Bridging Manual & Automated Workflows: CAD Drawing Data Extraction in I5.0

In the realm of manufacturing, Efficient cost estimation from customer data, like CAD drawings, is essential for optimizing resource allocation and maintaining a competitive advantage. These efforts align with I5.0 principles to enable a hybrid-intelligence-based approach for extracting the data. This selective interaction enhances human-machine collaboration and enables operators of various skill levels to participate in the process. The solution aims to streamline data extraction, minimize errors, and improve operator efficiency while maintaining operator control. In the use case of a Small-to-Medium Equipment Manufacturer specializing in the production of machine and plant parts, significant challenges arose from their manual, time-intensive process. For example, extracting dimensions from Computer-Aided Design (CAD) drawings involved manually entering data into spreadsheets for material cost estimation. This process required substantial cognitive effort and was prone to human error. To address this, this paper proposes a user-centric software design leveraging Optical Character Recognition (OCR) to detect and display dimensions from CAD drawings.