Research And Application Of Supplier Classification In Power Plant Equipment Industry

In recent years,as the development of domestic thermal power market continues to encounter the bottleneck and the annual output of thermal power shows overall downward trend,the company's net profit situation is not optimistic and the business risks are also growing.To improve the quality of enterprise operations management and effectively control the business risks,we must improve efficiency by reducing costs.The enterprise is a large-scale power plant boiler manufacturing company,whose procurement costs account for more than seventy-two percent of the total cost.However,because of the complexity of company's supply chain system,and the huge number of suppliers,it is difficult to carry out unified management.Therefore,how to reduce procurement cost through strategic procurement system optimization,and to make supply chain system more green,healthy and sustainable,has become the new opportunities and challenges for power plant boiler manufacturing enterprise managers to confront with.Based on in-depth analysis of supply chain management problems which utility boilers companies are facing,the objective of the thesis is to take appropriate strategies and differentiated supply vendor management,as well as to establish a scientific and practical evaluation system for one of materials by using Roland Berger's project of classification that divides materials into different models.The paper also uses the analytic hierarchy process to evaluate the key suppliers of materials model.The author evaluates key suppliers in the way of analytic hierarchy process.On the basis of the evaluation model of analytic hierarchy process,the research is applied to the classification of power plant equipment suppliers,taking the project of Taizhou power plant as an example,to conduct an empirical research to summarize the application methods of supplier classification management for power plant equipment industry and provide reference and ideas for reducing the cost of purchase and improving the operation efficiency of the supply chain.