Industrial Engineering


Industrial Engineering (AEINDBASC)

Undergraduate Program Administrator and Academic Advisor, Year 2
Gayle Lesmond
Room MC109, Mechanical Engineering Building 
416-978-4731
undergrad@mie.utoronto.ca

Undergraduate Student Advisor, Years 3-4
Yanna Sventzouris
Room MC109, Mechanical Engineering Building 
416-978-2454
undergrad@mie.utoronto.ca
 

Industrial Engineering (IE) is a discipline that applies engineering principles to the design and operation of organizations. Industrial Engineering students learn to analyze, design, implement, control, evaluate and improve the performance of complex organizations, taking into consideration people, technology and information systems. Industrial engineers use operations research, information engineering, artificial intelligence and human factors tools and methods to improve and optimize systems operations and performance.

Industrial engineers share the common goal of increasing an organization’s efficiency, profitability and safety in a variety of industries including health care, finance, retail, entertainment, government, information technology, transportation, energy, manufacturing and consulting. Unlike traditional disciplines in engineering and the mathematical sciences, IE addresses the role of the human decision-maker as a key contributor to the inherent complexity of systems and the primary benefactor of the analyses.

Industrial Engineering bears a close resemblance to management science, management engineering, operations research, operations management and systems engineering.

The objective of the Industrial Engineering program curriculum is to educate engineers who:

  • Employ effective analysis and design tools.
  • Integrate perspectives into a systems view of the organization.
  • Understand both the theory and the practice of Industrial Engineering.

In the first two years of the curriculum, the emphasis is placed on fundamental principles of engineering and core industrial engineering concepts. Tools taught in the second year include probability, psychology for engineers, fundamentals of object-oriented programming, operations research, differential equations, statistics, human-centered systems design and data modeling.

In third-year, students learn various perspectives on the operation of organizations, including productivity, information, ergonomics and economics. They also select technical electives allowing them to specialize in information engineering, artificial intelligence, operations research and human factors and investigate other IE areas such as business process engineering, design of information systems and data analytics. These same courses may be taken as fourth-year technical electives (schedule permitting). Therefore, students may use their fourth-year electives to pursue their specializations further in-depth or to investigate other IE areas.

In fourth-year, the central theme is the design and management of an organization as an integrated system. All students participate in a Capstone Design course that requires students to draw on knowledge from all years of the IE program to tackle a real-world project with an industry partner. There is also a research thesis option.

Job opportunities for IE graduates are diverse and offer challenging careers in a wide variety of industries, including consulting. Three prototypical jobs for new graduates include:

  • Manage an organizational supply chain to ensure new products can be successfully introduced into global sales channels.
  • Test the interaction features of a new software application.
  • Identify the increased capacity requirements necessary to accommodate the expected surgical volume of hospitals.
     

Minors

The Cross-Disciplinary Programs Office (CDP) offers a variety of minors and certificate programs that complement the Industrial Engineering curriculum. Students interested in pursuing an Engineering minor and/or certificate are encouraged to consult with the CDP. 
 

Graduate Studies in Industrial Engineering

The Department offers graduate studies and research opportunities in a wide range of fields within Industrial Engineering. These include human factors engineering, information engineering, management science, manufacturing, operations research, systems design and optimization, reliability and maintainability engineering. Subject areas include queuing theory, cognitive engineering, human-computer interaction and human factors in medicine. The programs available lead to MEng, MASc and PhD degrees. Evening courses are offered to accommodate participants who work full-time and are interested in pursuing M.Eng degrees. Additional information can be obtained from the Mechanical & Industrial Engineering Graduate Studies Office and mie.utoronto.ca/graduate.
 

INDUSTRIAL ENGINEERING (AEINDBASC)

INDUSTRIAL ENGINEERING (AEINDBASC)

FIRST YEAR INDUSTRIAL ENGINEERING

Fall Session – Year 1   Lect. Lab. Tut. Wgt.
Core Required Courses          
APS100H1: Orientation to Engineering F 1 - 1 0.25
APS110H1: Engineering Chemistry and Materials Science F 3 1 1 0.50
APS111H1: Engineering Strategies & Practice I F 3 1 1 0.50
CIV100H1: Mechanics F 3 - 2 0.50
MAT186H1: Calculus I F 3 - 1 0.50
MAT188H1: Linear Algebra F 3 1 1 0.50
Winter Session – Year 1   Lect. Lab. Tut. Wgt.
Core Required Courses          
APS106H1: Fundamentals of Computer Programming S 3 2 1 0.50
APS112H1: Engineering Strategies & Practice II S 2 2 - 0.50
ECE110H1: Electrical Fundamentals S 3 1 2 0.50
MAT187H1: Calculus II S 3 - 1 0.50
MIE100H1: Dynamics S 3 - 2 0.50
MIE191H1: Seminar Course: Introduction to Mechanical and Industrial Engineering S 1 - - 0.15

