IE 201 – FINANCIAL ENGINEERING
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSCME, BSME and BSIE Majors
Course (catalog) description
COURSE DESCRIPTION: IE 201 Financial Engineering, 3 Hours. Principles and techniques of
economic analysis in engineering and management science. Basic probability theory and
decision problems under risk and uncertainty.
Prerequisite(s)
PREREQUISITE(S): Math 181
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: Engineering Economy by L. Blank and
A. Tarquin, 7th edition, McGraw-Hill Science Publishers, 2011.
Course objectives
COURSE OBJECTIVES: This course introduces students to various aspects of financial analysis
that are necessary for all engineering programs. It introduces such topics as interest rates, cash
flows, project financial analysis, rate of return and alternatives comparison.
Topics covered
MAJOR TOPICS:
1
Economic decision making processes, concepts of cash flows, interest rate,
equivalence, minimum attractive rate of return
2
The time value of money
3
Shifted uniform and gradient series
4
Nominal and effective interest rates
5
Present worth analysis
6
Annual worth analysis
7
Rate of return analysis (single alternative)
8
Rate of return analysis (multiple alternatives)
12
Examinations
13
Final exam
Total
Hrs
5
6
4
6
6
4
5
5
2
2
45
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Type of Instruction
Lecture/Discussion
Recitation
Contact Hours/Week
2
1
Contribution of course to meeting the professional component
This course prepares students for financial transactions necessary for everyday life. It also
prepares them to be able to sell a project to management in industry. It makes them aware that
the financial end of a corporation, sometimes looked down on by engineers, is really very
important and helping the company to make a profit is an important goal.
Relationship of course to program outcomes
As shown in the BSIE Course Outcomes Matrix:
A
Ability to apply knowledge of mathematics, science and engineering
E
Ability to formulate and carry out mathematical solutions
H
The broad education necessary to understand the impact of engineering solutions in
global and societal context
Comments on outcomes
Following are possibly approaches to incorporating specific student learning outcomes into this
course:
A
Use of mathematical calculators and computers to carry out calculations
E
Students are required to formulate engineering problems based on scientific and
engineering principles
H
Students learn to measure the economical impact of different engineering solutions on
large systems (e.g society, countries, public, etc.)
These outcomes are what students are expected to gain from this course.
Person(s) who prepared this description and date of preparation
Pat Banerjee, Professor of Industrial Engineering, August 16, 2013.
250 ENGINEERING GRAPHICS AND DESIGN
TYPE OF COURSE: requirement for the following programs: ME, IE, and CE MAJORS
COURSE DESCRIPTION: Engineering design process, modeling and analysis. Product
dissection, prototyping. Technical communication, AutoCAD, engineering graphics software, 3D views, multiview projection, dimensioning and tolerancing, standards. Team design projects.
PREREQUISITE(S): Eligibility to register for ENG 160 English Composition I.
SAMPLE SOURCES AND RESOURCE MATERIALS: Engineering Design: A Project Based
Introduction, 4th Ed., Clive L. Dym, Patrick Little, and Elizabeth Orwin, John Wiley & Sons,
2013.
COURSE OBJECTIVES:
1. Students will be able to analyze the engineering function of existing products.
2. Students will be able to specify human needs as engineering design requirements.
3. Students will be able to generate, analyze, evaluate, and select among engineering design
solutions to meet specified requirements.
4. Students will be able to communicate technical ideas in writing and orally.
5. Students will be able to communicate technical ideas using accepted graphics standards and
modern computer tools.
6. Students will be able to work productively on an engineering team.
MAJOR TOPICS (LECTURE):
 Introduction to the Design Process
 Product Dissection, Reverse Engineering, Functional Analysis
 Communication: Technical Memos, Bibliographies
 Objectives, Metrics, Constraints, Customer Needs
 Generation, Assessment and Selection of Design Concepts
 Design Modeling and Analysis
 Proofs of Concept, Prototyping
 Communication: Oral Presentations
 Project Management, Work Breakdown Structures
 Communication: Technical Drawing.
 Views; Geometrical Dimensioning and Tolerancing; Standard
 Communication: Technical Reports
 Ethics issues
Hrs
1
2
1
3
2
3
1
1
2
1
9
1
2
MAJOR TOPICS (LABORATORY):
Hrs
 Team Project: Functional Analysis of Existing Device
8
 Computer Applications
8
 (Lab) Team Project: Design of a Device for a Client
14
 TOTAL: 30 + 30 hours of lab sessions where a 2-Dimensional CAD package is used.
During the lab sessions, students learn to use a commercial CAD package to apply the concepts
covered in lecture. The CAD package used is AutoCAD.
CREDIT HOURS: 3 hours
Type of Instruction Contact Hours/Week
Lecture
2
Instructor-led Laboratory
2
Contribution of course to meeting the professional component
This course presents an introduction to the engineering design process. Students learn the role
that ethics and economics play in the design process.
As shown in Outcomes Matrix:
c. Ability to design a system, component or process to meet desired needs
d. An ability to function on technical teams
f. Ability to understand professional and ethical responsibility
g. Ability to communicate effectively
h. The broad education necessary to understand the impact of engineering solutions in global
and societal context.
i.
