A Bibliometric Analysis of Automated System Maintenance Tools
Keywords:
Maintenance Tools, Simulation-Based, Reliability, Iot, Bigdata AnalyticsAbstract
The evolution of automated system maintenance tools has been pivotal in advancing industrial efficiency, reliability, and resilience. This study offers a bibliometric analysis spanning six decades (1964–2024), encapsulating its intellectual growth, milestones, and emerging trends. Early works established foundational methodologies like simulation-based optimization, while recent advancements incorporate AI, IoT, and big data analytics. The analysis reveals exponential growth in research output post-2010, emphasizing predictive maintenance and Industry 4.0 paradigms. Challenges include legacy system integration, scalability for SMEs, and standardization. This study provides a roadmap for future research, fostering innovations in autonomous maintenance systems for increasingly complex operational landscapes.
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