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The Bachelor of Science in Industrial Engineering degree requires a total of minimum 125 credit hours and a minimum cumulative grade point average (CGPA) of at least 2.00.

  • Engineering Courses (53 credit hours):
  • Technical Electives (TE) (15 credit hours): See section Technical Elective Program for Industrial Engineering Students for details on TE program.
  • Mathematics and Science Requirement (32 credit hours): MA 165, MA 166, MA 261, MA 265, MA 266, CHM 115, CS 159, PHYS 172 and PHYS 241.
  • Liberal Arts Requirement (25 credit hours):
    • English Language and Communication Skills (10 credit hours): ENGL 100, ENGL 106 and COM 114.
    • General Education Requirement (15 credit hours): Students must satisfy the requirements of the General Education as per the following conditions:
      1. Courses must be drawn from the following General Education areas at AUM: Speech and Communication, English Language and Literature, History, Fine Arts, Physical Education, Self-Development and Life Style, Culinary Arts, Ethics, Social Sciences, Psychological Sciences, Natural Sciences, Child Development and Family Studies, Economics and Philosophy (please refer to Course Catalogue, General Education section).
      2. In order to ensure sufficient exposure to General Education topics, unless otherwise specified by the degree requirements of the academic major, the student cannot take more than 2 courses from the same area/sub-area as, as shown in tables below:
      3.  

        Area Maximum Courses to Take
        English Language and Literature 2
        History 2
        Physical Education 2
        Culinary Arts 2
        Ethics 2
        Psychological Sciences 2
        Natural Sciences 2
        Child Development and Family Studies 2
        Economics 2
        Philosophy 2
        Area Sub-Area Maximum Courses to Take
        Fine Arts Arts and Design 2
        Theatre 2
        Music 2
        Fashion and Apparel Design 2
        Photography and Media 2
        Self-Development and Life Style       Academic and Career Skills Development 2
        Character and Leadership Skills Development 2
        Life Management Development 2
        Development of Thinking Skills 2
        Technology and Innovation 2

         

      4. Courses that are already required under other category General Education requirement:
        1. cannot be considered as a General Education course;
        2. do not count towards the 2-course limit in General Education requirement.
Technical Elective Program for Industrial Engineering Students

In general, a technical elective is a course that develops new professional skills and/or builds upon previously obtained skills. Courses must focus on the development of skills in engineering, mathematics, business, or selected natural or social sciences.

Students are encouraged to treat the selection of technical elective courses in a structured way. Strategies for choosing technical elective courses are provided below in subsection (Developing a Coherent Curriculum Plan). Students are encouraged to select technical elective courses based on their career objectives.

Technical Elective Requirements (TE)

The following requirements are specified for the technical elective program. These are the most basic requirements. Each IE student is required to take 15 credit hours of technical electives to complete their degree requirements. Every course taken as a technical elective must be taken for a letter grade.

1. IE Courses

Students are required to complete at least 6 of the 15 required technical elective credit hours with courses originated by the IE department. These courses are referred to as IE technical electives. There are additional guidelines as follows:

  1. IE 500 level courses;
  2. IE 490 courses; any course with this listing must have special approval by the IE Department to be considered for technical elective credit.
  3. IE 499 (Reserved for Engineering Honors students; up to 6 credit hours).
  4. IE 495 (Reserved for Co-Op / internship students (if any); student must complete 3 semesters to earn TE credit)
  5. IE 600 level courses; these require permission of instructor and the IE Department. Students must have a cumulative GPA of 3.2 or higher.

Students are encouraged to consult the list of pre-approved technical electives contained in the “Emphasis Area” section below.

2. Non-IE courses

Students in IE are encouraged to choose technical elective courses from outside the department if such courses align with their career goals. Each IE student has the option to take up to 9 credit hours of non-IE courses to complete the technical elective requirements.   The general criteria for non-IE courses that may be considered for TE credit are provided below. Approval of TE course falls under IE Department.

  1. 300-level or higher course taken in any other engineering major that are not duplicates of IE courses.
  2. PHYS courses at a level higher than PHYS 241
  3. CHM courses at a level higher than CHM 116
  4. MA courses more advanced than MA 301
Developing a Coherent Curriculum Plan

Each student in the Industrial Engineering program should strive to create a plan for their education that maximizes the opportunities available to them as AUM students. AUM offers a number of courses that count towards their elective requirements. Elective courses (regardless of their classification) should not be considered “space-filling” courses. Each course taken can be selected to fulfill a desire to obtain a specific skill-set, and/or satisfy a desire for non-career related interests. In many cases, a series of elective courses can be selected to satisfy special interests.

