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Course Descriptions

[Undergraduate Courses] [Graduate Courses]

Undergraduate Course Descriptions


IE 1104 - Introduction to Engineering

Description: (TCCN  = ENGR 1101) Introduction to basic engineering concepts. Students will become familiar with engineering and its many sub-fields, ethical responsibilities, creativity and design

Prerequisite: None.

Required or Elective: Required.

Student Learning Outcomes:

  • List academic resources available on campus
  • Explain UT-Arlington policies and procedures related to undergraduate students
  • Describe curriculum, research areas and career types in the different engineering professions that you might enter after completing your BS degree at UT-Arlington.
  • Interact with current UT-Arlington engineering seniors and recent UT-Arlington engineering alumni.
  • Explain the basis for and importance of engineering ethics.
  • Critique several engineering case studies for ethical and unethical behavior.
  • Work in multi-disciplinary teams to design and create a device to accomplish a stated goal.
  • Keep an updated logbook of classroom activities.

Topics Covered:

  • Class introduction, structure of engineering program
  • Catalog issues and engineering professionalism
  • Written communications
  • Teamwork
  • Team activity
  • Midterm
  • Engineering and student ethics (2 class periods)
  • Introduction to electrical engineering
  • Introduction to mechanical and aerospace engineering
  • Introduction to industrial engineering
  • Introduction to computer science & engineering
  • Introduction to civil engineering
  • Team project demonstrations

Credit and Contact Hours: 1 Hour Credit. 1 class session per week, 50 minutes per session
Student Outcomes: This course addresses the following student outcomes: d, f, and g.

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IE 1105 - Introduction to Industrial Engineering Lab

Description: Introduction to basic engineering concepts. Opportunities are provided to develop skills in oral and written communication, and department-specific material. Case studies are presented and analyzed.

Textbook(s): None.

Other Supplemental Materials: None.

Prerequisite: None.

Required or Elective: Required.

Student Learning Outcomes:

  • Understand the types of work industrial engineers do and how industrial engineering fits into various organizations
  • Create an individualized, detailed plan including a semester by semester class schedule to complete the BSIE curriculum.
  • Use the UTA research databases and appropriately cite your sources using Microsoft Word.
  • Use Microsoft Excel to analyze data collected in lab experiments. Evaluate the results of the analysis.
  • Describe basic concepts of a variety of industrial engineering tools.
  • Develop a PowerPoint presentation and deliver an oral report.
  • A understanding of the jobs that IEs can do, whatever the job is labeled

Topics Covered:

  • Introduction to industrial engineering; UTA Computers: Account setup, e-mail setup, IE web page operation
  • Presentations from IE student groups, IE lab exercise
  • Microsoft Word with lab
  • Microsoft Excel with lab
  • Microsoft PowerPoint with lab; Curriculum Overview
  • UTA Libraries: Introduction, Pulse system, On-line research databases with lab
  • Introduction to statistics and quality control with lab
  • Introduction to ergonomics with lab
  • Introduction to operations research with lab
  • Introduction to logistics with lab
  • Introduction to production and inventory control with lab
  • Ethics case studies with lab
  • Oral presentations

Credit and Contact Hours: 1 Hour credit. 2 class sessions per week, 1 hour 20 minutes per session
Student Outcomes: This course addresses the following student outcomes: d, f, and g.

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IE 2000 - Undergraduate Research

Description:Sophomore level undergraduate research. May be taken a maximum of three times.

Prerequisite: Departmental good standing and permission of instructor.

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IE 2305 - Computer Applications in Industrial Engineering Lab

Description:An overview of Industrial Engineering concepts and issues important to the design and operation of industrial and service systems. Students will learn the use of software tools developed to enhance the Industrial Engineer's ability such as database management, high level programming languages, electronic spreadsheets, and computer graphics.

Textbook(s):

  • Computer Applications in Industrial Engineering Part 1, Pearson Custom Publishing
  • Computer Applications in Industrial Engineering Part 2, Pearson Custom Publishing

Other Supplemental Materials: None.

Prerequisite: IE 1105 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes:

  • Use the six problem-solving steps to solve problems.
  • Set up and evaluate expressions and equations using variables, constants, operators, and the hierarchy of operations.
  • Use Visio to model problem solutions.
  • Develop problems using decision logic structure and loop logic structure and arrays.
  • Create a Microsoft Access database with multiple tables and establish table relationships.
  • Design, create and run queries in Microsoft Access.
  • Design, create and use forms and reports in Microsoft Access.
  • Design and create Pivot Tables and Pivot Charts in Microsoft Access.
  • Write procedures using VBA.
  • Use VBA and Microsoft Excel and Microsoft Access to solve Industrial Engineering Problems.

Topics Covered:

  • Introduction to industrial engineering; UTA Computers: Account setup, e-mail setup, IE web page operation
  • Programming Basics
  • Visio
  • Microsoft Access
  • Visual Basic of Applications

Credit and Contact Hours: 3 Hours credit. 2 class sessions per week, 1 hour 20 minutes per session.
Student Outcomes: This course addresses the following student outcomes: None.

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IE 2308 - IE Engineering Economics

Description: Methods used for determining the comparative financial desirability of engineering alternatives. Provides the student with the basic tools required to analyze engineering alternatives in terms of their worth and cost, an essential element of engineering practice. The student is introduced to the concept of the time value of money and the methodology of basic engineering economy techniques. The course will address some aspects of sustainability and will provide the student with the background to enable them to pass the Engineering Economy portion of the Fundamentals of Engineering exam.

Prerequisite: MATH 1426 or concurrent enrollment.

Credit and Contact Hours: 3 Hours credit. 2 class sessions per week, 1 hour 20 minutes per session.
Student Outcomes: This course addresses the following student outcomes: None.

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IE 3000 - Undergraduate Research

Description: Junior level undergraduate research. May be taken a maximum of three times.

Prerequisite: Departmental good standing and permission of instructor.

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IE 3301 - Engineering Probability

Description: Topics in engineering that involve random processes. Applications and backgrounds for topics in reliability, inventory systems, and queuing problems, including absolute and conditional probabilities, discrete and continuous random variables, parameter estimation, hypothesis testing, and an introduction to linear regression, experimental design, and analysis of variance.

Prerequisite: MATH 2425.

Required or Elective: Required.

Student Learning Outcomes:

  • Understand the basic concepts of probability theory and hypothesis testing
  • Apply those concepts to solving numerical problems especially those relating to probability distributions
  • Perform descriptive and inferential statistical analyses of data, and
  • Appreciate the use of a popular software, such as STATISTICA, SAS, or EXCEL for performing descriptive statistics and elementary statistical analyses, at least.

Topics Covered:

  • Descriptive statistics
  • Probability theory
  • Random variables and probability distributions
  • Mathematical expectations
  • Discrete probability distributions
  • Continuous probability distributions
  • Linear combinations of random variables
  • Sampling distributions
  • Estimation and confidence Intervals
  • Hypothesis testing
  • Introduction to Simple Linear Regression analysis

Credit and Contact Hours: 3 Hours credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.
Student Outcomes: This course addresses the following student outcomes: a and b.

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IE 3312 - Economics for Engineers

Description: Tools and methods used for determining the comparative financial desirability of engineering alternatives.

