Smart Condition Monitoring & Predictive Maintenance
Transforming a research-phase sensor trial into a full-scale predictive maintenance platform — reducing maintenance costs by 61% for industrial operators across 5 continents.
Reduced maintenance costs
Machine defects addressed through better monitoring
Improved oil management, reduced unplanned downtime
Situation
Sensor data trapped in a lab prototype
A global industrial company had developed IoT sensor technology that could monitor lubricant oil condition in real-time across heavy machinery — engines, generators, haul trucks, marine vessels. The sensor hardware worked. The research data was promising. But the technology was trapped in a lab-phase prototype with a handful of pilot customers and no scalable digital experience around it.
The existing solution was a bare-bones MVP driven entirely by the R&D team's assumptions about what users needed. No user research. No consideration for different roles. No path to becoming a commercial product.
They needed to turn a sensor trial into a service that industrial companies would actually pay for and use daily.
Challenge
Three problems, one platform
Multiple user types, conflicting needs
Four distinct roles — maintenance engineers, technical advisors, engineering managers, and operations managers — each with fundamentally different priorities, workflows, and information density requirements.
Industry-agnostic, context-specific
The platform needed to work across Power, Mining, Marine, and more — each with different equipment, sensors, and norms. A single configurable architecture that adapts without custom development per industry.
From data display to decision support
Translating raw sensor readings into actionable decisions: "change this oil now," "schedule maintenance next week," "this equipment is fine." A fundamental reframe from technology push to customer pull.
Our Approach
Applying the Itero Loop
We applied our four-phase iterative methodology to evolve the service from sensor trial to scaled product.
Understand
We interviewed maintenance engineers, technical advisors, engineering managers, and operations managers across multiple sites and industries. The goal wasn't to validate the existing MVP — it was to understand how each role actually made decisions about equipment maintenance.
Key insight: operators were using time-based maintenance schedules (change oil every X hours regardless of condition). The platform's real value was enabling the shift from time-based to health-based maintenance.
Shape
We designed four distinct user experiences tailored to how each role thinks and works:
- Maintenance Engineers — Glanceable equipment health with clear action recommendations.
- Technical Advisors — Deep trend analysis with oil property graphs and data export.
- Engineering Managers — Site-level cost tracking and productivity dashboards.
- Operations Managers — Multi-site bird's-eye view across 20+ locations.
For the industry-agnostic challenge, we designed a smart backend mapping layer — assets, equipment types, sensors, and configurations abstracted so the same UI adapts across verticals without custom development.
Build
We integrated usability testing into every agile sprint. Key deliverables included a live monitoring system translating sensor data into four clear states with actionable recommendations, a remaining oil life prediction engine with supporting trend visualizations, a real-time equipment health dashboard with filter, group, sort, and pin functionality, a self-service asset onboarding system reducing vendor dependency, and customizable reporting across live snapshots, historical analysis, and raw data exports.
Refine
We embedded analytics from the start — tracking which pages each user type visited, which features drove engagement, and how behavior differed by role, organization, and industry. This created a data-driven decision culture where every design choice was backed by evidence. Continuous remote usability testing across sprints generated a structured findings log that shaped every iteration.
Results
From pilot to global product
The platform transformed from a research-phase sensor trial into a fully commercialized, multi-industry digital product deployed across 5 continents.
Customers reporting reduced maintenance costs
Machine defects addressed through condition monitoring
Better oil management, reduced unplanned downtime
Industrial verticals served from a single platform
Distinct role-based user experiences
Shifted entire customer base to health-based maintenance