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https://doi.org/10.18260/p.262...
Article . 2016 . Peer-reviewed
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An Industrial Robotics Course for Manufacturing Engineers

Authors: Jeffrey L. Newcomer;

An Industrial Robotics Course for Manufacturing Engineers

Abstract

For many years the automobile industry was the home to more than half of the robots used in U.S. manufacturing. Recently, however, many other industries have been or are planning to introduce robots into their manufacturing processes. As such, an introduction to robotics in the context of manufacturing is becoming more important for students pursuing degrees in Manufacturing Engineering. There is, however, always a challenge when teaching robotics to find the correct balance between application and modeling. Many robotics courses taught in Electrical or Mechanical Engineering Departments have a tendency to emphasize modeling over application, but a well-prepared Manufacturing Engineer needs to understand where the challenges in robotics applications lie as well as understanding what is going on ‘under the hood’. This paper describes a new Industrial Robotics course for Manufacturing Engineering students at Western Washington University. The new course is based upon a course that had been part of a Manufacturing Engineering Technology program that has recently transitioned to Manufacturing Engineering. The goals of the new course are to find the right balance between modeling and application and be true to the applied nature of the new Manufacturing Engineering program. Therefore, the course is lab intensive to provide students with multiple opportunities to work with industrial robots. Students complete thirteen structured and semi-structured lab activities that introduce them to different aspects of applied robotics, including the design of end-effector tooling and fixtures for different tasks. Students work with three different robot configurations and two different operating systems, so they are exposed to some of the different options available and get experience with different interfaces and design philosophies. Students also get a brief introduction to machine vision systems through lab activities. The lab experience culminates in an open-ended, industry-sponsored project that requires students to apply ...

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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
1
Average
Average
Average
bronze
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