Course Schedule and Descriptions

This fundamental course develops the conservation laws governing the motion of a continuum and applies the results to the case of Newtonian fluids, which leads to the Navier-Stokes equations. From these general equations, some theorems are derived from specific circumstances such as incompressible fluids or inviscid fluids. Basic solutions to, and properties of, the governing equations are explored for the case of viscous, but incompressible, fluids. Topics included involve exact solutions, low-Reynolds-number flows, and laminar boundary layers.

A continuation of MIE1201: Advanced Fluid Mechanics I in which basic solutions and properties of the governing equations are explored for ideal-fluid flow and for compressible fluid flow. Topics include two-dimensional and three-dimensional potential flows, surface waves, acoustics, shock waves, subsonic and supersonic flows.

Pre-requisites: MIE1201 or equivalent

Constitutive relations used to describe the non-Newtonian behaviour of complex liquids and the physical bases for the relations is emphasized. Particular topics include the flow of a generalized Newtonian fluid; rheology of suspensions; viscoelastic behaviour of polymer solutions; mechanical models for macromolecules in solution and the formulation of constitutive equations for dilute polymer solutions; network and reptation models for entangled polymer chains and constitutive equations for concentrated polymer solutions and melts.

This is a first level course in turbulent flows following an exposure to basic undergraduate fluid mechanics. It deals with the governing equations of motion, statistical representation of the turbulent field and describes fundamental shear flows such as jets, wakes and boundary layers. Emphasis is placed on the physical aspects of the motion.

Finite difference and finite element methods in fluid mechanics are presented, with particular emphasis on incompressible flows and flows involving heat transfer. A brief survey of numerical linear algebra is followed by a discussion of stability, accuracy and convergence criteria. Model elliptic, parabolic and hyperbolic problems are then considered. Solution of the Navier-Stokes and energy equations in the vorticity-stream function and primitive variable forms is presented. A working knowledge of a computer language is required.

The basic partial differential equations of material transport by fluid flow is derived along with the most significant analytical solutions of these equations, e.g., fully developed laminar flow and heat transfer in pipes and channels. Prediction of heat and mass transfer rates based on analytical and numerical solutions of the governing partial differential equations. Heat transfer in fully developed pipe and channel flow, laminar boundary layers, and turbulent boundary layers. Approximate models for turbulent flows. General introduction to heat transfer in complex flows. Discussion will be centered on boundary conditions for heat transfer, similarity and dimensionless parameters, and boundary layer approximations.

The purpose of this course is tor provide a basic understanding of multiphase flows. In particular, the dynamics of drops and bubbles in various flow conditions will be presented. The course will introduce the important parameters involved in analyzing multiphase flows. The equation of mass, momentum, and energy for such systems will be presented. These equations will be solved for specific conditions. Also, the methodology for solving more complex multiphase flow problems will be described.

In this course, we cover fundamentals of transport processes, microfabrication and integration techniquest that are relevant to micro and nanofluidic systems. Such systems have a variety of applications, including laboratories-on-a-chip for diagnostic applications, miniature chemical or power plants, or cell culture units. Discussed topics include: pressure and electrically driven fluid flow and transport in small confinements, bulk fabrication processes relevant to microfluidic systems, integration of sensors and imaging, separations, microscale cell culture systems, chemical microreactors. Scaling rules for microfluidic systems and world-to-chip interfaces between microsystems and conventional (analytical) equipment will be discussed.The course consists of a lecture combined with project work leading to a research proposal and its presentation contributed by the course participants

Pre-requisites: An undergraduate course in one (preferably two) of: Fluid Mechanics, Microfabrication or Analytical Chemistry

This course will cover the fundamentals of flow phenomena in porous media, including pore structure, porosity, permeability, anisotropy, capillarity, drainage/imbibition and diffusion. Single-phase flow and immiscible multiphase flow will be discussed, including saturation and relative permeability. Experimental and numerical techniques for material characterization, such as Fractal Dimension, will be covered. Selected numerical modelling techniques will also be included. Students will review and critique journal articles and conference papers. They will also work on a term project and will be encouraged to relate this assignment to their current research projects.

This course is designed to provide students with a comprehensive view of the fundamental concepts of wind power projects, from inception and economic viability to implementation and operation. Students will learn an appreciation for the main components of wind power systems. In addition, this course will cover the identification and quantification of the wind resource, numerical modelling and CFD techniques applied to wind power systems, wind turbine aerodynamics, design and performance, wind turbine noise, wind farm design and economic and environmental evaluation of wind projects. A final project will be undertaken involving specific technology developments in the wind industry and its potential impact on existing facilities.

The primary emphasis of the course is materials properties relevant for some clean energy conversion technologies. More specifically, some materials such as inorganic solids and semi-conductors that play key roles in clean electricity production technologies such as fuel cells, gas turbines, and solar cells will be the primary focus, with their ionic and electronic conduction mechanisms and their relevance being the major part of the technical content of the course. That information will be combined with some overview-level information of a few different technologies on a broad level.

Review of tensor notation; analysis of stress in a continuum including principal stress, invariants, spherical and deviator tensors; analysis of deformation and strain in a continuum including Lagrangian and Eulerian descriptions, spherical and deviator tensors, strain rate tensors and compatibility equations; equilibrium equations; constitutive relations for general linear solid, application to elastic, plastic and viscoelastic solids; anisotropic elasticity, orthotropic materials.

