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Research on Key Technology of Order-Based Manufacturing Quality Management System

Author: ZhouChaoBin
Tutor: CaiZongZuo
School: Chang'an University
Course: Mechanical Manufacturing and Automation
Keywords: Order -oriented manufacturing Quality management Neural Network Pattern Recognition Fuzzy Evaluation
CLC: F274
Type: Master's thesis
Year: 2010
Downloads: 90
Quote: 2
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Abstract


In order to adapt to market changes , the mode of production of most SMEs shift from mass production to more varieties of small batch production and orders production oriented to the market and the needs of users to become one of the main mode of production of small and medium-sized enterprises . Order manufacturing companies from receiving the order to go through the design, manufacture, sales and service aspects of the product , be considered to complete the whole process of product realization . For orders based manufacturing enterprises , the quality is the key. The quality of the product is present in the product realization process , in order to ensure the quality of research orders based manufacturing quality management system is of great significance . To this end, we carried out a detailed study on the order type of the key technologies for manufacturing quality management system . The main work done in this paper are: 1 , describes the characteristics of the meaning of quality management and manufacturing enterprises , designed the functional structure of the order based manufacturing quality management system , analysis of the key technologies of the system implementation process . 2 , less quality characteristics data for order type manufactured , proposed the establishment of quality control charts and calculation process capability index calculation model based on group technology , and the algorithm using the advantage of the similarity theory to solve the less short- order manufacturing data board, and apply it to the manufacturing process quality control link . The example shows that the above-described approach is feasible . 3, BP neural network to solve the control chart pattern recognition problem , discusses the BP network control chart pattern recognition step for the simulation analysis . Simulation results show that BP neural network control chart pattern recognition is applicable to the production order type . Equipment selection quality of the manufacturing process of the two fuzzy evaluation method to evaluate a mathematical model of the fuzzy evaluation , and the algorithm , and a case study . The case study shows that the fuzzy evaluation method is feasible manufacturing process equipment selection .

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