Cutting dynamics identification by dynamic data system (DDS) modeling approach

T. Y. Ahn, K. F. Eman, S. M. Wu

Research output: Contribution to journalArticlepeer-review

18 Scopus citations


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.

Original languageEnglish (US)
Pages (from-to)91-94
Number of pages4
JournalJournal of Manufacturing Science and Engineering, Transactions of the ASME
Issue number2
StatePublished - May 1985

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Mechanical Engineering
  • Computer Science Applications
  • Industrial and Manufacturing Engineering

Fingerprint Dive into the research topics of 'Cutting dynamics identification by dynamic data system (DDS) modeling approach'. Together they form a unique fingerprint.

Cite this