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DNV GL – Digitisation of P&ID drawings

Case Studies 19/07/2019

The Oil & Gas industry has a vast amount of data that isn’t being used to its full potential. DNV GL wanted to advance their techniques to process and analyse large volumes of scanned engineering drawings in a quicker time frame and come up with a more efficient commercial solution for their clients in the oil and gas industry.

DNV GL collaborated with The Data Lab and Robert Gordon University to apply machine learning to their data to increase efficiency.

The project aimed to develop a fully automated solution to analyse and process complex engineering drawings. The industry deals with a lot of documents and drawings coming in a paper format that are very time consuming to extract information from. They were looking for a more efficient way of getting from paper copies into an electronic format. They have managed to reduce the time taken from 3 hours to 5 minutes, which is an incredible saving. An additional benefit is that it provides an enriched data set for further analysis in the future.

Find out more about this collaboration:

 

TDL were instrumental in getting the project up and running. We’re now looking at how to expand the project into other areas and to take this type of technology and develop it for a much wider range of applications.

Brian Bain PhD, Senior Principal Specialist, Safety Risk Excellence

 

The Data Lab is certainly helping in putting Scotland at the forefront when it comes to data science and innovation.

Dr Eyad Elyan, Reader in Machine Learning, School of Computing/Robert Gordon University

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