Integrated production and maintenance planning under uncertain demand with concurrent learning of yield rate

Huidong Zhang () and Dragan Djurdjanovic ()
Additional contact information
Huidong Zhang: University of Texas at Austin
Dragan Djurdjanovic: University of Texas at Austin

Flexible Services and Manufacturing Journal, 2022, vol. 34, issue 2, No 8, 429-450

Abstract: Abstract Strong interactions between decisions in the maintenance and production scheduling domains, and their impacts on the equipment yield rates necessitate maintenance and production decisions being optimized concurrently, with considerations of yield dependencies on the equipment conditions and production rates. This paper proposes an integrated decision-making policy for production and maintenance operations on a single machine under uncertain demand, with concurrent considerations and learning of yield dependencies on the equipment conditions and production rates. This policy is obtained through a two-stage stochastic programming model, which considers the variable demand, machine degradation, and maintenance times. This model incorporates outsourcing decisions and operational decisions regarding reworking, scraping of imperfect products to ensure the demand is adequately met. A closed-form reinforcement learning method is utilized to learn yield dependencies. Simulations confirm the necessity of yield learning and show the proposed method outperforms the traditional, fragmented approaches where the effects of production rates and machine conditions on the resulting yield rates are not considered. The two-stage stochastic setting is demonstrated by comparing with the traditional one-stage deterministic approach, where decisions are made based on the expected demand and production performance, with scrapping, reworking, and outsourcing decisions established before the demand and production performance are observed.

Keywords: Integrated decision-making; Maintenance scheduling; Production planning; Learning of yield rate; Two-stage stochastic programming (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations:

Downloads: (external link)
http://link.springer.com/10.1007/s10696-021-09417-8 Abstract (text/html)
Access to the full text of the articles in this series is restricted.

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:spr:flsman:v:34:y:2022:i:2:d:10.1007_s10696-021-09417-8

Ordering information: This journal article can be ordered from
http://www.springer.com/journal/10696

DOI: 10.1007/s10696-021-09417-8

Access Statistics for this article

Flexible Services and Manufacturing Journal is currently edited by Hans Günther

More articles in Flexible Services and Manufacturing Journal from Springer
Bibliographic data for series maintained by Sonal Shukla () and Springer Nature Abstracting and Indexing ().