163
Views
13
CrossRef citations to date
0
Altmetric
Original Articles

Optimal maintenance planning and crew allocation for multipurpose batch plants

&
Pages 355-377 | Published online: 21 Feb 2007
 

Abstract

A mathematical programming approach to optimize process plant performance subject to equipment failure is presented. The optimal production planning and scheduling in multipurpose process plants involves the efficient utilization of assets and resources to produce a number of products so as to satisfy market demands while optimizing a performance criterion. However, the degree of utilization of process plant components, within the time horizon of operation, critically depends on the level of equipment availability. The interactions between production and maintenance planning as well as the necessary links to quantify the strong interactions between them are studied. The preventive maintenance planning and crew allocation problem are used to demonstrate the effectiveness of the proposed approach. The overall problem is first formulated as an optimal control problem by integrating an aggregate production planning model with a continuous time Markov chain maintenance model. The resulting problem is then transformed into a mixed-integer linear programming model by using an Euler discretization scheme and appropriate linearizations of bilinear terms. Finally, extensions to include design aspects are also discussed. The applicability of the proposed approach is demonstrated by a number of illustrative examples.

Log in via your institution

Log in to Taylor & Francis Online

PDF download + Online access

  • 48 hours access to article PDF & online version
  • Article PDF can be downloaded
  • Article PDF can be printed
USD 61.00 Add to cart

Issue Purchase

  • 30 days online access to complete issue
  • Article PDFs can be downloaded
  • Article PDFs can be printed
USD 973.00 Add to cart

* Local tax will be added as applicable

Related Research

People also read lists articles that other readers of this article have read.

Recommended articles lists articles that we recommend and is powered by our AI driven recommendation engine.

Cited by lists all citing articles based on Crossref citations.
Articles with the Crossref icon will open in a new tab.