Selecting electives according to a coherent plan is always preferred compared with a random selection of courses. There are many ways to develop a coherent plan, an example is given in the subsection “emphasis areas” Alternative approaches should be discussed with the student’s academic advisor. Students should have a clear direction in mind (e.g., career goal) to allow the academic advisor to provide greater assistance in selecting potential courses.

Emphasis Areas

The IE program is developing several “emphasis areas” you may use to enhance your curriculum and guide your course selection decisions. Most of these emphasis areas focus on the usage of technical elective courses. Other emphasis areas may involve taking general education courses in conjunction with technical electives. Current emphasis areas include the following:

  • Human Factors
  • Financial Engineering
  • Operations Research
  • Production and Management Systems

Note that some of the emphasis areas correspond to core areas of the current IE curriculum. Students may choose to increase their knowledge of a core area with their technical (and general education) electives. The details contained are focused on developing skills necessary for each emphasis area and provides a listing of courses that provide the necessary skills, or build upon skills developed in the core IE curriculum.

Each emphasis area is strictly meant to be a guide for students when selecting courses (and potential career paths). No record of you completing the “requirements” of an emphasis area will be noted on your final transcript. However, some pursuing an emphasis area may result in a student completing the requirements for a minor, if offered.

1. Human Factors Emphasis Area

The field of Human Factors in Industrial Engineering focuses on the design of tools, machines, systems, tasks, jobs and environments for safe, comfortable and effective human involvement and interaction. The field is characterized by the systematic application of knowledge about sensory, perceptual, mental and psychomotor characteristics. Industrial engineers with a Human Factors background are better able to create designs that take into account human abilities and limitations, both physical and cognitive. Physical applications include the design of working environments that are safe and comfortable taking into consideration typical as well as handicapped physical human characteristics. Cognitive applications take into account the ways humans perceive, understand, and react to stimuli – and work to support safe, efficient, and expedient responses. Designs by Human Factors engineers aim to enhance operational use while simultaneously improving the quality of working life. Human Factors expertise is desired in industries requiring frequent interactions between humans and systems, such as the transportation, manufacturing, and healthcare industries. Example applications include laying out effective computerized information displays for doctors in operating rooms, designing ways that handicapped individuals can productively operate vehicles, determining mechanisms to keep workers safe in machining operations, and creating software logic to determine if drivers are impaired – and then processes to safely override impaired drivers’ actions.

Human Factors specialists have extensive knowledge of:

  • Human perception and cognition
  • Physical and physiological characteristics of humans
  • Human computer interaction
  • Ergonomics (study of work processes)

Human Factors specialists have effective technical skills in:

  • Work measurement
  • Job and task design and analysis
  • Modeling and problem-solving
  • Design of experiments

Courses

Courses taken from the following groupings help to provide students with a deeper understanding of human factors. The courses listed below are listed in Course Catalogue. They are meant to provide guidance as to what a student might take if they are interested in this emphasis area. The list of courses below is not exhaustive. In addition, the regularity of offerings of the listed courses is not guaranteed. Some courses are offered every semester, every other semester, or every other year. Other courses may have been offered at some point, but may not be offered again for a while, and we keep them in this list in hopes they will be offered again.

A. Statistics and Design of Experiments

IE 330: Probability and Statistics in Engineering II (REQ)

IE 533: Industrial Applications of Statistics (TE)

STAT 512: Applied Regression Analysis (TE)

STAT 514: Design of Experiments (TE)

B. Ergonomics

IE 386: Work Analysis and Design I (REQ)

IE 556: Job Design (TE)

IE 558: Safety Engineering (TE)

PSY 272: Introduction to Industrial-Organizational Psychology (TE)

C. Human Perception and Cognition

IE 486: Work Analysis and Design II (REQ)

IE 559: Cognitive Engineering of Interactive Software (TE)

IE 577: Human Factors in Engineering (TE)

PSY 310: Sensory and Perceptual Processes (TE)

D. Characteristics of Humans

PSY 314: Introduction to Learning (TE)

PSY 333: Motivation (TE)

PPSY 475: Work Motivation and Job Satisfaction (TE)

PSY 511: Psychophysics (TE)

2. Financial Engineering Emphasis Area

Financial engineering is a multidisciplinary field that deals primarily with financial instruments, especially derivative securities. The field applies engineering methodologies to problems in finance, and employs financial theory and applied mathematics, as well as computation and the practice of programming to make pricing, hedging, trading and portfolio management decisions.

