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research-article

Automated CMM inspection planning capture and formalization

[+] Author and Article Information
Dimitrios Anagnostakis

Heriot-Watt University, Riccarton Campus, Edinburgh, UK
da178@hw.ac.uk

J.M. Ritchie

Heriot-Watt University, Riccarton Campus, Edinburgh, UK
j.m.ritchie@hw.ac.uk

T Lim

Heriot-Watt University, Riccarton Campus, Edinburgh, UK
t.lim@hw.ac.uk

Raymond Sung

Renishaw plc, Research Park North, Riccarton, Edinburgh, UK
ray.sung@renishaw.com

Richard Dewar

Renishaw plc, Research Park North, Riccarton, Edinburgh, UK
rick.dewar@renishaw.com

1Corresponding author.

ASME doi:10.1115/1.4039194 History: Received October 15, 2017; Revised January 23, 2018

Abstract

Capturing the strategy followed during a Coordinate Measuring Machine (CMM) inspection planning session has been an extremely challenging issue due to the time-consuming nature of traditional methods, such as interviewing experts and technical documents data mining. This paper presents a methodology demonstrating how a motion capture-based system can facilitate direct and non-intrusive CMM operator logging for capturing planning strategies and representing in knowledge formats. With the use of recorded motion data, embedded knowledge and expertise can be captured automatically and formalized in various formats such as motion trajectory graphs, inspection plans, Integrated DEFinition (IDEF) model diagrams and other representations. Additionally, a part program can be generated for driving a CMM to execute component measurement. The system's outputs can be used to help understand how a CMM inspection strategy is planned, as well as training aids for inexperienced operators and the rapid generation of part programs.

Copyright (c) 2018 by ASME
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