Fuzzy-Neural Networks for a piloted Quality Management System
| Autor: | Samir Ben Ahmed, Taieb Ben Romdhane, Raouf Ketata, Hajer Ben Mahmoud Dammak |
|---|---|
| Rok vydání: | 2012 |
| Předmět: |
Decision support system
Quality management Computer science business.industry media_common.quotation_subject Fuzzy control system Machine learning computer.software_genre Reliability engineering Statistical classification Quality management system Unified Modeling Language Quality (business) Artificial intelligence business computer Test data media_common computer.programming_language |
| Zdroj: | 2012 16th IEEE Mediterranean Electrotechnical Conference. |
| DOI: | 10.1109/melcon.2012.6196488 |
| Popis: | The purpose of this paper is to provide a path for designing a tool for decision support to ensure the effectiveness of Quality Management System (QMS). For this, we propose a Fuzzy-Neural Networks (FNN) approach for improving the efficiency of such system. The aim of this approach is to classify the objectives for a real-world case study which presents a major problem for controlling the quality levels of its production lines. This approach provided a significant improvement when the testing data are various or complex. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|