Utilizing various derivative securities and other methods, financial engineering aims to precisely control the financial risk (both market and credit) that an entity takes on. Methods can be employed to take on substantial risks under certain events, or largely eliminate other risks by utilizing combinations of derivative and other securities. Financial engineering can be applied to many different types of currencies and pricing options. These include equity, fixed income such as bonds, commodities such as oil or gold, as well as derivatives, swaps, futures, forwards, options, and embedded options. Industrial Engineering graduates bring a unique perspective to these financial analyses due to the nature of the discipline and the techniques and skills acquired as part of the Industrial Engineering curriculum. Because of the breadth of engineering education and the mathematical focus of much of the discipline, Industrial Engineering graduates frequently find good opportunities with banks, financial management and consulting companies, and other firms that deal with securities and/or perform quantitative analyses.

Financial engineering specialists have extensive knowledge of:

  • Financial mathematics
  • Stochastic processes
  • Optimization
  • Simulation
  • Economics

Financial engineering specialists have effective technical skills in:

  • Programming
  • Data manipulation and analysis
  • Modeling and problem-solving

Courses

Courses taken from the following groupings help to provide students with a deeper understanding of financial engineering. The courses listed below are listed in the course catalogue. They are meant to provide guidance as to what a student might take if they are interested in this emphasis area. The list of courses below is not exhaustive. In addition, the regularity of offerings of the listed courses is not guaranteed. Some courses are offered every semester, every other semester, or every other year. Other courses may have been offered at some point, but may not be offered again for a while, and we keep them in this list in hopes they will be offered again.

A. Basics of Financial instruments

IE 544: Introduction to Financial Engineering (TE)

B. Modeling and Problem-Solving

  • Differential Equations:

MA 266: Ordinary Differential Equations (REQ)

MA 303: Differential Equations and Partial Differential Equations for Engineering and the Sciences (TE)

MA 428: Introduction to Fourier Analysis (TE)

  • Statistics:

IE 230: Probability and Statistics in Engineering I (REQ)

IE 330: Probability and Statistics in Engineering II (REQ)

STAT 420: Introduction to Time Series (TE)

STAT 512: Applied Regression Analysis (TE)

  • Stochastic Modeling:

IE 336: Operations Research – Stochastic Models (REQ)

IE 536: Stochastic Models in Operations Research (TE)

C. Simulation and Programming

CE 462: Object-Oriented Programming in C++ and Java (TE)

IE 581: Simulation Design and Analysis (TE)

CS 314: Numerical Methods (TE)

D. Economics

IE 343: Engineering Economics (REQ)

3. Operations Research Emphasis Area

Operations Research (OR) is the discipline of applying advanced analytical methods to support decision making. It is also sometimes referred to as Management Science or Decision Science. The discipline draws on knowledge from mathematical and computing sciences to analyze complex decision-making problems with the goal of creating optimal solutions.

Operations Research finds application to a wide variety of problems such as: determining what petroleum products to make out of which crude oils, selecting the best path to take in transportation networks, identifying the best product placements in retail establishments, scheduling operating rooms in hospitals, optimizing financial plans for investment companies, ensuring appropriate inventory levels for spare parts manufacturers, and many, many more.

Operations Research techniques are applied to a variety of different business functions ranging from finance to manufacturing and marketing, and they provide significant benefits in almost every industry. As such, Industrial Engineers with an OR focus have a wealth of career opportunities. OR Specialists can be found in healthcare, automotive, energy, metals, and discrete parts manufacturing industries, to name a few; they are also prevalent in the government sector helping analyze issues relating to defense, health, environment, and other issues. It should be noted that many OR-focused careers require students to possess an advanced degree. The courses listed below help to prepare students for advanced studies in OR. Operations Research specialists have extensive knowledge of:

  • Mathematical modeling and analysis
  • Probability and statistics
  • Optimization
  • Simulation

Operations Research specialists have effective technical skills in:

  • Programming
  • Data manipulation and analysis
  • Modeling and problem-solving

Courses

Courses taken from the following groupings help to provide students with a deeper understanding of Operations Research. The courses listed below are listed in the Course Catalogue. They are meant to provide guidance as to what a student might take if they are interested in this emphasis area. The list of courses below is not exhaustive. In addition, the regularity of offerings of the listed courses is not guaranteed. Some courses are offered every semester, every other semester, or every other year. Other courses may have been offered at some point, but may not be offered again for a while, and we keep them in this list in hopes they will be offered again.

