Production and energy mode control of a production-inventory system

Barış Tan, Oktay Karabağ*, Siamak Khayyati

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

7 Citations (Scopus)

Abstract

Energy efficiency in manufacturing can be improved by controlling energy modes and production dynamically. We examine a production-inventory system that can operate in Working, Idle, and Off energy modes with mode-dependent energy costs. There can be a warm-up delay to switch between one mode to another. With random inter-arrival, production and warm-up times, we formulate the problem of determining in which mode the production resource should operate at a given time depending on the state of the system as a stochastic control problem under the long-run average profit criterion considering the sales revenue together with energy, inventory holding and backlog costs. The optimal solution of the problem for the exponential inter-arrival, production and warm-up times is determined by solving the Markov Decision Process with a linear programming approach. The structure of the optimal policy for the exponential case uses two thresholds to switch between the Working and Idle or Working and Off modes. We use the two-threshold policy as an approximate policy to control a system with correlated inter-event times with general distributions. This system is modelled as a Quasi Birth and Death Process and analyzed by using a matrix-geometric method. Our numerical experiments show that the joint production and energy control policy performs better compared to the pure production and energy control policies depending on the system parameters. In summary, we propose a joint energy and production control policy that improves energy efficiency by controlling the energy modes depending on the state of the system.

Original languageEnglish
Pages (from-to)1176-1187
Number of pages12
JournalEuropean Journal of Operational Research
Volume308
Issue number3
DOIs
Publication statusPublished - 1 Aug 2023

Bibliographical note

Funding Information:
This work was supported by TUBITAK (Grant number 221M393) and European Union's Horizon 2020 Research and Innovation Programme [IN4ACT project under grant agreement no. 810318].

Funding Information:
This work was supported by TUBITAK (Grant number 221M393) and European Union’s Horizon 2020 Research and Innovation Programme [IN4ACT project under grant agreement no. 810318 ].

Publisher Copyright:
© 2022 The Authors

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