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2014-2015 Undergraduate Academic Catalog [ARCHIVED CATALOG]
Course Descriptions
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Industrial Engineering |
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IE 100 - Introduction to Industrial Engineering Profession 2 lecture hours 2 lab hours 3 credits
Course Description
This course is an introduction to the field of Industrial Engineering. The course introduces the student to a number of career paths in industry such as management engineering, quality, logistics, process improvement manager, etc., using guest speakers and tours to provide first-hand experience. This course will also introduce students to the common terminology used in Industrial Engineering as well as examine current trends in Industrial Engineering.
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• define and explain common industrial engineering terminology
• give examples of career opportunities in industrial engineering
• be aware of historic, contemporary, and futuristic perspectives of industrial engineering
• be aware of contemporary industrial engineering initiatives to reinvent and improve enterprises
Prerequisites by Topic
• None required
Course Topics
• Historic and contemporary views of IE (1.5 weeks)
• Engineering ethics (0.5 weeks)
• Quality (1 week)
• Process fundamentals and improvement perspectives (1 week)
• Ergonomics (1 week)
• Operations research and logistics (1 week)
• Management and leadership (1 week)
• Healthcare (1 week)
• Manufacturing (1 week)
• Contemporary IE initiatives and future trends (1 week)
Laboratory Topics
• A weekly two-hour lab will give time for a course project and multiple exercises aimed at developing student understanding of the field of Industrial Engineering
Coordinator
Charlene Yauch
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IE 193 - Computer Applications in Industrial Engineering 2 lecture hours 2 lab hours 3 credits
Course Description
This course provides basic familiarization, instruction, and competence with common computer applications used in the field of Industrial Engineering. The purpose of the course is to provide a student with expertise in using computational tools. These tools will be used in multiple subsequent courses and throughout the student’s career. The course will provide instruction in the use of these tools and laboratory time to practice their use while deepening understanding and expertise.
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• demonstrate Excel skills including descriptive statistics, use of the analysis toolpak, lookup functions, and pivot tables.
• be proficient at programming including macro recording, logic and conditional operators, procedures and subroutines, the object model, strings, loops, forms, and error handling.
• demonstrate basic skills using Access including creating a database and linking it to Excel.
Prerequisites by Topic
• None required
Course Topics
• Excel (5 weeks)
• General Programming (2 weeks)
• MS Visual Studio (3 weeks)
Laboratory Topics
• A weekly two-hour lab will use defined projects to exercise student skills as defined in the Course Outcome section
Coordinator
Charlene Yauch
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IE 203 - Applications of Statistics in Industrial Engineering 2 lecture hours 2 lab hours 3 credits
Course Description
This course emphasizes the importance and relevance of statistics in the field of Industrial Engineering. The purpose of the course is to further student understanding of applications of statistics in engineering. The course will concentrate on data collection, analysis and inference using statistical methods. A state-of-the-art statistics package will be used so that meaningful problems can be addressed. The course will provide instruction in the use of these tools and laboratory time to practice their use while deepening understanding and expertise. (prereq: MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• describe and define basic statistical terminology
• perform statistical analyses including identifying and working with probability distributions
• understand how and why statistics are an integral part of an engineering analysis
• draw inferences from data obtained by testing components and systems
• improve communications skills, both written and verbal
• understand the value of life-long learning and personal growth and development
Prerequisites by Topic
• Good understanding of probability, statistical distributions, hypothesis testing, and analysis of variance
Course Topics
• Minitab (1 week)
• Measurement error and propagation (1 week)
• Confidence intervals (1 week)
• Hypothesis testing (2 weeks)
• Correlation and linear regression (2 weeks)
• Multiple regression (1 week)
• Experimental design (2 weeks)
Laboratory Topics
• A weekly two-hour lab will use defined projects to exercise student skills as defined in the Course Outcome section
Coordinator
Aaron Armstrong
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IE 312 - Research Methods 3 lecture hours 0 lab hours 3 credits
Course Description
An introduction to scientific research methods for students interested in academic research, R & D, or analyzing and evaluating open-ended problems in business and industry. Topics covered will include planning a research study, gathering data, analyzing data, and presenting results, as well as development of interviews and surveys, reliability and validity, and quantitative and qualitative measurement methods. (prereq: junior standing in an engineering program)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• summarize the major steps involved in conducting scientific research
• give examples of different types of research
• plan a research study
• give examples of the different types of data that can be collected (quantitative and qualitative) and identify corresponding data collection techniques
• give examples of the different types of analysis that can be done
• describe critical issues related to the development of interviews and surveys
• explain reliability, validity, and research limitations
• appraise and criticize others’ research through a peer review process
• discuss substantive issues related to a research topic
• present results from a research study in a written report and an oral presentation
Prerequisites by Topic
• None required
Course Topics
• Overview of scientific research and research methods (1 week)
• Literature review (1 week)
• Experimental research (1 week)
• Interviews, surveys, and human subjects (1 week)
• Collection and analysis of data (1 week)
• Limitations of research and reporting results (1 week)
• Peer review (1 week)
• Publications and funding proposals (1 week)
• Corporate R&D (1 week)
• Presentation of student research projects (1 week)
Coordinator
Charlene Yauch
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IE 331 - Production Planning and Inventory Control 3 lecture hours 0 lab hours 3 credits
Course Description
Many businesses, including those in manufacturing, retail, and logistics, rely on Enterprise Resource Planning (ERP) systems for production control. This course provides a comprehensive review of the material planning and production control modules within an ERP system. Topics include forecasting, operations planning, master scheduling, and inventory control. It introduces students to the ERP software from SAP and compares traditional MRP approaches to newer approaches such as kanban. (prereq: MA 262 , junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• define and explain common terminology related to production planning and control
• utilize common forecasting techniques to predict future demand
• understand the EOQ model and trade-offs between lot size and other system parameters (capacity, utilization, lead time)
• manually apply the MRP algorithm with various lot sizing rules to generate planned order releases
• perform rough-cut capacity planning and calculate relevant system parameters such as capacity, utilization, and efficiency
• describe the difference between push and pull production systems and explain how various pull systems operate (kanban, conwip, POLCA)
• relate the Theory of Constraints to production planning and control activities
• utilize SAP software to analyze data from a sample company and perform common production control transactions
Prerequisites by Topic
• Basic understanding of statistics, variability, and linear regression
Course Topics
• Overview of production planning and inventory control (2 weeks)
• Overview of SAP software (3 weeks)
• Forecasting (2 weeks)
• Sales and operations planning (2 weeks)
• Master scheduling (2 weeks)
• Inventory management and MRP (2 weeks)
• Capacity management (1 week)
• Production activity control (0.5 weeks)
• Lean and JIT (0.5 weeks)
• Theory of Constraints (1 week)
Laboratory Topics
• No laboratory in this course
Coordinator
Charlene Yauch
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IE 336 - Contemporary Manufacturing Systems 2 lecture hours 2 lab hours 3 credits
Course Description
Contemporary manufacturing is viewed as an integrated system designed for maximum flexibility and rapid responsiveness. This course presents topics related to the design and analysis of manufacturing systems, including system improvement initiatives such as Lean and Quick Response Manufacturing. Laboratory exercises are included to enable students to practice techniques and analyze how various changes impact overall manufacturing system effectiveness. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• describe historic and contemporary perspectives of manufacturing systems.
