$15M Revenue Gain Through Yield Optimization
IoT integration, SAP S/4HANA, and advanced analytics transformed 50+ production units into a predictive operating model.
A global petrochemical manufacturer used ITChamps to connect plant data to SAP S/4HANA, deploy predictive maintenance models, and optimize yield in real time across 50+ production units.
The Challenge
Yield loss and reactive maintenance were eroding margin
The client operated 50+ production units across 12 facilities, but process data was incomplete, maintenance was reactive, and real-time visibility into yield drivers did not exist.
- Manual process data capture hid micro-inefficiencies and delayed response.
- Equipment failures were discovered during operation rather than predicted.
- Yield variability of 5-8% could not be traced to root causes.
- Legacy SCADA data was disconnected from SAP and production planning.
- No predictive capability existed for maintenance or feed-ratio optimization.
The Solution
Three-layer architecture across IoT, SAP integration, and analytics
ITChamps installed sensors on critical measurement points, streamed data into SAP via BTP, and built ML models for predictive maintenance, anomaly detection, and real-time yield optimization.
Deployed IoT sensors across pilot units and built the initial SAP integration layer.
Expanded data coverage, trained predictive models, and created dashboards for plant teams.
Moved to live optimization with operator training, alerting, and extended hypercare.
Results
Measured business impact
Cross-facility improvement after optimization was deployed in production.
Recovered value from higher yield and reduced process waste.
Equipment downtime fell from 12 hours to 2 hours per month.
Predictive maintenance reduced preventive maintenance spend.
Highlights
- Real-time visibility across all 50 production units.
- Predictive maintenance eliminated surprise failures and emergency shutdowns.
- Operators received live feed-ratio recommendations tied to yield outcomes.
- The platform created a repeatable template for future plant rollouts.
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