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contributor authorAnagnostakis, Dimitrios
contributor authorRitchie, James
contributor authorLim, Theodore
contributor authorSung, Raymond
contributor authorDewar, Richard
date accessioned2019-02-28T11:12:17Z
date available2019-02-28T11:12:17Z
date copyright6/12/2018 12:00:00 AM
date issued2018
identifier issn1530-9827
identifier otherjcise_018_03_031005.pdf
identifier urihttp://yetl.yabesh.ir/yetl1/handle/yetl/4253798
description abstractCapturing 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 nonintrusive 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.
publisherThe American Society of Mechanical Engineers (ASME)
titleAutomated Coordinate Measuring Machine Inspection Planning Knowledge Capture and Formalization
typeJournal Paper
journal volume18
journal issue3
journal titleJournal of Computing and Information Science in Engineering
identifier doi10.1115/1.4039194
journal fristpage31005
journal lastpage031005-12
treeJournal of Computing and Information Science in Engineering:;2018:;volume( 018 ):;issue: 003
contenttypeFulltext


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