Haben Gebreweld

This research aims to develop a comprehensive, multi-dimensional framework for assessing the industrial impact of intelligent maintenance technologies in the heavy machinery sector. By leveraging a mixed-methods approach, the study investigates industry-specific needs, adoption barriers, and measurable outcomes of predictive and prescriptive maintenance. Through literature reviews, qualitative interviews, and quantitative surveys, the research builds a robust
understanding of maintenance challenges and opportunities. Case studies and pilot testing in operational environments provide empirical validation for the proposed framework, ensuring its practical relevance. Expected outcomes include actionable insights for practitioners, scientific contributions to maintenance strategies, and a validated framework for optimizing operations, reducing costs, and improving safety across industries. The study addresses critical gaps in existing research, paving the way for intelligent maintenance adoption in complex, high-demand environments.