• compare and contrast manufacturing systems.
• compare and contrast contemporary manufacturing system improvement philosophies.
• identify and analyze important issues and decisions related to contemporary manufacturing systems.
• form alternative potential improvements to contemporary manufacturing systems.
• demonstrate knowledge of contemporary manufacturing systems either by redesigning a system or preparing a case study.
• examine the long-term costs and consequences associated with proposed changes to manufacturing systems, including considerations of sustainability.
• demonstrate written and graphical communication skills.
Prerequisites by Topic
• None required
Course Topics
• Manufacturing strategy and history (1 week)
• Flexibility and automation (0.5 weeks)
• Agile and virtual manufacturing (0.5 weeks)
• Lean manufacturing and value stream mapping (1.5 weeks)
• Quick response manufacturing (1 week)
• Concurrent engineering and design for assembly (1 week)
• Mass customization (1 week)
• Global and environmental issues (1.5 weeks)
• Project work and exams (1.5 weeks)
Laboratory Topics
• A weekly 2-hour lab is used for physical and computer simulations, demonstrations, and exercises that reinforce the course topics.
Coordinator
Charlene Yauch
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IE 340 - Project Management 3 lecture hours 0 lab hours 3 credits
Course Description
This course will enable the student to gain an understanding of the mechanics of guiding an engineering project from the initiation phase through project implementation and, finally, termination. The class will focus on the application of project management tools to engineering oriented projects, including the role of technology and the balance between cost, schedule and technical performance. (prereq: MA 262 or equivalent)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand the general issues related to the management of engineering oriented projects
• plan and develop the project objectives, scope and boundaries of a project with regard to the triple constraint of technical performance, cost and schedule
• use the Critical Path Method (CPM) and Activity on Node (AON) in the development of the project schedule
• identify and develop project metrics and deliverables
• define the project by creating the work breakdown structure, responsibility matrix and communication plan
• develop the project budget and understand how resources are allocated to a project
• understand how to monitor, control, evaluate and terminate the project
• better understand the various roles one may assume on an engineering team, including the responsibilities of the project manager
Prerequisites by Topic
• Basic understanding of probability and statistics.
Course Topics
• Introduction to Project Management in an engineering context and the characteristics of an Effective Project Manager (PM) including PM’s Roles and Responsibilities (1 week)
• Planning the Project - Project Charter, Project Initiation (including objective, scope, boundaries, triple contraint, stakeholders, project metric and deliverables), Communication Plan (2 weeks)
• Defining the Project - Work Breakdown structure, Responsibility Matrix and Project Accountability (2 weeks)
• Budgeting the Project (1 week)
• Scheduling the Project, including Critical Path Method (CPM) and Activity on Node (AON) (1 week)
• Allocating Resources to the Project, Monitoring and Controlling the Project, Evaluating and Terminating the Project (2 weeks)
• Leadership and Motivation (1 week)
Coordinator
Leah Newman
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IE 347 - Facilities Design 3 lecture hours 2 lab hours 4 credits
Course Description
This course covers facility layout planning methods, as well as the inter-relationships between physical layouts (of facilities, departments, or work cells), process flows, and material handling systems. Students learn techniques for generating and evaluating facility layout solutions and are introduced to analysis methods and decision factors for selecting a facility location. (prereq: junior standing, AE 1311 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• generate and evaluate solutions to facilities layout problems using both analytical and qualitative techniques
• generate and evaluate detailed layouts for manufacturing cells
• utilize the simplified systematic layout planning or systematic planning of manufacturing cells techniques on a real-world facility design project
• present 2-dimensional detailed layouts using CAD software
• understand both analytical and qualitative solution approaches to facilities location problems, as well as significant criteria to be considered
• present facility design project information orally and verbally in class presentations and a formal technical report
Prerequisites by Topic
• two-dimensional drawing with CAD software
Course Topics
• Overview of facilities design and introduction to course project (0.5 weeks)
• Simplified systematic layout planning (1.5 weeks)
• Manufacturing cells and systematic planning of cells (1 week)
• Equipment and flow analysis (0.5 weeks)
• Cell layout planning and detailed cell plans (2 weeks)
• Project planning and implementation (0.5 weeks)
• Personnel requirements and infrastructure systems (0.5 weeks)
• Layout algorithms (0.5 weeks)
• Warehouse layouts (0.5 weeks)
• Facility location models and site selection (0.5 weeks)
• Project work and class presentations (2 weeks)
Laboratory Topics
• A weekly 2-hour lab is used primarily for work on the course project, which is typically development of a facility layout for an industry client. The time is used for client visits, team meetings, and preparation of the project deliverables
Coordinator
Charlene Yauch
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IE 348 - Quality Assurance (SPC) 3 lecture hours 0 lab hours 3 credits
Course Description
Improved quality has been identified as one of the most critical issues facing business today, essential to assuring competitiveness in a global economy. While emphasis is placed upon the techniques of statistical process control and acceptance sampling, the course also details other graphical tools of quality analysis, explicitly connecting quality to productivity and costs. The course is intended to present quality concepts, tools and techniques in sufficient breadth so as to be applicable to both manufacturing and the service sector. (prereq: MA 262 , IE 203 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• discuss the importance of quality improvement as a strategic management issue
• list the fundamental concepts and techniques advanced by Deming, Juran, Fiegenbaum, and Crosby
• successfully characterize and evaluate process capability
• specify, create, implement, and interpret fundamental variables and attributes control charts
• utilize graphical methods for efficient data analysis and problem solving
• develop acceptance sampling plan OC curves
• specify and interpret basic acceptance sampling systems such as ANSI/ASQC Z1.9
• design appropriate quality control systems
• define the relationship between statistical design of experiments and process control techniques
• apply QA techniques to both manufacturing and service sectors
• improve communications skills
Prerequisites by Topic
• Good understanding of statistical distributions, variability, and using software to do hypothesis testing, analysis of variance, and conduct and interpret other statistical tests
Course Topics
• What is quality? (1 week)
• How is quality defined (1 week)
• Quality improvement (1 week)
• The DMAIC process (1 week)
• Methods and philosophy of SPC (1 week)
• Control charts for variables (1 week)
• Control charts for attributes (1 week)
• System capability analysis (1 week)
• CUSUM and EWMA charts (1 week)
• Acceptance sampling (1 week)
Laboratory Topics
• No laboratory in this course
Coordinator
Aaron Armstrong
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IE 377 - Safety in Engineering 3 lecture hours 0 lab hours 3 credits
Course Description
This course is designed to prepare the student for a leadership role in management to proactively and aggressively apply basic principles of safety in order to protect the occupational health of the workforce and the general public while improving the company’s bottom line. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• identify a variety of occupational hazards.
