Abstract
On-machine measurement (OMM), which is used to measure the machined surfaces of a workpiece during or after the machining of the workpiece, enables direct measurement within the workspace without moving the workpiece. However, although the three-dimensional geometric shape created by computer-aided design systems include various features, because such features are converted into non-uniform rational B-spline (NURBS) surfaces during OMM, measurement deviation occurs between a feature and its corresponding NURBS surface. In this paper, we suggest a method to generate the measurement path for 5-axis OMM in a way that recognizes the features necessary for measurement from NURBS surfaces whose feature data set was removed during the conversion processes. To verify the reliability of the measurement path generation system named OMV+, which was developed using the above method, we carried out an experiment to compare the measurement path that defines the measuring point on the feature and the path that defines the measuring point on the NURBS surface with the measured result using the touch probe on the machined workpiece.
This is a preview of subscription content, log in via an institution to check access.
Similar content being viewed by others
References
P. Gu and K. Chan, Generative inspection process and probe path planning for coordinate measuring machines, Journal of Manufacturing Systems, 15 (4) (1996) 240–255.
I. Ainsworth, M. Ristic and D. Brujic, CAD-based measurement path planning for free-form shapes using contact probes, International Journal of Advanced Manufacturing Technology, 16 (1) (2000) 23–31.
M. W. Cho and T. I. Seo, Inspection planning strategy for the on-machine measurement process based on CAD/CAM/CAI integration, International Journal of Advanced Manufacturing Technology, 19 (8) (2002) 607–617.
I. Hwang, H. Lee and S. Ha, Hybrid neuro-fuzzy approach to the generation of measuring points for knowledge-based inspection planning, International Journal of Production Research, 40 (11) (2002) 2507–2520.
H. Lee, M. W. Cho, G. S. Yoon and J. H. Choi, A computeraided inspection planning system for on-machine measurement—part I: Global inspection planning, KSME International Journal, 18 (8) (2004) 1349–1357.
M. W. Cho, H. Lee, G. S. Yoon and J. H. Choi, A computeraided inspection planning system for on-machine measurement—part II: Local inspection planning, KSME International Journal, 18 (2004) 1358–1367.
D. Elkott, H. Elmaraghy and W. Elmaraghy, Automatic sampling for CMM inspection planning of free-form surfaces, International Journal of Production Research, 40 (11) (2002) 2653–2676.
V. A. Albuquerque, F. W. Liou and O. R. Mitchell, Inspection point placement and path planning algorithms for automatic CMM inspection, International Journal of Computer Integrated Manufacturing, 13 (2) (2000) 107–120.
Y. J. Lin and P. Murugappan, A new algorithm for CAD-directed CMM dimensional inspection, International Journal of Advanced Manufacturing Technology, 16 (2) (2000) 107–112.
F. Mier and B. Frumbore, Fast minimum storage ray-triangle intersection, Journal of Graphics Tools, 2 (1) (1997) 21–28.
Acknowledgments
This research was supported by Basic Science Research Program through the National Research Foundation of Korea (NRF) funded by the Ministry of Education (2018R1D1A1 B07050199).
Author information
Authors and Affiliations
Corresponding author
Additional information
Recommended by Associate Editor Wonkyun Lee
Inwoong Yeo is a Senior Engineer of GUN Solution (http://www.gunsol.com), a company for OMM & manufacturing execution system (MES) & CNC machine monitoring system. He obtained his master’s degree in industrial engineering in 2019 at Ajou University, Korea. His current research interests are geometry modeling, real-time data communication of CNC & PLC & sensor module, design for manufacturing (DFM).
Inho Song is a technical specialist in Altair Engineering (http://www.altair.com), USA. He worked at Canegie Mellon University as research faculty and Ennova Technology as Senior Engineer. He obtained his Ph.D. degree in mechanical engineering in 2007 at Hanyang University. His current research interest are sketch based CAD system, GPU accelerated calculation, AI based computer aided engineering system, and complex geometry shape morphing.
Sanguk Cheon is an Assistant Professor in the Department of Intergrative Systems Engineeering at Ajou University. He holds a Ph.D in mechanical engineering from KAIST. He has 18 years of experience in CAD system development, mainly developing shipbuilding CAD systems. His current research interests are ship/plant CAD, geometric modeling, and industrial CAD/CAM applications.
Jeongsam Yang is a Professor in the Department of Industrial Engineering and is leading the CAD laboratory (http://cadlab.ajou.ac.kr) at Ajou University, Korea. He worked at Carnegie Mellon University (USA) and Clausthal University of Technology (Germany) as a visiting researcher, and the University of Wisconsin-Madison (USA) as a postdoctoral associate. He obtained his Ph.D. in mechanical engineering in 2004 at KAIST. His current research interests are product data quality (PDQ), VR application in product design, product data management (PDM), knowledge-based design system, and geometry modeling.
Rights and permissions
About this article
Cite this article
Yeo, I., Song, I., Cheon, SU. et al. Development of a feature-recognition and measurement path generation system based on NURBS surfaces for 5-axis on-machine measurement. J Mech Sci Technol 33, 3445–3455 (2019). https://doi.org/10.1007/s12206-019-0639-9
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s12206-019-0639-9