March 7 class in RS 211

This is a foundation course in the mechanics of cracked bodies. Both Airy´s stress function and Muskhelishvili´s complex potentials as well as the constitutive equations governing the elasto-plastic behaviour of flawed bodies will be examined. A detailed description of the analytical, numerical and experimental techniques adopted in the determination of Irwin´s stress intensity factor, Rice´s J-integral and Well´s COD will all be examined. Furthermore, the pertinent aspects of fatigue crack growth and the different fatigue design philosophies will be covered.

Pre-requisites: A strong background in the Theory of Elasticity and the Theory of Plasticity.

Manufacturing and design issues in foamed materials processing. Solution and diffusion of gas in polymers. Sorption experiments for determining the solubility and diffusivity. Plasticizing effect of gas in a polymer. Bubble nucleation theories. Processing strategies for the production of high nucleation density foams. Mathematical model of bubble growth. Processing strategies for the bubble growth control. Effect of melt strength on bubble coalescence. Continuous processing of microcellular foamed polymers.

Deals with the selection, analysis and design of load-bearing joints in metals, ceramics, plastics and composites. Consider welds (metal and plastic), rivets, threaded fasteners, adhesives, clamped joints, and various specialized methods of joining. These are examined with respect to stress analysis, manufacturing considerations, material selection, design applications, and cost.

Pre-requisites: Students must have taken at least one undergrad course in solid mechanics (two is recommended) and one course in machine design.

Introduction to CAD. Investigation and usage of the commercial software package, (I-DEAS). Design projects incorporating solid modeling, finite element analysis, animation as well as manufacturing aspects such as injection molding and NC machining will be undertaken. Introduction to design principles and theory. Axiomatic approach of N.P. Suh; the independence axiom, the information axiom, design matrix, design hierarchy and the mapping from functional to physical to process domains. Concurrent design, life cycle design.

This course will present established methods that aim to enhance creativity during conceptual design. In addition, current research relevant to creativity and conceptual design will be incorporated. Students will select current research conducted at a variety of international institutions, identify limitations of reported results, determine and perform further research that can be conducted within a course, and report results.Established creativity methods will be presented during lecture. Knowledge of this material will be evaluated through written examinations.Skills in identifying, planning, conducting and reporting relevant research will be evaluated through oral presentations and written reports.

The course will focus on the tribology of interacting solid surfaces in the dry or lightly lubricated state. Topics will include: surface microtopography, friction, wear, erosion, dry and marginally-lubricated contacts. Attention will also be paid to surface forces and issues related to tribology of micro-systems.

Smart materials are characterized by new and unique properties that can be altered in response to environmental stimuli. They can be used in a wide range of applications since they can exceed the current abilities of traditional materials especially in environments where conditions are constantly changing. This course is designed to provide an integrated introduction to smart materials and structures, and provide a strong foundation for further studies and research on these materials. Topics include: structure, processing, and properties of smart materials; dependence of properties on structure; processing and design; mechanical, thermal, electrical, magnetic and optical smart materials systems such as shape memory materials, electrostrictive materials, magnetostrictive materials, active polymers; design, modeling and applications of smart materials systems using CAD and FEA software packages.

This course is designed to provide graduate students advanced topics and case studies in multiphysics analysis in engineering materials in the context of continuum mechanics. This course provides a strong foundation for further studies/research applied in many areas such as development of adaptive and smart structures, biomaterials, electronic packaging, fuel cells, and other multidisciplinary fields of engineering. The course covers the most important issues related to material properties and modeling of mechanical, thermal, chemical, and electrical behavior and their couplings. The students will be introduced to the physical laws governing the sub-domains elasto-mechanics, heat balance, electrostatics, electrochemistry and their interactions. In addition, students will be introduced through projects to apply these concepts to engineering applications using COMSOL multiphysics software.

Starting with the analysis of simple discrete systems, the essential ideas of building up the governing equations of the system from those of its constituent parts is illustrated. The techniques of deriving a discrete set of equations for continuous systems are then outlined; specifically the variational and weighed residual procedures are examined and illustrated through some simple examples. The course then concentrates on applications to structural mechanics of solids. Programming for finite elements is also covered and students are encouraged to design and develop FEM software.

Pre-requisites: A strong background in PDEs, numerical analysis, and solid mechanics. Some knowledge of computer programming will be helpful.

This course covers the statistical analysis of data, featuring examples from various engineering fields. Topics will include: exploratory data analysis (graphical techniques, measures of location, scale, and association); basic probability (probability, random variables, and expectation); statistical inference (estimation and hypothesis testing); fundamentals of experimental design; regression analysis; the analysis of variance.

Thermodynamics and electrochemistry of fuel cell operation and testing; understanding of polarization curves and impedance spectroscopy; common fuel cell types, materials, components, and auxiliary systems; high and low temperature fuel cells and their applications in transportation and stationary power generation, including co-generation and combined heat and power systems; engineering system requirements resulting from basic fuel cell properties and characteristics.

