Teaching Optimization Theory and Practice in an Industrial Environment

2012 
I. Background The author has observed that many engineers who use optimization related software do not have formal training in this discipline. Based on interaction with users the author considers optimization still a niche discipline that is gaining significant visibility in the industrial environment. At Rolls-Royce these tools are also being coupled with Six Sigma or Robust Design methodologies. Although individuals could go back to local colleges or universities and take formal graduate level classes in this area, this option may not always be available due to work and/or personal commitments. Therefore, industry needs to invest time, money and people into teaching employees who will be using these complex design/analysis tools. This is evidenced by the significant amount of in-house training being conducted by Rolls-Royce and the company’s use of outside resources such as software vendors to teach these concepts. In this paper a three level approach is discussed to teaching employees in the area of optimization. This includes training on the use of specific software that is applied to company problems and in the education on the theory behind these tools. In addition to the multiple levels of teaching, mentoring is used to help guide students in applying optimization tools to typical projects. The author brings a perspective of combining academic teaching as an adjunct faculty member at Indiana University-Purdue University Indianapolis (IUPUI), with industrial teaching and full time practice at Rolls-Royce Corporation (Rolls-Royce) to teaching complex subjects in an industrial environment. In the academic environment the author provides a foundation to understanding the principles of optimization methods. Academic teaching has traditional lectures covering subject matter in the assigned textbook 1
    • Correction
    • Source
    • Cite
    • Save
    • Machine Reading By IdeaReader
    3
    References
    0
    Citations
    NaN
    KQI
    []