Prerequisite: MATH 1426 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: This course is designed to introduce students to the tools and methods used to evaluate, from an economic perspective, various engineering projects or endeavors. The course will introduce fundamental economic concepts like: the time value of money, equivalence, depreciation, taxes, and minimum acceptable rate of return. Specific methods used to evaluate potential investment opportunities will be presented and practiced. The role that depreciation and taxes play in these methods will be discussed. Techniques to identify the best project or group of projects to select based on a set of constraints will be presented. Methods used to identify the least cost alternative to fulfill a specific project’s needs will also be covered in the class.

By the end of the course, you should be able to:

  • Calculate the present, future, or equivalent periodic amount of a series of funds flowing into or out of an account over a period of time.
  • Quantitatively compare various interest rate expressions.
  • Quantitatively determine if a given investment alternative is economically attractive given a minimum acceptable rate of return constraint.
  • Quantitatively determine the best project or group of projects to conduct based on a set of limiting constraints.
  • Quantitatively determine the lowest cost alternative to satisfy the needs of a specific project.

Topics Covered:

  • Fundamental Concepts Concerning Economic Systems
  • The Time Value of Money including Interest and Interest Factors
  • Depreciation Models
  • Tax Considerations and Their Impact on Economic Decision Making
  • Economic Project Evaluation
  • Capital Budgeting
  • Break Even Models
  • Cost Comparisons
  • Replacement Analysis

Credit and Contact Hours: (3-0) 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.
Student Outcomes: This course addresses the following student outcomes: None.

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IE 3314 - Engineering Research Methods

Description: A continuation of IE 3301. Simple and multiple linear regression analysis, design of experiments, analysis of variance, and quality control statistics. Emphasis on the application of these methods to engineering data, with computerized data analysis.

Prerequisite: IE 3301 and MATH 2326.

Required or Elective: Required.

Student Learning Outcomes: At the end of this course students should be able to:

  • Understand the salient concepts related to regression analysis and analysis of variance in experimental designs
  • Design statistical experiments
  • Analyze engineering and related data using mainly regression analysis and analysis of variance techniques
  • Use the SAS software for analyses

Topics Covered:

  • Introduction to industrial engineering; UTA Computers: Account setup, e-mail setup, IE web page operation
  • Review of hypothesis testing and C.I. estimation
  • Simple linear regression
  • Using SAS for data analysis
  • Multiple linear regression
  • Analysis of variance concepts
  • Analysis of variance and experimental designs

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: b and k.

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IE 3315 - Operations Research I

Description: Introduction to the major deterministic techniques of operations research and their application to decision problems. Linear programming, integer programming, network analysis, dynamic programming, nonlinear programming. Course software is used. Project required.

Prerequisite: IE 3301 or concurrent enrollment and MATH 2326.

Required or Elective: Required.

Student Learning Outcomes: This course is designed to develop modeling skills and an ability to apply deterministic quantitative optimization methods to the decision-making process.

By the end of this course, the student should be able to formulate and solve deterministic models for various real-life industrial scenarios using the standard models presented in this course. Test questions will measure both the students’ ability to formulate such models, as well as solve them. In addition, computer solutions for a number of textbook problems must be submitted at the end of the semester.

Topics Covered:

  • Geometry of linear programming problem
  • Algebraic solution of linear programming problems
  • Simplex method
  • Duality theory
  • Dual simplex method
  • Transportation problem and algorithm
  • Assignment problem and algorithm
  • Integer programming
  • Network problems and algorithms
  • Goal Programming
  • Dynamic programming
  • Nonlinear programming
  • Tests

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session..

Student Outcomes: This course addresses the following student outcomes: a.

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IE 3343 - Metrics and Measurement

Description: This course presents methods for determining the most effective utilization of effort in the man-machine environment as well as systems and methods to measure enterprise performance. The computer competency evaluation is administered in this course for those students who have not had IE 1105.

Prerequisite: MATH 2326, IE 3312 or concurrent enrollment, and IE 3301 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: At the end of this course students should be able to:

  • Describe the characteristics of a useful metric.
  • Differentiate between normal times, standard times, and cycle times.
  • Balance an assembly line using various methods and evaluate the effectiveness of the solutions.
  • Design and conduct a stopwatch time study. Analyze the results.
  • Compare and contrast different Predetermined Motion Time Systems.
  • Describe the purpose of performance ratings.
  • Conduct a performance rating experiment and analyze the results.

Topics Covered:

  • Methods, Standards, and Work Design: Introduction
  • Problem Solving Tools
  • Operation Analysis
  • Proposed Method Implementation
  • Lean
  • Metrics
  • Time Study
  • Performance Rating
  • Allowances
  • Predetermined Time Systems
  • Work sampling
  • Indirect and Expense labor Standards
  • Standards Follow-Up and Uses

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: h.

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IE 4000 - Undergraduate Research

Description: Senior level undergraduate research. May be taken a maximum of three times.

Prerequisite: Departmental good standing and permission of instructor.

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IE 4191, 4291, 4391 - Special Problems in Industrial Engineering

Description: The investigation of special individual problems in industrial engineering under the direction of a faculty member.

Prerequisite: Consent of the department chairperson.

Required or Elective: Selected Elective.

Student Learning Outcomes: To provide students with an opportunity for independent study and the application of their academic training to practical situations, theoretical investigation, or design projects.

Topics Covered: Varies.

Credit and Contact Hours: Variable credit from 1 to 3 semester hours as arranged. Independent Study.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4300 - Topics in Industrial Engineering

Description: A study of selected topics in industrial engineering. May be repeated when topics vary.

Prerequisite: Consent of instructor and undergraduate advisor..

Required or Elective: Selected Elective.

Course Goals: To provide students access to new and varied course topics in Industrial Engineering.

Topics Covered:Varies.

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4302 - Engineering Administration and Organization

Description: A survey of administration, control and organization of engineering and research activities. Strategic planning as well as project planning and control are discussed.

Prerequisite: Accepted in an UTA engineering professional program.

Required or Elective: Required.

Student Learning Outcomes: Broad-coverage course for engineering majors addressing the principal topics of engineering management and program management.

Topics Covered:

  • Classical elements of management
  • History of the development of management thought
  • International ventures and their implications
  • Decision-making
  • Planning, IMP, IMS, Requirements
  • Influence diagrams and precedence
  • Program evaluation and review technique
  • Critical path method
  • Monte Carlo simulations in management
  • Financial plans
  • Forecasting
  • Strategic analysis
  • Organizational design
  • Technical report and proposal writing
  • Earned value management systems
  • Leadership
  • Team management
  • Integrated mfg and baseline processes
  • Schedule management
  • Cost management
  • Ethics applications in Managements

Credit and Contact Hours: 3 Hours Credit. 1 class session per week, 2 hour 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4303 - Production and Inventory Control

Description: Fundamental theory and design of systems for the control of production, inventories and their economic interaction, particularly in cases involving uncertainty of demand, of supply availability, and of production rates.

Prerequisite: IE 3301 and 3315.

Required or Elective: Required.

Student Learning Outcomes: At the end of this course students should be able to:

  • Identify and solve appropriate inventory control model problems given demand characteristics.
  • Use MRP to devise a manufacturing schedule.
  • Identify the basic metrics of a factory and describe their relationships.
  • Measure and explain the effects of variability on a manufacturing system.
  • Compare and contrast push versus pull systems.
  • Compute a schedule of jobs and evaluate the schedule effectiveness.

