Time Domain Simulation with Applications in Compliant Workpiece Milling

1 online resource (158 pages) : PDF

2016

University of North Carolina at Charlotte

High performance application fields, such as the defense, power, and aerospace industries, benefit from the enhanced product quality and reduced cost associated with machining thin-walled, metallic structures over traditional fabrication and assembly methods (e.g., sheet metal buildups). The mechanical properties of difficult-to-machine materials, such as titanium and nickel alloys, make them ideal candidates for compliant, thin-walled structures. Near net shape techniques have been used to manufacture compliant structures composed of hard-to-machine materials, but these techniques are often unable to achieve the required dimensional tolerances and surface finishes. Due to the inherent compliance of the preforms, stable machining is difficult to achieve. Prediction of stable machining parameters is therefore critical for the finish machining of such compliant workpieces.In this research, a time domain simulation is presented for predicting stable and unstable milling conditions with application to finish milling of compliant workpieces. Traditional lobe diagrams provide global stability predictions by dividing the domain of spindle speed and chip width into stable and unstable regions. Time domain simulation provides local information (forces, displacements, etc.) for individual spindle speed-chip width combinations. Stability metrics, based on the local information, are developed to extend the utility of the time domain simulation to provide the global stability predictions of traditional lobe diagrams. The time domain simulation global stability predictions and "local" information are validated experimentally.

doctoral dissertations

Mechanical engineering

Ph.D.

Chatter
Compliant
Flexible
Milling
Simulation

Mechanical Engineering

Schmitz, Tony

Smith, Scott
Ziegert, John
Davies, Matt
Zhou, Aixi

Thesis (Ph.D.)--University of North Carolina at Charlotte, 2016.

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