Client Case Study: Heritage Foods Ltd
Quality Control Automation for Food Manufacturer: Ensuring Consistency at Scale
90%
Defect Detection Rate
55%
Reduction in Quality Checks Time
100%
Batch Traceability
The Challenge: Manual Quality Control Creating Inconsistency Risks
As production increased to meet retail demand, the company’s reliance on visual inspection by quality control staff became a bottleneck. Different inspectors applied varying standards, and fatigue led to missed defects, risking customer complaints and potential product recalls.
The core operational issues were:
- Subjective Inspection Standards: Different quality control staff interpreted standards differently, creating product inconsistency.
- Inspection Fatigue: Staff inspecting thousands of items daily missed defects due to visual fatigue, particularly in final hour shifts.
- Manual Record-Keeping: Quality control data was recorded on paper then manually entered into spreadsheets, creating delays in identifying trends.
The Solution: Automated Quality Control System
Edderton Scott implemented an automated quality control system using computer vision technology to inspect products at production line speed while maintaining consistent standards and generating digital records.
Automated Quality Control Process
Production Line
→
Automated Inspection
→
Digital Quality Records
Computer vision system inspects every product at production speed with consistent standards and immediate defect detection.
Phase 1: Quality Standard Definition & System Calibration
We worked with quality managers to define precise, measurable quality standards for each product line, then calibrated the computer vision system against these standards using thousands of sample images.
Phase 2: System Implementation & Staff Training
We installed cameras and processing units along production lines, integrating with existing machinery control systems and training staff to interpret automated reports rather than conduct manual inspections.
- High-resolution cameras inspecting products from multiple angles at production line speed
- Machine learning algorithms detecting colour variations, size inconsistencies, and packaging defects
- Real-time alerting system flagging defects immediately for removal from production line
“The automated system has transformed our quality control. We now have consistent standards 24/7, and the data insights have helped us identify production issues we didn’t even know existed. Customer complaints have dropped by 80%.”
— Sarah Jenkins, Quality Director at Heritage Foods Ltd
The Outcome
The automated quality control system achieved a 90% defect detection rate compared to 65% with manual inspection. Quality check time reduced by 55% as staff shifted from inspection to monitoring and analysis roles. Complete batch traceability enabled rapid response to any quality issues, reducing potential recall scope by 95%. The system paid for itself within 14 months through reduced waste and improved customer satisfaction.