Topics Covered:

  • Manufacturing in America
  • Factory Physics
  • Inventory Control: From EOQ to ROP
  • The MRP Crusade
  • The JIT Revolution
  • Basic Factory Dynamics
  • Variability Basics
  • The Corrupting Influence of Variability
  • Push and Pull Production Systems
  • A Pull Planning Framework
  • Production Scheduling

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: e.

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IE 4304 - Enterprise Systems

Description: An extension of Production and Inventory Control (IE 4303), this course covers enterprise resource planning systems (ERP) in manufacturing, E-Commerce and supply chain environments. ERP software and case studies are reviewed.

Prerequisite: IE 4303.

Required or Elective: Selected Elective.

Student Learning Outcomes: At the end of this course students should be able to:

  • Describe an ERP system.
  • Evaluate an ERP implementation plan for successful and unsuccessful characteristics.
  • Model a resource allocation problem and use Solver to find an optimal solution.
  • Balance an assembly line using various models and evaluate the effectiveness of the solutions.
  • Differentiate between value added and non-value added activities.
  • Describe the steps required to implement group technology.
  • Form groups of parts and machines using various algorithms.
  • Evaluate a system with a constraint and formulate a plan for implementing theory of constraints methodology.
  • Describe the purpose of the SCOR model.
  • Orally communicate an effective written summary of an assigned reading.

Topics Covered:

  • Class introduction, modeling basics
  • Enterprise Resource Planning
  • Modeling using Excel
  • Line Balancing
  • Lean Engineering
  • Group Technology
  • Theory of Constraints
  • SCOR Model of Enterprises
  • Research Methodologies
  • Oral Presentations

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4308 - Quality Systems

Description: A comprehensive coverage of modern quality systems techniques to include the design of statistical process control systems, acceptance sampling, and process analysis and design.

Prerequisite: IE 3314 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: The objective of this course is to provide the student with an opportunity to acquire the fundamentals of statistical quality control methods as well as an appreciation of some practical approaches and solutions to some examples of real quality control problems.

Topics Covered:

  • Basic concepts
  • Process documentation
  • Process variation
  • Process sampling and the control chart
  • Process improvement with control chart
  • Variables control charts
  • Attributes control charts
  • Process diagnosis, capability and improvement
  • Specifications and inspection policy
  • Review of Deming and variability reduction
  • Project discussions
  • Exams

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: c, d, and Criterion 9.

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IE 4310 - Industrial and Product Safety

Description: Scientific, managerial, and legal aspects of safety hazard control and elimination in the industrial workplace. Methods for enhancing product safety.

Prerequisite: Accepted in an UTA engineering professional program.

Required or Elective: Selected Elective.

Student Learning Outcomes: To enhance the understanding of the scientific, managerial and legal aspects of safety that apply to the occupational environment.

At the end of this course students should be able to:

  • Interpret accident and safety statistics for the US and other countries
  • Quantify accident frequency and severity
  • Analyze the causes and consequences of industrial and product safety accidents
  • Interpret accident and injury information with respect to OSHA and other federal and state laws
  • Understand the science and engineering concepts associated with accidents in selected work environments (e.g. thermal, electrical, noise hazards, etc.)

Topics Covered:

  • Introduction to safety
  • Accident losses
  • Liabilities and safety legislation
  • Worker's compensation
  • OSHAct
  • Standards, codes, and other safety documents
  • Products safety and liability
  • Hazards and their control
  • Promoting safe practices
  • Appraising plant safety
  • Types of safety analyses
  • Planning for emergencies
  • Accident investigations
  • Accelerations, falls, falling objects, and other impacts
  • Mechanical injuries
  • Pressure hazards
  • Electrical hazards
  • Fires and suppression
  • Explosion and explosives
  • Toxic substances and confined spaces
  • Radiation

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4315 - Operations Research II

Description: A continuation of IE 3315 to probabilistic techniques of operations research and their application to decision models. Topics include z-transforms, linear difference equations, Markov chains, game theory, decision analysis, queuing theory, and non-quantitative aspects of decisions. Group projects are required.

Prerequisite: IE 3301, IE 3315, and MATH 3319 (or concurrent enrollment).

Required or Elective: Required.

Student Learning Outcomes: This course is designed to develop modeling and decision-making skills, including the ability to apply probabilistic quantitative methods.

By the end of this course, the student should be able to formulate and solve probabilistic models for various real-life industrial scenarios using the standard models presented in this course. Test questions will measure both the students’ ability to formulate such models, as well as solve them. In addition, computer solutions for a number of textbook problems must be submitted. Finally, each student must choose a real-world situation, model it using the tools of the course, then submit a written report and give a class presentation at the end of the semester.

Topics Covered:

  • Difference equations and z-transforms
  • Markov chains
  • Markov decision processes
  • Decision analysis
  • Game theory
  • Negotiation
  • Queuing theory
  • Presentation of group projects
  • Tests

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: a and e.

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IE 4318 - Enterprise Systems Design

Description: Design, analysis, and modeling of enterprises. Topics include enterprise architectures, structured system modeling methods, enterprise integration, and enterprise transformation.

Prerequisite:Accepted in an UTA engineering professional program.

Required or Elective: Required.

Student Learning Outcomes: The objective of this course is to introduce the concepts and basic tools of enterprise engineering.

Topics Covered:

  • Introduction to enterprise engineering
  • Structure of an enterprise
  • Transformation Methodology
  • SADT/IDEF0 Modeling Methodology
  • Activity Based Management
  • Balanced Scorecard
  • Use of methods and tools
  • Class Projects
  • Lean principles

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: c, k, and Criterion 9.

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IE 4322 - Enterprise Simulation

Description: The design and analysis of complex manufacturing and service systems using computer-based discrete-event simulation techniques. Topics include an introduction to simulation methods, and the design, construction and analysis of discrete-event simulation models, as well as their computer applications. The course also covers the execution and management of simulation projects and the formal presentation of their findings.

Prerequisite: IE 3314 and IE 4315.

Required or Elective: Required.

Student Learning Outcomes: This course is designed to provide students with a practical introduction to discrete-event simulation methods with specific emphasis on how this technology can be used to support the analysis of enterprise systems. These courses will present the concepts behind the discrete-event simulation method and provide the student with a hands-on opportunity to construct models of enterprise systems. This course will also focus on the use of a general discrete-event simulation project methodology.

At the end of this course students should be able to:

  • Manually replicate the execution of a Discrete-Event Simulation Engine.
  • Summarize the various tasks outlined in a Simulation Project Methodology.
  • Recall and discuss issues associated with establishing a discrete-event simulation capability within a company.
  • Design a computer-based discrete-event simulation model to represent a complex industrial/business/service system.
  • Analyze the output of a simulation model in order to verify the appropriateness of the model’s performance.
  • Evaluate various system configurations to determine the most appropriate system design and/or justify proposed changes to a given system.

Topics Covered:

  • System Modeling and Analysis
  • Construction of Simulation Models
  • Simulation Theory
  • Introduction to a simulation tool
  • Simulation output analysis
  • Simulation Project
  • Application of random distributions
  • Simulation project methodology
  • Creating a simulation capability

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week – 1 hour 20 minutes per session.

