Considering Pressure Of Resource Constraints Optimization Method Of Energy Consumption In Tire Curing Workshop

Tire manufacturing industry is a high energy consumption manufacturing industry. There are several characteristics in it, such as wide range of products, frequent switching of product orders, a wide variety of resource mediums as well as labor-intensive. There is great significance in quality assurance and reduction of energy consumption during the process of making tires.In this process, due to multiple energy medium, various kinds of specifications, products switching, the energy of Vulcanizer is quite different under different conditions. In addition, according to the technical requirements of curing process. Vulcanizer need some vapor pressure to hold pressure to provide process environment for tire curing process when it in the three different states of normal curing, stop-preheating and hollow turn waiting during product switching process. What is difficult for the problem in this paper is that the steam generated by boiler is a certain everyday, and the number of opening Vulcanizers are unknown under the determined total pressure. What’s more, the tire curing process is constrained by steam pressure under different machining conditions. How to determine the number of opening Vulcanizers and the steam input in different condition, and finally it converted into how to arrange to process different tire products in Vulcanizer with different parameters. There is a direct impact on the energy consumption of the whole tire production whether the scheduling plan is good. Therefore, this paper mainly research the production scheduling problem in curing workshop, and construct energy consumption model considering the constraint of pressure resources. The main research contents are as follows:(1) According to analyzing energy flow distribution in tire manufacturing process and the factors of energy consumption in the process of curing workshop, it is necessary to find the characteristics of tire manufacturing process in curing workshop. Then the engineering problem of actual tire curing is abstracted as the scheduling problem of single process and multiple machine and multiple batch workpiece.(2) Combined scheduling problem abstracted above with the input and output of tire energy, and aiming at the actual engineering problem of curing process. The energy consumption model considering the constraint of pressure resources is constructed.(3) Aiming at the problem of energy consumption scheduling in curing workshop, intelligent algorithm was considered to establish scheduling model and the problem was solved at the same time in this paper. The advantages of genetic algorithm and particle swarm algorithm are simple operation fast speed and so on. But there are also some disadvantages in them, such as they may trapped in local convergence due to "premature" and single population structure. In order to make use of the advantages and avoid the disadvantages, hybrid algorithm with two population was used to seeking solution. What’s more, local optimization ability of simulated annealing algorithm was introduced into it.(4) The research of experiment verification on the two different algorithms were conducted. The results of the experiment confirmed that hybrid algorithm of two population is better than single algorithm. Then, the two algorithms were compared according to the simulation results and the best algorithm was chosen. What’s more, the energy consumption optimization model was applied to the process of production scheduling of curing workshop.