A. Simulation

IE 580: System Simulation (TE)

IE 581: Simulation Design and Analysis (TE)

B. Optimization

IE 335: Operations Research – Optimization (REQ)

IE 535: Linear Programming (TE)

IE 538: Nonlinear Optimization Algorithms and Models (TE)

IE 634: Integer Programming (TE)

C. Mathematical Modeling and Analysis

IE 230: Probability and Statistics in Engineering I (REQ)

IE 336: Operations Research – Stochastic Models (REQ)

IE 536: Stochastic Models in Operations Research (TE)

MA 341: Foundations of Analysis (TE)

MA 375: Introduction to Discrete Mathematics (TE)

D. Programming and Problem-solving

CS 314: Numerical Methods (TE)

4. Production and Management Systems Emphasis Area

The Production and Management Systems emphasis area focuses on the overall production and distribution of goods and services. The specialization aims to continuously improve material flow in a manner that enhances the quality of the final product and service while reducing the costs and waste to producers, workers and consumers. Industrial Engineering applications that fall under this emphasis include production planning, scheduling, and control; robotic design and implementation; materials handling, logistics, and storage systems design and control; and facilities location and design. As such, IEs with this focus are found in all sorts of diverse production and supply chain environments all over the world: automotive, electronics, healthcare materials, pharmaceuticals, energy system components, package delivery, etc. Industrial Engineers with a Production and Management Systems background often are involved with quality control using statistical techniques for productivity improvement. In addition, they frequently use operations research techniques to solve production problems that require an optimal blending of economic, human, and physical resources. Production systems specialists have extensive knowledge of:

  • Six sigma, total quality management, just-in-time
  • Facilities design
  • Optimization
  • Simulation

Production systems specialists have effective technical skills in:

  • Programming
  • Data manipulation and analysis
  • Modeling and problem-solving

Courses

Courses taken from the following groupings help to provide students with a deeper understanding of production and management systems. The courses listed below are listed in the course catalogue. They are meant to provide guidance as to what a student might take if they are interested in this emphasis area. The list of courses below is not exhaustive. In addition, the regularity of offerings of the listed courses is not guaranteed. Some courses are offered every semester, every other semester, or every other year. Other courses may have been offered at some point, but may not be offered again for a while, and we keep them in this list in hopes they will be offered again.

A. Quality Management and Control

IE 330: Probability and Statistics in Engineering II (REQ)

IE 530: Quality Control (TE)

IE 533: Industrial Applications of Statistics (TE)

MGMT 405: Six Sigma and Quality Management (TE)

IE 566: Production Management and Control (TE)

STAT 513: Statistical Quality Control (TE)

STAT 514: Design of Experiments (TE)

B. Simulation

IE 580: Systems Simulation (TE)

IE 581: Simulation Design and Analysis (TE)

C. Design and Analysis of Production Systems

IE 383: Integrated Production Systems I (REQ)

IE 484: Integrated Production Systems II (TE)

IE 582: Advanced Facilities Design (TE)

IE 583: Design and Evaluation of Material Handling Systems (TE)

IE 579: Design and Control of Production and Manufacturing Systems (TE)

IE 230 - Probability and Statistics in Engineering I

An introduction to probability and statistics. Probability and probability distributions. Mathematical expectation. Functions of random variables. Estimation. Applications oriented to engineering problems.

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IE 330 - Probability and Statistics in Engineering II

Continuation of IE 230. Introduction to statistical inference and experimental design. One- and two-sample tests, confidence intervals, contingency and goodness of fit tests. Correlation, regression, single and multi-factor ANOVA, non-parametric methods. Applications to statistical quality control.

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IE 332 - Computing in Industrial Engineering

Introduction to computing in industrial engineering. Reinforcement of scientific programming skills on typical IE tasks, together with introduction to simulation and related computer tools.

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IE 335 - Operations Research - Optimization

Introduction to deterministic optimization modeling and algorithms in operations research. Emphasis on formulation and solution of linear programs, networks flows, and integer programs.

