Capacity Allocation of an Integrated Production and Service System

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 study, 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.

Capacity management for a leasing system with different equipment and batch demands

“…They formulated the capacity rationing problem as a MDP, characterized the optimal policy, and developed a heuristic by fluid approximation. Wang et al (2021) studied the joint decision on production and allocation for a queuing system with different customer classes. Yang et al (2022) explored the rationing policy for a leasing company with two types of containers.…”

“…Wang et al. (2021) studied the joint decision on production and allocation for a queuing system with different customer classes. Yang et al.…”

Dynamic Contract Design of Product-Service Supply Chain considering Consumers’ Strategic Behavior and Service Quality

“…Furthermore, some scholars have studied capacity allocation problem of PSS. Wang et al consider production service systems consisting of a service center and a manufacturing facility, which provides products and related services, and study the capacity allocation problem of the production service systems [46]. Moreover, Xu et al review 71 research literature studies of the PSSC and analyze the future research opportunities and research strategies of the PSSC [47].…”

Managing demand by upgrade programs and markdown pricing with a product rollover

“…Another related literature is concerned with the product‐service system, also referred to as the product‐as‐service system and manufacturing servitization (Vandermerwe & Rada, 1988; Wang et al, 2021), where products are offered together with associated services. Resta et al (2017) presented a conceptual framework to help firms in designing and managing product‐service systems within the context of supply chains.…”