Publication Type

Conference Proceeding Article

Publication Date

4-2017

Abstract

We consider an unreliable production system with a contractual relationship with a customer for a firm delivery date. We focus on the production-related decisions of the manufacturer. We assume that production rate is constant as long as the system is up and running but the randomness in production is due to downtimes as a result of breakdowns and scheduled preventive maintenance activities. The maintenance of the production facility is outsourced to a contractor. As production output is random, the manufacturer needs to make two important decisions, viz (i) how much time to allow for production taking into account the trade-off between the penalty fee if actual production time turns out to be longer than the deadline and the inventory holding cost if the production time is shorter than the allowed time and (ii) how to design the maintenance outsourcing contract to maximize its own profit while satisfying the contractor's reservation (minimum) profit requirements. This is a finite horizon optimization problem. A regenerative stochastic process is identified and analysed to develop the cost function over the finite horizon. The optimization problem will be illustrated through numerical examples. Some managerial insights with regard to coordination and some extensions will also be provided.

Keywords

Maintenance, Reliability, Availability, Outsourcing, Channel coordination

Discipline

Operations and Supply Chain Management

Research Areas

Operations Management

Publication

Proceedings of the International Conference on Industrial Engineering and Operations Management 2017

First Page

243

Last Page

244

ISBN

9780985549763

Publisher

IEOM Society

City or Country

Canton, MI

Creative Commons License

Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License
This work is licensed under a Creative Commons Attribution-Noncommercial-No Derivative Works 4.0 License.

Additional URL

http://www.xcdsystem.com/ieom/2017Annual/papers/62.pdf

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