This course takes a 360° perspective on product design: beginning at the market need, evolving this need into a concept, and optimizing the concept. Students will gain an understanding of the steps involved and the tools utilized in developing new products. The course will integrate both business and engineering concepts seamlessly through examples, case studies and a final project. Some of the business concepts covered include: identifying customer needs, project management and the economics of product design. The engineering design tools include: developing product specifications, concept generation, concept selection, FAST diagrams, orthogonal arrays, full and fractional factorials, noises, interactions, tolerance analysis and latitude studies. Specific emphasis will be placed on robust and tunable technology for product optimization and generating product families. Critical Parameters will be developed using the Voice of the Customer (VOC), FAST diagrams and a House of Quality (HOQ).

Pre-requisites: MIE231H1 F/MIE236H1 F or equivalent

Variational principles and Lagrange´s Equations, Hamilton´s principle. Kinematics of rigid body motion, Euler angles, rigid body equations of motion. Hamilton´s equations, cyclic coordinates, Legendre transformations. Canonical transformations, Hamilton-Jacobi theory.

Multi-degree of freedom systems, using both analytical and approximate methods. Vibrations of continuous systems, including strings, bars and membranes. Natural modes of plate vibration - approximate methods such as Rayleigh´s Energy Methods, Rayleigh-Ritz Method, Galerkin´s Method, and assumed mode method. Introduction to finite element analysis.

Non-linear systems. Mathematical pendulum. Duffing and Van der Pol Oscillators. Mathieu equation. Analytical and numerical solutions. Sub and super harmonics. Stability and bifurcation.

Pre-requisites: MIE1005H or equivalent

Robotic control problem formulation, advance dynamic formulation for control application, dynamic model formulations, linear, nonlinear, stability definitions, local and global stability methods, integration of manipulator dynamic equations of motion, differential-algebraic systems.

Pre-requisites: A background in Mechanisms and Vibrations

This course introduces some of the main concepts in nonlinear control systems design, with special emphasis on issues of practical relevance. The first part of the course is a review of basic stability analysis tools for nonlinear systems. The second part introduces a number of continuous time nonlinear controller design approaches, including controller design for systems with input and output nonlinearities, high gain controller design, passivity based controller design, and gain scheduling. The last part of the course covers the design of sampled data nonlinear controllers, which addresses the design of discrete time controllers for nonlinear continuous time systems.

This course introduces the design of intelligent robots – focusing on the principles and algorithms needed for robots to function in real world environments with people. Topics that will be covered include autonomy, social and rational intelligence, multi-modal sensing, biologically inspired and anthropomorphic robots, and human-robot interaction. Class discussions will centre on the interactive, personal, assistive and service robotics fields.

Pre-requisites: MIE404 and MIE444, or equivalent

This course will focus on the non-destructive testing and evaluation of structures by ultrasonics. Background topics will include methods of ultrasonic signal generation, various modes of sound propagation in isotropic and non-isotropic materials, behaviour of sound at material discontinuities and signal processing.

The course will focus on the integration of facilities (machine tools, robotics) and the automation protocols required in the implementation of computer integrated manufacturing. Specific concepts addressed include flexible manufacturing systems (FMS); interfaces between computer aided design and computer aided manufacturing systems.

Pre-requisites: At least one manufacturing course during U/G studies. Else, subject to instructor's permission.

This course provides students with analytical tools to design, model, analyze and control mechatronic systems. The class deals with properties of linear and nonlinear systems, system identification methods, parametric and non-parametric techniques for the analysis and estimation of stationary and non-stationary signals, and design of filters with applications to Mechatronic systems. The class also provides techniques for the modeling of various system components into a unified approach and tools for the simulation of the performance of these systems.The instructor will not use laboratory or computer facilities during the allocated lecture time but will require the students to work on projects and homework assignments by using the software package Matlab. Matlab is currently available on the ECF network.

This course will present the fundamental basis of microelectromechanical systems (MEMS). Topics will include: micromachining/microfabrication techniques, micro sensing and actuation principles and design, MEMS modeling and simulation, and device characterization and packaging. Students will be required to complete a MEMS design term project, including design modeling, simulation, microfabrication process design, and photolithographic mask layout

Pre-requisites: MIE222H1S, MIE342H1F

A course in which the postulatory approach is used to develop the theory of thermodynamics. The postulates are stated in terms of a variational principle that allows them to be applied to systems subjected to fields, to phase transitions, and to systems in which surface effects are dominant. The thermodynamic stability of systems is examined and examples of stable, metastable and unstable systems are discussed.

Pre-requisites: Undergraduate thermodynamics

Thermodynamics is reviewed. Quantum mechanics is introduced and used to define the possible microscopic states of macroscopic systems. For macroscopic systems in thermodynamic equilibrium, the concept of ensemble averages is introduced and the postulates of statistical mechanics are used to calculate their thermodynamic properties from knowledge of their molecular nature. Entropy is interpreted in terms of quantum mechanical concepts. The thermal properties of solids, of gases adsorbed on solid surfaces, of electrons in solids, of radiation, and of ideal gases are studied.

Pre-requisites: MIE 1101H, Advanced Classical Thermodynamics, or equivalent

Statistical thermodynamics is reviewed. The concept of quantum mechanical transition probabilities is applied to develop a theory of kinetics, called Statistical Rate Theory. One postulate is added to those of statistical mechanics in order to formulate the theory. The objective of Statistical Rate Theory is to predict the rate of processes in terms of the equilibrium or material properties of the system. The theory is applied to predict the rate of simple chemical reactions, the rate of gas adsorption on well defined solid surfaces, and the rate of liquid evaporation.

