Abstract
The study mainly focuses on resource allocation optimization for industrial product-service systems (IPS2). The development of IPS2 leads to sustainable economy by introducing cooperative mechanisms apart from commodity transaction. The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio. Three basic rules for resource allocation optimization are put forward to improve system operation efficiency and cut unnecessary costs. An approach based on fuzzy multiple linear regression (FMLR) is developed, which integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems, which helps reduce those costs caused by unnecessary resource transfer. The iteration mechanism is introduced in the FMLR algorithm to improve forecasting accuracy. A case study of human resource allocation optimization in construction machinery industry is implemented to test and verify the proposed model.
Highlights
The development of industrial product-service systems (IPS2) has greatly transformed business models from product economy to service economy [1]
The randomness and fluctuation of service requests from customers lead to the volatility of IPS2 resource utilization ratio
By the conclusions and applications of existing work, it can be found out that the fuzzy multiple linear regression (FMLR) method integrates the strength and concision of multiple linear regression in data fitting and factor analysis and the merit of fuzzy theory in dealing with uncertain or vague problems by imitating human decision making processes, which matches the requirements in solving the IPS2 resource allocation optimization problems
Summary
The development of industrial product-service systems (IPS2) has greatly transformed business models from product economy to service economy [1]. With the fast development of intelligent manufacturing technologies, homogenization of products in function, quality, and capability has intensified competition in technical innovation Based on this situation, more companies are trying to seek new opportunities and differentiated competition in business mode innovation by offering personalized and ultraexperienced services with high quality, fast response, and good customer experience. In procedure A, different external factors may cause the uncertainty of customer needs and randomness of service requests. This leads to the volatility of service orders and tasks in Procedure B.
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