Rough-cut machining an impeller with 3-axis and 5-axis NC machines




Suhaimi, M. A.
Kim, Dong-Won
Lee, Jong-Yeong
Velasquez Arriaza, Oscar

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DEStech Publications, Inc.


This study presents an efficient rough-cutting strategy for machining a centrifugal impeller. Much of the machining time is consumed in rough cutting, where unnecessary stock materials are removed in between impeller blades. Thus, most of researchers focus on 5-axis rough machining of an impeller, controlling all the five axes simultaneously as fast as possible. In previous research, we introduced a 3-axis machining strategy that removes as much material as possible from the areas between blades. Thus, the main purpose of the research was to improve the machining efficiency by reducing the machining time. We achieved 19 percent of total machining time reduction by using the 3-axis rough machining. For further improvement, this paper will introduce an improved 3-axis machining strategy by applying feed-rate scheduling for more efficient rough cutting. There are two types of feed rate scheduling, namely, cutting force and material removal rate based scheduling. This research will focus on feed-rate scheduling based on cutting force to increase the feed-rate onto an allowable level. Current research in feed-rate scheduling applies cutting force calculations for each cutter-workpiece engagement, experimenting with different depth-of-cut layers. In this paper, we will calculate cutting force for each cutter-workpiece engagement by employing a finite element method. Cutting tool and workpiece geometry will be meshed and analyzed to find out best feed-rate scheduling. The rest of material that is left from the 3-axis machining will be removed by 5-axis machining. The result shows that by applying this hybrid roughing strategy, namely, 3-axis machining with feed-rate scheduling and 5-axis machining, total rough machining time can be reduced significantly up to 43 percent.


Paper presented at the Proceedings of the 24th International Conference on Flexible Automation & Intelligent Manufacturing, held May 20-23, 2014 in San Antonio, Texas, and organized by the Center for Advanced Manufacturing and Lean Systems, University of Texas at San Antonio
Includes bibliographical references


Cutting machines, Machine-tools--Numerical control, Turbomachines--Efficiency, Turbomachines--Blades