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@article{201869,
        author = {Prof.JADHAV VILAS SUBHASH},
        title = {AI-Based Predictive Maintenance System},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {12},
        pages = {8114-8115},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=201869},
        abstract = {The AI-Based Predictive Maintenance System is an intelligent solution designed to monitor machine health and predict equipment failures before they occur. Traditional maintenance methods often lead to increased downtime and maintenance costs due to unexpected machine breakdowns or unnecessary servicing. The proposed system uses Artificial Intelligence (AI) and Machine Learning (ML) techniques to analyze real-time data collected from sensors such as vibration, temperature, and current sensors. The collected data is processed and analyzed using machine learning algorithms like Random Forest and Support Vector Machine (SVM) to detect abnormal machine conditions. The system predicts machine status as normal, warning, or failure and generates alerts for timely maintenance actions. This approach helps reduce downtime, improve productivity, minimize maintenance costs, and enhance equipment reliability. The system is highly useful in modern industries and supports Industry 4.0-based smart manufacturing applications.},
        keywords = {Support Vector Machine, Unnecessary Servicing, Real-Time Data},
        month = {May},
        }