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Open AccessArticle

Product Service System Availability Improvement through Field Repair Kit Optimization: A Case Study

Graduate School of Engineering Practice, Institute of Engineering Research, Seoul National University, Seoul 08826, Korea
This article is a re-written and extended version of “Improving Product Service System Availability through Field Repair Kit Optimization” presented at the 2nd East Asia Industrial Engineering Workshop (EAWIE 2015), Seoul, Korea, on 7 November 2015.
Appl. Sci. 2019, 9(20), 4272; https://doi.org/10.3390/app9204272
Received: 11 September 2019 / Revised: 29 September 2019 / Accepted: 9 October 2019 / Published: 12 October 2019
(This article belongs to the Special Issue Computer-Aided Manufacturing and Design)
Product service system (PSS) is becoming a popular business model, where companies offer product based service to customers to realize steady recurring revenue. However, to provide PSS-based service to customers in reliable way, PSS need to be supplemented with a field repair kit onsite, in case of parts failure and PSS shutdown. The field repair kit consists of frequently used spare parts in multiple quantities. However, mismatch in spare parts type and quantities in the field repair kit will results in sub-par performance of PSS for both customer and company. In this paper, a case study involving industrial PSS repair kit optimization is presented. In the case study, the field repair kit for complex industrial printing system is cost optimized, while satisfying the system availability requirement, specified by the maintenance contract between the company and the customer. Key analysis steps and results are presented to offer insight into the PSS field repair kit optimization, offering useful references to industrial practitioners. View Full-Text
Keywords: product service system (PSS); availability; field repair kit product service system (PSS); availability; field repair kit
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Suh, E.S. Product Service System Availability Improvement through Field Repair Kit Optimization: A Case Study. Appl. Sci. 2019, 9, 4272.

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