Abstract
The optimal configuration of manufacturing resources in the cloud manufacturing environment has always been the focus of research on various advanced manufacturing systems. Aiming at the problem of manufacturing resources optimization configuration for middle and lower batch customization enterprises in cloud manufacturing environment, this paper gives a bi-level programming model for manufacturing resources optimization configuration in cloud manufacturing environment which fully considers customer satisfaction and enterprise customization economic benefits. The method firstly identifies the relationship between customer demands and customer satisfaction through questionnaires and quantifies the Kano model effectively. Then, it uses Quality Function Deployment (QFD) to transform customer demand characteristics into engineering characteristics and integrates the qualitative and quantitative results of the Kano model. Next, the method establishes enterprise economic benefits function according to the factors of order quantity and input cost. Furthermore, a comprehensive nonlinear bi-level programming model is established based on cost, time, and quality constraints. The model is solved by intelligent algorithm. Finally, the validity and feasibility of the model are verified by model simulation of actual orders of an enterprise. This method effectively realizes the optimal configuration of manufacturing resources in the cloud manufacturing environment, while maximizing the interests of both suppliers and demanders.
Highlights
In today’s economic globalization, the market has gradually transformed from a seller’s market to a buyer’s market which has prompted more and more companies to start from traditional stock-based production to order-based production, in order to better meet the demand for products and services. e order-based production model requires companies to provide customers with the best possible products and services in the shortest possible time, while reducing the production costs of the company as much as possible [1]. e “cloud manufacturing” production model provides a new development model for the development of the manufacturing industry
Complexity explore and research [4]. erefore, this paper presents a bi-level planning manufacturing resource optimization configuration model based on customer satisfaction and economic benefits. e structure of this paper is as follows: Section 2 introduces the current state of research on manufacturing resource optimization configuration; Section 3 introduces problem description of the paper; Section 4 details the manufacturing resources optimization configuration model proposed in this paper; Section 5 simulates the model with an instance; Section 6 and Section 7 make a brief discussion and conclusion, respectively
Akbaripour et al proposed a new mixed integer programming (MIP) model to solve the process of service selection optimization and scheduling (SSOS) under the condition of cost and quality over time which the model is applied to the motorcycle manufacturing task in the cloud manufacturing environment [6]
Summary
In today’s economic globalization, the market has gradually transformed from a seller’s market to a buyer’s market which has prompted more and more companies to start from traditional stock-based production to order-based production, in order to better meet the demand for products and services. e order-based production model requires companies to provide customers with the best possible products and services in the shortest possible time, while reducing the production costs of the company as much as possible [1]. e “cloud manufacturing” production model provides a new development model for the development of the manufacturing industry. E order-based production model requires companies to provide customers with the best possible products and services in the shortest possible time, while reducing the production costs of the company as much as possible [1]. Manufacturing resources optimization con guration as a core component of cloud manufacturing which is the key link to reduce the cost of resource use and improve the e ciency of resource utilization [3]. How to scienti cally and e ciently realize the optimal con guration of production and processing resources, improve the utilization e ciency of production and processing resources, and provide customers with better production and processing services, which become an important issue for the cloud manufacturing model to Complexity explore and research [4]. How to scienti cally and e ciently realize the optimal con guration of production and processing resources, improve the utilization e ciency of production and processing resources, and provide customers with better production and processing services, which become an important issue for the cloud manufacturing model to Complexity explore and research [4]. erefore, this paper presents a bi-level planning manufacturing resource optimization configuration model based on customer satisfaction and economic benefits. e structure of this paper is as follows: Section 2 introduces the current state of research on manufacturing resource optimization configuration; Section 3 introduces problem description of the paper; Section 4 details the manufacturing resources optimization configuration model proposed in this paper; Section 5 simulates the model with an instance; Section 6 and Section 7 make a brief discussion and conclusion, respectively
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