• apply analytical tools to define occupational hazards.
• apply intervention strategies for ameliorating occupational hazards.
• find information and other resources regarding occupational hazards.
• understand how to solve problems related to safety and occupational health, and how to present aforementioned information.
• better understand the critical value of lifelong learning.
Prerequisites by Topic
• None
Course Topics
• Introduction to safety, historical background, trends in safety engineering, safety roles (organization, employees, regulation) (1.5 weeks)
• Occupational Safety and Health (OSH) legislation (1 week)
• Worker’s compensation, economic aspects of OSH (1 week)
• Accident causation (1 week)
• Record keeping and analysis (.5 week)
• Hazard analysis (.5 week)
• Risk perception, human error and reliability (1 week)
• Safety inspections (.5 week)
• Mechanical and other hazards, hazardous substances, materials handling (1 week)
• Cumulative trauma and other ergonomic issues (1 week)
• Employee training, motivation and attitudes, developing a successful safety program (1 week)
Coordinator
Leah Newman
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IE 381 - Deterministic Modeling and Optimization 3 lecture hours 0 lab hours 3 credits
Course Description
Modeling requires building a logical or mathematical representation of a system and using the model to assist the decision making process. This course examines modeling techniques for systems in which the variables influencing performance are deterministic (non-random). These techniques include linear programming, transportation and assignment algorithms, inventory models and network analysis. Case studies and computer algorithms are utilized. (prereq: MA 127 , junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand, develop, and apply deterministic (non-random) mathematical models to engineering and operational problems
• use these models to assist the decision-making process
• develop an understanding of how these methods impact business and industry
• use computer software to solve these engineering problems
• improve problem solving skills
• improve communications skills
Prerequisites by Topic
• College algebra
• Mathematical procedures for solving systems of linear equations
Course Topics
• Introduction to quantitative management (2 classes)
• Graphical solution of linear programming LP problems (4 classes)
• Applications of LP (3 classes)
• Computer solutions to LP problems (2 classes)
• LP sensitivity, duality (3 classes)
• Transportations & assignments algorithms (3 classes)
• Network analysis algorithms (3 classes)
• Inventory control models (4 classes)
• Introduction to integer and goal programming (2 classes)
• Examinations (3 classes)
Laboratory Topics
• No laboratory
Coordinator
Aaron Armstrong
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IE 382 - Stochastic Processes 3 lecture hours 0 lab hours 3 credits
Course Description
This course continues the modeling approach to problem solving by presenting techniques used to analyze and design systems affected by random variables. Queuing theory, Markov processes, and decision theory are examined. Case studies and computer algorithms are utilized. (prereq: MA 262 , junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• identify and apply quantitative analysis techniques to engineering problems
• use quantitative management technique results to analyze alternative solutions and assist in decision making
• develop an understanding of how these methods impact business and industry
• improve problem solving skills
• improve communication skills
Prerequisites by Topic
• Basic understanding of probability theory and probability distributions
Course Topics
• Introduction to Quantitative Management (1 class)
• Probability Review (2 classes)
• Fundamentals of Decision Theory (3 classes)
• Decision Theory and Utility Theory (3 classes)
• Project Management (3 classes)
• Queuing Theory (5 classes)
• Markov Analysis (3 classes)
• Simulation (2 classes)
• Dynamic Programming (5 classes)
• Review (1 class)
• Examinations (2 classes)
Laboratory Topics
• No laboratory in this course
Coordinator
Aaron Armstrong
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IE 383 - Simulation 3 lecture hours 2 lab hours 4 credits
Course Description
Focusing on discrete-event systems, this course incorporates spreadsheets, simulation languages, and simulation software to analyze, design, and improve production and service systems. The simulation process and statistical analysis of input and output are addressed. A strong emphasis is placed on decision making and design. (prereq: IE 382 and IE 193 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• perform simulations of basic manufacturing and service systems
• select, analyze, and/or design processes using simulation
• improve problem solving skills
• improve communication skills
Prerequisites by Topic
• Understanding of probability distributions, queuing theory, computer programming and statistics
Course Topics
• Introduction to Discrete Event Simulation (2 classes)
• Simulation theory and techniques (2 classes)
• Random Number Generation (2 classes)
• Logic of Single-Queue, Single-Server Systems (2 classes)
• Basic Nodes and Control Statements (6 classes)
• Resources and Gates (3 classes)
• Logic and Decision Nodes (4 classes)
• Statistical Analysis (3 classes)
• Simio Software (3 classes)
• Simulation with Excel (3 classes)
• MPX dynamic modeling (3 classes)
• Applications (2 classes)
• Examinations (2 classes)
Laboratory Topics
• To gain familiarity with simulation using Excel and Simio
• A design project may be conducted as a portion of the lab
• Also, visits to companies and guest speakers who use simulation may be scheduled
Coordinator
Aaron Armstrong
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IE 391 - Industrial Engineering Junior Project 2 lecture hours 2 lab hours 3 credits
Course Description
This course is intended to serve as an opportunity for third-year students to apply subjects they have learned thus far to a real-world engineering problem. These problems are sponsored by business/industry and require some choices as to the specific engineering tools that will be used. Following tool selection, data gathering, and analysis, the students are required to reach a recommended solution. Students work in teams under the supervision of a faculty member who leads the students through this problem-solving process. This course is intended to serve as a precursor to the Capstone Engineering Design project courses (IE 4901 and IE 4902 ) scheduled in the senior year. (prereq: two of the following: IE 3621 , IE 348 , or IE 381 ) (coreq: IE 423 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• select tools, gather data, build models, and analyze processes used in projects in business and industry
• exhibit professional behaviors in dealing with external clients
• demonstrate competence in planning and scheduling methods
• demonstrate professional written and verbal presentation techniques
Prerequisites by Topic
• Must have some knowledge of specific industrial engineering techniques that are likely to relate to the course project. Need to have 2 of the following 3 prerequisites: quality control, ergonomics, or operations research. Must also have already taken engineering economics or be taking it as a corequisite so that knowledge of time value of money, value comparisons, and economic decision making for engineering projects can be applied to the junior project
Course Topics
• Working with clients (1 week)
• Project definition, proposal writing, deliverables (1 week)
• Teamwork and leadership styles (1 week)
• Library research (1 week)
• Professional behavior (1 week)
• Planning and scheduling (1 week)
• Data gathering (1 week)
• Tool selection (1 week)
• Model building (1 week)
• Written and verbal presentation techniques
Laboratory Topics
• All laboratory work will be done at the sponsor site or in an MSOE lab, as needed by a particular project
Coordinator
Charlene Yauch
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IE 423 - Engineering Economy 3 lecture hours 0 lab hours 3 credits
Course Description
This subject is intended to provide the fundamental techniques for quantifying engineering and business decisions, especially those in which the time value of money is significant. It deals with cost, value, and work concepts and emphasizes the applications of funds invested in capital assets and facilities and the returns on such investments. (prereq: sophomore standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• analyze and evaluate financial alternatives by determining the worth of systems, products and services in relation to cost
• correctly apply discounted cash-flow analysis to evaluate proposed capital investments
• acquire, analyze and interpret project data
• recognize, formulate and analyze cash-flow models
• determine economic feasibility when evaluating alternatives
• apply sensitivity analysis to economic decision making
• explain the results of the cash flow models to managers and others not versed in engineering economic analysis
Prerequisites by Topic
• College algebra
Course Topics
• Why engineering economy?
