Arunmozhiselvan C

Digital Predictive Maintenance (PdM) and Asset Reliability professional with 19+ years of global experience across India and Canada. Specialized in ultrasound, Vibration-based PdM for industrial gearboxes, manufacturing, oil & gas, wind, and port industries, driving asset reliability and proactive failure prevention. Successfully transitioned from traditional predictive maintenance into Digital PdM and Industrial AI, with hands-on experience in IIoT-enabled monitoring systems, remote diagnostics platforms, sensor data analytics (ultrasound, temperature, vibration), and AI-driven fault detection initiatives.

Proven expertise in deploying scalable asset monitoring solutions, enabling predictive maintenance strategies, improving reliability, and reducing unplanned downtime across industrial sectors. Currently driving innovation in AI/ML-enabled ultrasound analytics, wireless sensor technologies, and digital asset intelligence solutions to accelerate Industry 4.0 transformation and reliability excellence.

Senior Manager, South India - UE Systems IMENA Pvt Ltd. - South India

(2025-02)

• Leading Digital PdM transformation initiatives across industrial assets including wind turbines, gearboxes, and electrical systems.
• Enabled early identification of critical asset failures, improving reliability and reducing unplanned downtime across multiple industrial deployments.
• Supporting AI/ML-enabled ultrasound diagnostics, including anomaly detection and predictive fault classification models.
• Managing Ultrasound AMC project implementation and Reliability frameworks for Equipment Audits, Failure Modes, Effects, Criticality Analysis (FMECA) for HT/LT Motor bearings, Industrial Gearboxes, and wind turbine drive-train assets.
• Sound wave Timeseries pattern anomaly diagnosis and prediction, Implementation of best practices of condition-based Lubrications, General Bearing applications, Slow speed bearings, Electrical assets, Wind Turbine Drive Train bearings.
• Executing ISO Level I and Level II certified Training program across India.
• Enabled successful deployment of Ultrasound-based PdM solutions across IMENA by delivering application-specific training, software enablement, and technical consulting to 150+ users.
• Implemented reliability best practices and FMECA through equipment audits, and deployed condition monitoring technologies to enhance asset performance.
• Designed end to end solution architectures, technical proposals for Online wireless/wired ultrasound monitoring systems for critical assets including led deployment and support to ensure reliable PdM solution adoption (WTG, GB).
• Conducted technical audits for wind Turbine drive train bearings, Pulp mill and implemented of IIoT-smart lubrication ultrasound monitoring solutions (OnTrak, 4cast).
• Led pre-deployment feasibility assessments, including network design, cable routing, and systems integration for remote monitoring platforms.
• Integrated UltraTrak Smar 850S sensors with OnTrak platforms, and DCS, enabling real-time monitoring, data acquisition and predictive maintenance insights.
• Designed and optimized large-scale ultrasound, Vibration asset databases (3000+ assets), improving data quality, monitoring efficiency, and decision-making.
• Eliminated potential catastrophic operational failure at DP World by engineering an early ultrasound defect diagnostic framework, saving an estimated thousands in unplanned terminal downtime.
• Post Level I training course customers successfully identified steam trap failures and shared positive feedback from Cargill.
• Predicted high-critical slow-speed bearing failures and supported timely maintenance actions (MCPI).
• Identified and trended WTG main bearing faults using 4cast systems, supporting failure analysis (ITC).
• Received customer appreciation for effective Level I technical training delivery (Cargill, DP World, Tata Steel, JSW, Deepak Fertilizer).
• Successfully predicted faults in 33 kV feeder VCBs using ultrasound diagnostics, with findings validated during OEM maintenance activities.
• Delivered Ultrasound-based electrical condition monitoring projects for key clients including SAIL, CPCL, Powerica, and JLL, covering 66/33 kV substations, 230 kV yards, and HT/LT Motor Bearings.
• Implemented condition monitoring solutions for wind turbine CRB and main bearing applications.
• Performed data-driven diagnosis and asset health assessments using continuous monitoring data.
• Enabled customer adoption of remote monitoring technologies for slow-speed bearing applications.

OnTrack Technical Specialist - UE Systems Canada - Canada

(2023-08 - 2024-11)

• Implemented IIoT-based online PdM systems, including commissioning, integration, and analytics platform deployment.
• Delivered multi-sensor PdM analytics (ultrasound, vibration, temperature), generating customer-facing reports and actionable asset health insights.
• Developed customer dashboards and asset health reports, translating condition data into actionable insights.
• Supported industrial cybersecurity compliance and system validation.
• Delivered customer enablement and technical support, including training, data review sessions, and solution adoption guidance.
• Collaborated across product, engineering, and service teams to ensure effective deployment and continuous improvement of digital PdM solutions.
• Enabled transition from reactive to predictive maintenance strategies, improving asset monitoring effectiveness and maintenance decision-making.
• Supported deployment of wireless bearing health monitoring systems integrated with smart precision lubrication.
• Enabled proactive maintenance through remote condition monitoring and asset health insights.

BE - Mechanical Engineer - Annamalai University (2004)