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Massachusetts Institute of Technology

Stepping toward a smarter factory at Canam

Abstract

dc:description.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.

Degree

thesis:*
Name thesis:degree_name
Master
Department dc:contributor.department
Sloan School of Management
Grantor dc:publisher
Massachusetts Institute of Technology
Year dc:date.issued
2020

Author and committee

dc:creator, dc:contributor.*
Author dc:creator
  • Woodruff, David(David T.)
Advisor dc:contributor.advisor
  • Jung Hoon-Chun and Roy Welsch.

Subjects

dc:subject × 3

Rights

dc:rights
Statement dc:rights
  • 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.
Language dc:language.iso
eng

Identifiers

dc:identifier.*
Handle dc:identifier.uri
https://hdl.handle.net/1721.1/126983
OAI identifier oai:identifier
oai:dspace.mit.edu:1721.1/126983

Chain of custody

source
Harvested from
MIT
Base URL
dspace.mit.edu/oai/request
Last updated
2026-07-22
Source record
OAI-PMH GetRecord
citation

Woodruff, David(David T.). Stepping toward a smarter factory at Canam. Massachusetts Institute of Technology, 2020. https://hdl.handle.net/1721.1/126983