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dc.contributor.advisorJung Hoon-Chun and Roy Welsch.en_US
dc.contributor.authorWoodruff, David(David T.)en_US
dc.contributor.otherSloan School of Management.en_US
dc.contributor.otherMassachusetts Institute of Technology. Department of Mechanical Engineering.en_US
dc.contributor.otherLeaders for Global Operations Program.en_US
dc.date.accessioned2020-09-03T16:47:24Z
dc.date.available2020-09-03T16:47:24Z
dc.date.copyright2020en_US
dc.date.issued2020en_US
dc.identifier.urihttps://hdl.handle.net/1721.1/126983
dc.descriptionThesis: M.B.A., Massachusetts Institute of Technology, Sloan School of Management, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionThesis: S.M., Massachusetts Institute of Technology, Department of Mechanical Engineering, in conjunction with the Leaders for Global Operations Program at MIT, May, 2020en_US
dc.descriptionCataloged from the official PDF of thesis.en_US
dc.descriptionIncludes bibliographical references (pages 129-130).en_US
dc.description.abstractCanam 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.en_US
dc.description.abstractIn 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.en_US
dc.description.abstractThe 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..en_US
dc.description.statementofresponsibilityby David Woodruff.en_US
dc.format.extent130 pagesen_US
dc.language.isoengen_US
dc.publisherMassachusetts Institute of Technologyen_US
dc.rightsMIT 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.en_US
dc.rights.urihttp://dspace.mit.edu/handle/1721.1/7582en_US
dc.subjectSloan School of Management.en_US
dc.subjectMechanical Engineering.en_US
dc.subjectLeaders for Global Operations Program.en_US
dc.titleStepping toward a smarter factory at Canamen_US
dc.typeThesisen_US
dc.description.degreeM.B.A.en_US
dc.description.degreeS.M.en_US
dc.contributor.departmentSloan School of Managementen_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Mechanical Engineeringen_US
dc.contributor.departmentLeaders for Global Operations Programen_US
dc.identifier.oclc1191223861en_US
dc.description.collectionM.B.A. Massachusetts Institute of Technology, Sloan School of Managementen_US
dc.description.collectionS.M. Massachusetts Institute of Technology, Department of Mechanical Engineeringen_US
dspace.imported2020-09-03T16:47:22Zen_US
mit.thesis.degreeMasteren_US
mit.thesis.departmentSloanen_US
mit.thesis.departmentMechEen_US


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