In recent years, the increasingly severe risks and challenges in global economy have facilitated leading manufacture powers to adopt reindustrialization strategy. Service-oriented manufacturing has become the main area and national strategy during the manufacturing transformation and upgrading. “Made in China 2025”, sharing the same focus on the transition to service-oriented manufacturing as German Industry 4.0 and the US Industrial Internet Strategy, also regards service-oriented manufacturing as a major action plan. After the transformation of manufacturing enterprises into service-oriented ones, the operation system has changed from pure production into a new integrated system combining production and service together. However, a large number of service-oriented manufacturing companies still use the old resource and capacity management methods, or directly borrow the management methods of a pure service system to manage the integrated production and service system, which may cause heavy losses. What is needed to mentioned that, there is no current research carried out on the capacity management of this kind of integrated system.

Therefore, Prof. WANG Kangzhou and his research team carried out related research and explore the capacity allocation policy for an IPSS that consists of a manufacturing facility and a service center.

Here is the detailed information of this paper mentioned above.

• -Title: Capacity Allocation of an Integrated Production and Service System

• -Journal: Production and Operations Management

• -Author: Kangzhou Wang, Shouchang Chen, Zhibin Jiang, Weihua Zhou, Na Geng

• -Abstract: Manufacturing servitization has become a major trend in industry that is implemented by so called integrated production and service systems (IPSSs) to offer not only products but also their associated services. In this paper, we explore the capacity allocation policy for an IPSS that consists of a manufacturing facility and a service center. The IPSS serves two classes of customers, each demanding a specific product produced at the manufacturing facility and, subsequently, the associated service offered by the service center. We formulate this problem of resource allocation as a Markov decision process. Our analysis suggests that it is optimal to serve the customer with the larger cost saving rate and slower service rate, where the cost saving rate equals service rate times the sum of holding cost and waiting cost. Then we explore production control policies coupled with optimal service ones. We demonstrate that, with light service traffic, the system under the optimal production policy becomes similar to a make‐to‐stock system. Such a system can effectively hedge the system uncertainty. Therefore, the optimal production policy for the IPSS is also a hedging point policy. Under this policy, switching and idling curves split the state space into three regions: one without any production, the two others for production of two type products respectively. We also discuss the optimal control policies of the two extensions of the IPSS (one with multiple types of product and customers, and the other with a single product and two classes of customers) and find that the characters of the optimal production and service policy still hold. Finally, we develop three heuristic integrated scheduling policies. Numerical experiments show that one is very effective.

• -Link:https://doi.org/10.1111/poms.13407