Abstract
In spite of the success of the stream of variation (SoV) approach to modeling variation propagation in multistation machining processes (MMPs), the absence of machining-induced variations could be an important factor that limits its application in accurate variation prediction. Such machining-induced variations are caused by geometric-thermal effects, cutting-tool wear, etc. In this paper, a generic framework for machining-induced variation representation based on differential motion vectors is presented. Based on this representation framework, machining-induced variations can be explicitly incorporated in the SoV model. An experimentation is designed and implemented to estimate the model coefficients related to spindle thermal-induced variations and cutting-tool wear-induced variations. The proposed model is compared with the conventional SoV model resulting in an average improvement on quality prediction of 67%. This result verifies the advantage of the proposed extended SoV model. The application of the new model can significantly extend the capability of SoV-model-based methodologies in solving more complex quality improvement problems for MMPs, such as process diagnosis and process tolerance allocation, etc.
Original language | English (US) |
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Article number | 021002 |
Journal | Journal of Manufacturing Science and Engineering |
Volume | 134 |
Issue number | 2 |
DOIs | |
State | Published - 2012 |
Keywords
- cutting force-induced variations
- cutting-tool wear-induced variations
- differential motion vector
- geometric-thermal variations
- quality improvement
- variation propagation modeling
ASJC Scopus subject areas
- Control and Systems Engineering
- Mechanical Engineering
- Computer Science Applications
- Industrial and Manufacturing Engineering