ECONOMIC EFFICIENCY OF AI IMPLEMENTATION IN ELECTRICAL EQUIPMENT DIAGNOSTICS AND MAINTENANCE

A comprehensive assessment of the economic efficiency of implementing artificial intelligence (AI) in the diagnostics and maintenance of electrical equipment was conducted. Key advantages and potential risks of such integration were identified, and a methodology for quantitatively evaluating the economic benefits from optimizing technical maintenance and reducing accident rates was developed. A methodological approach involving a comparative analysis of traditional and AI-enhanced models was applied. The economic evaluation included calculating reductions in downtime, inventory optimization, decreased repair costs, extended equipment lifespan, and AI implementation costs. A sensitivity analysis was conducted, and recommendations were developed. The results demonstrate that AI implementation shows a significant positive economic effect. Maintenance cost reduction reaches 20-30%, and downtime reduction is 15-25%. The reliability and safety of the electric power system are enhanced, and inventory management is optimized. Equipment lifespan increases by 10-15%, and the investment payback period ranges from 1.5-3 years. The study concludes that the implementation of AI in the diagnostics and maintenance of electrical equipment is economically justified. AI technologies enable a shift to predictive strategies, reducing operational costs, minimizing downtime, increasing reliability, and extending equipment lifespan. The necessity for further research on standardization and integration of AI solutions is emphasized.

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Publication Details

Journal
ГРААЛЬ НАУКИ
Published
2025-06-20
DOI
https://doi.org/10.36074/grail-of-science.20.06.2025.017
Primary Topic
Mining and Industrial Processes
Type
article
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article

ECONOMIC EFFICIENCY OF AI IMPLEMENTATION IN ELECTRICAL EQUIPMENT DIAGNOSTICS AND MAINTENANCE

Oleg Petruchenko, Vadim Lobodzinsky, Anna Yu. Palamarchuk, Andrii O. Petruchenko
ГРААЛЬ НАУКИ
Mining and Industrial Processes
article

ECONOMIC EFFICIENCY OF AI IMPLEMENTATION IN ELECTRICAL EQUIPMENT DIAGNOSTICS AND MAINTENANCE

Oleg Petruchenko, Vadim Lobodzinsky, Anna Yu. Palamarchuk, Andrii O. Petruchenko
article en

Abstract

A comprehensive assessment of the economic efficiency of implementing artificial intelligence (AI) in the diagnostics and maintenance of electrical equipment was conducted. Key advantages and potential risks of such integration were identified, and a methodology for quantitatively evaluating the economic benefits from optimizing technical maintenance and reducing accident rates was developed. A methodological approach involving a comparative analysis of traditional and AI-enhanced models was applied. The economic evaluation included calculating reductions in downtime, inventory optimization, decreased repair costs, extended equipment lifespan, and AI implementation costs. A sensitivity analysis was conducted, and recommendations were developed. The results demonstrate that AI implementation shows a significant positive economic effect. Maintenance cost reduction reaches 20-30%, and downtime reduction is 15-25%. The reliability and safety of the electric power system are enhanced, and inventory management is optimized. Equipment lifespan increases by 10-15%, and the investment payback period ranges from 1.5-3 years. The study concludes that the implementation of AI in the diagnostics and maintenance of electrical equipment is economically justified. AI technologies enable a shift to predictive strategies, reducing operational costs, minimizing downtime, increasing reliability, and extending equipment lifespan. The necessity for further research on standardization and integration of AI solutions is emphasized.

ГРААЛЬ НАУКИ(53)
National Technical University of Ukraine “Igor Sikorsky Kyiv Polytechnic Institute” (UA)
Openalex Percentile: Top 67%
Mining and Industrial Processes
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