Predictive Maintenance: The New Creator of a Manufacturing Enterprise's Points-of-Difference

ABSTRACT: Effective use of predictive maintenance creates enormous points-of-difference that bolster a manufacturing firm’s competitiveness. However, systematic review indicated that even if the stringent use of an effective predictive equipment maintenance plan creates points-of-difference that bolster a manufacturing firm’s competitiveness, empirical evidence still indicated poor management support to be a problem in most manufacturing enterprises. Poor management support often mutates into inadequate resource allocation. This affects the investment in the right technologies, sensors, and software for measuring and alerting management about the failing state of equipment performance. Predictive maintenance is also often affected by poor training to improve skillfulness. Combined with the difficulties of managing and influencing change from a reactive equipment maintenance mindset to a predictive approach, these were found to undermine the overall effectiveness of predictive maintenance.

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Publication Details

Journal
Zenodo (CERN European Organization for Nuclear Research)
Published
2025-10-27
DOI
https://doi.org/10.5281/zenodo.17453567
Primary Topic
Quality and Supply Management
Type
article
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article

Predictive Maintenance: The New Creator of a Manufacturing Enterprise's Points-of-Difference

Zenodo (CERN European Organization for Nuclear Research)
Quality and Supply Management
article

Predictive Maintenance: The New Creator of a Manufacturing Enterprise's Points-of-Difference

article en

Abstract

ABSTRACT: Effective use of predictive maintenance creates enormous points-of-difference that bolster a manufacturing firm’s competitiveness. However, systematic review indicated that even if the stringent use of an effective predictive equipment maintenance plan creates points-of-difference that bolster a manufacturing firm’s competitiveness, empirical evidence still indicated poor management support to be a problem in most manufacturing enterprises. Poor management support often mutates into inadequate resource allocation. This affects the investment in the right technologies, sensors, and software for measuring and alerting management about the failing state of equipment performance. Predictive maintenance is also often affected by poor training to improve skillfulness. Combined with the difficulties of managing and influencing change from a reactive equipment maintenance mindset to a predictive approach, these were found to undermine the overall effectiveness of predictive maintenance.

Zenodo (CERN European Organization for Nuclear Research)
University of South Africa (ZA)
No poverty
Openalex Percentile: Top 32%
Quality and Supply Management
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