Smart Condition Monitoring & Predictive Maintenance - IoT Unchanged 2
Transforming a research-phase sensor trial into a full-scale predictive maintenance platform — reducing maintenance costs by 61% for industrial operators across 5 continents.
The Situation
A global industrial company had developed IoT sensor technology that could monitor lubricant oil condition in real-time across heavy machinery. The sensor hardware worked. The research data was promising. But the technology was trapped in a lab-phase prototype.
The Challenge
Multiple user types, conflicting needs
Four distinct roles with fundamentally different priorities and workflows.
Industry-agnostic, context-specific
Single configurable architecture across Power, Mining, Marine, and more.
From data display to decision support
Translating raw sensor readings into actionable maintenance decisions.
Our Approach
User Research
Research with maintenance engineers, technical advisors, engineering managers, operations managers.
Multi-role UX
Four distinct user experiences with abstracted backend mapping.
Platform Development
Live monitoring, prediction engine, health dashboard, self-service onboarding.
Continuous Improvement
Embedded analytics, remote usability testing, structured findings log.