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IE 336 - Operations Research - Stochastic Models

Introduction to probabilistic models in operations research. Emphasis on Markov chains, Poisson processes, and their application to queuing systems.

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IE 343 Engineering Economics

Cost measurement and control in engineering studies. Basic accounting concepts, income measurement, and valuation problems. Manufacturing cost control and standard cost systems. Capital investment, engineering alternatives, and equipment replacement studies.

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IE 370 - Manufacturing Processes I

Principal manufacturing processes; metal cutting, grinding and metal forming operations, machine tools, and tools and tooling. Nontraditional machining and welding. Introduction to computer-aided manufacturing and computer-aided graphics and design, N/C programming, robots, and flexible manufacturing systems. Classroom and laboratory demonstrations included.

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IE 383 - Integrated Production Systems I

Basic concepts in the design and operational control of integrated production systems. Includes topics on facility layout and material handling, material flow and information flow, resource and capacity planning, and shop floor control and scheduling.

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IE 386 - Work Analysis And Design I

Fundamentals of work methods and measurement. Applications of engineering, psychological, and physiological principles to the analysis and design of human work systems.

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IE 431 - Industrial Engineering Design

Capstone design experience for industrial engineering students involving analysis and synthesis of unstructured problems in practical settings. Students work in teams to formulate issues, propose solutions, and communicate results in formal written and oral presentations. This course is a continuation of IE 300. Graduation Projects Guidelines at the College of Engineering and Technology apply.

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IE 474 - Industrial Control Systems

Introduction to automatic controls with reference to automation of industrial machines and processes, including linear dynamic systems, feedback control, and elements of systems analysis. Introduction to digital control.

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IE 486 - Work Analysis and Design II

Continuation of IE 386. Applications of engineering, computer sciences, information sciences, and psychological principles and methods to the analysis and design of human work systems.

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EE 201 - Linear Circuit Analysis I

Volt-ampere characteristics for circuit elements; independent and dependent sources; Kirchhoff’s laws and circuit equations. Source transformations; Thevenin’s and Norton’s theorems; superposition, step response of 1st order (RC, RL) and 2nd order (RLC) circuits. Phasor analysis, impedance calculations, and computation of sinusoidal steady state responses. Instantaneous and average power, complex power, power factor correction, and maximum power transfer. Instantaneous and average power.

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ME 200 - Thermodynamics I

First and second laws of thermodynamics, entropy, reversible and irreversible processes, properties of pure substances. Application to engineering problems.

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ME 270 – Basic Mechanics I

Vector operations, forces and couples, free body diagrams, equilibrium of a particle and of rigid bodies. Friction. Distributed forces. Centers of gravity and centroids. Applications from structural and machine elements, such as bars, trusses, and friction devices. Kinematics and equations of motion of a particle for rectilinear and curvilinear motion.

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NUCL 273 - Mechanics of Materials

Analysis of stress and strain; equations of equilibrium and compatibility; stress-strain laws; extension, torsion, and bending of bars; membrane theory of pressure vessels; combined loading conditions; transformation of stresses and principal stresses; elastic stability, elected topics.

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ENGR 131 - Transforming Ideas to Innovation I

Introduces students to the engineering professions using multidisciplinary, societally relevant content. Developing engineering approaches to systems, generating and exploring creative ideas, and use of quantitative methods to support design decisions. Explicit model-development activities (engineering eliciting activities, or EEAs) engage students in innovative thinking across the engineering disciplines at AUM. Experiencing the process of design and analysis in engineering including how to work effectively in teams. Developing skills in project management, engineering fundamentals, oral and graphical communication, logical thinking, and modern engineering tools (e.g., Excel and MATLAB).

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ENGR 132 - Transforming Ideas To Innovation II

Continues building on the foundation developed in ENGR 131. Students take a more in depth and holistic approach to integrating multiple disciplines perspectives while constructing innovative engineering solutions to open-ended problems. Extending skills in project management engineering fundamentals, oral and graphical communication, logical thinking, team work, and modern engineering tools (e.g., Excel and MATLAB).

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ENGR 100 - First-Year Engineering Lectures

An introduction to the engineering profession.

