Literature DB >> 28691120

Gaps Analysis of Integrating Product Design, Manufacturing, and Quality Data in The Supply Chain Using Model-Based Definition.

Asa Trainer1, Thomas Hedberg2, Allison Barnard Feeney2, Kevin Fischer3, Phil Rosche4.   

Abstract

Advances in information technology triggered a digital revolution that holds promise of reduced costs, improved productivity, and higher quality. To ride this wave of innovation, manufacturing enterprises are changing how product definitions are communicated - from paper to models. To achieve industry's vision of the Model-Based Enterprise (MBE), the MBE strategy must include model-based data interoperability from design to manufacturing and quality in the supply chain. The Model-Based Definition (MBD) is created by the original equipment manufacturer (OEM) using Computer-Aided Design (CAD) tools. This information is then shared with the supplier so that they can manufacture and inspect the physical parts. Today, suppliers predominantly use Computer-Aided Manufacturing (CAM) and Coordinate Measuring Machine (CMM) models for these tasks. Traditionally, the OEM has provided design data to the supplier in the form of two-dimensional (2D) drawings, but may also include a three-dimensional (3D)-shape-geometry model, often in a standards-based format such as ISO 10303-203:2011 (STEP AP203). The supplier then creates the respective CAM and CMM models and machine programs to produce and inspect the parts. In the MBE vision for model-based data exchange, the CAD model must include product-and-manufacturing information (PMI) in addition to the shape geometry. Today's CAD tools can generate models with embedded PMI. And, with the emergence of STEP AP242, a standards-based model with embedded PMI can now be shared downstream. The on-going research detailed in this paper seeks to investigate three concepts. First, that the ability to utilize a STEP AP242 model with embedded PMI for CAD-to-CAM and CAD-to-CMM data exchange is possible and valuable to the overall goal of a more efficient process. Second, the research identifies gaps in tools, standards, and processes that inhibit industry's ability to cost-effectively achieve model-based-data interoperability in the pursuit of the MBE vision. Finally, it also seeks to explore the interaction between CAD and CMM processes and determine if the concept of feedback from CAM and CMM back to CAD is feasible. The main goal of our study is to test the hypothesis that model-based-data interoperability from CAD-to-CAM and CAD-to-CMM is feasible through standards-based integration. This paper presents several barriers to model-based-data interoperability. Overall, the project team demonstrated the exchange of product definition data between CAD, CAM, and CMM systems using standards-based methods. While gaps in standards coverage were identified, the gaps should not stop industry's progress toward MBE. The results of our study provide evidence in support of an open-standards method to model-based-data interoperability, which would provide maximum value and impact to industry.

Entities:  

Keywords:  Model-based definition; digital manufacturing; product data verification and validation; product lifecycle management

Year:  2016        PMID: 28691120      PMCID: PMC5497522          DOI: 10.1115/MSEC2016-8792

Source DB:  PubMed          Journal:  Proc ASME Int Conf Manuf Sci Eng


  2 in total

1.  Testing the Digital Thread in Support of Model-Based Manufacturing and Inspection.

Authors:  Thomas Hedberg; Joshua Lubell; Lyle Fischer; Larry Maggiano; Allison Barnard Feeney
Journal:  J Comput Inf Sci Eng       Date:  2016-03-08       Impact factor: 1.855

2.  Enabling Smart Manufacturing Research and Development using a Product Lifecycle Test Bed.

Authors:  Moneer Helu; Thomas Hedberg
Journal:  Procedia Manuf       Date:  2015-10-21
  2 in total
  3 in total

1.  Using graphs to link data across the product lifecycle for enabling smart manufacturing digital threads.

Authors:  Thomas D Hedberg; Bajaj Manas; Jaime A Camelio
Journal:  J Comput Inf Sci Eng       Date:  2020       Impact factor: 1.855

2.  Contextualising manufacturing data for lifecycle decision-making.

Authors:  William Z Bernstein; Thomas D Hedberg; Moneer Helu; Allison Barnard Feeney
Journal:  Int J Prod Lifecycle Manag       Date:  2018

3.  Method for enabling a root of trust in support of product-data certification and traceability.

Authors:  Thomas D Hedberg; Sylvere Krima; Jaime A Camelio
Journal:  J Comput Inf Sci Eng       Date:  2019       Impact factor: 1.855

  3 in total

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