2023 ASEE Annual Conference & Exposition

Teaching Vibration and Modal Analysis Concepts in Traditional Subtractive Machining to Mechanical Engineering Technology Students

Presented at Engineering Technology Division (ETD) Technical Session 3

Vibration, in traditional subtractive machining like milling and single point turning, is an undesirable effect. Light vibration causes poor surface finishes, leading to the rejection of machined parts. Heavy vibration causes poor surface finishes as well but can also lead to catastrophic tool failure. To avoid vibration, machinists will adjust spindle speeds and feed rates whenever tool chatter occurs. Since vibration is an inherent reality in milling and turning, it is necessary for mechanical engineering technology students to learn how to analyze vibration in manufacturing processes.

Finite Element Analysis (FEA) is an analysis tool that has been used in mechanical engineering courses for quite some time. Mechanical engineering technology students, however, do not typically get exposed to more in-depth courses of vibration and modal analysis. To assist mechanical engineering technology students into concepts of vibration and modal analysis in a manufacturing environment, FE modeling serves as an excellent learning tool. An FE model of an extended long milling cutter enables students to visualize the properties of a vibrating system and relate the natural frequencies back to spindle speed. Forced vibration models help them understand the resulting cutter displacements from the input force excitation. Modal analysis and forced vibration exposure help students understand the characteristics of vibration and how to mitigate this undesirable effect from traditional machining methods.

The assessment results from a student self-reflection survey for exposing vibration and modal analysis support the need to expose mechanical engineering technology students to these concepts. Student responses to open ended questions indicate they are able to grasp some concepts of vibration analysis using FEA as an analysis tool.

Authors
  1. Dr. David Michael Labyak Michigan Technological University [biography]
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