Case Study - Manufacturing | Automated Inspection
Automating assembly-line quality inspection using vision-driven workflows and intelligent automation.
- Client
- Confidential Manufacturing Partner
- Year
- Service
- Robotic Vision, Automation, Systems Integration
Overview
A global manufacturing partner asked us to solve chronic quality issues on an assembly line where small, intermittent defects were escaping visual checks. The existing process relied on manual inspection and ad-hoc measurements that slowed throughput and increased rework.
We proposed a camera-based inspection system combined with a lightweight ML perception pipeline and deterministic automation to triage, log and route suspected defects for automated rework or human review.
What we did
- Vision system design (camera calibration & placement)
- ML-based defect detection & multimodal validation
- Edge processing + structured JSON output
- Automation integration (rework routing, MES & PLC events)
- Operator HMI & QA dashboard
The solution removed a long-standing bottleneck on our line. Faults that previously needed manual review are now flagged precisely, and throughput has noticeably improved.
Operations Lead
- Fully autonomous Online Inspection of engine manufacturing processes for assemblies & sub-assemblies.
- Zero Manual Supervison
Technical summary
- Perception: On-line camera feeds processed by a compact vision model producing structured JSON events for each part.
- Validation: Multi-stage checks (appearance + measurement heuristics) to reduce false positives.
- Automation: Event → workflow translator that raises MES/PLC events and triggers rework conveyors or holds.
- UX: Operator HMI with contextual evidence (thumbnail, measurement overlays, timestamps) for quick decisions and audit trails.
Outcome
The pilot delivered a 45% reduction in inspection errors, 30% throughput improvement, and near 100% uptime on measurement & calibration systems. The solution moved the plant from reactive inspection to proactive quality assurance.