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ENGR 126 - Engineering Problem Solving and Computer Tools

Introduction to the solving of open-ended engineering problems and the use and of computer software, including UNIXTM, computer communications, spreadsheets, and MATLAB. Explicit model-development activities are utilized, and students are expected to develop skill at working in teams. This is emphasized both in laboratories and on projects.

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MA 165 - Analytic Geometry and Calculus I

Introduction to differential and integral calculus of one variable, with applications. Conic sections.

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MA 166 - Analytic Geometry and Calculus II

Continuation of MA 165. Vectors in two and three dimensions. Techniques of integration, infinite series, polar coordinates, surfaces in three dimensions.

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MA 261 - Multivariate Calculus

Planes, lines, and curves in three dimensions. Differential calculus of several variables; multiple integrals. Introduction to vector calculus.

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MA 265 - Linear Algebra

Introduction to linear algebra. Systems of linear equations, matrix algebra, vector spaces, determinants, eigenvalues and eigenvectors, diagonalization of matrices, applications.

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MA 266 - Ordinary Differential Equations

First order equations, second and nth order linear equations, series solutions, solution by Laplace transform, systems of linear equations. It is preferable but not required to take MA 265 either first or concurrently.

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CHM 115 - General Chemistry I

Stoichiometry; atomic structure; periodic properties; ionic and covalent bonding; molecular geometry; gases, liquids, and solids; crystal structure; thermochemistry; descriptive chemistry of metals and non-metals.

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CS 159 - Programming Applications for Engineers

Fundamental principles, concepts, and methods of programming (C and MATLAB), with emphasis on applications in the physical sciences and engineering. Basic problem solving and programming techniques; fundamental algorithms and data structures; and use of programming logic in solving engineering problems. Students are expected to complete assignments in a collaborative learning environment.

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PHYS 172 - Modern Mechanics

Introductory calculus-based physics course using fundamental interactions between atoms to describe Newtonian mechanics, conservation laws, energy quantization, entropy, the kinetic theory of gases, and related topics in mechanics and thermodynamics. Emphasis is on using only a few fundamental principles to describe physical phenomena extending from nuclei to galaxies. 3-D graphical simulations and numerical problem solving by computer are employed by the student from the very beginning.

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PHYS 241 - Electricity and Optics

Electrostatics, current electricity, electromagnetism, magnetic properties of matter. Electromagnetic waves, geometrical and physical optics.

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ENGL 100 / ENL 100 - English for Academic Studies

This course is designed to support students in their transition from sheltered English language instruction to content-rich University and university courses. It is based on a widely-used process approach to writing, which demands considerable reading, writing and interaction among students. All writings and discussions are done in English in order to maximize opportunities for developing fluency in both formal and informal uses of the language in academic settings.

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ENGL 106 - First-Year Composition

This course provides extensive practice in writing clear and effective prose. Instruction focuses on organization, audience analysis, style, and research-based writing.

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COM 114 / ENL 120 - Fundamentals of Speech Communication

This course will use small groups and large-group instructions to teach the basic concepts of oral communication in informal, semi-formal and formal contexts. The overall goal is to create a learning environment that encourages students to make clear connections between professional and “real world” communication in addition to providing an opportunity for students to play an active role in their learning process.

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CHM 116 - General Chemistry II

A continuation of CHM 115. Solutions; quantitative equilibria in aqueous solution; introductory thermodynamics; oxidation-reduction and electrochemistry; chemical kinetics; qualitative analysis; further descriptive chemistry of metals and nonmetals.

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IE 300 - Industrial Engineering Seminar

A lecture-demonstration series emphasizing evaluation of career options, identification and development of professional skills, and introducing students to the formal design process of an industrial engineering project. Examples of career-related topics include choosing a job, and post-graduate education in engineering or other disciplines. Examples of professional skill topics covered include interviewing, writing, intellectual property and ethics. This course is considered as Phase One of the Graduation Project. Students work in a team to identify a problem, prepare literature review, and develop the methodology. Graduation Projects Guidelines at the College of Engineering and Technology apply.

 

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MA 303 - Differential Equations and Partial Differential Equations for Engineering and the Sciences

This is a methods course for juniors in any branch of engineering and science. Basic techniques for solving systems of linear ordinary differential equations. Series solutions for second order equations, including Bessel functions, Laplace transform, Fourier series, numerical methods, separation of variables for partial differential equations and Sturm-Liouville theory.

