Process Automation

Manufacturing Automation: 40% Efficiency Increase

How we transformed a Sydney-based manufacturing company's quality control process using computer vision and automated reporting, reducing manual inspection time by 75%.

Manufacturing automation facility

The Challenge

A Sydney-based manufacturing company was struggling with manual quality control processes that were time-consuming, error-prone, and creating bottlenecks in their production line. With increasing demand and tight quality requirements, they needed a solution that could maintain high standards while scaling operations.

Our Solution

We implemented a comprehensive automation solution featuring:

  • Computer vision system for automated defect detection
  • Real-time quality control dashboard
  • Automated reporting and compliance documentation
  • Integration with existing manufacturing execution systems (MES)
  • Machine learning algorithms for continuous improvement

Implementation Process

1

Assessment & Planning (Week 1-2)

Conducted detailed analysis of existing processes and identified optimization opportunities.

2

System Development (Week 3-8)

Built and trained computer vision models using historical quality control data.

3

Integration & Testing (Week 9-10)

Integrated the system with existing infrastructure and conducted comprehensive testing.

4

Deployment & Training (Week 11-12)

Deployed the solution and trained staff on the new automated processes.

Project Results

40% efficiency increase
75% reduction in manual work
$2.1M annual savings
99.5% accuracy rate

Technologies Used

Computer VisionPythonTensorFlowAzure IoTPower BI

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