Lake Superior State University
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Alum Success

"I chose to transfer to Lake Superior State University because of the personal attention I would receive. I did not want to attend a large university where I would be a number lost in the masses. The well-rounded curriculum allowed me to obtain my position at John Deere. Having a good balance of theory and hands-on knowledge is critical for my position and Lake State gave me a good foundation in these skills."

Maria DiValentin, Mechanical Engineering 2001
Field Service Representative,
John Deere Power Systems
Waterloo, IA

School of Engineering

Senior Projects 2009-2010

Team I2 Logo

 

Team Industrial Innovations

Members:

  • Brett Allossery
  • Mark Brown
  • Graham Tomkins
  • Jonathan Valley
  • Devon Vogt
  • Jake Weinmann

Faculty Advisor:

  • Mr. Jon Coullard

Company:

  • Precision Edge Surgical Products Co.

Industrial Contact:

  • Mr. Duke Pepin
  • Mr. Joel Diemer

Project Description: Automated Robotic Work Cell

Precision Edge Surgical Products Company manufactures surgical drills. These undergo a laser etching process to mark them with lot numbers, company logo and depth lines. Team II constructed an automated robotic work cell to load and unload a laser etching machine. This eliminates the need for a worker to be present, and increases the overall throughput of the etching process. The work cell can be easily converted to the manual mode to allow an operator to etch a small batch of parts or perform quality control checks.

Links to the 2009-2010 Senior Projects Teams:

A Spatial Analysis of Greenhouse Gasses and Household Income

Scott Sowers

Emissions of greenhouse gases (GHG) by industries have been increasing at an exponential rate in the past century. As these emissions increase in number of sources, as well as amount of output, the impact on the environment becomes more significant. However, the United States relies heavily on industry for creation of new products, materials, and economic factors such as employment. Industries attract employment opportunities, which in return attract living accommodations. The basis of this project was to see if there is any spatial correlation between GHG emissions and income of households (within a county) of a GHG emitter. Using Geographical Information Science (GIS), we are able to search for a correlation between lower class households and amounts of GHG emissions. After processing the data, we are able to show that there is no trend in GHG emissions and the proximity to lower class households. Towards the end of the project, we were able to see an extremely slight trend of lower amounts of GHG emissions near upper class households. The project also provides the statistics, or any autocorrelation, of the data for significance testing to determine whether or not there is a probability of the relationship. The statistics provided will be the R2 value, regression, and correlation.

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