Pre-requisites: MIE 1101H, Advanced Classical Thermodynamics, and MIE1107H, Statistical Thermodynamics, or equivalent

Formulation of the equation of conduction, initial and boundary conditions. Solutions of one-two and three- dimensional problems. Transient systems; heating and cooling. Extended surfaces; fins and spines. Heat conduction in porous systems. Steady and transient numerical methods.

Homogeneous and heterogeneous nucleation and bubble growth. Thermodynamic equilibrium and stability during phase change. Pool Boiling. Flow patterns. Models of two-phase flow. Heat transfer in flow boiling. Condensation.

This course will cover the fundamentals of thermal plasmas: Introduction to thermal plasma processing; plasma generation, arcs, radio frequency (rf) inductively coupled plasmas, microwave (mw) plasmas; theory of the equilibrium plasma, the Ellenbas-Heller equation for the electric arcs, theory of rf and mw plasmas, ambipolar diffusion; two- temperature plasma model; heat transport processes in thermal plasmas, heating and melting of powders in thermal plasmas, particle trajectory and heating history.

Analysis of the various processes occurring in internal combustion engines. Thermodynamic analysis will be conducted using gas cycles and fuel-air cycles and the results compared to actual engine cycles. The influence of air, fuel and exhaust flows, heat and mass loss, and friction is considered. The combustion process is examined, especially its influence on exhaust emissions.

This course will deal with the basic theory of combustion in the steady state, with consideration of theories of flame propagation, flame stabilization, limits of inflammability, ignition, quenching, etc., and discussion will include both laminar and premixed flames, diffusion flames, flames and detonation.

This course will develop a mathematical framework for treating a variety of inter-disciplinary diffusion-related periodic phenomena. The fundamental properties of diffusion-wave fields will be discussed and Green functions will be derived as building blocks for the presentation of case studies directly applicable in a wide range of experimental methodologies in such areas as heat transfer, electrical conduction and light scattering. The course is intended for students and researchers in fields that involve non-destructive evaluation with thermal waves, semiconductor and electronic device carrier plasma waves, and biomedical laser tissue diffuse photon density wave diagnostics. The selection of topics each time the course is given will reflect the interests of the class. Some familiarity with analytical techniques at the level of MIE 1801 or equivalent is highly recommended.

Pre-requisites: MIE1801

Engineering Applications of Sound, Electromagnetic, Thermal and Photonic Waves: The course describes basic characteristics of sound, electromagnetic, photonic and thermal waves and their applications for engineers. Course material will include properties of wave propagation, electromagnetic spectrum, photons, as well as applications of sound waves, light (optical fiber - based technologies), lasers, X-rays and thermal waves in engineering.

Reactor Physics and the Nuclear Fuel Cycle - This course covers the basic principles of the neutronic design and analysis of nuclear power reactors. Topics include radioactivity, neutron interactions with matter, the fission chain reaction, nuclear reactors, neutron diffusion and moderation, the critical reactor equation, nuclear reactor fuels, nuclear fuel cycle and economics, nuclear waste management and non-proliferation.

Thermal and Mechanical Design of Nuclear Power Reactors - This course covers the basic principles of the thermo-mechanical design and analysis of nuclear power reactors. Topics include reactor heat generation and removal, nuclear materials, diffusion of heat in fuel elements, thermal and mechanical stresses in fuel and reactor components, single-phase and two-phase fluid mechanics and heat transport in nuclear reactors, and core thermo-mechanical design.

This course provides fundamentals and applications for thermal and hydraulic design of heat exchangers. It covers a wide range of relevant topics including the main considerations for equipment selection and design, and different methods of analysis for performance (rating) and sizing. More specialized design considerations such as flow-induced vibration are also introduced. The objective is for students to become familiar with the design and specification of industrial heat exchangers by solving practical problems using a synthesis of other mechanical engineering subjects such as thermodynamics, heat transfer, and fluid mechanics.

Principles of biomedical photoacoustics and biothermophotonics for tissue imaging applications. Spectroscopic properties of tissue and blood. Introduction to laser and photon-density-wave propagation in turbid media, pulsed laser and frequency-domain photoacoustic and photothermal wave generation mechanisms in tissues, detection schemes and engineering of diagnostic instrumentation focused on high-contrast, high-resolution sub-surface imaging (e.g. deep-seated breast tumors). Case studies from the international biomedical photoacoustics and thermophotonics literature with special focus on the diagnostics of cancerous lesions.Students will use course-derived knowledge of methods and the existing field literature to formulate, discuss and report possible scientific and/or engineering approaches / solutions to a topic among a selection of current biomedical problems suggested by the instructor.

Variational Calculus: introduction to calculus of variations; Euler-Lagrange equation; extensions to several variables; constrained extremals; methods of approximation. Integral Equations: their classification; series solution; boundary integral equations; delta function responses, Green´s functions, approximate techniques. Linear and Nonlinear Systems: phase space; chaos; differential algebraic systems; dynamic systems.

The course introduces descriptions of computational techniques for solving engineering problems using MATLAB software. Analytical and numerical methods applied for solving differential equations are briefly described. The MATLAB programming environment and techniques are studied along with visualization and animation techniques. The course topics include but are not limited to: solutions of ordinary and partial differential equations in one and two dimensions, data fitting, numerical integration, and random systems. Students will be required to solve problems using MATLAB programming techniques. Basic programming skills and knowledge of differential equations are highly desirable.

