The dynamics of the cutting process have been conventionally characterized in terms of the Dynamic Cutting Force Coefficients (DCFC) which represent its transfer characteristics at discrete frequencies. However, this approach fails to obtain the transfer function of the process in closed analytical form. Anticipating the stochastic nature of the cutting process and the double modulation principle, a two-input one-output multivariate system was postulated for the dynamic cutting process identification model. The Dynamic Data System (DDS) methodology was used to formulate and characterize the dynamic cutting process using Modified Autoregressive Moving Average Vector (MARMAV) models. Subsequently, transfer functions of the inner and outer modulation dynamics of the cutting processes were obtained from the identified models.
Skip Nav Destination
Article navigation
May 1985
This article was originally published in
Journal of Engineering for Industry
Research Papers
Cutting Dynamics Identification by Dynamic Data System (DDS) Modeling Approach
T. Y. Ahn,
T. Y. Ahn
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
Search for other works by this author on:
K. F. Eman,
K. F. Eman
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
Search for other works by this author on:
S. M. Wu
S. M. Wu
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
Search for other works by this author on:
T. Y. Ahn
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
K. F. Eman
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
S. M. Wu
Mechanical Engineering Department, University of Wisconsin, Madison, WI 53706
J. Eng. Ind. May 1985, 107(2): 91-94
Published Online: May 1, 1985
Article history
Received:
July 10, 1984
Online:
July 30, 2009
Citation
Ahn, T. Y., Eman, K. F., and Wu, S. M. (May 1, 1985). "Cutting Dynamics Identification by Dynamic Data System (DDS) Modeling Approach." ASME. J. Eng. Ind. May 1985; 107(2): 91–94. https://doi.org/10.1115/1.3185988
Download citation file:
Get Email Alerts
Cited By
Multi-pass laser polishing of as-built DED surfaces
J. Manuf. Sci. Eng
Classification of Chip-Level Defect Types in Wafer Bin Maps Using Only Wafer-Level Labels
J. Manuf. Sci. Eng (July 2024)
Few-Shot Classification of Wafer Bin Maps Using Transfer Learning and Ensemble Learning
J. Manuf. Sci. Eng (July 2024)
Effects of Antifoaming Agents on Manufacturing Silver Dendrites Through Fluoride-Assisted Galvanic Replacement Reaction
J. Manuf. Sci. Eng (June 2024)
Related Articles
Multi Frequency Solution of Chatter Stability for Low Immersion Milling
J. Manuf. Sci. Eng (August,2004)
Identification of Spindle Integrated Force Sensor’s Transfer Function for Modular End Mills
J. Manuf. Sci. Eng (February,2006)
Minimizing the Effect of Out of Bandwidth Modes in Truncated Structure Models
J. Dyn. Sys., Meas., Control (March,2000)
Determination of Inner and Outer Modulation Dynamics in Orthogonal Cutting
J. Eng. Ind (November,1987)
Related Proceedings Papers
Related Chapters
QRAS Approach to Phased Mission Analysis (PSAM-0444)
Proceedings of the Eighth International Conference on Probabilistic Safety Assessment & Management (PSAM)
Modeling and Simulation of Cutting Temperature Field with Serrated Chip
International Conference on Mechanical and Electrical Technology, 3rd, (ICMET-China 2011), Volumes 1–3
Modeling of Cutting Force in Vibration-Assisted Machining
Vibration Assisted Machining: Theory, Modelling and Applications