• Interest and interest rate
• Rate of return
• Equivalence
• Engineering economics terminology
• Minimum Attractive (or Acceptable) Rate of Return (MARR)
• Cash flows
• Single-payment factors
• Uniform series present worth factor and capital recovery factor
• Sinking fund factor and uniform series compound amount factor
• Interpolation
• Arithmetic gradient factors
• Geometric gradient series factors
• Determination of an unknown interest rate
• Determination of an unknown number of years
• Combining factors
• Nominal and effective interest rates; interest rates varying over time
• Present worth analysis
• Annual worth analysis
• Rate of return analysis
• Benefit-cost ratio analysis
• Breakeven and sensitivity analysis
• Payback period analysis
Laboratory Topics
• No laboratory
Coordinator
Leah Newman
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IE 426 - Materials and Manufacturing Processes 3 lecture hours 2 lab hours 4 credits
Course Description
The properties of materials and transformation of materials into fabricated components and finished goods are the focus of this course. Manufacturing processes studied include bulk deformation, sheet metal processes, plastics processes, metal casting, welding, and others. The course emphasizes the relative advantages and disadvantages of various processing techniques, including economic considerations. (prereq: ME 207 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• distinguish important capabilities and limitations for the following types of manufacturing processes: heat treatment, machining, bulk deformation, metal casting, plastics processes, welding, mechanical assembly, integrated circuit fabrication and electronics assembly
• select an appropriate manufacturing process given part design and relevant parameters
• understand how material properties influence choice of and are affected by manufacturing processes
• develop a manufacturing process plan for a discrete part using one or more of the processes listed in the first bullet (above) that meets acceptable levels of cost and quality
• display part geometry using multiple 2-dimensional views
• present technical information in a formal written report
Prerequisites by Topic
• Basic chemistry
• Mechanics of materials
Course Topics
• Materials and heat treatment (1.5 weeks)
• Measurement and surfaces (.5 weeks)
• Sheet metal processes (.5 weeks)
• Metal casting (1 week)
• Machining (2 weeks)
• Bulk deformation (.5 weeks)
• Polymers and plastics processes (1 week)
• Welding (1 week)
• Mechanical assembly (.5 weeks)
• Integrated circuit and electronics manufacturing (.5 weeks)
• Non-traditional processes and/or micro- and nano-fabrication (up to 1 week, if time permits)
Laboratory Topics
• Sand casting
• Machining
• Welding
• Materials testing (tensile strength, hardness, roughness)
• Plastics
• Plant tour
• Process selection and project work
Coordinator
Charlene Yauch
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IE 431 - Six Sigma Methods 3 lecture hours 0 lab hours 3 credits
Course Description
Six Sigma incorporates statistical tools and a continuous improvement philosophy to provide a powerful methodology for eliminating waste, improving processes and ultimately, increasing the financial performance of an organization. This course introduces the student to the basic Six Sigma methodology including the statistical techniques necessary to implement and complete a Six Sigma project. Students will be expected to complete a project and may earn a Six Sigma green belt certification upon successful completion of the course. (prereq: junior standing, MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand and define Six Sigma terminology
• understand and perform the five steps of the Six Sigma methodology (DMAIC)
• complete a team-based project involving the design, construction, testing, and improvement of a small system
• develop an understanding of how these methods impact business and industry
• use computer software to solve engineering problems
• improve problem solving skills
• improve communications skills by writing a formal report and making an oral presentation and demonstration of a working system
Prerequisites by Topic
• Basic understanding of probability, statistical distributions, and analysis of variance
Course Topics
• Define stage (1.5 weeks)
• Measure stage (2.5 weeks)
• Analyze stage (4 weeks)
• Improve stage (1.5 weeks)
• Control stage (1 week)
Coordinator
Charlene Yauch
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IE 440 - Team Leadership/Facilitation 2 lecture hours 2 lab hours 3 credits
Course Description
This course examines the role of the industrial engineer as a team leader and facilitator. Identification of personal strengths and weaknesses with respect to leadership will be addressed. The students will develop skill through leadership and facilitation opportunities as presented in class and during class projects. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• describe what facilitation is and what shaped it a a profession
• identify critical planning techniques (e.g. agendas, meeting room checklist, logistics)
• be in a position to give/receive constructive feedback
• describe strategies for managing through conflict in groups
• facilitate a brainstorming session
• understand how and when to use flipcharts
• describe and utilize strategies t help groups make decisions
• assist a team in overcoming decision deadlock
• describe the many tools of facilitation, their purpose and when to use each
• understand how different leadership skills impact team/group performance
• understand the impact of motivation and satisfaction on team/group performance
Prerequisites by Topic
• None
Course Topics
• History of facilitation/facilitation basics (1 week)
• Effective meetings (1 week)
• Team conflict/group dynamics (1 week)
• Brainstorming and critical thinking (1 week)
• Asking questions/active listening (1 week)
• Group decision making (1 week)
• Facilitation Toolkit (1 week)
• Self-awareness (2 weeks)
• Emotional intelligence
• Self-efficacy
• Leadership (1 week)
Laboratory Topics
• There is a two-hour lab associated with this course, at which time the topics discussed during lecture are reinforced. Students are involved in practicing the art of facilitation. The lab time is also used to work on the class project–developing a design for a campus innovation lab.
