Tom and Lonnie Chat: Artificial Intelligence, Pushing Your Machines Through Chatter and into Productivity

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Process parameters in milling are typically selected using tool supplier and handbook recommendations, or previous experience. If unstable behavior (chatter) is observed, the conventional wisdom is to reduce the spindle speed and axial depth of cut. In this podcast, we will discuss stability maps in machining, which separate stable and unstable (or chatter) combinations of cut depth and spindle speed. Using knowledge of the stability maps, spindle speed and axial depth of cut can actually be increased to eliminate chatter. This enables improvement in material removal rates and productivity while eliminating chatter. 
We will show how to create stability maps, which exist for every tool-holder-machine combination, and how to use them to select optimal stable parameters to maximize productivity and eliminate chatter.  We will discuss the application of artificial intelligence/machine learning (AI/ML) for learning stability maps in a production environment. An automated method for learning the stability maps and identifying optimal process parameters in an industrial environment with closed-loop control and machine learning using modern machine tools will be presented. We will discuss how this work is moving from the laboratory and research and development centers into production operations. Join us to see how some of the latest concepts in AI and ML can help you to eliminate chatter and improve productivity at the same time.

Conference: IMTS Content

Type: Tom & Lonnie Chat Series