Study On Quality Prediction Technique Of Supply Chain Using ABPM Network

Manufacturing industry is the material basis of national economic and socialdevelopment, which is also an important embodiment of comprehensive nationalstrength. The21st Century is a decisive century to China, when China must transformfrom a big manufacturing country to a powerful nation, and implement nationaleconomic flying in the round. To meet the rapidly growing market demand and remaininvincible in the fierce international competition, the country and enterprises mustattach great importance to product quality and service quality, and try to find methodsof managing and controlling product quality and service quality.With society progressing continually and technology developing rapidly, thecompetition between modern enterprises has evolved into the competition betweensupply chain, and the quality of supply chain has become the most important factor formanufacturing enterprises to participate in market competition, win customersatisfaction, and finally gain success, while the quality condition of the entire supplychain depends on the quality status of each process and links and related enterprises inthe supply chain. In recent years, experts have gradually focused the manufacturingresearch on supply chain coordination of quality management and control.Modern manufacturing supply chain is a complex system, with human resources,capital, materials, energy and information as the input of the system, and the tangibleproducts and intangible services as the output of the system, while any link in the chainwith a problem will affect other member companies in the supply chain. In order toensure the supply chain working healthy and stably, the research on quality assuranceability of supply chain (quality prevention, diagnosis and control technology) is veryimportant, which truly reflects the thinking of "prevention" in supply chain qualitymanagement. In this paper,"adaptive variable step size BP neural network algorithm"was introduced into the quality prediction technique research of supply chain, providinga new direction for the quality prediction technique research of manufacturing supplychain. The main contents of the paper are as follows:First of all, the research background, research significance, source of the subject,quality management of modern manufacturing supply chain, as well as the researchstatus at home and abroad and the researching thoughts and framework were introducedin this paper. Secondly, the theory of supply chain quality management and control wasexpounded, the general purposes and features of supply chain quality prediction wereanalyzed, then the quality prediction theory, models and processes based on customersatisfaction and process control were studied, and the quality prediction theory systemand technic framework of manufacturing supply chain were finally established.Thirdly, the key quality characteristics of each stage or link in supply chain wereabstracted from the perspective of customer satisfaction and process control. And theDelphi Method and expert scoring-analytic hierarchy process were used to build thequality prediction index system of manufacturing supply chain.Then, the principles and processes of neural network prediction algorithm werestudied deeply, and the adaptive variable step size BP neural network algorithm（ABPM）was used to establish the quality prediction mathematical model of supplychain.Finally, the functional requirements analysis and design program of establishingthe manufacturing supply chain quality prediction module were studied, themanufacturing supply chain quality management system within prediction module wasdeveloped, with a brief introduction.