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Title
Ultrasound Based Predictive Maintenance
Description
The basis of this project was to analyze the potential cost savings derived from the implementation of an ultrasonic flaw detector for gas pipes in factories. The group began by researching the market of the Industrial Internet of Things. IIoT is a very attractive market for investment, as connected technologies are become both more advanced and more affordable. Factory automation also saves costs of human capital, maintenance, and bad product cost as well as safety. After doing this preliminary research, the group continued by identifying potential solutions to current shortcomings of the manufacturing status quo. After narrowing down the options, the ultrasonic flaw detector appeared to have the highest potential for success in Company X's factories. The group began doing research on what physical components would go into this solution. They found pricing for all of the various parts of such a device as well as estimated labor, maintenance, and implementation costs. After estimating these costs, the team began the construction of a detailed financial model to generate the hypothetical net present value of such a tool. After presenting two times to a panel of Company X employees, the group decided to focus only on cost savings for Company X, and not the potential revenues of selling the whole solution. They ran a sensitivity analysis on all of the factors that contributed to the NPV of the project, and discovered that the estimated percentage of scrapped product resulting from gas leaks and the percentage of gas lost to leaks contributed the most to the NPV.
Date Created
2017-05
Contributors
- Flick, Jacob (Co-author)
- Alam, Mustafa (Co-author)
- Nguyen, Mong (Co-author)
- Zhang, Zihan (Co-author)
- Simonson, Mark (Thesis director)
- Hertzel, Michael (Committee member)
- Department of Finance (Contributor)
- Department of Information Systems (Contributor)
- WPC Graduate Programs (Contributor)
- School of International Letters and Culture (Contributor)
- School of Mathematical and Statistical Sciences (Contributor)
- Barrett, The Honors College (Contributor)
Topical Subject
Resource Type
Extent
24 pages
Language
eng
Copyright Statement
In Copyright
Primary Member of
Series
Academic Year 2016-2017
Handle
https://hdl.handle.net/2286/R.I.43007
Level of coding
minimal
Cataloging Standards
System Created
- 2017-10-30 02:50:58
System Modified
- 2021-08-11 04:09:57
- 3 years 3 months ago
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