Student Outcomes: This course addresses the following student outcomes: c, k, and Criterion 9.

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IE 4325 - Automation and Robotics I

Description: Study of the use of industrial automation and robotics technologies in manufacturing industries. The course introduces the major classes of industrial automation. Issues associated with the successful deployment of automation are presented. Laboratory exercises focus on a practical introduction to various automation technologies.

Prerequisite: IE 4303 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: This course is designed to provide students with a general overview of industrial automation. These courses will attempt to always present these technologies in the context of how they support the needs of the larger manufacturing enterprise. The course will present general topics which are common to all classes of industrial automation. Specific types of industrial automation like robotics and numerical control will also be introduced. Laboratory exercises will allow the students to observe and use representative examples of the types of industrial automation discussed in the class.

At the end of this course students should be able to:

  • Describe the primary factors which determine the characteristics of a manufacturing enterprise.
  • Describe the characteristics of the four classes of industrial automation and have the ability to identify the type of manufacturing operations each of these automation classes best supports.
  • Identify and list the general types of sensors and actuators associated with industrial automation.
  • Discuss the various types of Industrial Controls and explain which control method or technology is better suited for a given environment or application.
  • List the different classes of industrial robots and explain how you would select a specific class of industrial robot for a given application.
  • Design a system, component, or process that uses industrial automation technology to meet a set of application requirements.
  • Demonstrate your ability to use industrial automation tools.

Topics Covered:

  • Manufacturing Systems Concepts
  • Classification of Industrial Automation
  • Automation System Design Strategy
  • Industrial Control
  • Sensors, Actuators & Other Components
  • Numerical Control
  • Industrial Robotics
  • Discrete Control with PLCs and PCs
  • Inspection Technologies

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week – 1 hour 20 minutes per session. 2 laboratory sessions per week – 1 hour 20 minutes per session.

Student Outcomes: This course addresses the following student outcomes: c, and k.

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IE 4339 - Product Development, Producibility and Reliability Design

Description: This course covers the product and process development and engineering design process with focus on collaborative design in the enterprise environment. Manufacturing, reliability, testing, logistical and product support considerations are emphasized.

Prerequisite: Accepted in an UTA engineering professional program

Required or Elective: Required.

Student Learning Outcomes: Survey of topics in concurrent engineering, collaborative design, producibility and reliability in the product development process.

Topics Covered:

  • Product development
  • Requirements definition and con design
  • Trade-Off analysis
  • Detailed design and test
  • Manufacturing and supply chain
  • Design for people
  • Producibility
  • Reliability
  • Projects

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4343 - Facilities Planning and Design

Description: The course covers strategic facilities planning through detailed facilities layout design. Considerations include product flow, space and activity relationships, personnel requirements, material handling, and layout. Traditional and contemporary issues in manufacturing and their impact on facilities design including receiving, shipping, warehousing, and integration with manufacturing and supporting operations are explored. Facilities planning models and the process of evaluating, selecting, preparing, presenting, and implementing the facilities plan are covered.

Prerequisite: IE 4303 or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: This course is designed to develop facilities planning and layout skills, including the ability to apply quantitative methods to decision-making in the areas of selecting, preparing, presenting, and implementing facilities plans. These skills have broad applications and can be useful for the planning and design of a manufacturing enterprise, hospital, airport, warehouse/distribution center, bank, office, retail store, etc.

At the end of this course students should be able to:

  • Explain the "Winning Facilities Planning Process"
  • Determine product, process, and schedule design interactions & Develop personnel requirements
  • Analyze flow, space, and activity relationships with impact to material handling and layout alternatives
  • Integrate receiving, shipping, warehousing with manufacturing and supporting operations
  • Apply standards of professional and ethical responsibility
  • Prepare and present a detailed facilities planning project report and layout documenting all steps taken (define problem, generate alternatives, evaluate, select) including justification of your final recommendation.

Topics Covered:

  • Product, process, and schedule design
  • Activity relations and space requirements
  • Personnel requirements
  • Material handling
  • Layout planning models and design algorithms
  • Receiving, shipping, warehousing and integration with manufacturing and supporting operations
  • Quantitative facilities planning models
  • Evaluating, selecting, preparing, presenting, and implementing the facilities plan
  • Project presentations

Credit and Contact Hours: : 3 Hours Credit. 2 lecture sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: c and f.

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IE 4344 - Human Factors Engineering

Description: Study of the interactions between people and their work, workplace, and the environment. Involves identification, measurement, analysis, and evaluation of interactions via human physical and mental capacities and limitations, and social interactions.

Prerequisite: IE 3301, IE 3312, and IE 3343.

Required or Elective: Required.

Student Learning Outcomes: To achieve an understanding of the capabilities and limitations of people in a human-machine-environment system, and of the principles and techniques of integrating people into the system to enhance safety and efficiency in task performance.

At the end of this course students should be able to:

  • Identify human-work problems in occupational and living environments
  • Measure and understand human capacities for work
  • Measure and understand physical and mental demands on human beings for specific tasks
  • Understand the scientific concepts in designing environments, equipment and work methods for enhancing performance and minimizing stresses on the worker

Topics Covered:

  • Human factors concepts
  • Anthropometry and design
  • Biomechanics
  • Work physiology
  • Manual Materials Handling
  • Hand tool design
  • Information processing
  • Displays – mainly visual and auditory
  • Controls
  • The environment
  • Usability – consumer products

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: b, g, and h.

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IE 4345 - Knowledge and Technology Management

Description: IE 4345 KNOWLEDGE AND TECHNOLOGY MANAGEMENT (3-0) Review of contemporary issues in knowledge management, knowledge engineering, technology management, and intelligent systems. Topics include knowledge acquisition, intelligent database design, decision support systems, artificial intelligence technologies, designs and tools, and collaborative development.

Other Supplemental Materials: Handouts and UTA approved clickers, they can be purchased from other students or the book store. You will need to register them with the company.

Prerequisite: Accepted in an UTA engineering professional program.

Required or Elective: Required.

Student Learning Outcomes: This class covers many new and state-of-the-art topics in intelligent systems, decision support systems, knowledge management, knowledge engineering, intelligent systems, expert systems, data mining, etc. The focus will be on the book, outside readings, and projects. This course is evolving; so the course requirements will be defined as the course progresses.

Class learning objectives:

  • Overview, terminology, and concepts of intelligent systems, knowledge engineering, knowledge management and applied AI.
  • When and how to use case based reasoning, neural networks, expert systems, data mining, genetic algorithms, fuzzy logic, agents, etc.
  • Engineers, management and non-programmers role in these areas.

Topics Covered:

  • Applied A.I.
  • Intelligent systems
  • Expert systems
  • Case-based Reasoning
  • Domain knowledge
  • Projects

Credit and Contact Hours: 3 Hours Credit. 2 class sessions per week, 1 hour 20 minutes per session, or 3 class sessions per week, 50 minutes per session.

Student Outcomes: This course addresses the following student outcomes: None.

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IE 4349 - Industrial Automation

Description: Project oriented course focusing on the design, implementation, and operation of technology. An in-depth study of the design and deployment of industrial technology to meet the needs of high-precision, multi-product environments. The laboratory activities associated with the course provide practical experience.

Prerequisite: IE 4325.

Required or Elective: Selected Elective.