This courses covers the basic principles and design of selected alternative energy systems. Systems discussed include solar thermal systems, solar photovoltaic, wind technology, fuel cells, and energy storage.

Pre-requisites: MIE210H, MIE312H and some knowledge of chemistry, or equivalent courses

Introduction to combustion theory. Chemical equilibrium and the products of combustion. Combustion kinetics and types of combustion. Pollutant formation. Design of combustion systems for gaseous, liquid and solid fuels. The use of alternative fuels (hydrogen, biofuels, etc.) and their effect on combustion systems.

The course deals with practical problems associated with the design of experiments in Human Factors research, with an emphasis on the use of statistical packages and data analysis tools. Topics covered will include analysis of variance, non- parametric statistics, balanced and unbalanced block designs (including Latin squares), confidence intervals, etc. Stress is given to practical problems and the intuitive understanding of applied statistics.

This course is intended for people carrying out graduate level research in Human Factors. It covers a variety of techniques for recording and analyzing empirical data. Topics to be covered include psychophysical methods, subjective scaling, questionnaires, signal detection theory, information theory, physiological monitoring, spectral analysis, tracking, and manual control modeling. There is no textbook for the course. Evaluation is based on a series of assignments related to the topics covered in class.

This course deals with the cognitive engineering of complex sociotechnical systems, such as nuclear power plants. The focus will be on describing and applying various tools for analyzing complex work environments, to uncover the information required for making design decisions. The goal of the course is to provide students with an awareness of the unique human factors challenges posed by sociotechnical systems, and of the types of methods that are required to deal with such problems.

Pre-requisites: MIE1409 and MIE1407 or permission from instructor

This course will be held in conjunction with the undergraduate course MIE448H; graduate students will follow the same curriculum of lectures and laboratory exercises and will write the same tests and examinations. Graduate candidates in this course will, however, be expected to write up their laboratory reports on their own and more extensively than the undergraduates. An additional project will be assigned, requiring exploration in depth of a selected topic.

The course will focus on how to design computer-based interfaces for complex human-machine systems. An ecological approach will be adopted, pointing to the importance of understanding the structure of the work environment and then trying to present that information in a way that takes advantage of human perceptual systems. Various design techniques for enhancing the informativeness of interfaces will be discussed within the context of several design applications. (Held in conjunction with the undergraduate course MIE449H).

Introduction to ergonomics in industrial settings. Biomechanics related to manual materials handling, repetitive strain injuries, visual and auditory limitations, human information processing and short term memory limitations, psychomotor skill, anthropometry and workspace layout, population stereotypes, design of controls and displays, circadian rhythms and design of shift work schedules. Exclusions: MIE240H or MIE343H.

A survey of theoretical and applied issues in human interaction with automation. Topics included are: philosophy of human-machine systems, types and levels of automation, models of human-automation interaction, function allocation, mode error, bias, trust, workload and situation awareness, automation interfaces, decision-aiding, adaptable and adaptive (intelligent) automation, supervisory control, and management of human-automation systems

Pre-requisites: MIE1403 or MIE1409

This course covers various statistical models used in empirical research, in particular human factors research, including linear regression, mixed linear models, non-parametric models, generalized linear models, time series modeling, and cluster analysis. For various observational and experimental data, students will be proficient in generating relevant hypotheses to answer research questions, selecting and building appropriate statistical models, and effectively communicating these results through interpretation and presentation of results. Basic knowledge in probability, statistics, and experimental design is required. The course will not focus on the design of experiments. In addition to homework assignments and exams, the students will review and critique journal articles and conference papers for the validity of the use of various statistical models. The students will work on a term long project of their choice and will be encouraged to relate this assignment to their current research projects. The examples used in class and the assignments will be drawn from human factors research. However, the students will not be required to use human factors data for their project.

The course will cover a wide range of human factors topics related to transportation, in particular motor vehicle transportation. The students will gain an understanding of road user characteristics and limitations and how these affect design of traffic control devices and the roadway. The course topics include: history and scope of human factors in transportation; vision and information processing in the context of driving; driver adaptation; driver education, driver licensing and regulation; traffic control devices; crash types, causes, and countermeasures; alcohol, drug, and fatigue effects; forensic human factors.

The course will be taught in the form of lectures followed by relevant case studies involving practical application of knowledge gained. Case studies, and related assigned readings, will involve human factors in relation to crash pattern analysis and countermeasure selection, highway and traffic control design issues, driver regulation policy issues, and forensic investigation. The students will work on two projects, one in each half of the term, on topics of their choice. They will be asked to make presentations on these projects.

The integration of human factors into engineering projects. Human factors integration (HFI) process and systems constraints, HFI tools, and HFI best practices. Modelling, economics, and communication of HFI problems. Examples of HFI drawn from energy, healthcare, military, and software systems. Application of HFI theory and methods to a capstone design project, including HFI problem specification, concept generation, and selection through an iterative and open-ended design process.

Information Engineering focuses on the representation and use of information in the context of the web. The first part of the course covers the Semantic Web, including XML, RDF, Linked Data, Provenance, Trust and Data Mashup. The second part covers web-based Knowledge Representations, including: Description Logic, OWL, SWRL, and Ontologies.