• Introduction to the design project–“Innovation Lab,” including team ground rules exercise and scope of control exercise
• Observing group process
• Team goals, roles, milestones
• Effective meetings
• Conflict exercise
• Team project work
• Divergence/convergence practice on team project
• Active listening lab
• Group Styles Inventory simulation and debrief
• Personal Leadership Brand
Coordinator
Leah Newman
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IE 449 - Quality Management 3 lecture hours 0 lab hours 3 credits
Course Description
This course addresses the strategic role of quality in business and industry. It focuses on management’s role in achieving quality excellence, the structures and systems needed to support a total quality strategy, and the main statistical and analytical tools for achieving quality improvement and control. The focus of this course is global and includes applications and examples ranging from high-tech companies to service industries such as health care, insurance, and distribution. (prereq: IE 348 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand the importance of quality as a corporate-wide system, rather than a separate function within the organization
• know how quality impacts companies in the manufacturing and service sectors
• understand the cost of quality and what contributes to a high cost of quality
• be familiar with the ISO-9000 series of standards, how these are managed and implemented within a company, and the auditing/certification process
• utilize various analytical and documentation techniques for problem solving, defining customer requirements, and ensuring compliance
Prerequisites by Topic
• Good understanding of statistical process control, acceptance sampling, and quality improvement tools
Course Topics
• Introduction to quality management, business approaches to quality, and cost of quality (2 weeks)
• ISO 9000 and related quality standards (4 weeks)
• Analytical techniques for problem solving, defining customer requirements, and ensuring compliance (3 weeks)
• Project/research work (1 week)
Coordinator
Charlene Yauch
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IE 460 - Design for Quality 3 lecture hours 0 lab hours 3 credits
Course Description
This course covers the basic approaches to statistically designed experiments including hypothesis testing by the use of ANOVA, Analysis of Means, Student t, F, Chi-square and Z tests, and decision making by use of statistics, factorial, and Taguchi methods. (prereq: MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• recognize applicability of experimental design techniques
• plan and conduct a designed experiment
• analyze experimental data, draw conclusions, and make recommendations regarding process improvements
Prerequisites by Topic
• Basic understanding of probability, statistical distributions, calculating means and standard deviations, student “t” tests and central limit theorem
Course Topics
• Review of Statistics (3 classes)
• Hypothesis Testing (6 classes)
• Analysis of Means (6 classes)
• Applications of Factorial Designs (2 classes)
• One-Way and Two-Way, ANOVA (4 classes)
• Fractional Factorial designs (3 classes)
• Taguchi Methods (5 classes)
• Examinations (2 classes)
Laboratory Topics
• No laboratory in this course
Coordinator
Aaron Armstrong
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IE 470 - Topics in Industrial Engineering 3 lecture hours 0 lab hours 3 credits
Course Description
This course considers subject matter in several of the newer, emerging areas of industrial engineering and management theory and practice. Thus, the content changes regularly. (prereq: junior standing and consent of instructor)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Depends on course topic(s).
Prerequisites by Topic
• None required
Course Topics
• Topics that have been covered in this course include supply chain management, applying IE techniques to healthcare, quick response manufacturing, and advanced human factors.
Laboratory Topics
• None applicable
Coordinator
Charlene Yauch
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IE 483 - Advanced Simulation Modeling 3 lecture hours 0 lab hours 3 credits
Course Description
This course continues the material presented in IE 383 (Simulation) and focuses on statistical concerns. Emphasis is placed on the analysis of the statistical nature of simulation. Probability distributions are examined for appropriateness and data fit. Run length is determined for appropriateness and confidence intervals are used to describe the output. (prereq: IE 383 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• use intermediate simulation modeling techniques
• incorporate transporters and conveyors into models
• build and test a random number generator
• generate random variates
• model discrete/continuous systems
• perform steady-state analysis of simulation models
• employ variance reduction techniques in models
• conduct a comprehensive simulation study, including a final presentation and technical paper
Prerequisites by Topic
• Basic knowledge of discrete-event simulation modeling
Course Topics
• Introduction to Simulation (1 class)
• Simulation language and modeling construct review (1 week)
• Intermediate modeling and steady-state analysis (1 week)
• Verification & validation and entity transfer (1 week)
• Transporters and conveyors (1 week)
• Discrete/continuous systems (2 weeks)
• Random number generation (1 week)
• Variance reduction (1 week)
• Designing and conducting simulation experiments (1 week)
• Project reports (1 week)
Laboratory Topics
• No laboratory for this course
Coordinator
Aaron Armstrong
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IE 499 - Independent Study 1 lecture hours 0 lab hours 3 credits
Course Description
This course allows the student, with faculty guidance, to concentrate on an approved subject of special interest not covered in regularly scheduled courses. This may take the form of individual or small group supervised study, literature review, analysis, design or laboratory study. (prereq: senior standing, approval of faculty advisor and program director)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• Depends on course topic(s).
Prerequisites by Topic
• None required
Course Topics
• Agreed upon by student, faculty advisor, and program director.
Laboratory Topics
• Not applicable
Coordinator
Charlene Yauch
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IE 2450 - Work Planning and Methods Development 2 lecture hours 2 lab hours 3 credits
Course Description
This course introduces students to the principles and techniques associated with work planning, methods analysis, and job design, including time studies, predetermined time systems, work sampling, and standards development. (prereq: MA 262 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• conduct methods, time, and motion studies utilizing a variety of techniques including graphical analysis tools, traditional stop-watch time studies, predetermined time systems, and work sampling
• develop work standards
• describe the advantages and limitations associated with standard data systems
• identify improvement opportunities based on work methods analysis and work measurement
• understand how labor reporting and incentive systems relate to methods analysis and work measurement
Prerequisites by Topic
• Basic understanding of statistical distributions and variability
Course Topics
• Introduction to work methods and work methods improvement (1 week)
• Graphical analysis tools (1 week)
• Time studies (1 week)
• Standard data systems (1 week)
• Predetermined time systems (1 week)
• Work sampling (1 week)
• Physiological work measurement (1 week)
• Labor reporting (1 week)
• Incentives (1 week)
• Increasing productivity (1 week)
Laboratory Topics
• A weekly two-hour lab will give time for multiple lab exercises aimed at giving students hands-on experience with analysis of work methods and work measurement, including time studies, predetermined time systems, physiological work measurement, and the effects of incentives
Coordinator
Charlene Yauch
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IE 3621 - Ergonomics 3 lecture hours 2 lab hours 4 credits
Course Description
This course introduces students to the capabilities and limitations of humans and how that relates to product and job design. Includes physical and cognitive aspects of work, as well as micro- and macro- ergonomics concerns. (Students enrolling in this class may not enroll in SS 464 ). (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand how people fit into technological systems
• recognize the capabilities and limitations of human perceptual-motor capabilities
• recognize the capabilities and limitations of human cognitive functioning and why people make errors
• explain the negative effects that poor work system design and poor product design have on humans
• recognize the human indicators of fatigue and stress
• appreciate the importance of organization and job design factors for performance and satisfaction
• define the ethical application of human factors in designing products and processes
• recognize ergonomic deficiencies in different environments (i.e., office, manufacturing and classrooms)
• evaluate and generate ergonomic solutions to the aforementioned ergonomic deficiencies
• present project information during class presentations as well as in a formal technical report
• write reports that describe human performance
Prerequisites by Topic
• None
Course Topics
• Introduction to and history of human factors and ergonomics, effectiveness and cost effectiveness of ergonomics, human factors investigations (1 week)
• Human information processing and usability; vision and visual display design; hearing, smelling, auditory and olfactory display design; touch and tactile displays and controls (2 weeks)
• Basic anatomy, physiology and biomechanics; physical workload, heat stress and cold stress (1 week)
• Anthropometry and design, work posture and design (1 week)
• Manual materials handling and design; repetitive motion injuries and hand tool design; vibration; automation (1 week)
• Ergonomics of computer workstations, design of manufacture and maintenance (1 week)
• Training and cognitive task analysis; task, organization and job analysis; shift work (1 week)
• Accidents, human error and safety (1 week)
• Macro-ergonomics: job and organization design; engineering ethics (1 week)
Laboratory Topics
• The course includes a 2 hour lab each week where the students will be engaged in demonstrating their understanding of the lecture topics. Lab time will also be used to work on the course project
Coordinator
Leah Newman
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IE 3770 - Computer Integrated Manufacturing 3 lecture hours 2 lab hours 4 credits
Course Description
This course deals with factors and principles related to automation systems for manufacturing. It compares manual and automated systems for production processes, material handling, storage systems, inspection, and product identification. It includes hands-on lab instruction in topics such as robotic programming, flexible manufacturing systems, and using a coordinate measuring machine (CMM). (prereq: IE 426 or ME 323 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• distinguish important capabilities and limitations related to CIM systems, particularly with respect to robotics, identification technologies, computer aided process planning, inspection technologies, manual or automated manufacturing systems, and automated material handling and storage systems
• select and justify a type of manufacturing system (single or multi-station, manual or automated, GT cell, FMS, transfer line, etc.) for a given production scenario
• select and justify a material transport system and a storage system for a given production scenario
• perform calculations related to production rate, production capacity, and storage capacity
• distinguish important capabilities and limitations of robotic processes
• program a robot using a software interface
• analyze a line balancing problem using a heuristic algorithm
• understand flexible automated production systems through use of the Festo FMS.
