IndiaManufacturing2023 – ongoing

Reliance Industries

Rotary equipment monitoring and early fault detection

Reliance reported 406 faults identified through rotary equipment monitoring

WorkingCompany's own claim

Problem

Reliance needed earlier warnings of rotating equipment failures so maintenance teams had more time to intervene.

Approach

Reliance combined machine learning with engineering models to compare actual and predicted equipment conditions. Its team integrated Honeywell and Expert Microsystems software and worked with engineers to define failure symptoms and test models.

Results

406faults identified since the critical-equipment programme began, reported by RelianceCompany's own claim[1]

1,095rotating assets modelled across 10 Indian sites, reported by RelianceCompany's own claim[1]

Takeaway

The system prioritised faults using equipment criticality and fault severity. Identified faults were not a count of prevented breakdowns.

Sources

Manage motors with models
Control1 Oct 2025News article

Source summaries

[1]Control1 Oct 2025

Reliance's maintenance digitalisation lead described its equipment monitoring deployment. He reported 406 faults identified and 1,095 rotating assets modelled across 10 sites.

Full details are in the original sources.

Added 1 Nov 2026 · Updated 1 Nov 2026