Skip to main navigation Skip to search Skip to main content

Prescriptive maintenance: A comprehensive review of current research and future directions

  • Alessandro Giacotto*
  • , Henrique Costa Marques
  • , Alberto Martinetti
  • *Corresponding author for this work

Research output: Contribution to journalReview articleAcademicpeer-review

277 Downloads (Pure)

Abstract

Purpose: Providing a comprehensive literature review to consolidate existing knowledge, advancements and future directions in the field. By synthesizing the state of research, this work enhances the understanding of Prescriptive Maintenance (PsM) methodologies, applications and potential benefits to assist researchers in identifying fruitful avenues for further investigation, and guide practitioners in implementing PsM strategies to improve maintenance outcomes in their industries.

Design/methodology/approach: Through a systematic, multistage, specialists audited analysis of peer-reviewed articles, conference papers, books sections, thesis, magazines and industry reports, this work provides a literature review analyzing PsM origins, definitions, enablers, outputs and emerging trends.

Findings: PsM concept evolved in recent years representing a shift from traditional maintenance, leveraging prescriptive analytics, data-driven modeling and optimization techniques to enable proactive decision-making and optimal resource allocation. By harnessing PsM, organizations can anticipate and mitigate failures, optimize maintenance actions and enhance asset reliability.

Research limitations/implications: Existing literature points out the following challenges for PsM implementation: prescriptive analytics improvement, scalability of frameworks, development of prototypes, processes integration; PsM maturity assessment; asset health prognostics assertiveness, real-time data availability and adoption of cost functions to grasp business and environmental, social and governance (ESG) costs.

Practical implications: Optimal deployment of resources with little or no human intervention in the maintenance decision process and the creation of new services improving reliability and operational performance.

Social implications: By optimizing maintenance, not only direct costs diminish but also environmental, social and governance (ESG) related costs decrease by reducing energy waste during equipment’s operating phase, assessing the ecological impact of providing maintenance to operators and line maintenance stakeholders and, consequently, minimizing or even eliminating harmful effects on the environment and the human.

Originality/value: Work consolidating existing PsM-related knowledge and indicating future work is a gap in the literature. This paper fills this gap.

Original languageEnglish
Pages (from-to)129-173
Number of pages45
JournalJournal of quality in maintenance engineering
Volume31
Issue number1
DOIs
Publication statusPublished - 4 Mar 2025

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 9 - Industry, Innovation, and Infrastructure
    SDG 9 Industry, Innovation, and Infrastructure
  2. SDG 12 - Responsible Consumption and Production
    SDG 12 Responsible Consumption and Production

Keywords

  • 2025 OA procedure
  • Optimization
  • Prescriptive analytics
  • Prescriptive maintenance
  • Proactive maintenance
  • Literature review

Fingerprint

Dive into the research topics of 'Prescriptive maintenance: A comprehensive review of current research and future directions'. Together they form a unique fingerprint.

Cite this