Manufacturing system energy-saving operation decision-making method and device based on fuzzy Petri net

Abstract

The invention belongs to the field of energy-saving optimization of the production and manufacturing industry, and discloses a manufacturing system energy-saving operation decision-making method and device based on a fuzzy Petri net. The method comprises the following steps: (1) acquiring real-time state information of a machine and real-time in-process product levels of upstream and downstream buffer areas of the machine as input variables of an energy-saving decision; (2) taking the decision state of the machine as an output variable, establishing a fuzzy reasoning rule base of an energy-saving operation decision, and determining influence weights of an input variable and the output variable; (3) establishing a fuzzy Petri net model of an energy-saving operation decision according to theinput and output variables, the influence weight and a fuzzy reasoning rule base; (4) obtaining the credibility of a conclusion proposition through fuzzy Petri network reasoning calculation; and (5)the decision corresponding to the conclusion proposition with the maximum credibility being the machine decision state at the current moment. While the yield of the production system is effectively maintained, remarkable energy consumption saving can be achieved, the execution process is simple, and the application range is wide.

Description

technical field [0001] The invention belongs to the field of energy-saving optimization in the manufacturing industry, and more specifically relates to a method and equipment for energy-saving operation decision-making of a manufacturing system based on fuzzy Petri nets. Background technique [0002] As a pillar industry of global economic development, while manufacturing creates a lot of wealth for human beings, it also inevitably exacerbates problems such as global energy shortage, climate warming, and environmental pollution. Green and energy-saving manufacturing has become the main development trend of the international manufacturing industry in the 21st century. In addition, the development of emerging technologies such as the Internet of Things has also laid the foundation for the efficient and low-carbon operation of manufacturing systems. [0003] At present, research on energy-saving production in manufacturing systems mainly includes research and development of en...

AI Technical Summary

Problems solved by technology

However, due to the dynamics and random uncertainty of the manufacturing system, as well as the highly nonlinear energy consumption of machinery and equipment, it is often difficult to model, analyze and predict the energy consumption of the manufacturing system with a simple mathematical model. The actual random factors such as area are also difficult to describe in the optimization model

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