Prerequisites by Topic
• General understanding of a variety of manufacturing processes (such as machining, sheet metal stamping and forming, and plastic injection molding)
Course Topics
• Robotics, discrete control, PLCs (2 weeks)
• Material handling and storage systems (1 week)
• Automated data capture and identification technologies (1 week)
• Inspection and inspection technologies (2 weeks)
• Various types of manual and automated manufacturing systems (2.5 weeks)
• Flexible manufacturing systems (1 week)
• Computer aided process planning and digital manufacturing (0.5 weeks)
Laboratory Topics
• Programming a robot
• Operating and programming a CMM
• Operating and analyzing a FMS
• Bar codes and RFID
• Line balancing
Coordinator
Charlene Yauch
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IE 4001 - Industrial Engineering Cooperative Practicum 1 1 lecture hours 0 lab hours 1 credits
Course Description
Students complete the first quarter of approved, supervised cooperative employment. A written report of the work performed is required, as well as a draft of a technical paper related to the work experience. (prereq: sophomore standing and consent of program director)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• No course learning outcomes appended.
Prerequisites by Topic
• No prerequisites by topic appended.
Course Topics
• No course topics appended.
Coordinator
Charlene Yauch
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IE 4002 - Industrial Engineering Cooperative Practicum 2 1 lecture hours 0 lab hours 1 credits
Course Description
Students complete the second quarter of approved, supervised cooperative employment. A written report of the work performed is required, as well as a draft of a technical paper related to the work experience. (prereq: IE 4001 and consent of program director)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• No course learning outcomes appended.
Prerequisites by Topic
• No prerequisites by topic appended.
Course Topics
• No course topics appended.
Coordinator
Charlene Yauch
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IE 4003 - Industrial Engineering Cooperative Practicum 3 1 lecture hours 0 lab hours 1 credits
Course Description
Students complete the third quarter of approved, supervised cooperative employment. A written report of the work performed is required, as well as a draft of a technical paper related to the work experience. (prereq: IE 4002 and consent of program director)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• No course learning outcomes appended
Prerequisites by Topic
• No prerequisites by topic appended
Course Topics
• No course topics appended
Coordinator
Charlene Yauch
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IE 4260 - Design for Manufacture and Assembly 2 lecture hours 2 lab hours 3 credits
Course Description
Product design has become increasingly challenging with shorter design/development cycles and the need to address numerous competing concerns, including usability, maintainability, reliability, disposability, and more. This course covers design guidelines and analytical techniques that can be utilized to improve product designs with the primary goal of simplifying manufacturing and assembly processes, thus making the production operations more cost-effective across the product’s life cycle. (prereq: IE 426 or ME 323 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand the benefits associated with designing components and products with the entire product life cycle in mind
• understand how early design decisions can influence manufacturing processes, product costs, inspection practices, and supply chains
• evaluate and compare alternative component and assembly designs for manufacturability and cost effectiveness
• know some of the specific design changes and design guidelines that enable a component or product to have greater manufacturability, usability, maintainability, reliability, and disposability
• make and justify trade-offs between competing design objectives
Prerequisites by Topic
• Knowledge of a variety of manufacturing processes
Course Topics
• Product life cycle and design objectives (1 week)
• DFA (2 weeks)
• DFM for various manufacturing processes (5 weeks)
• Design for other objectives (1 week)
• Project work and exams (1 week)
Laboratory Topics
• The 2-hour weekly lab will be used to evaluate current product and component designs and to create improved designs. Students will disassemble one or more products and practice using various analytical techniques, as well as documenting new designs using CAD software
Coordinator
Charlene Yauch
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IE 4332 - Lean 3 lecture hours 0 lab hours 3 credits
Course Description
Lean techniques can be used to improve any business process and make companies globally competitive. During this course students will learn to identify what is value-added and what is waste in any business process and to eliminate identified waste. Students will also learn the value of teamwork in a Lean Enterprise and will be introduced to the concepts of 5S, Value Stream Mapping and Kaizen. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• explain lean thinking and management methods
• explain the House of Lean
• describe the seven forms of waste in business
• explain the five principles of lean and how to implement them in business
• understand and be able to apply the concept of value add and non-value add activities
• explain and prepare a value stream map
• explain and calculate takt time
• explain the difference between “push” and “pull” and apply tools to accomplish pull
• explain and apply 5S, cellular layouts, and leveling
• explain kaizen
• explain and apply A3
Prerequisites by Topic
• None
Course Topics
• Toyota Philosophy and culture, lean leadership, and lean wastes (1.5 weeks)
• People development and team building (1 week)
• Process stability, flow and value stream mapping (1.5 weeks)
• Standard work (.5 weeks)
• 5S, cellular layouts, and level loading (1 week)
• Total productivity maintenance (.5 weeks)
• Manufacturing cells and setup reduction (1 week)
• Push vs. pull and kanban systems (1 week)
• Kaizen and change management (1 week)
• Toyota problem solving technique (1 week)
Coordinator
Leah Newman
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IE 4336 - Quick Response Manufacturing 3 lecture hours 0 lab hours 3 credits
Course Description
Producing products profitably in an increasingly competitive world market requires speed and agility. Companies and organizations that can get their products and services to customers quickly tend to do so more efficiently and reliably and with better quality than do slower companies. This course will develop students’ abilities to sustainably and efficiently reduce the amount of time processes take to complete. Special focus will be placed on process mapping, production modeling, product development, cellular manufacturing, and mass customization. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• analyze important issues and decisions related to quick response manufacturing
