← Gautam Parab

Manufacturing 4.0: AI-Driven Analytics for Predictive Maintenance

Scheduled maintenance services equipment on a calendar; predictive maintenance services it on evidence. This paper treats that transition as an analytics engineering problem rather than a modelling one.

It covers the ingestion and conditioning of industrial sensor and telemetry data, failure-mode modelling and remaining-useful-life estimation, and the integration path into existing maintenance and ERP workflows — the step at which most predictive maintenance programmes stall. The economics are examined directly: what unplanned downtime costs, what false-positive interventions cost, and where the break-even sits.

DOI: 10.36948/ijfmr.2024.v06i06.33539