Accendo Reliability

Your Reliability Engineering Professional Development Site

  • Home
  • About
    • Contributors
    • About Us
    • Colophon
    • Survey
  • Reliability.fm
    • Speaking Of Reliability
    • Rooted in Reliability: The Plant Performance Podcast
    • Quality during Design
    • CMMSradio
    • Way of the Quality Warrior
    • Critical Talks
    • Asset Performance
    • Dare to Know
    • Maintenance Disrupted
    • Metal Conversations
    • The Leadership Connection
    • Practical Reliability Podcast
    • Reliability Hero
    • Reliability Matters
    • Reliability it Matters
    • Maintenance Mavericks Podcast
    • Women in Maintenance
    • Accendo Reliability Webinar Series
  • Articles
    • CRE Preparation Notes
    • NoMTBF
    • on Leadership & Career
      • Advanced Engineering Culture
      • ASQR&R
      • Engineering Leadership
      • Managing in the 2000s
      • Product Development and Process Improvement
    • on Maintenance Reliability
      • Aasan Asset Management
      • AI & Predictive Maintenance
      • Asset Management in the Mining Industry
      • CMMS and Maintenance Management
      • CMMS and Reliability
      • Conscious Asset
      • EAM & CMMS
      • Everyday RCM
      • History of Maintenance Management
      • Life Cycle Asset Management
      • Maintenance and Reliability
      • Maintenance Management
      • Plant Maintenance
      • Process Plant Reliability Engineering
      • RCM Blitz®
      • ReliabilityXperience
      • Rob’s Reliability Project
      • The Intelligent Transformer Blog
      • The People Side of Maintenance
      • The Reliability Mindset
    • on Product Reliability
      • Accelerated Reliability
      • Achieving the Benefits of Reliability
      • Apex Ridge
      • Breaking Bad for Reliability
      • Field Reliability Data Analysis
      • Metals Engineering and Product Reliability
      • Musings on Reliability and Maintenance Topics
      • Product Validation
      • Reliability by Design
      • Reliability Competence
      • Reliability Engineering Insights
      • Reliability in Emerging Technology
      • Reliability Knowledge
    • on Risk & Safety
      • CERM® Risk Insights
      • Equipment Risk and Reliability in Downhole Applications
      • Operational Risk Process Safety
    • on Systems Thinking
      • The RCA
      • Communicating with FINESSE
    • on Tools & Techniques
      • Big Data & Analytics
      • Experimental Design for NPD
      • Innovative Thinking in Reliability and Durability
      • Inside and Beyond HALT
      • Inside FMEA
      • Institute of Quality & Reliability
      • Integral Concepts
      • Learning from Failures
      • Progress in Field Reliability?
      • R for Engineering
      • Reliability Engineering Using Python
      • Reliability Reflections
      • Statistical Methods for Failure-Time Data
      • Testing 1 2 3
      • The Hardware Product Develoment Lifecycle
      • The Manufacturing Academy
  • eBooks
  • Resources
    • Special Offers
    • Accendo Authors
    • FMEA Resources
    • Glossary
    • Feed Forward Publications
    • Openings
    • Books
    • Webinar Sources
    • Journals
    • Higher Education
    • Podcasts
  • Courses
    • Your Courses
    • 14 Ways to Acquire Reliability Engineering Knowledge
    • Live Courses
      • Introduction to Reliability Engineering & Accelerated Testings Course Landing Page
      • Advanced Accelerated Testing Course Landing Page
    • Integral Concepts Courses
      • Reliability Analysis Methods Course Landing Page
      • Applied Reliability Analysis Course Landing Page
      • Statistics, Hypothesis Testing, & Regression Modeling Course Landing Page
      • Measurement System Assessment Course Landing Page
      • SPC & Process Capability Course Landing Page
      • Design of Experiments Course Landing Page
    • The Manufacturing Academy Courses
      • An Introduction to Reliability Engineering
      • Reliability Engineering Statistics
      • An Introduction to Quality Engineering
      • Quality Engineering Statistics
      • FMEA in Practice
      • Process Capability Analysis course
      • Root Cause Analysis and the 8D Corrective Action Process course
      • Return on Investment online course
    • Industrial Metallurgist Courses
    • FMEA courses Powered by The Luminous Group
      • FMEA Introduction
      • AIAG & VDA FMEA Methodology
    • Barringer Process Reliability Introduction
      • Barringer Process Reliability Introduction Course Landing Page
    • Fault Tree Analysis (FTA)
    • Foundations of RCM online course
    • Reliability Engineering for Heavy Industry
    • How to be an Online Student
    • Quondam Courses
  • Webinars
    • Upcoming Live Events
    • Accendo Reliability Webinar Series
  • Calendar
    • Call for Papers Listing
    • Upcoming Webinars
    • Webinar Calendar
  • Login
    • Member Home
Home » LMS » Higher Education » University of Toronto

by Fred Schenkelberg Leave a Comment

University of Toronto

University of Toronto

Program Description

Centre for Maintenance Optimization and Reliability Engineering (C-MORE)

The Centre for Maintenance Optimization and Reliability Engineering is directed by Professor Andrew K.S. Jardine within the Department of Mechanical and Industrial Engineering at the University of Toronto.

