Journal article
Modelling the effect of flank wear on machining thrust stability
International journal of advanced manufacturing technology, v 23(11-12), pp 857-864
01 Jun 2004
Featured in Collection : UN Sustainable Development Goals @ Drexel
Abstract
This paper discusses an analytical assessment of the effect of cutting tool flank wear on machining stability along the thrust direction in a turning operation based on an analysis of frequency band root-mean-square (RMS) level of the accelerometer signals. The energy content of machining at the tool-tip/workpiece interface along the flank is represented by the RMS signal level, in comparison to the random vibration of the cantilever portion of the tool holder. The RMS signals measured from a tool-post accelerometer in stable machining with tool wear effect are calculated using the frequency band RMS method at the first natural frequency of the cantilever portion of the tool holder. Increasing flank wear results in increasing stability and decreasing RMS in the thrust direction in machining. For model validation, a series of machining experiments were performed under the condition of various flank wear/land widths, while the RMS signals from a tool-post accelerometer were collected and studied. It was found that theoretical predictions were shown to be in agreement with experimental results.
Metrics
Details
- Title
- Modelling the effect of flank wear on machining thrust stability
- Creators
- S Liang - Georgia Institute of TechnologyY Kwon - Department of Mechanical Engineering, Jeonju Technical College, Jeonju, KoreaR Chiou - Goodwin College
- Publication Details
- International journal of advanced manufacturing technology, v 23(11-12), pp 857-864
- Publisher
- Springer Nature B.V
- Resource Type
- Journal article
- Language
- English
- Academic Unit
- Engineering Technology
- Web of Science ID
- WOS:000222025700010
- Scopus ID
- 2-s2.0-3142526755
- Other Identifier
- 991019167790904721
UN Sustainable Development Goals (SDGs)
This publication has contributed to the advancement of the following goals:
InCites Highlights
Data related to this publication, from InCites Benchmarking & Analytics tool:
- Collaboration types
- Domestic collaboration
- International collaboration
- Web of Science research areas
- Automation & Control Systems
- Engineering, Manufacturing