Student Learning Outcomes: This course will provide an understanding of the relationships between the process and product requirements of a manufacturing activity in order to analyze, design, and develop the concepts needed to put together integrated systems.

Topics Covered: As a project course, the topics depend on the area of focus for that semester. Topics will vary depending on the semester.

  • A brief history of robotics
  • Fundamentals of robot technology, programming, and applications
  • Control systems and components
  • Robot motion analysis and control
  • Robot end effectors
  • Sensors in robotics
  • Machine vision
  • Robot programming
  • Robot languages
  • Artificial intelligence
  • Robot cell design and control
  • Economic analysis for robotics
  • Material transfer and machine loading/unloading
  • Processing operations
  • Assembly and inspection
  • An approach for implementing robotics
  • Safety, training, maintenance, and quality
  • Social and labor issues
  • Robotic technology of the future
  • Future applications

Credit and Contact Hours: 3 Hours Credit. 2 sessions per week, 1 hour 20 minutes per session. Labs are required but can be scheduled by the student.

Student Outcomes: This course addresses the following student outcomes: None.


IE 4350 - Industrial Engineering Capstone Design

Description: This course provides an open-ended design experience through the planning and design of an enterprise. Typically, the student selects a product; determines the necessary processes, equipment, capacities, routings, and personnel required; develops supporting material handling, inventory, and quality systems; and designs the fully integrated enterprise including facility layout with estimated cost of operation. Contemporary project management techniques are utilized. The design experience project includes submittal of approximately nine written and oral presentations culminating in a written project report and oral presentation at the end of the semester. IE 4350 is the capstone design course and draws on material from the total industrial engineering curriculum. The impact of engineering design on society is discussed.

Other Supplemental Materials: None.

Prerequisite: All required 4000 level IE courses or concurrent enrollment.

Required or Elective: Required.

Student Learning Outcomes: This course provides an open-ended capstone project design experience through the planning and layout of a manufacturing or service enterprise. In addition to the capstone project, we will review, discuss, analyze and evaluate various contemporary issues in IE, project management techniques, practical applications of IE techniques in “The Goal”, ethics considerations in engineering, resume preparation and interview techniques, and other relevant topics of mutual interest as time permits. The student will demonstrate the ability to satisfy ABET Outcomes as described below via key assignments.

  • ABET Criterion 3 (c)an ability to design a system, component, or process to meet desired needs within realistic constraints such as economic, environmental, social, political, ethical, health and safety, manufacturability, and sustainability
    Key assignment: Capstone Design Project
  • ABET Criterion 3 (f) an understanding of professional and ethical responsibility
    Key assignment: Incident at Morales
  • ABET Criterion 3 (g) an ability to communicate effectively
    Key assignment: Contemporary Issues Presentations
  • ABET Criterion 3 (i) a recognition of the need for, and an ability to engage in life-long learning
    Key assignment: Homework Assignment and Final Exam Question
  • ABET Criterion 3 (j) a knowledge of contemporary issues
    Key assignment: Contemporary Issues Presentations and Follow-up Exam Questions
  • ABET Criterion 5. Professional Component: Students must be prepared for engineering practice through the curriculum culminating in a major design experience based on the knowledge and skills acquired in earlier course work and incorporating appropriate engineering standards and multiple realistic constraints.
    Key assignment: Capstone Design Project
  • ABET Criterion 9. The program must demonstrate that graduates have the ability to design, develop, implement & improve integrated systems that include people, materials, information, equipment and energy. The program must include in-depth instruction to accomplish the integration of systems using appropriate analytical, computational and experimental practices.
    Key assignment: Capstone Design Project

Topics Covered:

  • Capstone project
  • Capstone projectContemporary issues
  • Capstone projectProfessional and ethical responsibility
  • Capstone projectInterview skills and resume preparation techniques
  • Capstone projectPractical IE application of IE techniques in “The Goal”

Credit and Contact Hours: 3 Hours Credit. 2 lecture sessions per week, 1 hour per session, and 2 laboratory sessions per week, 1 hour 20 minutes per session.

Student Outcomes: c, f, g, i, j, Criterion 5, and Criterion 9.

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IE 4378 - Introduction to Unmanned Vehicles Systems

Description: Introduction to UVS (Unmanned Vehicle Systems) such as UAS (Unmanned Aircraft Systems), UGS (Unmanned Ground System) and UMS (Unmanned Maritime System), their history, missions, capabilities, types, configurations, subsystems, and the disciplines needed for UVS development and operation. UVS missions could include student competitions sponsored by various technical organizations. This course is team-taught by engineering faculty.

Prerequisite: Admission to a professional engineering or science program.

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IE 4379 - Unmanned Vehicle System Development

Description: Introduction to the technologies needed to create an UVS (Unmanned Vehicle System). Integration of these technologies (embodied as a set of sensors, actuators, computing and mobility platform sub-systems) into a functioning UVS through team work. UVS could be designed to compete in a student competition sponsored by various technical organizations or to support a specific mission or function defined by the instructors. This course is team-taught by engineering faculty.

Prerequisite: B or better in IE 4378 and admission to the UVS certificate program.

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Graduate Course Descriptions


IE 5191 - Advanced Studies in Industrial Engineering

Description: Individually approved research projects and reading courses in industrial engineering. Such individual studies will be graded A, B, C, D, F or X. Subject to the approval of the Graduate Advisor, IE 5191, 5291 and 5391 may be repeated as the topics change. In addition, work on a thesis substitute will be performed under IE 5391. In this case, IE 5391 is graded P/F/R.

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IE 5291 - Advanced Studies in Industrial Engineering

Description: Individually approved research projects and reading courses in industrial engineering. Such individual studies will be graded A, B, C, D, F or X. Subject to the approval of the Graduate Advisor, IE 5191, 5291 and 5391 may be repeated as the topics change. In addition, work on a thesis substitute will be performed under IE 5391. In this case, IE 5391 is graded P/F/R.

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IE 5300 - Topics in Industrial Engineering

Description: A study of selected topics in industrial engineering. May be repeated when topics vary.

Prerequisite: consent of instructor and Graduate Advisor.

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IE 5301 - Advanced Operations Research

Description: A survey of quantitative methods to develop modeling and decision-making skills. Topics include linear programming, goal programming, the simplex and dual simplex algorithms, transportation and assignment problems, integer programming, network analysis, nonlinear programming, decision trees, Markov Chains, and queuing theory.

Prerequisite: IE 3301 or IE 5317 or equivalent.

Topics Covered:

  • Linear difference equations and z-transforms
  • Markov chains
  • Markov decision processes
  • Decision analysis and games theory
  • Queuing theory
  • Goal Programming
  • Nonlinear Programming

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IE 5302 - Introduction to Industrial Engineering

Description:An introduction to the fundamental principles of Industrial Engineering. Topics include Human Factors Engineering, Metrics and Measurement, Production and Inventory Control, Quality Systems, Simulation and Optimization, and Facilities Planning and Design.

Prerequisite: Graduate Standing.

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IE 5303 - Quality Systems

Description:Principles and practices of industrial quality control. Topics include the Deming philosophy, process improvements, statistical process control, process capability analysis and product acceptance.

Prerequisite: IE 3301, or IE 5317, or equivalent.