Approved Course Substitutions

  1. Students are able to substitute MAT186H1 with the online calculus course APS162H1.
  2. Students are able to substitute MAT187H1 with the online calculus course APS163H1.
  3. Students are able to substitute APS110H1 with the online course APS164H1.
  4. Students are able to substitute CIV100H1 with the online course APS160H1.

SECOND YEAR INDUSTRIAL ENGINEERING

Fall Session – Year 2   Lect. Lab. Tut. Wgt.
MAT238H1: Differential Equations and Discrete Math F 3 - 2 0.50
MIE236H1: Probability F 3 - 2 0.50
MIE242H1: Foundations of Cognitive Psychology F 3 3 - 0.50
MIE250H1: Fundamentals of Object Oriented Programming F 2 3 - 0.50
MIE262H1: Deterministic Operations Research F 3 2 1 0.50
Winter Session – Year 2   Lect. Lab. Tut. Wgt.
MIE223H1: Data Science S 3 2 - 0.50
MIE237H1: Statistics S 3 1 2 0.50
MIE240H1: Human Factors Engineering S 3 - 2 0.50
MIE245H1: Data Structures and Algorithms S 3 1 1 0.50
MIE263H1: Stochastic Operations Research S 3 - 2 0.50

THIRD YEAR INDUSTRIAL ENGINEERING

Fall Session – Year 3   Lect. Lab. Tut. Wgt.
Core Required Courses          
MIE353H1: Data Modelling F 3 2 1 0.50
MIE358H1 (Engineering Economics, formerly MIE258H1) F 3 - 1 0.50
MIE360H1: Systems Modelling and Simulation F 3 2 1 0.50
MIE370H1: Introduction to Machine Learning F 3 2 - 0.50
Technical Elective (Choose One):          
APS360H1: Applied Fundamentals of Deep Learning F 3 1 - 0.50
CSC384H1: Introduction to Artificial Intelligence F 3 - - 0.50
MIE344H1: Ergonomic Design of Information Systems F 3 3 - 0.50
MIE354H1: Business Process Engineering F 3 2 - 0.50
MIE365H1: Advanced Operations Research F 3 2 1 0.50
MIE368H1  F 2 3 1 0.50
MIE434H1 (formerly MIE343H1) F 3 3 - 0.50
Winter Session - Year 3   Lect. Lab. Tut. Wgt.
Core Required Courses          
MIE350H1: Design and Analysis of Information Systems S 3 1 1 0.50
MIE359H1: Organization Design S 4 - - 0.50
MIE363H1: Operations and Supply Chain Management S 3 - 2 0.50
Technical Elective (Choose One):          
APS360H1: Applied Fundamentals of Deep Learning S 3 1 - 0.50
MIE304H1: Introduction to Quality Control S 3 1 2 0.50
MIE345H1: Case Studies in Human Factors and Ergonomics S 3 - 2 0.50
MIE367H1: Cases in Operations Research S 3 - 2 0.50
MIE369H1: Introduction to Artificial Intelligence S 3 2 - 0.50
Complementary Studies Elective          
CS Elective S       0.50
  1. Practical Experience Requirement - As described in the beginning pages of this chapter, students are required to have completed a total of 600 hours of acceptable practical experience before graduation (normally during their summer periods).
    1. For students following the “old” curriculum: At least two of the four (0.5 credit) Complementary Studies Electives to be taken between third and fourth year must be Humanities/Social Sciences courses (see the Complementary Studies section at the beginning of this chapter). Students are responsible for ensuring that each elective taken is approved. Please consult the electives list available on the Engineering Office of the Registrar's website.
    2. For students following the “new” curriculum: At least two of the three (0.5 credit) Complementary Studies Electives to be taken between third and fourth year must be Humanities/Social Sciences courses (see the Complementary Studies section at the beginning of this chapter). Students are responsible for ensuring that each elective taken is approved. Please consult the electives list available on the Engineering Office of the Registrar's website.