This course will explore the use of data and knowledge representation concepts in the creation of generic, reusable and common-sense models of industrial enterprises. From the domain direction, we will review and unify existing reference model efforts that provide a taxonomy of terms that span many of the functions of an industrial enterprise. From the generic direction, we will review Artificial Intelligence common-sense modeling concepts of activity, resources, constraints, etc. as a basis for providing upper levels of the taxonomy.

Pre-requisites: MIE1501

This course will explore theoretical techniques for the design and analysis of formal ontologies. Topics will include the design of verified ontologies, methodologies for proving properties about ontologies, and applications of classification theorems from mathematics. These techniques will be applied to ontologies that are currently being used in government and industry.

Pre-requisites: MIE457 and MIE1501

This course is a research seminar that focuses on recent developments in the area of XML Retrieval. With the increasing use of XML data to represent information in the Web and within and across organizations, there is a growing need for Information Engineers that are knowledgeable of the systems and the processes that manage and retrieve XML information. This seminar will provide an overview of the different issues and approaches put forward by the Database and Information Retrieval communities, covering both the problem space (basic concepts, requirements, and models) and the solution space (approaches, and techniques). The evaluation will be based on course presentations and a project. The project will focus on developing and/or evaluating techniques applicable in the context of the INEX (Initiative for the Evaluation on XML Retrieval) project, with the goal of producing publishable research contributions.

Branch and bound, implicit enumeration, cutting planes, all integer tableau methods, quadratic 0-1 algorithms, commercial software, Benders´ decomposition, Lagrangian relaxation, column generation, several practical applications from the literature.

Pre-requisites: MIE262, APS1005 or equivalent

A course on the fundamentals of stochastic processes and their application to mathematical models in operational research. Topics discussed will include a review of probability theory, Poisson processes, renewal processes, Markov chains and other advanced processes. Emphasis on applications in inventory, queuing, reliability, repair and maintenance, etc.

Pre-requisites: MIE231 and MIE365, or permission from instructor

A course in queuing theory, emphasizing general methods in the study of Markovian and non-Markovian systems, tandem queues, networks of queues, priority and bulk queues. Current research and applications in Operational Research and Industrial Engineering.

Pre-requisites: MIE1605 or equivalent, and permission from the Instructor

A course in renewal theory, Markov renewal theory, regenerative and semi-regenerative processes, Markov and semi-Markov processes and decision processes with emphasis on applications in production/inventory control, maintenance, communication systems, flexible manufacturing systems.

Pre-requisites: MIE1605 or permission from Instructor

This course presents selected topics in single agent multiple criteria decision making such as Pareto optimality, multi-objective simplex method, interactive articulation of preferences and goal programming. It also presents current work in multi agent decision making such as Nash equilibrium and Cournot solutions. It also contrasts the variational inequality approach with complementary programming approach, illustrates the use of agents to reduce risk and describes the application to industries such as electricity and telecom. In addition two new modelling paradigms, Mathematical Programming with Equilibrium Constraints (MPEC) and Equilibrium Programming with Equilibrium Constraints (EPEC), will be discussed with solution procedures.

Pre-requisites: Strong background in Operations Research and permission from the Instructor

This course will cover the modeling of basic and complex systems using discrete event simulation software, and related statistical methods for selecting input probability distributions, generating random variates, and making statistical inferences from simulation results. Topics will include variance-reduction techniques, experimental design and the application of optimization techniques to simulation models. Exclusion: MIE360 or equivalent. General Level Course.

This is a course on stochastic dynamic programming with an emphasis on infinite horizon Markov decision processes. The approach will include basic concepts in optimization theories in linear vector space, different types of optimality criteria, solution techniques, and approximation approaches.

Pre-requisites: Permission of Instructor

This course reviews a wide variety of methodologies in the healthcare sector. Although many of the problems of O.R. in healthcare are analytically similar to problems in other industries, many others are quite unique due to certain characteristics of the healthcare systems. For example, the possibility of death, quality of life, difficulty of measuring quality and value of outcomes, multiple decision makers (doctors, nurses, patients, administrators), and the concept of access to healthcare as a right. We consider strategic problems of system design and planning (large allocation decisions), operational and tactical problems of management, monitoring and control methodologies; and medical management involving disease detection and treatment models.

Pre-requisites: Intro to Operations Research (deterministic and stochastic)

Heuristic search, constraint propagation, retraction techniques, tabu search, simulated annealing, genetic algorithms, iterated local search, hybrid optimization. The course will emphasize algorithms and empirical analysis while using scheduling as a specific application area to explore the solution techniques.

Pre-requisites: MASc/PhD or permission of the instructor

Rigorous introduction to the theory of linear programming. Simplex method, revised simplex method, duality, dual simplex method. Post-optimality analysis. Interior point methods. Decomposition methods. Network flow algorithms. Maximum flow, shortest path, assignment, min cost flow problems.

Pre-requisites: MIE262, APS1005 or equivalent

Theory and computational methods of non-linear optimization. Convex sets, convex and concave functions. Unconstrained and Constrained Optimization. Quadratic Programming. Optimality conditions and convergence results. Karush-Kuhn-Tucker conditions. Introduction to penalty and barrier methods. Duality in nonlinear programming.

