Optimising Image Processing for Precision Manufacturing

How we helped BMW Group Hams Hall speed up QA and cut storage by 90%.

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Project Overview

Ghyston developed a sophisticated image management solution for BMW Group Hams Hall, a premium automotive manufacturing facility that specializes in precision engine production. The solution was designed to transform how quality assurance teams access and utilize critical inspection data captured during the manufacturing process.

Technical Challenge

The project required creating a system that could efficiently process high-resolution TIFF images from multiple production lines. These images are essential for quality verification, but their uncompressed format created significant storage demands and accessibility challenges within the manufacturing environment.\r Our technical team needed to design a solution that would: * Process and compress images without losing quality-critical details

  • Handle varying metadata formats from different inspection systems
  • Operate reliably in a high-volume production setting
  • Provide an intuitive interface for non-technical users

Engineering Solution

Leveraging our expertise in industrial software development, we created a standalone application built on modern .NET architecture. The solution incorporated: * Multi-threaded processing to handle hundreds of images per hour

  • Advanced compression techniques that maintained critical image quality while reducing file sizes by 90%
  • A configurable metadata parser that standardized information across different imaging systems
  • Background processes with intelligent error recovery to ensure continuous operation
  • A web-based dashboard for system monitoring and configuration

The application was packaged as a self-contained executable that could be deployed across multiple workstations without complex installation requirements.

Outcome

The implemented solution transformed the facility's quality assurance capabilities: * Processing capacity of 800 images per hour per production station

  • Storage efficiency improved, reducing annual storage requirements from 16.8TB to 1.6TB per station
  • Image retrieval time reduced from 30 minutes to seconds
  • Engineers can now focus on analysis rather than searching for data

The system now handles approximately 7 million images annually per station with exceptional reliability. Beyond these immediate benefits, the solution has established a foundation for potential future advanced analytics capabilities, supporting the manufacturer's long-term quality assurance strategy.

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