Methodological foundations for forecasting economic benefits from the transition to condition-based predictive maintenance using the MACPOM methodology

Анотація

The relevance of the study is determined by the growing complexity of industrial systems and the need to transition from time-based and reactive maintenance to condition-based approaches. Traditional strategies do not ensure alignment between technical parameters and economic performance, resulttin in higher costs and productivity losses.

The purpose of the article is to develop and substantiate a methodological approach to forecasting the economic benefits of predictive maintenance through integrating technical monitoring, diagnostics, and prediction with economic evaluation, based on the MACPOM methodology.

Methods include system analysis, generalisation, modelling, and economic evaluation, combining sensor monitoring, digital modelling, and predictive analytics.

Results show that integrating technical condition data, remaining useful life, and cost parameters enables quantitative assessment of economic effects, including reduced downtime, maintenance costs, and operational losses.

Conclusions confirm that integrated cyber-physical approaches improve decision-making and reduce total costs.

Future research should focus on improving economic assessment under uncertainty and adapting models to industry-specific conditions.