Pre-requisites: MIE262, APS1005 or equivalent

Healthcare Operations Management
The objective of this course is to provide advanced research training to doctoral students in the area of healthcare operations management. To this end, the course is focused on the design and improvement of healthcare processes and facility networks. An initial segment of the course will be devoted to a review of fundamental queueing models and their applications healthcare. The use of empirical methods in healthcare operations management will also be discussed. Building on this methodology framework, the course will then focus on the phases of the healthcare continuum, highlighting the differentiating characteristics of each phase. In particular, the design and improvement of preventive care, ambulance services, emergency care, acute care and chronic care systems will be studied. The lectures will be grounded in the care practices for several medical conditions including stroke and breast cancer.

The goal of the course is to introduce students to principles of reliability from a practical point of view. The course covers principles of quality, principles of reliability, reliability of systems, failure rate data and models, quality and reliability in design and manufacturing, and reliability and availability in maintenance including cost models. Some other topics could be covered, depending on timing. A moderate knowledge of probability and statistics is a requirement.

Pre-requisites: Any second year engineering or higher level course in probability and statistics

Determination of optimal maintenance and replacement practices for components and capital equipment; resources of manpower and machinery required for implementation of maintenance practices; and the use of mathematical models in the development of a maintenance information system. The lectures will be supplemented by case study assignments: E.g., Short-term deterministic replacement; Short-term probabilistic replacement; OREST, PERDEC, AGE/CON, SMS and EXAKT programs.

Awareness of the importance of quality has increased dramatically. Continuous quality improvement is a key factor leading to company´s success and an enhanced competitive position. The course covers the following topics in Quality Assurance: Introduction to quality engineering. Loss function. Quality standards: ISO 9000 and QS 9000. TQM. Quality cost analysis. Process modeling and hypothesis testing. Statistical process control for long and short production runs. Process capability analysis. Capability indexes. Fitting the distribution. Elements of the likelihood theory. Weibull analysis. Six sigma quality. An overview of the quality standards in acceptance sampling.

MIE561 is a “cap-stone” course. Its purpose is to give students an opportunity to integrate the Industrial Engineering tools learned in previous courses by applying them to real world problems. While the specific focus of the case studies used to illustrate the application of Industrial Engineering will be the Canadian health care system, the approach to problem solving adopted in this course will be applicable to any setting. This course will provide a framework for identifying and resolving problems in a complex, unstructured decision-making environment. It will give students the opportunity to apply a problem identification framework through real world case studies. The case studies will involve people from the health care industry bringing current practical problems to the class. Students work in small groups preparing a feasibility study discussing potential approaches. Although the course is directed at Industrial Engineering fourth year and graduate students, it does not assume specific previous knowledge, and the course is open to students in other disciplines.

This course takes a practical approach to scheduling problems and solution techniques, motivating the different mathematical definitions of scheduling with real world scheduling systems and problems. Topics covered include: job shop scheduling, timetabling, project scheduling, and the variety of solution approaches including constraint programming, local search, heuristics, and dispatch rules. Also covered will be information engineering aspects of building scheduling systems for real world problems.

Pre-requisites: MIE262

The purpose of this course is to provide a working knowledge of methods of analysis of problems and of decision making in the face of uncertainty. Topics include decision trees, subjective probability assessment, multi-attribute utility approaches, goal programming, Analytic Hierarchy Process and the psychology of decision making.

Pre-requisites: MIE231/MIE236 or equivalent

This course will focus on capital budgeting, financial optimization, and project evaluation models and their solution techniques. In particular, linear, non-linear, and integer programming models and their solutions techniques will be studied. The course will give engineering students a background in modern capital budgeting and financial techniques that are relevant in practical engineering and commercial settings

Pre-requisites: Linear Algebra, Probability and Statistics, Calculus at the undergraduate level

This course is designed for people with an interest in continuing education and teaching in the engineering workplace. The course content is applicable to the development of courses, training programs, or the development of documentation such as instructions. Basic concepts in adult learning and current research in professional education will be introduced and discussed. Students will be required to develop training and teaching materials. By the end of the course, students should have an understanding of the important ideas that currently inform the practice of professional education and have experience applying these ideas to the development of instructional documents. Exclusion: MIE 3002H.

This course introduces optimization techniques applicable in solving various engineering programs. These techniques are widely used in engineering design, optimal control, production planning, reliability engineering, and operations management. The contents of this course can be classified into two major categories: modeling techniques and Optimization algorithms. Topics include linear programming, sensitivity analysis, nonlinear programming, dynamic programming, decision making under uncertainty, new developments in optimization techniques. The course will also examine several case studies to gain understanding of real applications of optimization techniques.

Pre-requisites: none. Exclusions: Previous course in Operations Research (OR) equivalent to MIE262.

This course will provide students with the core concepts of innovation including: strategic thinking, transformational change management, innovative enterprise design & development, and sustaining a culture of innovation. This seminar style course will equip students with the knowledge and the skills to manage innovation at strategic and operational levels. The management of innovation is interdisciplinary and multi-functional, requiring the international alignment of market forces, technological systems and organizational change to improve the competitiveness and effectiveness of organizations and society. We shall argue that the process of innovation management is essentially generic, although organization, technological and market specific factors will constrain choices and actions. This course will incorporate both academic readings to provide the broad theory of innovation, but most of the readings and discussion will be based on the instructor´s many years of hands on practical experience in innovation in a variety of industry sectors.