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IE 533 - Industrial Applications of Statistics

Credit Hours: 3

Pre: IE 330

The application of statistics to the effective design and analysis of industrial studies relating to manufacturing and human factors engineering in order to optimize the utilization of equipment and resources. Emphasis on conducting these studies at the least cost.

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STAT 512 - Applied Regression Analysis

Credit Hours: 3

Pre: IE 330

Inference in simple and multiple linear regression, residual analysis, transformations, polynomial regression, model building with real data, nonlinear regression. One-way and two-way analysis of variance, multiple comparisons, fixed and random factors, analysis of covariance. Use of existing statistical computer programs.

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STAT 514 - Design Of Experiments

Credit Hours: 3

Pre: STAT 512

Fundamentals, completely randomized design; randomized complete blocks; latin square; multi-classification; factorial; nested factorial; incomplete block and fractional replications for 2n, 3n, 2m x 3n; confounding; lattice designs; general mixed factorials; split plot; analysis of variance in regression models; optimum design. Use of existing statistical programs.

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IE 556 - Job Design

Credit Hours: 3

Pre: IE 386 or IE 577

Task analysis, personnel selection and training, job and organization design, and criteria development and use. Human factors related to job design in order to increase job satisfaction and productivity.

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IE 558 - Safety Engineering

Application of human factors and engineering practice in accident prevention and the reduction of health hazards are presented. The objective of this course is to provide an understanding of the safety and health practices which fall within the responsibilities of the engineer in industry. Special attention is devoted to the detection and correction of hazards and to contemporary laws and enforcement on occupational safety and health.

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PSY 272 - Introduction to Industrial-Organizational Psychology

Credit Hours: 3

Pre: PSY 120 or PSY 100

Survey of psychological principles and research methods relevant to organizations and industry. Topics covered include research methodology, individual differences, personnel selection, performance measurement, training, motivation, job satisfaction, emotions, work stress, and leadership.

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IE 559 - Cognitive Engineering Of Interactive Software

Theory and applications of software design to improve productivity and job satisfaction on information processing and cognitive tasks in the work place. Human information processing models and cognitive theories will be used to provide a theoretical basis for how to choose and display information to the user. Other topics include user-friendly displays and empirical approaches to software design. Applications of the design theory are stressed by class projects.

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IE 577 - Human Factors In Engineering

Survey of human factors in engineering with particular reference to human functions in human-machine systems, and consideration of human abilities and limitations in relation to design of equipment and work environments.

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PSY 310 - Sensory and Perceptual Processes

A survey of the study of psychological experiences caused by stimulation to the senses. Topics include theory and research in seeing, hearing, touching, smelling, and tasting as experienced by humans and other animals.

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PSY 314 - Introduction to Learning

This course deals with the theoretical and practical implications of learning principles and findings. Various theories of learning are examined and the implications of these theories and the learning approach in general are emphasized for a variety of practical problems.

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PSY 333 - Motivation

The course offers a survey of current research and theory in motivation. The effects of both learned and unlearned motives on behavior are discussed. Examples of topics covered are: hunger, aggression, pain, emotion, stress, frustration, conflict, needs for achievement, affiliation, and power.

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PSY 475 - Work Motivation and Job Satisfaction

Psychological processes and current theories of work motivation and job satisfaction and their practical implications.

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PSY 511 - Psychophysics

An examination of the relationship between physical stimuli and perception (visual, auditory, haptics, etc.). Includes a review of various methods for studying this relationship and of the mathematical and computational tools used in modeling perceptual mechanisms. Permission of instructor required.

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MA 428 – Introduction to Fourier Analysis

Topics include: Fourier series, convolutions, kernels, summation methods, Fourier transforms, applications to the wave, heat, and Laplace equations.

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STAT 420 - Introduction to Time Series

An introduction to time series analysis suitable for actuarial science, engineering, and sciences. Model building and forecasting with ARMA and ARIMA models. Resampling methods for confidence intervals. Multivariate, state-space, and nonlinear models. Volatility models (ARCH and GARCH). Smoothing in time series.

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IE 536 - Stochastic Models in Operations Research I

An introduction to techniques for modeling random processes used in operations research. Markov chains, continuous time Markov processes, Markovian queues, reliability and inventory models.

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CE 462 - Object-Oriented Programming In C++ and Java

C++ and Java programming languages, including classes, inheritance, encapsulation, polymorphism, class derivation, abstract classes, interfaces, static class members, object construction and destruction, namespaces, exception handling, function, overloading and overriding, function name overload resolution, container classes, and template classes.