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IE 5304 - Advanced Engineering Economy

Description: Analysis of capital investments in engineering and technical projects. Topics include decision analysis methods, cash flows, revenue requirements, activity-based analysis, multi-attribute decisions, probabilistic analysis and sensitivity/risk analysis.

Prerequisite: graduate standing.

Student Learning Outcomes:

  • The students will be able to determine the equivalent value of money at a specified time given the timing of deposits and the assumed time value of funds.
  • The students will be able to select the most attractive interest rate offered by various lending institutions in various compound and simple interest forms.
  • The students will be able to determine if an independent investment opportunity is economically attractive.
  • The student will be able to determine the least-cost alternative of multiple solutions in a cost comparison scenario.
  • The students will be able to identify the best project(s) to perform from a set of potential projects that are all independently economically attractive.

Topics Covered:

  • Introduction to engineering economy
  • Interest factors and equivalence
  • Depreciation and depreciation models
  • Tax considerations
  • Evaluation of a single investment (internal rate of return, net present value, cash flows, etc.)
  • Revenue requirements
  • Capital budgeting
  • Break-even models (linear and nonlinear)
  • Cost comparisons
  • Replacement analysis

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IE 5305 - Linear Programming

Description:Theory and applications of linear programming including linear programming formulation, the simplex method, duality, revised simplex, general linear programs, infeasibility, the dual simplex method, column generation, and network flow problems

Prerequisite: IE 3315 or IE 5301.

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IE 5306 - Dynamic Optimization

Description: Dynamic optimization methods including dynamic programming, the calculus of variations, and optimal control theory. Emphasis is on the modeling and solution of practical problems using these techniques.

Prerequisites: IE 3301 and IE 3315, or IE 5317, or equivalent.

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IE 5307 - Queueing Theory

Description:The fundamentals of queueing theory including Markovian birth-death models, networks of queues, and general arrival and service distributions.

Prerequisites: IE 3301 or IE 5317, or equivalent.

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IE 5309 - Stochastic Processes

Description: The study of probabilistic model building including the fundamentals of both discrete and continuous Markov chains, queueing theory and renewal theory.

Prerequisites: IE 3301 or IE 5317, or equivalent.

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IE 5310 - Production Systems Design

Description: Methods for the design and analysis of manufacturing and logistics systems. Emphasis is placed on reducing cycle time, increasing throughput, lowering variation, and improving both quality and customer responsiveness through modeling techniques.

Prerequisites: IE 5317 or equivalent, IE 5301 or concurrent and IE 5329 or concurrent or equivalent.

Student Learning Outcomes: This course is designed for the student already knowledgeable of basic queuing theory, inventory control, and probability models. By the end of the course, the student will be able to analyze and evaluate the underlying behavior of manufacturing systems using a systematic approach.

Topics Covered:

  • Philosophy of Factory Physics, Modeling & Basic Manufacturing Principles
  • Manufacturing Systems in America
  • JIT and Lessons From History
  • Factory Objectives, Measures, & Controls
  • The Basics of Variability & Its Corrupting Influence
  • Push & Pull Production Systems, "Lean" Manufacturing
  • People – the Human Element
  • Principles in Practice: TQM, CONWIP, Supply Chain and Capacity Issues, etc.
  • Synthesis – "Putting It All Together"

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IE 5311 - Decision Analysis

Description:A survey of methods for making optimal decisions. Topics include decision models, formal logic, fuzzy controls, statistical decision theory, game theory, multiobjective decisions, stochastic programming, information theory and qualitative aspects of the decisions.

Prerequisites: IE 5301 or concurrent.

Student Learning Outcomes: This course is designed to develop decision-making skills using logical reasoning and quantitative methods.

  • By the end of this course, you should be able to:
  • Analyze statements for their logical consistency.
  • Derive valid conclusions from given assumptions.
  • Understand fuzzy reasoning for subjective information.
  • Design a simple fuzzy control system.
  • Quantify subjective preferences through utility theory.
  • Calculate rational game theoretic decisions in competitive situations.
  • Use Bayesian methods for decision making and for estimating statistical parameter and testing hypotheses.
  • Understand the limits of human decision making and be able to recognize common decion-making errors.

Topics Covered:

  • Sentential logic
  • Fuzzy logic and control
  • Various Decision criteria
  • Take-home quiz 1
  • Utility theory
  • Game theory
  • Statistical decision theory
  • Information theory
  • Errors in decision making
  • Limits of decision making

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IE 5312 - Planning and Control of Enterprise Systems

Description:A continuation of IE 5329 covering enterprise resource planning systems (ERP) and other advanced production control techniques. Computer modeling is emphasized.

Prerequisites: IE 5329.

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IE 5313 - Reliability and Advanced Quality Control Topics

Description: Includes advanced quantitative topics in reliability design and quality control. Management of reliability and quality control functions are also included.

Prerequisites: IE 4308 or IE 5303.

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IE 5314 - Safety Engineering

Description: Methods to identify, measure, analyze, and evaluate safety hazards in the workplace. Scientific and managerial methods to prevent or control safety hazards.

Prerequisites: Graduate Standing.

Topics Covered:

  • Safety and Health Programs - Development
  • Accident and their Effects
  • Theories of Accident Causation
  • SHAct, Standards, and Liability
  • Worker's Compensation
  • Standards, codes, and other safety documents
  • International Standards Organization (ISO)
  • Standards for controlling stress due to noise, vibration, heat and cold
  • Product Safety and Liability
  • Ethics and Safety
  • Planning for Emergencies
  • Safety Analysis and Prevention (Hazards and their Control)
  • Warnings
  • Quantifying Plant Safety
  • Accident Investigations
  • Promoting Safety - Management and its Responsibilities
  • Ergonomics and Personnel Characteristics
  • Stress and Safety
  • Environments
  • Selected sections from the following topics:
    • Heat and Cold Stress
    • Accelerations, falls, falling objects, and other impacts
    • Mechanical injuries
    • Pressure hazards
    • Electrical hazards

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IE 5317 - Introduction to Statistics

Description: Topics include descriptive statistics, set theory, combinatorics, mathematical expectation, probability distributions, confidence interval estimation, regression analysis, analysis of variance, and design of experiments.

Prerequisites: Math 2326 or equivalent and permission of advisor.

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IE 5318 - Applied Regression Analysis

Description: An in-depth study of one predictor variable followed by the matrix approach to multiple linear regression. Topics include estimation, prediction, analysis of variance, residual analysis, transformations, multicollinearity, model selection, weighted least squares, ridge regression, and robust regression.

Prerequisites: IE 3301 or IE 5317 or equivalent.

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IE 5319 - Advanced Statistical Process Control and Time Series Analysis

Description: Design of control schemes for statistical monitoring and control of modern manufacturing systems. Topics include charts for process control, effect of autocorrelation on SPC charts, and sampling plans for acceptance inspection.

Prerequisites: IE 3301 and IE 5303 or equivalent.

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IE 5320 - Enterprise Engineering Methods

Description: A survey of enterprise engineering methods. Topics include system development methodology, discussion of enterprise architectures, activity modeling, business modeling, activity-based performance analysis, and process improvement.

Prerequisites: Graduate Standing.

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IE 5321 - Enterprise Analysis and Design

Description: An in-depth study of techniques useful for the analysis and design of the manufacturing enterprise. This course presents an advanced process description technique that is used, with simulation and activity based costing, to facilitate analysis and design.

