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Forced or self-excited vibrations during machining are major causes affecting surface finish and dimensional precision of machined parts, as well as tool wear and component breakdowns. One critical scientific approach to achieve major reduction or elimination of machining vibration is to fully understand the structure dynamics, in particular the modal parameters of the machining system, so that optimal machining conditions can be selected or controlled to eliminate the adverse effects of vibration. However, during machining, these modal parameters could change substantially due to the geometry, force, and temperature conditions. In this project, we propose to investigate a new in-process structural identification technology, instead of standard off-line use of impact hammers or shakers, so that ever-changing structural modal parameters can be identified in real time. The proposed technology utilizes commonly available sensors combined with analytic models based on an innovative structural identification paradigm, denoted as Iterative Output-Only Identification (IOOI). The IOOI method is based on the analytical models of machining that have established the sensitivity of the vibration parameters to the cutting parameters such as spindle speed, width and depth of cut and modal parameters such as damping ratio and the natural frequency of the critical vibration modes of the structure. This creates a system of equations where unknown parameter such as vibration frequencies and damping ratios could be found considering the laws that govern their relationship to the known parameters, mainly spindle speed and depth and width of cut and measured parameters, in particular vibration frequencies. Since the precision of the identified parameters such as natural frequencies are extremely important for finding of robust conditions for machining, an iterative approach would be used to improve the precision of calculation of unknown parameters in each iteration step. This IOOI method will first be applied to machining setups with a single dominant mode of vibration in full engagement milling where the relationship between the vibration frequencies and the natural frequencies are well studied. The study will in addition establish the relationship between vibration frequencies in more challenging setups of low immersion milling (milling with small width of cut to tool diameter ratio) and setups with multiple modes of vibration affecting the dynamics of machining in different cutting conditions; particularly when the modes have close natural frequencies. The project's final steps are case studies for implementation of IOOI. Two specific applications are planned: Milling of super alloys with ceramic tools and high speed machining of aluminum. The vibration problem is most detrimental to both applications. The scientific team consists of experienced researchers at University West collaborating with a steering group of senior researchers

Participating researchers:
Mahdi Eynian

Collaboartion partners:
GKN Aerospace
Sandvik Coromant

External funding from: