Manufacturing · 2023
Predictive maintenance across a 38-plant estate
Edge data and ML models that cut unplanned downtime 18% and turned maintenance from a cost center into a strategy.
A global industrial manufacturer — Manufacturing · 38 plants
Client
A global industrial manufacturerManufacturing · 38 plants
Technology stack
ROI
214% over 18 months, payback in 11 months.
Client overview
A global manufacturer ran maintenance reactively across 38 plants, with unplanned downtime costing tens of millions annually. Asset data existed but was siloed by site and vendor.
Business challenge
Unify siloed operational data across brownfield equipment, build predictive models that maintenance teams trusted, and shift from calendar-based to condition-based maintenance without disrupting production.
Approach
We delivered an edge-to-cloud data platform, standardized asset taxonomies, and built ML models validated against historian data and technician input. A pilot at three plants proved reliability before scaling, with change management built in.
Business impact
Maintenance shifted from reactive to predictive, downtime and spare-parts cost fell, and the unified data platform became the foundation for quality and energy initiatives.