NDLI: Positional, geometrical, and thermal errors compensation by tool path modification using three methods of regression, neural networks, and fuzzy logic

Content Provider	Springer Nature Link
Author	Eskandari, Sina Arezoo, Behrooz Abdullah, Amir
Copyright Year	2012
Abstract	One of the main sources of inaccuracy in production is machine tool errors. In this study, a method is introduced to model and compensate positional, geometrical, and thermally induced errors of machine tools by an offline technique. Thermal errors are modeled by three ways of multiple linear regression, artificial neural networks, and neuro-fuzzy modeling. The required database is provided by measuring errors using a laser interferometer. Subsequently, the models are evaluated and the best one which is neuro-fuzzy with a mean square error of 0.375 μm is chosen to predict the errors using developed software. The experimental procedure is optimized by a preliminary broad assessment. Volumetric errors are calculated using rigid body kinematic and applied to modify the initial G-codes. The introduced method is validated by compensating errors on a free-form which shows significant average improvement of errors.
Starting Page	1635
Ending Page	1649
Page Count	15
File Format	PDF
ISSN	02683768
Journal	The International Journal of Advanced Manufacturing Technology
Volume Number	65
Issue Number	9-12
e-ISSN	14333015
Language	English
Publisher	Springer-Verlag
Publisher Date	2012-06-17
Publisher Place	London
Access Restriction	One Nation One Subscription (ONOS)
Subject Keyword	CNC Thermal errors Geometrical errors Positional errors Offline compensation G-code Industrial and Production Engineering Production/Logistics/Supply Chain Mechanical Engineering Computer-Aided Engineering (CAD, CAE) and Design
Content Type	Text
Resource Type	Article
Subject	Industrial and Manufacturing Engineering Control and Systems Engineering Mechanical Engineering Computer Science Applications Software

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