Fuzzy Petri Net Based Intelligent Machine Operation of Energy Efficient Manufacturing System

Abstract

In a manufacturing system, the idle status of machine consuming huge amounts of energy cannot bring any added value. How to reduce the energy waste of idle period through the real time control of machine status has become a challenging goal in an energy-efficient manufacturing environment. To address this problem, we propose a fuzzy Petri net based fuzzy reasoning approach to reduce the idle period by switching the on/off status of machines. The approach uses the real time data collected from the system, which include the level of upstream and downstream buffers, as well as the working status of the machine. The fuzzy rules are described by analyzing the decision intention according to the human knowledge. Simulation experiments show that this approach can effectively reduce the energy consumption with accepted throughput loss for a serial manufacturing system.