Downtime & reactive maintenance cycles
Failures repeat because event history, work orders, and utilization signals aren’t analyzed together.
Key problems
Forecast volatility & planning gaps
Planning relies on inconsistent inputs; forecast error isn’t tracked by the right hierarchies.
Fragmented asset & production reporting
Multiple systems and spreadsheets create conflicting KPIs and slow decisions.
Slow root-cause analysis & exception handling
Teams spend time explaining problems instead of getting an actionable risk queue.
What we deliver
Predictive maintenance analytics
Failure patterns, MTBF, MTTR drivers, and early warning signals tied to work-order actions.
Planning systems across demand, inventory & capacity
Forecast baselines, error metrics, bias tracking, and conversion into buffers and service-level targets
Plant performance dashboards
OEE-style views, throughput, downtime reasons, and constraint visibility for weekly cadence.
Governance: KPI layer, monitoring & adoption
Semantic model, definitions, freshness checks, and adoption playbook for operators and leaders.
Deliverables
Architecture, roadmap & MVP plan
Curated models across assets, maintenance events, production & planning hierarchies
Dashboards for plant & leadership cadence
Model evaluation & monitoring approach for accuracy, drift & overrides
Frequently Asked Questions
What data is needed for predictive maintenance?
Real-Time IoT sensor data, historical maintenance logs, asset information (make, model and specifications) and environmental or operational conditions.
What is a “digital twin readiness” approach?
Establishing the asset hierarchy, event model, and KPIs so telemetry and maintenance data becomes actionable.
How long for a Pilot/MVP?
Typically 4–12 weeks for a scoped asset class or single plant.
How do you ensure adoption?
Exception-first dashboards, named KPI owners, and embedding reviews into weekly operating cadence.
How do you measure success?
Improved OEE , faster interventions, increased forecast accuracy and reduced manual reporting effort.