The client is a global leader in providing digital ecosystems for industries including manufacturing and infrastructure.
To deliver a digital ecosystem, the client analyzes factory installation schematics, which are often aged and riddled with inconsistencies. Depending on the schematics’ complexity, it can take trained staff anywhere from three hours to two full days to analyze, clarify and digitalize them.
The company needs the digitalized schematics to be further used by various appliances asfully actionable data. Its database holds information about the object, its position, connections, function and detailed technical parameters. Later, the schematics are merged with 3D scans of an industrial installation to provide a real-view interactive map of the entire system, including the automated notifications about inconsistencies and potential challenges to overcome. Thus, simple scanning was not enough—manual, detailed analysis was required to extract all of the information.
deepsense.ai developed a model that recognizes and adds descriptions for all symbols used in the installation documentation. The model recognizes inconsistent symbols that differ by size, angle, and proportions.
Overcoming the numerous hurdles involved, the model delivers a fully digitalized version of the documentation.
The schematics are fully digitalized, including the technical descriptions of all components. The model reduces the work to a 30-minute review done by a specialist. It also handles the most tedious tasks, thus reducing the effort required of human specialists and the number of errors they make performing them.