Model of a fuzzy autonomation system for a steel wire roll mill

Abstract

In the present paper, an autonomation system based on fuzzy logic is proposed for a steel wire rolling mill to minimize a quality problem related to surface finish. Autonomation is a lean manufacturing concept that integrates automation with a human factor. The ability of self-diagnosis is achieved in the automated line by incorporating a computational intelligence tool like fuzzy logic. The decision support model proposed here provides intelligent decisive signals similar to the fuzzy capability of human brain. Fuzzy Logic control (FLC) model is designed to recognize the events that are likely to create defects and output action signals are generated. Speed difference between conveyor rollers and rolled products, percentage of carbon content and impact force on groove rollers are the three inputs and it produces two outputs in the form of either Andon (a visual signal) or line stoppage. By using Multiple Input and Multiple Output (MIMO) autonomation system, surface defects can be prevented by monitoring level of inputs.