Intelligent Diagnosis System for Shop Floor Control Using Data Mining Techniques

This paper aims to develop and demonstrate intelligent diagnosis system that ensures effective supporting the decision-maker in determining the cause and potential solutions to unpredictable problems or events detected by monitoring factory-wide operating processes. The algorithm for accomplishing rapid, cost-effective, and high reliable diagnosis system is well-designed with C++ as an object-oriented programming language under Windows OS platform. A windows-based prototype system for intelligent diagnosis system with real-time status data collected from shop floor is also suggested and demonstrated by using C++ programming language and C4.5 learning algorithm.