[show_to accesslevel=”free” no_access=”login to view program details ⇒”]Summary

C-MORE’s research is driven by close interactions with industry, in particular with MORE consortium members and with researchers at universities world-wide. Our focus is on real-world research in engineering asset management in the areas of condition-based maintenance, spares management, protective devices, maintenance and repair contracts, and failure-finding intervals. These strong industry connections not only benefit the companies we work with but also our graduate students, who find work in maintenance divisions of industry leaders after graduation.

C-MORE website: http://cmore.mie.utoronto.ca/ 

Graduate Program in Mechanical and Industrial Engineering

Overview

The Department of Mechanical and Industrial Engineering accepts qualified applicants for study in a wide range of topics, spanning the breadth of mechanical and industrial engineering, including applied mechanics, robotics and manufacturing; biomedical engineering; computer aided design and materials engineering; energy studies, thermodynamics and surface science; environmental engineering; fluid sciences; information systems and enterprise engineering; operations research; and human factors/ergonomics.

  • The Master of Applied Science degree program provides students with an opportunity to pursue research-intensive advanced studies in a particular field of interest.
  • The Master of Engineering degree program is designed for students preparing for advanced professional activity; it is not a research-oriented degree.
  • The Doctor of Philosophy degree program is for students anticipating a career in which they will be performing or directing research at the most advanced level.

Master of Applied Science

Minimum Admission Requirements

  • Applicants must normally have a minimum average of B+, or equivalent, in each of the final two years of an accredited four-year undergraduate program in engineering or a closely related field.
  • Applicants are also assessed on publications, work experience, the school and program to which each previous degree pertains, evidence of exceptional communication skills, references, and the availability of financial resources, space, and suitable supervision.

Program Requirements

  • At the beginning of each student’s program, a professor in the Department will be identified as the supervisor who will guide the student in the research program and selection of courses.
  • For students with an adequate undergraduate background, the program will normally consist of 2.5 full-course equivalents (FCE) and a thesis.
  • MASc students are required to participate in the non-credit seminar course JDE 1000H during their first or second session of registration.
  • MASc students, in their first year of study, are required to attend at least 70% of seminars that are part of the MIE Seminar Series. MASc students who complete the requirement will receive credit for SRM 3333Y
  • Master’s Seminar Series.
  • Normal Program Length
  • 6 sessions (full-time)

Master of Engineering

Minimum Admission Requirements

  • Applicants must normally have a minimum average of B+, or equivalent, in each of the final two years of an accredited four-year undergraduate program in engineering or a closely related field.Applicants are also assessed on publications, work experience, the school and program to which each previous degree pertains, evidence of exceptional communication skills, references, and the availability of financial resources.
  • Applicants are also assessed on publications, work experience, the school and program to which each previous degree pertains, evidence of exceptional communication skills, references, and the availability of financial resources.

Program Requirements

  • 5.0 full-course equivalents (FCE) or 3.5 FCE plus a supervised project. A majority of the courses must be taught by the Department of Mechanical and Industrial Engineering.
  • The program may be taken on a full-time or part-time basis.
    Normal Program Length
  • 3 sessions (full-time); 6 sessions (part-time)

Doctor of Philosophy

Minimum Admission Requirements

Admission to a PhD program is reserved for those who are able to present evidence of superior academic and research ability. Students may be admitted to the PhD program via one of three routes:

  1. Master’s degree. Appropriate University of Toronto master’s degree, or its equivalent from a recognized university, with a minimum B+ average.
  2. Direct entry. Exceptionally strong applicants with a University of Toronto bachelor’s degree or equivalent and an appropriate background may apply directly to the PhD program. Applicants are advised to consult the Graduate Coordinator before applying to ensure that they possess the appropriate admission requirements for direct entry.
  3. Transfer. Very strong MASc students may apply to transfer to the PhD program after completing only one year of the MASc program.

