Research On Vendor Selection And Order Allocation In Locomotive Industry In Cloud Manufacturing

New information technology, such as cloud computing, Big Data and the Internet of things, has raised a new industrial revolution around the world. Intelligent manufacturing technology and "Industry 4.0" are already emerging. Manufacturing is getting more intelligent, service-oriented and greener. The combination of information technology and manufacturing is deeply changing the business mode of enterprises in product design, manufacturing process and operation management and so on. With the convergence of manufacturing and information technology, based on the Internet, cloud computing and big data, the industrial pattern is turning into "customized mass production" and "service-oriented manufacturing" around the professional service activities through manufacturing life-cycle (especially the front-end and back-end).As an important basis of our national economy, locomotive manufacturing enterprises have complex product structure and multiple components and parts. The traditional manufacturing mode has been unable to meet volatile market demand because of inefficient use of resources. Therefore, Li Bohu and his partners put forward the concept of "Cloud Manufacturing". The Ministry of Science and Technology proposed the idea of cloud manufacturing based on the concept in order to improve the extent of resources sharing and serve customers with high-added value, low cost and international service. Up till now, some related research about cloud manufacturing, such as the cloud manufacturing platform of Aerospace Science and Technology Group and China CNR corporations limited, are both focused on structure construction and key technologies, while research on cloud manufacturing management theory is relatively less which is not conductive to the further development of cloud manufacturing. As Li Bohu said, cloud manufacturing was not a purely technical issue but it changed the overall situation of the manufacturing industry. The lack of relative management method seriously restricted the application of cloud manufacturing.Focusing on the actual purchasing demands of locomotive industry in cloud manufacturing, to improve customer satisfaction, the method and theory of vendor selection and order allocation for locomotive industry in cloud manufacturing are investigated.Firstly, according to concept of cloud manufacturing, the members and their interactions, characteristics and operational mode, characteristics of manufacturing resources and services of supply chain in cloud manufacturing are introduced. Based on the analysis of a large amount of literature on vendor evaluation index system, method and order allocation techniques, with literature review and investigation, the key factors that influence vendor evaluation and order allocation in cloud manufacturing are identified.The method of ascertaining attribute weight based on ANP for vendor evaluation and order allocation in cloud manufacturing is presented to deal with high subjectivity in indicators quantization. On the basis of analysis of process in vendor evaluation and order allocation in cloud manufacturing, with the key factors that influence vendor evaluation and order allocation, the index system is established with BOCR. Further, the ANP model for vendor evaluation and order allocation is identified combined with expert’s score. The attribute weight is calculated with matrix.Considering the balance between supply and demand, the production capability of vendors and quality constraints, the model for vendor selection and order allocation in cloud manufacturing is proposed. With the weight of each index identified above, it is converted into a single objective problem. Furthermore, the GA is used to solve the model.Finally, programming model for vendor selection and order allocation in cloud manufacturing is applied in A Locomotive Group. The vendor evaluation system is constructed based ANP. GA is used to solve the model. The application in A Locomotive Group shows the effectiveness of the model and provides insights into vendor selection and order allocation in cloud manufacturing for customers.