PROFESSIONAL EXPERIENCE YEAR

Students registered within this program, and all other undergraduate programs within the Faculty of Applied Science and Engineering, may elect to enroll and participate in the Professional Experience Year Co-Op Program (PEY Co-Op). The PEY Co-op program requires that qualified students undertake a paid, full-time 12-16 month continuous work period with a cooperating industry. Details are described in the beginning of this chapter. More information can be found in the PEY Co-op section of the calendar.

FOURTH YEAR INDUSTRIAL ENGINEERING

Note: The Industrial Engineering program is undergoing a major curriculum change that will take effect over multiple stages. The fourth year of the program as outlined below corresponds to the requirements of the old program. If you are following the new curriculum, please review the fourth year requirements here.

Fall Session – Year 4   Lect. Lab. Tut. Wgt.
Core Required Courses:          
MIE463H1: Integrated System Design F 3 - 2 0.50
MIE490Y1: Capstone Design Y - - 4 1.00
Technical Electives (Choose Two):          
APS360H1: Applied Fundamentals of Deep Learning F 3 1 - 0.50
APS502H1: Financial Engineering F - - 3 0.50
CSC384H1: Introduction to Artificial Intelligence F 3 - - 0.50
MIE434H1 (formerly MIE343H1) F 3 3 - 0.50
MIE344H1: Ergonomic Design of Information Systems F 3 3 - 0.50
MIE354H1: Business Process Engineering F 3 2 - 0.50
MIE365H1: Advanced Operations Research F 3 2 1 0.50
MIE368H1: Analytics in Action F 2 3 1 0.50
MIE435H1: *Early-stage design methods F 2 2 1 0.50
MIE440H1: * Design of Effective Products F 2 2 1 0.50
MIE451H1: Decision Support Systems F 3 1 1 0.50
MIE498H1: Research Thesis F - - 4 0.50
MIE498Y1: Research Thesis Y - - 4 1.00
MIE523H1: Engineering Psychology and Human Performance F 3 3 - 0.50
MIE524H1: Data Mining F 3 2 - 0.50
MIE562H1: Scheduling F 3 - 2 0.50
MIE566H1: Decision Making Under Uncertainty F 3 - 2 0.50
Complementary Studies Elective          
CS Elective F/Y       0.50
Winter Session - Year 4   Lect. Lab. Tut. Wgt.
Core Required Courses:          
MIE359H1 (Organization Design, formerly MIE459H1) S 4 - - 0.50
MIE490Y1: Capstone Design Y - - 4 1.00
Technical Electives (Choose Two):          
APS360H1: Applied Fundamentals of Deep Learning S 3 1 - 0.50
APS502H1: Financial Engineering S - - 3 0.50
BME466H1: Drug Delivery at Biological Barriers and Interfaces S 3 - 1 0.50
BME488H1: Introduction to Immunoengineering S 2 - 1 0.50
MIE345H1: Case Studies in Human Factors and Ergonomics S 3 - 2 0.50
MIE367H1: Cases in Operations Research S 3 - 2 0.50
MIE369H1: Introduction to Artificial Intelligence S 3 2 - 0.50
MIE424H1: Optimization in Machine Learning S 3 1 - 0.50
MIE457H1: Knowledge Modelling and Management S 3 1 1 0.50
MIE469H1: Reliability and Maintainability Engineering S 3 - 2 0.50
MIE498H1: Research Thesis S - - 4 0.50
MIE498Y1: Research Thesis Y - - 4 1.00
MIE519H1: * Advanced Manufacturing Technologies S 3 - - 0.50
MIE535H1: Electrification Via Electricity Markets S 3 1 1 0.50
MIE542H1: Human Factors Integration S 3 - 2 0.50
MIE561H1: Case Studies in Healthcare S 3 - 2 0.50
MIE567H1: Multi-agent Reinforcement Learning S 3 - 2 0.50
Complementary Studies Elective          
CS Elective S/Y       0.50
  1. The Department is not able to schedule all fourth-year courses without conflict. However, students are required to select courses that allow for a conflict-free timetable.

  2. Technical electives in each of the 3F, 3W and 4F, 4W sessions must be chosen from the provided listings. Students who want to take a technical elective substitute are required to obtain formal Departmental approval from the Undergraduate Office.

