Predicting Energy Usage During Milling Based on Workpiece Properties

Published in UC Berkeley Master's Report, 2015

Recommended citation: H. Budinoff, 2015. "Predicting Energy Usage During Milling Based on Workpiece Properties," Master's report, Department of Mechanical Engineering, University of California, Berkeley.

Abstract: The work presented in this thesis focuses on improving material selection by developing a better understanding of the factors that drive energy consumption in machining. Choice of material, like choice of manufacturing process, depends on many factors, especially the desired function of the part. However, there currently is not enough research for designers to make informed decisions when considering the importance of energy consumption. A designer trying to choose between two different aluminum alloys with similar functional properties currently has no way of knowing which material would be more energy efficient. New materials also present potential challenges: it is currently difficult to estimate the energy required to machine a novel material with a particular set of properties without prior experimentation.