• understand manufacturing system dynamics (particularly how lot size and utilization influence lead time)
• measure Manufacturing Critical-path Time, the QRM metric, in a variety of manufacturing, service, and logistical applications
• discuss quick response manufacturing in the context of production and office operations
• demonstrate knowledge of quick response manufacturing by redesigning a system or process to reduce the process lead time
• demonstrate knowledge of MPX rapid modeling software by utilizing it for process/system analysis and QRM focused improvements
Prerequisites by Topic
• None
Course Topics
• Benefits of QRM
• Performance and time measurement
• System dynamics and response time spiral
• Reorganizing functional production departments into manufacturing cells
• Designing, implementing, and operating manufacturing cells
• Making capacity and lot sizing determinations/decisions
• Building models and analyzing results using MPX software
• Production planning in a QRM environment
• POLCA and ConWIP production control systems
• Customer and supplier relations with QRM
• Office and service cells
• New product introduction and product lifecycle with QRM principles
Coordinator
Charlene Yauch
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IE 4621 - Socio-technical Systems 3 lecture hours 0 lab hours 3 credits
Course Description
Socio-technical Systems (STS) is a method that might be used to analyze manufacturing and service jobs, as well as entire organizations through the study of classical theories and techniques of management and organizational behavior (i.e., Frederick Taylor’s Scientific Management, Elton Mayo’s Human Relations, etc.), as well as more recent developments related to quality of working life, change management, and the macro-ergonomic analysis and design process. This course includes analysis of both social and technical systems within an organization in an effort to improve the design and functionality of the entire system. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• describe what engineering socio-technical systems means, what it covers, and what shaped it as a profession
• understand socio-technical systems engineering theory
• understand how to apply the socio-technical systems theory and analytical methods to design or assist in the redesign of an organization
• understand how to conduct a socio-technical systems analysis of a work process
• understand how different leadership skills impact team/group performance
• understand how organizational culture impacts employee morale and performance
• understand the impact of motivation and satisfaction on team/group performance
Prerequisites by Topic
• None
Course Topics
• Open and other systems (.5 weeks)
• History of socio-technical systems (.5 weeks)
• Socio-technical systems - The environment (1 week)
• Socio-technical systems - The social system (1 week)
• Socio-technical systems - The technical system (1 week)
• Socio-technical system design, redesign and analysis (2 weeks)
• Macro-ergonomics and organizational design and participation (1 week)
• Socio-technical applications and case studies (3 weeks)
Coordinator
Leah Newman
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IE 4622 - Organization and Job Design 3 lecture hours 0 lab hours 3 credits
Course Description
Organizations are becoming increasingly more complex with regards to how business is accomplished when considering issues of cultural and emotional intelligence of employees, the impact of globalization as well as quality of working life issues. This course assists in the design, implementation and diffusion of productive organizations and an individual’s role within the organization. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand the theories associated with organization and job design
• understand how to apply the job design theories and analytical methods in an effort to redesign a job and/or an organization
• conduct a detailed job analysis
• understand how different leadership skills and other organizational management approaches and how they impact team/group performance
• understand how organizational culture impacts employee morale and performance
• understand the impact of motivation and satisfaction on team/group performance
Prerequisites by Topic
• None
Course Topics
• Organizational Management Theories - Overview (1 week)
• Job Design Theories (1 week)
• Job Analysis Data Collection Methods (2 weeks)
• Employee Motivation (1 week)
• Teamwork and Participation (1 week)
• Job Redesign and Case Studies (3 weeks)
• Employer/Employee Ethics (1 week)
Coordinator
Leah Newman
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IE 4773 - Computer Aided Manufacturing/CNC Machining/Rapid Prototyping 2 lecture hours 2 lab hours 3 credits
Course Description
This course teaches students the fundamentals of computer aided manufacturing (CAM), computer numerical control (CNC) machining, and rapid prototyping (RP). Students will learn how to program a CNC machine using manual G/M code programming and computer aided manufacturing software. The course also provides an overview of rapid prototyping (freeform fabrication) technologies, and students will compare part production via RP and CNC. (prereq: IE 426 or ME 323 or consent of instructor, AE 1311 or ME 1601 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• distinguish important capabilities and limitations of CNC machining and RP processes
• manually write a CNC program for a CNC mill and a CNC lathe
• use CAD/CAM software to create and execute CNC programs to machine workpieces on a CNC mill (for student-generated designs: 2.5D milling, hole-making, and 3D contour milling)
• explain workholding concepts and their importance to CNC machining operations
• select cutting tools and cutting conditions for various types of machining operations (drilling, facing, pocketing, etc.)
• set up a CNC machining center, with oversight from a lab technician
Prerequisites by Topic
• Knowledge of machining processes (milling, drilling, turning, etc.). Must know how to create a part design using 3-dimensional CAD software
Course Topics
• Review of machining processes (1 week)
• CNC machining and programming for mills (2 weeks)
• CAM software and project work (4 weeks)
• Workholding (0.5 weeks)
• Rapid prototyping (1 week)
• CNC machining and programming for lathes (0.5 weeks)
• Canned programs and quick code (0.5 weeks)
• Multi-axis machining (0.5 weeks)
Laboratory Topics
• The 2-hour weekly lab, plus some additional lecture class periods are used for working with the CAM software package to create CNC programs. The programs are thoroughly simulated and tested before running them on a Haas VF-1 machining center. Students also learn how to set up and operate the Haas.