  3. Industrial Engineering students are required to complete a two-term Capstone Design project, MIE490Y1, supervised by a licensed member of the University of Toronto teaching staff.


    1. For students following the “old” curriculum: At least two of the four (0.5 credit) Complementary Studies Electives to be taken between third and fourth year must be Humanities/Social Sciences courses (see the Complementary Studies section at the beginning of this chapter). Students are responsible for ensuring that each elective taken is approved. Please consult the electives list available on the Engineering Office of the Registrar's website.
    2. For students following the “new” curriculum: At least two of the three (0.5 credit) Complementary Studies Electives to be taken between third and fourth year must be Humanities/Social Sciences courses (see the Complementary Studies section at the beginning of this chapter). Students are responsible for ensuring that each elective taken is approved. Please consult the electives list available on the Engineering Office of the Registrar's website.
  4. Approval to register for the fourth-year thesis course (MIE498H1 or MIE498Y1) must be obtained from the Associate Chair - Undergraduate and is normally restricted to fourth year students with a cumulative grade point average of at least 2.7. A summer thesis course is also available.


MINORS

The Cross Disciplinary Programs Office (CDP) offers a variety of minors and certificate programs that complement the Industrial Engineering curriculum. Students interested in pursuing an Engineering minor and/or certificate are encouraged to consult with the CDP.


Courses not offered in 2025-2026

  • MIE509H1
  • MIE520H1

Industrial Engineering Courses

Applied Science and Engineering (Interdepartmental)

APS100H1 - Orientation to Engineering

APS106H1 - Fundamentals of Computer Programming

APS110H1 - Engineering Chemistry and Materials Science

APS111H1 - Engineering Strategies & Practice I

APS112H1 - Engineering Strategies & Practice II

APS360H1 - Applied Fundamentals of Deep Learning

APS490Y1 - Multi-Disciplinary Capstone Design

APS502H1 - Financial Engineering

Civil Engineering

CIV100H1 - Mechanics

Electrical and Computer Engineering

ECE110H1 - Electrical Fundamentals

Mathematics

MAT186H1 - Calculus I

MAT187H1 - Calculus II

MAT188H1 - Linear Algebra

MAT238H1 - Differential Equations and Discrete Math

Mechanical and Industrial Engineering

MIE100H1 - Dynamics

MIE191H1 - Seminar Course: Introduction to Mechanical and Industrial Engineering

MIE223H1 - Data Science

MIE236H1 - Probability

MIE237H1 - Statistics

MIE240H1 - Human Factors Engineering

MIE242H1 - Foundations of Cognitive Psychology

MIE245H1 - Data Structures and Algorithms

MIE250H1 - Fundamentals of Object Oriented Programming

MIE262H1 - Deterministic Operations Research

MIE263H1 - Stochastic Operations Research

MIE344H1 - Ergonomic Design of Information Systems

MIE345H1 - Case Studies in Human Factors and Ergonomics

MIE350H1 - Design and Analysis of Information Systems

MIE353H1 - Data Modelling

MIE354H1 - Business Process Engineering

MIE359H1 - Organization Design

MIE360H1 - Systems Modelling and Simulation

MIE363H1 - Operations and Supply Chain Management

MIE365H1 - Advanced Operations Research

MIE367H1 - Cases in Operations Research

MIE368H1 - Analytics in Action

MIE369H1 - Introduction to Artificial Intelligence

MIE370H1 - Introduction to Machine Learning

MIE424H1 - Optimization in Machine Learning

MIE434H1 - Industrial Ergonomics and the Workplace

MIE435H1 - *Early-stage design methods

MIE440H1 - * Design of Effective Products

MIE451H1 - Decision Support Systems

MIE457H1 - Knowledge Modelling and Management

MIE463H1 - Integrated System Design

MIE469H1 - Reliability and Maintainability Engineering

MIE490Y1 - Capstone Design

MIE498H1 - Research Thesis

MIE498Y1 - Research Thesis

MIE509H1 - AI for Social Good

MIE519H1 - * Advanced Manufacturing Technologies

MIE523H1 - Engineering Psychology and Human Performance

MIE524H1 - Data Mining

MIE535H1 - Electrification Via Electricity Markets

MIE542H1 - Human Factors Integration

MIE561H1 - Case Studies in Healthcare

MIE562H1 - Scheduling

MIE566H1 - Decision Making Under Uncertainty

MIE567H1 - Multi-agent Reinforcement Learning

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