Enhancing undergraduate understanding of subtractive manufacturability through virtualized simulation of CNC machining

Roby Lynn, Kathryn W. Jablokow, Christopher Saldana, Thomas Marshall Tucker, Thomas Kurfess

Research output: Contribution to journalConference articlepeer-review

4 Scopus citations


The design process can often introduce manufacturing challenges, and designers must be able to understand these challenges in order to minimize them. Frequently, the experience level of mechanical engineering students is insufficient for them to consider the limitations that manufacturing processes impose upon design, and they often design parts that are either difficult or impossible to manufacture. This work describes the development, implementation, and analysis of a system used to rapidly provide students with the knowledge they need to consider manufacturing challenges for machining processes. An experimental group of students was trained in the use of a software package (SculptPrint) that provides visualizations of the turning process and taught how to operate various computer numerical control (CNC) machine tools. A separate control group of students was trained on the operation of manual machine tools and did not receive access to the turning visualizations. Knowledge assessments were given to both groups to measure their understanding of a variety of topics in manufacturability. Analysis of the survey results indicates that student understanding of geometrical limitations in the turning process can be dramatically improved by employing visualizations of manufacturing processes.

Original languageEnglish (US)
JournalASEE Annual Conference and Exposition, Conference Proceedings
StatePublished - Jun 24 2017
Event124th ASEE Annual Conference and Exposition - Columbus, United States
Duration: Jun 25 2017Jun 28 2017

All Science Journal Classification (ASJC) codes

  • General Engineering


Dive into the research topics of 'Enhancing undergraduate understanding of subtractive manufacturability through virtualized simulation of CNC machining'. Together they form a unique fingerprint.

Cite this