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Process Automation

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Optical Character Recognition On Engineering Drawings To Achieve Automation In Document Management

The client had over 20 years of engineering drawings that required audit, digitisation,  and consolidation into a document management system. With limited resources and a condensed time period due to the sale of assets, using human resources presented a number of issues.

Challenges

Quality

Ensuring the fidelity of the digitised drawings was critical.

Time

Condensed timeline due to an impending sale of assets.

Resources

Limited human resources and expertise in document management.

Volume

Over 20 years’ worth of engineering drawings had to be audited.

Streamlining Document Management

How an Engineering Firm Overcame Decades of Data Challenges?

As organisations grow and evolve, the need for efficiently managing a plethora of documents becomes a critical challenge.

Our client, a renowned engineering firm, was confronted with the mammoth task of auditing, digitising, and consolidating over 20 years’ worth of engineering drawings.

Further complicating the scenario was the sale of assets that demanded this effort be completed within a condensed time frame.

Traditional methods, heavily reliant on manual human resources, presented logistical and quality challenges, not to mention the extended duration required for completion.

Automation impacts

Unlocking Efficiency

96%

Accuracy on compatible drawings

70%

Reduction in human resource input

60%

Reduction in expected processing time

Our Process

A Step-by-Step Breakdown of Our Engineering Drawing Digitisation

Data Processing

Normalised and cleaned up the drawings for better OCR readability.

Custom Model Training

Trained machine learning models to recognise the unique textual and graphical elements in the engineering drawings.

OCR Integration

Implemented the trained models into an OCR system capable of scanning and digitising the drawings.

Isolation For QAQC

Identified and isolated drawings where OCR had limitations, earmarking them for further quality checks.

Our Approach

Intelligent Engineering Drawing Automation

We decided to employ Optical Character Recognition (OCR) technology to automate the extraction of details from the engineering drawings.

For the machine learning aspect, we utilised Keras and TensorFlow frameworks to train custom models tailored for the intricacies of engineering drawings.

Operational Efficiency Through Intelligent Document DigitiSation

A Case Study in OCR and Machine Learning Integration

The project demonstrates the immense value of integrating advanced technologies like OCR and machine learning in overcoming operational challenges. By utilising a smart mix of Keras and TensorFlow for OCR, we successfully automated a substantial part of the document digitisation process for our client, significantly cutting down both time and human resource requirements. By focusing on continuous improvement and adaptation, we aim to make this solution even more robust and versatile for the client’s future needs.

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