Research On Key Techniques Of Module Construction And Quality Control For Large Scale Air Separation Systems

Product diversification and cost is a pair of contradictory for the customization of large air separation equipment, and modular design is an effective method for solving this problem. Quality Control is of great importance for large air separation equipment production enterprise. In order to optimize the modular design and quality control of air separation equipment, quality characteristic extraction technology, module construction technology and module quality evaluation are researched in this paper. At last, the theory is successfully used in actual product development and has achieved good effect.The main contents of this dissertation are as follows:Chapter 1 gives the review of the content and research status of the product modular design and quality control. Based on analyzing the structure and demand condition of large air separation equipment, the content and research development of customer demand modeling technology for product modular design, product quality characteristic extraction technology, product module construction technology and product module quality evaluation are introduced. At last, the research background, research content and structural frame are given.Chapter 2 researches the quality characteristic extraction technology for large air separation equipment. Combining with the characteristics of the large air separation equipment's customer demand, the customer demand is divided to content and structure, the matter-element-based customer demand topological structure model is established. Multiple attribute evidence reasoning theory is used to construct the quality house of the large air separation equipment. At last, an example is given to validate the feasibility of the method.Chapter 3 researches the quality-based module construction method. The quality characteristic of large air separation equipment is used as the criterion of module construction, the rough set is used to preliminary classify the sample parts in Hilbert Space, and then the numbers of modules, the lower approximation of modules and the upper approximation of modules are obtained. Based on above mentioned results, improved non-dominated sorting genetic algorithm was used for searching the optimal module partition solution. At the end of this chapter, large scale deep cooling air-separating equipment's module partition process as a practical case is provided to illustrate the application and validation of the proposed method through simulation and computation.Chapter 4, in this chapter, the constructed module quality is evaluated, and a multiple-criteria evaluation method based on vague cross entropy is given. Vague set is used to model the assessment information, vague cross entropy is used to express the fuzzy degrees of assessment information, and the distance measure method in traditional TOPSIS is replaced by vague cross entropy to measure the differences of vague sets. Then the Module quality assessment information under different criterions is composited and the final result is got. At last, large air separation equipment's model quality is evaluated to check the availability of the above method.Chapter 5, combined with the company's real demand and research results in this dissertation, a software system about module construction and quality control for large air separation equipment manufacturing enterprises is developed.Chapter 6 summarizes the main research content and results in this dissertation, and the future research direction of the author is given.