This course will teach students the application of the tools and techniques of innovation management including: strategic and systems thinking, business process management, creativity and problem solving, solution design & implementation, effective organizational teamwork and project management. This seminar style course aims to equip students with the knowledge and skills to apply the tools of creativity and innovation to solve a real world technological business problem. Applying innovation will enable students in a team approach to actually use the tools in the class and on an industrial project either at their employer (preferably) or an external enterprise. This course will also incorporate both academic scholarly papers that will build on the readings in the Management of Innovation APS1012 course. In addition the instructor will provide coaching based on many years of hands on practical experience solving technological problems in a variety of industry sectors. Though not mandatory it would be ideal if students have completed the course APS1012 - Management of Innovation in Engineering - that provides students with a conceptual understanding of the broad field of strategic innovation.

Interested students must attend the first class

This course builds upon the concepts presented in APS 1001H - Project Management, to provide students with practical knowledge and application of the most critical elements for project success.

The course is split into two parts:

The first half examines the project lifecycle, to provide students with a roadmap of when certain concepts are applicable, and to which level of detail. Each class will consist of a review of applicable concepts, an in-depth look at some key elements and how they are applied (including tools and approaches), and a discussion involving real-life examples.

The second half of the course focuses on advanced concepts not covered in detail in APS 1001H. These include change management, troubled projects and premature termination, program management, and advanced skill sets for project managers.

Pre-requisites: APS 1001H

This course is designed for engineering students interested in starting a business venture that advances social and/or environmental good. The course provides students with as real a “social entrepreneurship” experience as is possible within a course setting – students will, independently or in groups, construct a Business Model for their entrepreneurial idea, and will pitch their model to a panel of Angel investors. Most lectures will run workshop-style: industry experts (in social marketing, social finance, HR, law and other fields), along with real social entrepreneurs, will work one-on-one with students to help refine their business models in preparation for the investment pitch. Other lectures, along with course readings, will focus on understanding the field of social entrepreneurship, with a particular emphasis on topics relevant to engineering such as clean tech commercialization and the growing field of “impact investing”.

The students will be exposed to classical equity valuation methods, such as discounted cash flow analysis, net asset value, fundamental analysis and relative value analysis, using measures such as P/E multiples and P/Cash flow multiples. The students will be introduced to the principles of Bond and Stock valuations with a special emphasis on its relation to the cost of capital. The course will take an in depth view of capital budgeting, capital investment decisions and project analysis and evaluations. It will introduce students to the concept risk and return in equity markets. The students will get hands on experience in calculating cost of capital and hence the appropriate discount rate to use in valuations. Theory of optimal capital structure and financial leverage will be discussed in addition to economic value added principles. The relevance of dividends and dividend policy will be debated in class. The concept of “does dividend policy matter" will be subject of a vigorous debate. Finally the topic of mergers and acquisitions will be covered in depth, with particular reference to recent mergers of Canadian companies.

The students will be exposed to classical equity valuation methods, such as discounted cash flow analysis, net asset value, fundamental analysis and relative value analysis, using measures such as P/E multiples and P/Cash flow multiples. The students will be introduced to the principles of Bond and Stock valuations with a special emphasis on its relation to the cost of capital. The course will take an in depth view of capital budgeting, capital investment decisions and project analysis and evaluations. It will introduce students to the concept risk and return in equity markets. The students will get hands on experience in calculating cost of capital and hence the appropriate discount rate to use in valuations. Theory of optimal capital structure and financial leverage will be discussed in addition to economic value added principles. The relevance of dividends and dividend policy will be debated in class. The concept of “does dividend policy matter" will be subject of a vigorous debate. Finally the topic of mergers and acquisitions will be covered in depth, with particular reference to recent mergers of Canadian companies.

This course is to provide students with a framework for understanding the defining supply chain systems while developing an understanding of the complexity, opportunities, and pit-falls of management issues regarding these systems. Topics will include inventory theories, transportation, postponement strategies, supply chain dynamics, value of information, supply chain flexibility, and risk management. We will focus on the analytical decision support tools (both models and applications) as well as on the organizational models that successfully allow companies to develop, implement and sustain supplier management and collaborative strategies.

Pre-requisites: one or two undergrad courses on probability and statistics

This course will examine the integration of sustainable development issues (including climate change) into current engineering practice, and show how the incorporation of the associated ideas is bringing resource, ecological, and social issues into the mainstream of engineering design. Course discussions and presentations will include methods for evaluating the sustainability of projects; the selection of appropriate project goals considering issues of regulation, measurement, and stakeholder involvement; global perspectives and the effects of differing international priorities; and conflicts between responsibility and innovation, ethics and practice. Students will develop a thorough understanding of sustainability in engineering as it is currently practiced, and the challenges and opportunities that societal issues present to the profession. The course will be delivered as a mix of presentations, workshops and discussions.

Students may take only one reading course for credit in a degree program, unless special authorization has been granted by the Graduate Studies Committee.

Students may take only one reading course for credit in a degree program, unless special authorization has been granted by the Graduate Studies Committee.

Students may take only one reading course for credit in a degree program, unless special authorization has been granted by the Graduate Studies Committee.

Students may take only one reading course for credit in a degree program, unless special authorization has been granted by the Graduate Studies Committee.