Program Requirements

  • At the beginning of each student’s program, a professor in the Department will be identified as the supervisor and will guide the student in the research program and selection of courses.
  • Minimum departmental standards in course work: students with a master’s degree normally are required to complete 2.5 full-course equivalents (FCE) and a thesis.
  • Direct-entry students admitted with a bachelor’s degree are required to complete 4.0 FCE plus a thesis. Transfer students must complete a total of 4.0 FCE plus a thesis.
  • Students are required to participate in the non-credit seminar course JDE 1000H during their first or second session of registration.
  • PhD students in their first and second years of study are required to attend at least 70% of seminars that are part of the MIE Seminar Series. PhD students who complete the requirement will receive credit for SRD 4444Y Doctoral Seminar Series.
  • Each PhD student must pass a qualifying examination, a seminar presentation, additional annual progress meetings, the departmental PhD examination, and the SGS PhD final oral examination.
  • PhD students are required to be on campus full-time unless special permission is obtained for off-campus study.

Normal Program Length

4 years (full-time PhD); 5 years (transfer or direct-entry)

Courses in Mechanical and Industrial Engineering

Note: Courses vary from year to year.

See: http://www.mie.utoronto.ca/graduate/courses/

  • Operations Research
  • MIE 1603H Integer Programming
  • MIE 1605H Stochastic Processes I: Introduction to Stochastic Processes
  • MIE 1606H Queueing Theory
  • MIE 1607H Stochastic Processes II: Modeling and Optimization
  • MIE 1609H Multiple Criteria Decision Making
  • MIE 1613H Discrete Event Simulation
  • MIE 1615H Stochastic Dynamic Programming
  • MIE 1616H Healthcare Management
  • MIE 1619H Constraint Programming and Local Search
  • MIE 1620H Linear Programming and Network Flows
  • MIE 1621H Nonlinear Optimization
  • MIE 1699H Special Topics in Operations Research
  • MIE 1721H Reliability
  • MIE 1723H Engineering Maintenance Management
  • MIE 1727H Quality Assurance I
  • MIE 561H Healthcare Systems
  • MIE 562H Scheduling
  • MIE 566H Decision Analysis

Contacts

Web: www.mie.utoronto.ca/contact/grad.php
E-mail: grad.admission@mie.utoronto.ca
Telephone: 416- 978-8823
Fax: 416-978-3453
Snail Mail:Department of Mechanical and Industrial Engineering
University of Toronto
5 King’s College Road
Toronto, Ontario M5S 3G8
Canada

For more information

send email 

 

visit website

[/show_to]

View Previous View Next

About Fred Schenkelberg

I am the reliability expert at FMS Reliability, a reliability engineering and management consulting firm I founded in 2004. I left Hewlett Packard (HP)’s Reliability Team, where I helped create a culture of reliability across the corporation, to assist other organizations.

Leave a Reply Cancel reply

Your email address will not be published. Required fields are marked *

[hide_from visible_to='public']Please login to have full access.

[login-form]
[password-recovery-link text='Lost Password? Click here to have it emailed to you.']

If you haven't registered, it's free and takes only a moment to create an account with your email only.

Register

Your membership brings you all these free resources:

  • Live, monthly reliability webinars & recordings
  • eBooks: Finding Value and Reliability Maturity
  • How To articles & insights
  • Podcasts & additional information within podcast show notes
  • Podcast suggestion box to send us a question or topic for a future episode
  • Course (some with a fee)
  • Largest reliability events calendar
  • Courses on a range of topics - coming soon
  • Resource area full access
  • Basic tutorial articles
  • With more in the works just for members

[/hide_from][show_to accesslevel="Free" ]
Thanks for being a member [member_first_name]!
[/show_to]

  • Higher Education
    • City University of Hong Kong
    • Arizona State University
    • Indian Institute of Technology Kharagpur
    • Rutgers University
    • University of Arizona
    • University of Wisconsin – Madison
    • University of Maryland
    • University of Toronto
    • Texas State University
    • University of West of Scotland
    • Southern Methodist University
    • Beihang University
    • Georgia Tech
    • Norwegian University of Science and Technology
    • Heriot Watt University
    • Vanderbilt University
    • Federation University
    • University of Tennessee
    • Tsinghua University
    • LuleÃ¥ University of Technology

© 2026 FMS Reliability · Privacy Policy · Terms of Service · Cookies Policy

Book the Course with John
  Ask a question or send along a comment. Please login to view and use the contact form.
This site uses cookies to give you a better experience, analyze site traffic, and gain insight to products or offers that may interest you. By continuing, you consent to the use of cookies. Learn how we use cookies, how they work, and how to set your browser preferences by reading our Cookies Policy.