Development of a Pilot Manufacturing Cyberinfrastructure With an Information Rich Mechanical CAD 3D Model Repository

Abstract

Data driven advanced manufacturing research is dependent on access to large datasets made available from across the product lifecycle — from the concept design phase all the way down to end use and disposal. Despite such data being generated at a rapid pace, most product design data is archived in inaccessible silos. This is particularly acute in academic research laboratories and with data generated during product design and manufacturing courses. This project seeks to create an infrastructure that allow users (academia and the general public) to easily upload project data and related meta-data. Current manufacturing research must shift from siloed repositories of product manufacturing data to a federated, decentralized, open and inter-operable approach. In this regard, we build ‘FabWave’ a cyber-infrastructure tool designed to capture manufacturing data. In its first pilot implementation, we focused our attention to gathering information rich 3D Mechanical CAD data and related meta-data associated with them, with the intent to make it easier for users to upload and access product design data. We describe workflows that we have initially tested out within the two academic universities and under two different course structures. We have also developed automated workflows to gather license appropriate CAD assemblies from commercial repositories. Our intent is to create the only known largest available CAD model set within academia for enabling research in data-driven computational research in digital design, fabrication and quality control.

A Literature Review of the Digital Thread: Definition, Key Technologies, and Applications

“…They established a digital thread-driven information interaction architecture, designed PRSC processes, and constituted the digital thread to achieve near-real-time information interaction between enterprises across regions and dynamic changes. Bharadwaj et al [112] developed a large and continually evolving CAD model repository named "FabWave". Recognizing the significance of capturing and accessing various forms of data generated throughout the product lifecycle, including failed designs, unstructured data, and data from product and prototype design, as well as the manufacturing process, FabWave advances data-driven approaches to product design and manufacturing.…”

B-rep Matching for Collaborating Across CAD Systems

“…Other data-driven CAD applications include segmentation [Cao et al 2020], classification [Bharadwaj et al 2019], and reverse engineering of editable models Uy et al 2022;Xu et al 2021]. Recent work looks at reducing the size of the dataset necessary to train these models using self-supervision [Jones et al 2022].…”

Classifying Component Function in Product Assemblies with Graph Neural Networks

“…Adoption of design repositories in research and industry has been slow due to resource commitment, human curation, intuition-based knowledge extraction, and lack of well-structured product data. Efforts have been made to improve design repository generation by limiting subjectivity through taxonomy standardization [41,42,43,6,44]. Furthermore, recent approaches have been introduced to streamline data addition to design repositories [45].…”