Prerequisites: IE 5320 and IE 5322, or concurrent enrollment.

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IE 5322 - Simulation and Optimization

Description: An in-depth study of discrete event simulation theory and practice. Optimization and search techniques used in conjunction with simulation experiments are introduced. A commercial simulation software application is used.

Prerequisite: IE 5317 or equivalent.

Student Learning Outcome:

  • The students will be able to manually replicate the execution of a Discrete-Event Simulation Engine.
  • The students will be able to summarize the various tasks outlined in a Simulation Project Methodology.
  • The students will be able to recall and discuss issues associated with establishing a discrete-event simulation capability within a company.
  • The student will be able to design a computer-based discrete-event simulation model to represent a complex industrial/business/service system.
  • The students will be able to analyze the output of a simulation model in order to verify the appropriateness of the model’s performance.
  • The students will be able to evaluate various system configurations to determine the most appropriate system design and/or justify proposed changes to a given system.

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IE 5326 - Industrial Biomechanics

Description:The development and application of biomechanical models of physical work tasks, especially manual materials handling and hard-arm work activities.

Prerequisites: Graduate Standing.

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IE 5329 - Production and Inventory Control Systems

Description: The fundamentals of production and inventory control systems. The economic impacts of fluctuating demand, supply availability and production rates are examined.

Prerequisites: Graduate Standing.

Student Learning Outcomes:

  • Identify and solve appropriate inventory control model problems given demand characteristics.
  • Use MRP to devise a manufacturing schedule.
  • Identify the basic metrics of a factory and describe their relationships.
  • Measure and explain the effects of variability on a manufacturing system.
  • Compare and contrast push versus pull systems.
  • Compute a schedule of jobs and evaluate the schedule effectiveness.

Topics Covered:

  1. Manufacturing in America(.5 classes)
  2. Factory Physics? (.5 classes)
  3. Inventory Control: From EOQ to ROP (6 classes)
  4. The MRP Crusade (2 classes)
  5. The JIT Revolution (2 classes)
  6. Basic Factory Dynamics (2 classes)
  7. Variability Basics (3classes)
  8. The Corrupting Influence of Variability (3 classes)
  9. Push and Pull Production Systems (1 class)
  10. A Pull Planning Framework (4 classes)
  11. Production Scheduling (3 classes)

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IE 5330 - Automation and Advanced Manufacturing

Description: The design of automated and advanced production processes for manufacturing. Topics include numerical control, robotics, group technology, just-in-time, automated inspection and flexible manufacturing systems.

Prerequisites: graduate standing.

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IE 5331 - Industrial Ergonomics

Description:The analysis and design of physical work, workplace, and hand tools using ergonomic principles for enhancing performance, health, and safety. Work refers mainly to whole body and hand-arm activities, while workplace refers to industrial and computerized office environments. Applications focus on people's anthropometric, musculoskeletal and psychological characteristics.

Prerequisites: Graduate standing.

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IE 5332 - Nonlinear Programming

Description: Methods for nonlinear optimization including classical theory; gradient methods; sequential unconstrained methods; convex programming; genetic algorithms; simulated annealing; and separable, quadratic, and geometric programming.

Prerequisites: graduate standing.

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IE 5333 - Logistics Transportation Systems Design

Description: The design and analysis of domestic and international transportation systems of people, processes, and technology. Topics include the role of transportation in the extended enterprise, transportation modeling and optimization techniques, value-added supply chain issues, and financial performance measures.

Prerequisites: IE 5317 or equivalent, IE 5301 or concurrent, and 5329 or concurrent, or equivalent.

Student Learning Outcomes: This course is designed for the student already knowledgeable of basic queuing theory, inventory control, and probability models. By the end of the course, the student will be able to analyze and evaluate the underlying behavior of logistics transportation systems and integrated supply chain networks using a systematic approach.

Topics Covered:

  • Intro to Supply Chain Management and Value-Added Supply Chain Issues
  • Logistics Network Configuration
  • Procurement & Outsourcing, Transportation Systems (Rail, Air, Trucking, etc.)
  • International Issues in Logistics
  • Information Technology and Decision Support Systems
  • Supply-Chain Integration, Strategic Alliances

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IE 5334 - Logistics Distribution Systems Design

Description: The design and analysis of distribution systems of people, processes and technology. The focus is on distribution, warehousing and material handling. Topics include the role of the warehouse in the extended enterprise, warehouse planning, process design, layout, equipment selection, workforce and workplace issues, and financial performance measures.

Prerequisites: IE 5317 or equivalent, IE 5301 or concurrent, and IE 5329 or concurrent, or equivalent.

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IE 5335 - Advanced Occupational Environmental Hygiene Engineering

Description: Interaction of workers with physical environmental agents such as heat, cold, noise, vibration, illumination, radiation, and gravity. The design of work and the workplace to control environmental stresses, and their effects on workers' performance, health and safety.

Prerequisites: graduate standing.

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IE 5338 - Human Engineering

Description: Human structural, physiological, psychological, and cognitive capacities and limitations in the workplace, and their effects on the design of work systems to enhance productivity, and maintain health and safety.

Prerequisites: IE 3301 or equivalent, or consent of instructor.

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IE 5339 - Product Design, Development, Producibility, and Reliability Design

Description: This course covers product development and engineering design process with a focus on collaborative design. Software, manufacturing, reliability, testing, logistical and product support considerations are emphasized.

Prerequisites: Graduate Standing.

Student Learning Outcomes:

  1. Students will demonstrate an understanding of the terminology, acronyms and concepts of product development, producibility and reliability.
  2. For this area of knowledge, the objectives include ABET criteria of
  3. Recognition of the need for, and an ability to engage in life-long learning
  4. Knowledge of contemporary issues (current, modern)
  5. Ability to use the techniques, skills, & modern engineering tools necessary for engineering practice

Last Updated: For Fall 2010 Semester

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IE 5342 - Metrics and Measurement

Description: Work measurement, methods improvements, and performance measurement. A survey of enterprise and management measurement systems is presented.

Prerequisites: IE 5317 or equivalent.

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IE 5345 - Management of Knowledge and Technology

Description: Review of contemporary issues in knowledge management, databases, decision support systems, and intelligent systems. Topics include knowledge acquisition, intelligent database design, decision support systems, data mining, knowledge transfer, and collaborative development.

Prerequisites: Graduate Standing.

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IE 5346 - Technology Development and Deployment

Description: Review of management issues in developing and implementing new technologies and methodologies into an organization. Topics include technology forecasting, management of technology based projects, technological competitiveness, technology alliances, and collaboration.

Prerequisites: Graduate Standing.

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IE 5350 - Graduate Design Capstone

Description: Practicum in Industrial Engineering techniques consisting of professional level experience in a relevant company, agency, or institution. This technical experience is directed by a supervising professor and requires the writing of a professional report.

Prerequisites: 24 hours of graduate work in Industrial Engineering.

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IE 5351 - Introduction to Systems Engineering

Description: This course includes a survey of concepts, principles and processes required to engineer complex systems throughout the life-cycle from concept through disposal.

Prerequisites: graduate standing and permission of advisor.

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IE 5352 - Systems Engineering I

Description: A study of systems engineering topics including technical planning and management, supply processes, requirements definition and analysis, functional analysis, and trade-off analysis.