Coordinator
Charlene Yauch
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IE 4823 - Financial Engineering 3 lecture hours 0 lab hours 3 credits
Course Description
Finance and economic analysis is a growing area of employment for engineers. The purpose of this class is to increase the student’s ability to apply engineering methods to finance, insurance, economics, and risk management. This is a student directed course where the interests of the participating students will influence the content and objectives of the course. Student influenced course topics may include but are not necessarily limited to: options pricing theory, futures contracts and other financial instruments, real options, risk management, and game theory. Industry applications and case studies illustrate concepts and challenges. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand how engineering methods apply to finance, insurance, and economics
• understand options, futures, and other financial instruments
• understand real options
• understand risk and how risk is evaluated and incorporated into financial models
• apply game theory concepts to financial analysis
Prerequisites by Topic
• None
Course Topics
• Introduction to financial engineering
• Application of engineering methods to finance, insurance, and economics
• Mathematical modeling for financial analysis and decision making
• Options, futures, and other financial instruments
• Real options
• Evaluating risk and incorporating it into financial models
• Game theory
• Industry applications and case studies
Coordinator
Charlene Yauch
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IE 4880 - Supply Chain Engineering 3 lecture hours 0 lab hours 3 credits
Course Description
Supply chain management and logistical planning and execution are critical areas for many businesses and industries. This class is intended to increase students’ understanding of how to apply engineering methods to supply chain related problems. Student influenced course topics may include but are not necessarily limited to: supply chain demand modeling, multi-tier forecasting and coordination, negotiation strategies, total acquisition cost calculation, make versus buy decision analysis, integration of supply chain with product development, dynamic lot sizing inventory models, and the bullwhip effect. Industry applications and case studies illustrate concepts and challenges. (prereq: junior standing)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand how engineering methods apply to supply chain problems
• model a dynamic supply chain
• forecast demand and incorporate this forecast across the supply chain model
• complete a capacity planning analysis
• understand negotiation strategies and where to apply them
• explain software tools and methods available for logistical network design and operation
• understand make versus buy decisions and the associated cost analysis
• understand the bullwhip effect and how it can be dampened
Prerequisites by Topic
• None
Course Topics
• introduction to supply chain engineering
• operations research models for supply chain analysis
• forecasting
• capacity planning
• negotiation strategies
• software tools and methods for logistics network design
• make versus buy decisions
• bullwhip effect
• integration problems in supply chain management
• industry applications and case studies
Coordinator
Charlene Yauch
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IE 4901 - Industrial Engineering Senior Design Project I 2 lecture hours 2 lab hours 3 credits
Course Description
This is the first of a two- (three-) course sequence in developing and executing a team capstone design project in Industrial Engineering. The purpose of this project is to demonstrate the students’ ability, working within a design team, to integrate the knowledge, skills, and experiences acquired in the Industrial Engineering program. Evaluation of user (client) needs, development of an engineering specification, appropriate evaluation criteria, and techniques for design in the presence of conflicting design constraints (quality, productivity, safety, cost) are reviewed. This course includes an external client-sponsored design project and a design proposal submitted to, and approved by, the client. Interdisciplinary teams are encouraged. (prereq: senior standing, EN 241 , EN 132 , consent of instructor)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• understand the client’s situation and define the problem/opportunity with a clear and concise project purpose and scope
• utilize input from the client to establish performance improvement objectives
• define an appropriate solution methodology, collect relevant data and information, and identify relevant analytical methods and tools
• create a detailed and executable project schedule
• utilize agendas and minutes to plan for and document the results of client meetings
• communicate, verbally and in writing, the project proposal and project plan
• function as an effective team member in the context of a real-world project
Prerequisites by Topic
• Must have sufficient knowledge of specific industrial engineering techniques that are likely to relate to the course project (such as operations research, manufacturing systems analysis, lean manufacturing, production control, ergonomics, safety, etc.). Must have successfully completed the junior project class, demonstrating the student’s ability to work successfully within a team on a client-sponsored industrial engineering project.
Course Topics
• Project proposals (2 weeks)
• Teamwork, performance evaluations, peer feedback (2 weeks)
• Formal presentations (2 weeks)
• Project schedules (1 week)
• Literature review and library research (1 week)
• Data gathering and analysis (1 week)
• Formal technical reports (1 week)
Laboratory Topics
• All laboratory work will be done at the sponsor site or in an MSOE lab, as needed by a particular project
Coordinator
Charlene Yauch
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IE 4902 - Industrial Engineering Senior Design Project II 1 lecture hours 3 lab hours 3 credits
Course Description
In this second of the senior design courses, the student teams execute the design proposal developed in IE 4901 . The design is documented in a written team report and orally defended before a faculty review panel. Typically, the project is also presented to the client in a separate presentation, often at the client facility. (prereq: IE 4901 )
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• utilize relevant industrial engineering methods and tools to collect and analyze data
• formulate creative alternatives, perform systematic comparisons of alternatives, and formulate recommendations based on quantitative and qualitative evaluations
• justify recommendations based on quantitative and qualitative performance metrics, taking the context of the client organization into consideration
• communicate, verbally and in writing, the project methodology, results, recommendations, and organizational impact
• write an abstract that is clear and concise, emphasizing the most important aspects of the project and its potential for impact at the client organization
• develop a poster that creates interest and clearly highlights key aspects of the project
Prerequisites by Topic
• Must have developed a client-approved project proposal in IE-4901
Course Topics
• Topics are geared towards helping the students satisfactorily complete their projects
• Topics may vary depending on the content of the projects and the specific strengths and weaknesses of the students enrolled in the course
• Topics covered could include review of technical information or techniques, technical writing, and effective oral presentations
Laboratory Topics
• All laboratory work will be done at the sponsor site or in an MSOE lab, as needed by a particular project
Coordinator
Charlene Yauch
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IE 4903 - Industrial Engineering Senior Design Project III 1 lecture hours 3 lab hours 3 credits
Course Description
This course provides a mechanism for a design team, with approval received during IE 4901 from the course coordinator and faculty advisor, to undertake a larger scope project with correspondingly longer planned duration. The final project presentation and written report is then scheduled at the end of IE-4903, with IE 4902 including a status report. If IE-4903 is approved, no grade for IE 4902 will be issued until IE-4903 is completed. This course satisfies the requirements of an Industrial Engineering elective. (prereq: IE 4902 , consent of instructor)
Course Learning Outcomes
Upon successful completion of this course, the student will be able to:
• utilize relevant industrial engineering methods and tools to collect and analyze data
• formulate creative alternatives, perform systematic comparisons of alternatives, and formulate recommendations based on quantitative and qualitative evaluations
• justify recommendations based on quantitative and qualitative performance metrics, taking the context of the client organization into consideration
• communicate, verbally and in writing, the project methodology, results, recommendations, and organizational impact
• write an abstract that is clear and concise, emphasizing the most important aspects of the project and its potential for impact at the client organization
• develop a poster that creates interest and clearly highlights key aspects of the project
Prerequisites by Topic
• Must have developed a client-approved project proposal in IE-4901 and been given consent by the course coordinator and faculty advisor to undertake a larger scope project
Course Topics
• This course is administered similarly to an independent study course. Student teams meet weekly with their advisor to discuss project progress and concerns
• Topics covered in weekly meetings are geared towards helping the students satisfactorily complete their projects
• Topics may vary depending on the content of the projects and the specific strengths and weaknesses of the students enrolled in the course
• Topics covered could include review of technical information or techniques, technical writing, and effective oral presentations
Laboratory Topics
• All laboratory work will be done at the sponsor site or in an MSOE lab, as needed by a particular project
Coordinator
Charlene Yauch
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