RESEARCH REPORT

In brief

In brief

  • Engineering Data Digitization (EDD) aims at AI-supported digitization of very important yet complex engineering documents.
  • EDD is considered an accelerator and enabler for the implementation of Digital Twins.
  • It’s main components are a scanning / ingestion engine for engineering documents followed by advanced machine learning / AI supported Optical Character Recognition (OCR) of the engineering asset symbols.
  • We can thereby dramatically reduce the price per digitalized engineering document and speed up the digitalization of our clients engineering documents.


Today’s problem with setting up your Digital Twins is that client’s are facing serious constraints. The main factors are:

  • The documents to be entered into the engineering software solution are often legacy paper or other unreadable formats and therefore are very costly to digitize. In addition, the market is faced with very constrained digitization capacity since limited engineering capacities have to be used to scan and interpret digitized paper documents to ensure consistent quality of these vital documents.
  • As a result, the planed digitization of plants takes a long time and is costly, limiting both software vendors in usage adoption & plant operators in moving to Industry X.0.

Our answer is the EDD solution: EDD lifts the constraint on the document digitization by using scanning and Optical Character Recognition (OCR). OCR will digitize documents and our AI based engine will correctly identify the engineering symbols. It will then extract structured data from the document base and output into a universally readable data format.

Accenture Engineering Digitization

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