Welding quality control
Automatically inspect welds.
Welding quality control uses computer vision and process data to detect pores, cracks and shape defects, flagging faulty welds immediately.
- Higher quality
- Cost reduction
- Faster processes
rework
scrap
payback
detection accuracy
Calculated from reduced rework, less scrap and fewer complaints.
- 01
Data integration
Consolidate data from ERP, MES and further sources for Welding quality control.
- 02
Data quality
Clean, harmonise and validate data for plausibility.
- 03
Model development
Train and validate the Welding quality control model on historical data.
- 04
Pilot
Pilot Welding quality control 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.
Camera images
Images from inspection cameras on lines.
Machine data
Condition, parameters and production counters.
MES data
Production orders, feedback and machine data.
Quality data
Inspection results, lab values and complaints.
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.
IT
Builds on a scalable and secure data infrastructure.
Controlling
Quantifies effects and supports budgeting.
Higher quality
Cost reduction
Faster processes
More safety
Higher efficiency
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.
Digital twin
Models can be reused in simulations.