Real-time optimization method of tire building-vulcanization production energy consumption based on intelligent algorithm

Abstract

The invention discloses an intelligent algorithm-based method for optimizing tire building-vulcanizing production energy consumption in real time. According to the method, workshop production energy consumption data and real-time production status are obtained through effectively arranging data acquisition equipment in a building-vulcanizing workshop, and a production processing system energy consumption model is established by combining the history energy consumption data, so that the building and vulcanizing processes are abstracted into a flexible flow-shop scheduling problem, the machines and workpieces are coded and an intelligent algorithm is adopted to reasonably schedule the processes, so as to obtain a feasible solution with the optimum fitness.

Description

technical field [0001] The invention relates to a real-time optimization method for workshop production energy consumption, in particular to a real-time optimization method for tire building-vulcanization production energy consumption based on an intelligent algorithm. Background technique [0002] In recent years, global energy demand has increased sharply, energy prices have continued to rise, and people's awareness of environmental protection has gradually increased, making "low-carbon economy" an important trend in the development of my country's manufacturing industry. The tire industry is a traditional labor, resource and technology-intensive high-energy manufacturing industry. The industry is gradually leading the tire consumer market with "energy-saving, environmental protection, safety, intelligence, and high-efficiency" products. Tire companies are also accelerating the adjustment of product structure and optimization and upgrading. , to realize the transition to a...

AI Technical Summary

Problems solved by technology

In the production of rubber tire enterprises, there are mainly two production processes of molding and vulcanization. These two processes are concentrated in production, have many constraints, and consume a lot of energy. The quality of the scheduling plan will directly affect the efficiency of the entire tire production process, and will also Have a huge impact on energy consumption levels

[0003] The Chinese patent application with the application number CN201310299342.3 "An Embedded Carbon Emission Monitoring and Detection System in the Vulcanization Process" realizes carbon emission monitoring and detection through an embedded system, and the Chinese patent application with the application number CN201410475461.4 "A Hybrid Based Optimum Scheduling Method of Energy Consumption in Tire Vulcanization Workshop Based on Genetic Algorithm "Based on Hybrid Genetic Algorithm, Optimal Scheduling of Energy Consumption in Tire Vulcanization Workshop Can Save Energy and Reduce Production Costs for Enterprises; Chinese Patent Application No. CN201010621470.1 "Tire Vulcanization Production Control system and operation adjustment" According to the vulcanization production control process, a production line integrated control system and method are proposed to realize the automatic management of vulcanization production; the Chinese patent application with the application number CN201510084152.9 "Flexible synthesis considering the dual objectives of cost and time Scheduling method" In order to solve the problem that the current flexible comprehensive scheduling method only considers the single goal of product completion time, resulting in high production costs, a flexible comprehensive scheduling method considering the dual objectives of cost and time is proposed

[0004] Although the above-mentioned technical solutions can achieve optimization results and have greatly promoted the optimization of energy consumption and the improvement of production efficiency, there are still the following problems in the realization of real-time optimization of energy consumption: 1) Due to the lack of real-time energy consumption information Comprehensive collection and extraction, production managers often cannot directly obtain real-time energy consumption information, resulting in a lag in scheduling based on energy consumption information, making it difficult to achieve optimal scheduling results

2) The optimization process is relatively complicated, and the solution efficiency is slow at the same time, which is not suitable for industrial production

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