2026-09-19T02:25:35Zhttps://dspace.mit.edu/server/oai/requestoai:dspace.mit.edu:1721.1/1269832021-07-05T14:03:20Zcom_1721.1_7582com_1721.1_7581col_1721.1_131023
Jung Hoon-Chun and Roy Welsch.
Woodruff, David(David T.)
Sloan School of Management.
Massachusetts Institute of Technology. Department of Mechanical Engineering.
Leaders for Global Operations Program.
Sloan School of Management
Massachusetts Institute of Technology. Department of Mechanical Engineering
Leaders for Global Operations Program
2020-09-03T16:47:24Z
2020-09-03T16:47:24Z
2020
2020
https://hdl.handle.net/1721.1/126983
1191223861
Thesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Thesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020
Cataloged from the official PDF of thesis.
Includes bibliographical references (pages 129-130).
Canam Group ("Canam") is a manufacturer of steel components and building products used in the construction industry. The company uses a distributed network of manufacturing centers throughout North America to build and ship joist and deck product to its customers. Each manufacturing center utilizes a similar set of equipment assets in the production process. Equipment assets are not connected to a data collection system capable of monitoring their performance and health. As a result, comparing the performance of similar equipment across sites is a challenge for the organization. The motivation for this thesis is to determine how Internet of Things (IIoT) technologies can be applied to an industrial business like Canam to improve asset monitoring capabilities. An experimental approach is used to demonstrate how IIoT frameworks discussed in literature can be employed in practice.
In the first experiment, a network connectivity audit is performed to answer a set of practical questions about data communication within an industrial machine network. In the second experiment, a commercial tool is deployed at a specific equipment asset and integrated into the production workflow to collect data about the performance of the equipment. Downtime data collected from the IIoT tool deployed in the experimentation phase is compared with data collected using an existing manual data collection process. The data collected from the IIoT device revealed a systematic under-reporting of downtime in the manual process. Machine availability was shown to be 46% as compared to 90% recorded in the manual process. A model is presented to demonstrate that improving availability of critical equipment could lead to a 6% increase in plant throughput.
The thesis concludes by combining the findings of the experimental results and literature review to develop a framework from which the business can establish an organizational vision for IIoT, an implementation plan, a project scoping methodology and vendor selection criteria..
by David Woodruff.
M.B.A.
S.M.
M.B.A. Massachusetts Institute of Technology, Sloan School of Management
S.M. Massachusetts Institute of Technology, Department of Mechanical Engineering
130 pages
eng
Massachusetts Institute of Technology
MIT theses may be protected by copyright. Please reuse MIT thesis content according to the MIT Libraries Permissions Policy, which is available through the URL provided.
http://dspace.mit.edu/handle/1721.1/7582
Sloan School of Management.
Mechanical Engineering.
Leaders for Global Operations Program.
Stepping toward a smarter factory at Canam
Thesis
application/pdf
2020-09-03T16:47:22Z
Publication
Master
Sloan
MechE
unknown
unknown
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<Abstract>Canam Group ("Canam") is a manufacturer of steel components and building products used in the construction industry. The company uses a distributed network of manufacturing centers throughout North America to build and ship joist and deck product to its customers. Each manufacturing center utilizes a similar set of equipment assets in the production process. Equipment assets are not connected to a data collection system capable of monitoring their performance and health. As a result, comparing the performance of similar equipment across sites is a challenge for the organization. The motivation for this thesis is to determine how Internet of Things (IIoT) technologies can be applied to an industrial business like Canam to improve asset monitoring capabilities. An experimental approach is used to demonstrate how IIoT frameworks discussed in literature can be employed in practice.</Abstract>
<Abstract>In the first experiment, a network connectivity audit is performed to answer a set of practical questions about data communication within an industrial machine network. In the second experiment, a commercial tool is deployed at a specific equipment asset and integrated into the production workflow to collect data about the performance of the equipment. Downtime data collected from the IIoT tool deployed in the experimentation phase is compared with data collected using an existing manual data collection process. The data collected from the IIoT device revealed a systematic under-reporting of downtime in the manual process. Machine availability was shown to be 46% as compared to 90% recorded in the manual process. A model is presented to demonstrate that improving availability of critical equipment could lead to a 6% increase in plant throughput.</Abstract>
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