Rework reduction
Systematically minimise rework.
Rework reduction identifies the most frequent root causes and their links to machines, tools and shifts, prioritising countermeasures based on data.
- Higher quality
- Cost reduction
- Higher efficiency
rework
costs
payback
first-pass yield
Calculated from saved rework costs and higher throughput.
- 01
Data integration
Consolidate data from ERP, MES and further sources for Rework reduction.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the Rework reduction model on historical data.
- 04
Pilot
Pilot Rework reduction in one area and collect feedback.
- 05
Rollout
Scale the solution and integrate it into operational processes.
Steps
Data sources
Stakeholders
From first data access to production – every step delivers a tangible interim result.
MES data
Production orders, feedback and machine data.
Quality data
Inspection results, lab values and complaints.
Machine data
Condition, parameters and production counters.
HR data
Shift plans, qualifications and absences.
Product data
Bills of materials, variants and life cycles.
ERP data
Master and transaction data from ERP.
Quality management
Secures compliance with standards and regulations.
Production manager
Uses insights directly in daily operations.
Controlling
Quantifies effects and supports budgeting.
IT
Builds on a scalable and secure data infrastructure.
Higher quality
Cost reduction
Higher efficiency
Faster processes
Higher margins
With a solid data foundation this use case gets faster, cheaper and far more stable.
Central data platform
Real-time data integration
Scalable analytics pipelines
Reusable data products
Predictive quality
Same data reveals quality deviations.
OEE monitoring
Availability data complements process metrics.
Predictive maintenance
Sensor data provides wear indicators.