The Research On The Key Technologies Of The Optimization And Automatization In The Beer Production Processing

The beer production is a traditional industry of our country. With the development of the national economy and the improvement of life, our beer industry has an unprecedented development, and playes a very important role of the national economy. Nevertheless, as the increasingly fierce competition and the gradually opening market in the beer companies, there is great practical significance for the study of the beer process control and optimization. However, the process of beer production is a complex industrial system. Although the traditional control and optimization theories are mature, but the application on the complex industrial system still exists limitations. With the development of the intelligence, there are many intelligent optimization algorithms which are independent of the issue, such as the ant colony algorithm, genetic algorithm, and so on. Through the analog or explanation of some natural phenomenas or processes to develop, the intelligent algorithms are suitable for the control and optimization of complex industrial systems. Therefore they provide a new way of solving complex problems.In the paper, baseing on the beer production process, the intelligent optimization algorithms, the optimization of beer recipe and the scheduling optimization of beer production have been studied, also the automation technology and the application of beer production process have also been researched.The workes and innovations of the paper are as follows:(1) Aiming at shortcomings of ant colony algorithm in the process of iteration, inspired by the characteristics of human social activities, there are two improved operator presented in the paper. They are curiosity factor and tax operator which respectively emulating innovative thinking and the tax effectiveness of human society. Simulation results show that the ant colony algorithms, added improved operator, are very effective to improve the overall optimization capabilities. But also the necessary theoretical foundation has been provided for the following research on application.(2) The relationship mode between beer flavor and raw materials has been establishment. The optimization design of beer recipe has also been discussed, and an improvement of ant colony optimization Algorithm is presented for the problem with continuous domain. Beer recipe determines the flavor, quality, cost and other important indicators of the product, but the recipe still rely on the experience and the test methods, which has blindness and is difficult to satisfy various parameters. Therefore the intelligent design optimization of beer recipe has been studied, and a variable scale ant colony algorithm is presented to enhance ant colony algorithm for the domain optimization problem. Finally, by using fuzzy comprehensive evaluation and neural network paper, the beer flavor indicators are first been quantitative researched. The results show that the beer recipe design of ant colony optimization is obviously superior to the traditional formula design method, so the new design method has a good industrial value. In addition, compared with the traditional ant colony algorithm, the improved ant colony algorithm can effectively reduce the amount of computation and shorten the calculation time, is more suitable for resolving continuous domain optimization problem.(3) By analysing the beer production and the process, the beer production scheduling models have been established, and production scheduling optimization method has been researched. Due to the characteristics of semi-continuous beer production and rapid response to changing requirements, all the production activities and economic benefits are greatly dependent on production planning and scheduling. Therefore, the problem of beer production scheduling has been researched in the paper. In order to reduce the size and complexity of the issue, the project has been divided into beer production scheduling and equipment scheduling, and long-term production plans model as well as short-term equipment scheduling model is set up. Then, the ant colony optimization algorithm has been used to solve optimal scheduling problems. The simulation results show that the ant colony algorithm is better than genetic algorithms, and other intelligent algorithm for better solutions, and the ant colony optimization scheduling method of beer production can guarantee the stability of inventory, reduce the negative impact of market volatility.(4) Aiming at a few traditional control difficult in the production of beer, such as fermenter temperature control and filtration layer monitoring of candle filter, the effective intelligent control strategies has been introduced by research and analysis and the results show that the intelligent control strategies are effective. By the systematic analysis of their characteristics of objects in the beer production process, the network structure and the hardware configuration of computer control has been discussioned. In addition, an effective design of automated control software has been presented.