASJC Scopus subject areas
- Management of Technology and Innovation
- Strategy and Management