The Impact of AI-Enhanced Predictive Maintenance on Operational Cost Reduction: The Moderating Role of Kaizen—An Exploratory Study  

Section: Research Paper
Issue
Vol. 20 No. 70 (2026): Regional Studies Journal
Pages
427-466

Abstract

Research Idea: AI-enhanced predictive maintenance is a modern approach that facilitates the early prediction of faults, reduces unplanned downtime, and minimizes resource waste, thereby contributing to lower operational costs and greater performance efficiency. Within this context, Kaizen serves as a complementary approach to continuous improvement and waste reduction in industrial companies.


Objective: This research aims to examine the effect of AI-enhanced predictive maintenance on operational cost reduction and to test the moderating role of Kaizen in strengthening this effect within industrial companies.


Methodology: The research adopted a deductive-analytical approach based on a review of recent literature on smart maintenance and Kaizen costing. Appropriate statistical methods were also employed to analyze questionnaire data and test the research hypotheses using IBM SPSS Statistics, Version 24.


Results: The findings indicate that AI-enhanced predictive maintenance represents a shift in the management of maintenance costs, from addressing the costs associated with downtime after failures occur to the early prediction of faults and their associated costs. The results of testing the first hypothesis confirmed a statistically significant positive effect of AI-enhanced predictive maintenance on reducing operational costs, accounting for 44% of the variance, and highlighting its role in minimizing unplanned downtime and improving the efficiency of operational resource utilization.


Conclusion: The research concludes that AI-enhanced predictive maintenance contributes to reducing operational costs and improving financial and operational performance, while the adoption of Kaizen strengthens this effect by supporting continuous improvement and reducing waste. The research recommends expanding the application of predictive maintenance systems and adopting Kaizen practices in industrial companies, particularly in production lines and equipment for which downtime results in substantial operational costs.

Keywords:

Predictive Maintenance; Artificial Intelligence; Operational Costs; Kaizen; Industrial Companies.

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Authors

Rabab A. Shihab Alabadi

Faculty of Management and Economics, University of Mosul

Identifiers

DOI: 10.33899/rsj.v20i70.64741

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The Impact of AI-Enhanced Predictive Maintenance on Operational Cost Reduction: The Moderating Role of Kaizen—An Exploratory Study  . (2026). مجلة دراسات إقلیمیة, 20(70), 427-466. https://doi.org/10.33899/rsj.v20i70.64741
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The Impact of AI-Enhanced Predictive Maintenance on Operational Cost Reduction: The Moderating Role of Kaizen—An Exploratory Study  . (2026). مجلة دراسات إقلیمیة, 20(70), 427-466. https://doi.org/10.33899/rsj.v20i70.64741