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WILL MODEL-BASED DEFINITION ACCELERATE THE INSPECTION PHASE IN THE MANUFACTURING PROCESS?

Published online by Cambridge University Press:  19 June 2023

Pekka Uski ,
Joni Nieminen  and
Asko Ellman
Pekka Uski*
Affiliation:
Etteplan
Joni Nieminen
Affiliation:
Tampere University of Applied Sciences
Asko Ellman
Affiliation:
Tampere University
*
Uski, Pekka, Etteplan, Finland, [email protected]

Abstract

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Model-Based Definition provides several benefits for communicating between engineering and other downstream stakeholders. Particularly, semantic PMI information included in 3D models benefits both CAM programming and inspection phases. However, the efficiency of generating CAM- and CAI codes automatically according to the semantic PMI information varies due to the compatibility of different systems. This paper focuses on the experiment that we made on inspecting three different parts with the Coordinate Measuring Machine (CMM). We compared four different programming methods and found that the efficiency of inspecting depends on the serial size of the parts. The completely automatic CAI-programming method does not necessarily produce the most effective CAI code compared to the competent human programmer. This is notable, especially in large series due to achieved cumulative time savings in the inspection of each part. With small series, fully automatic PMI method and human-assisted automatic PMIfp method provide significant benefits in the inspection process due to time savings in CAI-programming work.

Keywords

Computer Aided Design (CAD)Product Lifecycle Management (PLM)Tolerance representation and management
Type
Article
Information
Proceedings of the Design Society , Volume 3: ICED23 , July 2023 , pp. 3899 - 3908
Creative Commons
Creative Common License - CCCreative Common License - BYCreative Common License - NCCreative Common License - ND
This is an Open Access article, distributed under the terms of the Creative Commons Attribution-NonCommercial-NoDerivatives licence (http://creativecommons.org/licenses/by-nc-nd/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is unaltered and is properly cited. The written permission of Cambridge University Press must be obtained for commercial re-use or in order to create a derivative work.
Copyright
The Author(s), 2023. Published by Cambridge University Press

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