Maintenance strategy selection using AHP and ANP algorithms: A case study

Selim Zaim, Ali Turkyílmaz, Mehmet F. Acar, Umar Al-Turki, Omer F. Demirel

Research output: Contribution to journalReview articlepeer-review

79 Citations (Scopus)


Purpose - The purpose of this paper is to demonstrate the use of two general purpose decision-making techniques in selecting the most appropriate maintenance strategy for organizations with critical production requirements. Design/methodology/approach - The Analytical Hierarchical Process (AHP) and the Analytical Network Process (ANP) are used for the selection of the most appropriate maintenance strategy in a local newspaper printing facility in Turkey. Findings - The two methods were shown to be effective in choosing a strategy for maintaining the printing machines. The two methods resulted in almost the same results. Both methods take into account the specific requirements of the organization through its own available expertise. Practical implications - The techniques demonstrated in this paper can be used by all types of organizations for selecting and adopting maintenance strategies that have higher impact on maintenance performance and hence overall business productivity. The two methods are explained in a step-by-step approach for easier adaptation by practitioners in all types of organizations. Originality/value - The value of the paper is in applying AHP and ANP decision-making methodologies in maintenance strategy selection. These two methods are not very common in the area of maintenance, and hence add to the pool of techniques utilized in selecting maintenance strategies.

Original languageEnglish
Pages (from-to)16-29
Number of pages14
JournalJournal of Quality in Maintenance Engineering
Issue number1
Publication statusPublished - Mar 30 2012


  • AHP
  • ANP
  • Maintenance
  • Maintenance planning
  • Maintenance strategy
  • Strategy selection
  • Turkey

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Strategy and Management
  • Industrial and Manufacturing Engineering

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