Prerequisites: IE 5351.

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IE 5353 - Systems Engineering II

Description: A continuation of IE 5352. Topics include risk management, systems design and implementation, acquisition processes, assessment and control, earned value management, technical process management, and enabling products.

Prerequisites: IE 5352.

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IE 5354 - Systems Engineering III

Description: A continuation of IE 5353. Topics include system verification, validation and transition to use, specialty engineering, improving SE processes, SE and relationships to international programs, object oriented systems engineering and configuration management. A comprehensive student project it required.

Prerequisites: IE 5353.

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IE 5391 - Advanced Studies in Industrial Engineering

Description: Individually approved research projects and reading courses in industrial engineering. Such individual studies will be graded A, B, C, D, F or X. Subject to the approval of the Graduate Advisor, IE 5191, 5291 and 5391 may be repeated as the topics change. In addition, work on a thesis substitute will be performed under IE 5391. In this case, IE 5391 is graded P/F/R.

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IE 5398 - Thesis

Description: Graded F, R.

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IE 5698 - Thesis

Description: Graded P, F, R.

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IE 6197 - Research in Industrial Engineering

Description: Supervised research projects directed toward the dissertation. Graded P, R, F.

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IE 6297 - Research in Industrial Engineering

Description: Supervised research projects directed toward the dissertation. Graded P, R, F.

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IE 6301 - Enterprise Architectures and Frameworks

Description: A survey of enterprise architectures and analysis frameworks that have been proposed for the integration of large complex enterprise systems. Emphasis is placed on state-of-the-art approaches.

Prerequisites: IE 5320.

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IE 6302 - Facilities Planning and Design

Description: Facilities planning through layout design. Product flow, space-activity relationships, personnel requirements, and material handling are considered, as well as receiving, shipping, warehousing, and integration with manufacturing. Facilities planning models are explored.

Prerequisite: IE 5317 or equivalient, IE 5301 or concurrent, and IE 5339, or concurrent or equivalent.

Student Learning Outcomes: This course is designed to develop facilities planning and layout skills, including the ability to apply quantitative methods to decision-making in the areas of selecting, preparing, presenting, and implementing facilities plans. These skills have broad applications and can be useful for the planning and design of a manufacturing enterprise, hospital, airport, warehouse/distribution center, bank, office, retail store, etc.

  • By the end of the course, you should be able to:
  • Explain the "Winning Facilities Planning Process"
  • Determine product, process, and schedule design interactions & Develop personnel requirements
  • Analyze flow, space, and activity relationships with impact to material handling and layout alternatives
  • Integrate receiving, shipping, warehousing with manufacturing and supporting operations
  • Apply standards of professional and ethical responsibility
  • Prepare and present a detailed facilities planning project report and layout documenting all steps taken (define problem, generate alternatives, evaluate, select) including justification of your final recommendation.

Topics Covered:

  • Strategic Facilities Planning
  • Product, Process, and Schedule Design
  • Flow, Space, and Activity Relationships
  • Personnel Requirements, Material Handling, and Layout
  • Receiving, Shipping, Warehousing and Integration with Manufacturing and Supporting Operations
  • Facilities Planning Models; Evaluating, Selecting, Preparing, Presenting, and Implementing the Facilities Plan

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IE 6303 - Combinatorial Optimization

Description: A survey of problems and algorithms in combinatorial optimization. Topics include integer programming formulation, branch-and-bound and cutting plane algorithms, computational complexity, and polyhedral theory.

Prerequisites: IE 5301 or consent of instructor.

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IE 6305 - Engineering Management I

Description: The management of the engineering function in high-technology industry with principal emphasis on the historical development of industrial management principles, decision-making and planning.

Prerequisites: Graduate standing.

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IE 6306 - Engineering Management II

Description: The management of the engineering function in high-technology industry with principal emphasis on human resources and staffing, directing and leading, and controlling.

Prerequisites: IE 6305.

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IE 6308 - Design of Experiments

Description:Introduction to statistical design and analysis of experiments with applications from engineering, health care and business. Analysis includes analysis of variance, multiple comparisons and model adequacy. Designs include complete factorial, complete block, incomplete block, Latin square, Youden, two-level fractional factorial and hierarchically nested.

Prerequisites: IE 5318 or consent of instructor.

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IE 6309 - Response Surface Methodology and Computer Experiments

Description: Empirical model building and process optimization using experimental design and statistical modeling. The first half of the course covers first and second order models and designs, multi-response experiments and mixture experiments. The second half introduces designs based on Latin hypercubes, orthogonal arrays, and number-based theoretic methods, plus models using kriging, multivariate adaptive regression splines and neural networks.

Prerequisites: IE 6308

Student Learning Outcomes:

  1. At the end of this course, students should be able to:
  2. Understand fundamental concepts of matching experimental designs with analysis models.
  3. Recognize types of experimental designs and analysis models.
  4. Perform and interpret a proper response surface analysis.
  5. Perform and interpret a proper computer experiment study.

Topics Covered:

  • Response SurfaceMethodology(RSM)
  • 1.2First-OrderModels
    • SecondOrderModels
  • 1.4MultiresponseExperiments
  • 1.5MixtureExperiments
  • Design and Analysis of Computer Experiments(DACE)

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IE 6310 - Industrial Applications

Description: Project oriented course focusing on the requirements and selection criteria for the integration of technology into simple and complex industrial activities.

Prerequisites: IE 5330

Student Learning Outcomes: This course will provide an understanding of the relationships between the process and product requirements of a manufacturing activity in order to analyze, design, and develop the concepts needed to put together integrated systems.

Topices Covered: As a project course, the topics depend on the area of focus for that semester. Topics will vary for each semester. Contact the Professor for this year’s topic.

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IE 6397 - Research in Industrial Engineering

Description: Supervised research projects directed toward the dissertation. Graded P, R, F.

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IE 6399 - Dissertation

Description: Graded F, R.

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IE 6697 - Research in Industrial Engineering

Description: Supervised research projects directed toward the dissertation. Graded P, R, F.

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IE 6699 - Dissertation

Description: Graded F, R, P, W.

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IE 6997 - Research in Industrial Engineering

Description: Supervised research projects directed toward the dissertation. Graded P, R, F.

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IE 6999 - Dissertation

Description: Graded P, F, R.

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IE 7399 - Doctoral Degree Completion

Description:This course may be taken during the semester in which a student expects to complete all requirements for the doctoral degree and graduate. Enrolling in this course meets minimum enrollment requirements for graduation, for holding fellowships awarded by The Office of Graduate Studies and for full-time GTA or GRA positions. Students should verify that enrollment in this course meets other applicable enrollment requirements. To remain eligible in their final semester of study for grants, loans or other forms of financial aid administered by the Financial Aid Office must enroll in a minimum of 5 hours as required by the Office of Financial Aid. Other funding sources may also require more than 3-hours of enrollment. Additional hours may also be required to meet to requirements set by immigration law or by the policies of the student's degree program. Students should contact the Financial Aid Office, other sources of funding, Office of International Education and/or their graduate advisor to verify enrollment requirements before registering for this course. This course may only be taken once and may not be repeated. Students who do not complete all graduation requirements while enrolled in this course must enroll in a minimum of 6 dissertation hours (6699 or 6999) in their graduation term. Graded P/F/R.

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