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
Citation
MOOSA, Sharafali; TARAKCI, Hakan.; KULKARNI, Shailesh; and Shahul Hameed, Raja Abdul Razack.
On setting the delivery due date with production on a machine under outsourced maintenance. (2017). Proceedings of the International Conference on Industrial Engineering and Operations Management 2017. 243-244.
Available at: https://ink.library.smu.edu.sg/lkcsb_research_all/11
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.
Additional URL
http://www.xcdsystem.com/ieom/2017Annual/papers/62.pdf