Global Manufacturing Group · Manufacturing
Predictive Maintenance for Industrial IoT
Connected time-series sensor data from 800+ machines to a predictive failure model, enabling proactive maintenance scheduling and eliminating costly unplanned shutdowns.
Primary Impact
41% reduction in unplanned downtime
Industry
Manufacturing
Engagement
End-to-End Delivery
The Challenge
The Problem We Were Brought In To Solve
Unplanned equipment failures were costing the client an average of £2.4M per incident in lost production. We built an IoT data ingestion platform processing 15GB of sensor telemetry per day.
Our Approach
How We Engineered the Solution
Our team conducted a rigorous discovery process to understand the client's existing data landscape, systems architecture, and team capabilities. We designed a bespoke solution architecture tailored to the client's constraints — balancing performance requirements against infrastructure cost, regulatory compliance, and maintainability. Every design decision was validated against the primary success metric before a single line of production code was written.
IoT
Time-Series
Anomaly Detection
The Outcome
Measurable Results Delivered
Primary Metric Achieved
41% reduction in unplanned downtime
The solution was deployed to production within the agreed timeline, with full handover documentation, operational runbooks, and a 90-day monitoring period to ensure stability. The client's team was trained on the new platform and the system has continued to perform within SLA parameters since launch.
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