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IE 581 - Simulation Design and Analysis

An introduction to simulation of stochastic systems on digital computers. Emphasis is on the fundamentals of simulation as a statistical experiment. Topics include uniform random numbers, input modeling, random variate generation, output analysis, variance reduction, and optimization.

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CS 314 – Numerical Methods

Iterative methods for solving nonlinear equations; direct and iterative methods for solving linear systems; approximations of functions, derivatives, and integrals; error analysis.

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IE 580 - Systems Simulation

Philosophy and elements of digital simulation language. Practical application of simulation to diverse systems. Computer simulation exercises and applications are required.

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IE 535 - Linear Programming

Optimization of linear objective functions subject to linear constraints. Development of theory and algorithmic strategies for solving linear programming problems.

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IE 538 - Nonlinear Optimization Algorithms and Models

Survey of computational tools for solving constrained and unconstrained nonlinear optimization problems. Emphasis on algorithmic strategies and characteristic structures of nonlinear problems.

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IE 634 - Integer Programming

An advanced course on theory and algorithms for integer and mixed integer optimization problems. Convergence of integer programming algorithms, dual relaxations, Benders decomposition, cutting plane theory, group theory of integer programs, and linear diophantine equations.

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IE 230 - Probability and Statistics in Engineering I

An introduction to probability and statistics. Probability and probability distributions. Mathematical expectation. Functions of random variables. Estimation. Applications oriented to engineering problems.

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MA 341 - Foundations of Analysis

An introductory course in rigorous analysis, covering real numbers, sequences, series, continuous functions, differentiation, and Riemann integration.

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MA 375 - Introduction to Discrete Mathematics

Induction, permutations, combinations, finite probability, relations, graphs, trees, graph algorithms, recurrence relations, generating functions. Problem solving in all these areas.

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IE 530 - Quality Control

Principles and practices of statistical quality control in industry. Control charts for measurements and for attributes. Acceptance sampling by attributes and by measurements. Standard sampling plans. Sequential analysis. Sampling inspection of continuous production.

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MGMT 405 - Six Sigma and Quality Management

The course provides an overview of various tools and methods for total quality management.

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IE 566 - Production Management Control

Background and development of production management, plus current concepts and controls applicable to production management functions.

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STAT 513 – Statistical Quality Control

A strong background in control charts including adaptations, acceptance sampling for attributes and variables data, standard acceptance plans, sequential analysis, statistics of combinations, moments and probability distributions, applications.

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IE 484 - Integrated Production Systems II

Extensions of topics on the design and operational control of integrated production systems. Includes production databases, facility layout, material handling, advanced control and scheduling, and physical distribution. Case studies, lab assignments, and projects.

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IE 582 - Advanced Facilities Design

Theoretical and applied aspects of manufacturing systems layout. Emphasis on contemporary manufacturing, including the layout of cellular systems, automated material handling systems, and storage systems.

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IE 583 - Design and Evaluation of Material Handling Systems

Analysis for design and evaluation of material handling systems with emphasis on material flow control and storage. Analytic models and simulation used. Economic justification models for material handling systems.

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IE 579 - Design and Control of Production and Manufacturing Systems

Design and control of discrete part manufacturing systems in contemporary production environments, with emphasis on flexible, demand-driven, product-based manufacturing. Currently used planning and control methodologies, such as MRP, OPT, and JIT are reviewed and integrated with appropriate facility design methodologies, including cellular design algorithms. Introduction to Computer Integrated Manufacturing (CIM) architecture and reference models and relevant control procedures, including basis approaches to appropriate data management methodologies.

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E 386 - Work Analysis And Design I

Fundamentals of work methods and measurement. Applications of engineering, psychological, and physiological principles to the analysis and design of human work systems.

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IE 486 - Work Analysis and Design II

Continuation of IE 386. Applications of engineering, computer sciences, information sciences, and psychological principles and methods to the analysis and design of human work systems.

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MA 301 – Introduction to Proof Through Real Analysis

An introduction to abstract reasoning in the context of real analysis. Topics may include axioms for the real numbers, mathematical induction, formal definition of limits, density, decimal representations, convergence of sequences and series, continuity, differentiability, the extreme value, mean value and intermediate value theorems, and cardinality. The emphasis, however, is more on the concept of proof than on any one given topic.

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