Recognition of the need for, and an ability to engage in life-long learning
j. A knowledge of contemporary issues
k. Ability to use techniques, skills, and modern engineering tools necessary for engineering
Person(s) who prepared this description and date of preparation
Michael J. Scott, August 23, 2014.
Comments on outcomes
c.
Ability to design a system, component or process to meet desired needs. Students are
introduced to the steps involved in the design process including identification of objectives,
analysis of function, concept generation and selection, prototyping and proof-of-concept testing,
and documentation. Students complete a major team design project and construct a device to
fulfill a specified need.
d.
Ability to function on multidisciplinary teams. Students complete four different team
projects, with students from the Mechanical, Industrial, and Civil Engineering programs mixed
in four-person teams. Students complete a team contract, which is a graded assignment, and
evaluate their own and their team members' contributions both at mid-project and after the
assignment is completed.
f.
Ability to understand professional and ethical responsibility. In discussing the design
process, students are introduced to the notion of ethics in design.
g.
Ability to communicate effectively. Students must demonstrate communication through
engineering graphics, written reports and technical memos, and oral presentation. Students are
required to work with the UIC Writing Center to improve their written communications.
h.
The broad education necessary to understand the impact of engineering solutions in a
global and societal context. Design reports and product dissection reports include discussions of
the context of the devices in question, with outside references cited as needed.
i.
Recognition of the need for, and an ability to engage in life-long learning. Students
participate in a product dissection project and three team design projects that require particular
knowledge outside the scope of the textbook and other materials that are standard for the class.
They experience authentically the need to pursue novel information in any engineering design
project.
j.
A knowledge of contemporary issues. The design project includes a required assessment
of the environmental impact of their design, as measured by the embodied carbon and embodied
energy of the materials chosen for the design. Students use a standard instrument for this
assessment. The results are graded, and the environmental impact of the device is also scored in
the final contest.
k. Ability to use techniques, skills, and modern engineering tools necessary for engineering.
Students use state-of-the-art software packages in order to perform engineering drafting.
Students are encouraged to acquire personal versions of the AutoCAD software used in the class,
which is free for student use.
These outcomes are what students are expected to gain from this course.
IE 342 – PROBABILITY AND STATISTICS FOR ENGINEERS
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSIE Major
Course (catalog) description
COURSE DESCRIPTION: IE 342 Probability and Statistics for Engineers, 3 Hours. Probability,
random variables, mathematical expectation, discrete and continuous distributions, estimation
theory, test of hypotheses, and introduction to standard experimental design.
Prerequisite(s)
PREREQUISITE(S): Math 181 Calculus II, 5 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: Probability and Statistics for Engineers
and Scientists, by Ronald E. Walpole, Raymond H. Myers, Sharon L. Myers and Keying E. Ye,
9th Ed., Prentice Hall, 2011.
Course objectives
COURSE OBJECTIVES: This course introduces students to various aspects of statistical
analysis. The objective is to expose the students to elements of probability and probability
distributions, and statistical inference. We try to keep a balance between theory (topics 1 to 5)
and methodology (topics 6, 7 and 8). The students use differential and integral calculus to
investigate different properties of random variables and their functions. They also learn how to
apply statistical analysis to solve real-life problems. Many examples are used to show the
applicability of the probability theory and statistical analysis.
Topics covered
MAJOR TOPICS:
1
Probability
2
Random variables and probability distributions
3
Mathematical expectation
4
Discrete probability distributions
5
Continuous probability distributions
6
Random sampling and sampling distributions
7
Estimation theory
8
Test of hypotheses
9
Class quizzes
10
Final exam
Total
Hrs
8
5
5
5
5
5
4
4
2
43
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Contact Hours/Week
Type of Instruction
3 Hrs
Lecture/Discussion
Outcomes
A
B
E
Comments on outcomes
Ability to apply knowledge of mathematics,
science and engineering.
Students are able to use mathematical
calculations in solving engineering problems.
Also, students are able to formulate engineering
problems based on scientific and engineering
principles. Much of the course deals with the
statistical aspects of data.
An ability to design and conduct experiments,
as well as to analyze and interpret data.
Ability to analyze, interpret and determine
significant parameters to aid in understanding
data. Also, students develop the ability to analyze,
interpret and determine significant parameters to
aid in understanding data.
An ability to identify, formulate, and solve
engineering problems.
Students develop the ability to understand
what is needed, formulate problems
mathematically and build on fundamental
knowledge and apply it to new situations
through completing homework assignments.
Ability to use the techniques, skills, and
K modern engineering tools necessary for
engineering practice
Demonstrate knowledge of computer usage in
engineering analysis. Some homework requires
use of computers. The students can use Microsoft
Excel or any other statistical software in their
projects. Extra sessions will be held (if necessary)
to demonstrate the software.
Person(s) who prepared this description and date of preparation
Professor Nan Ratisoontorn, Assistant Professor of Industrial Engineering, August, 2013
These outcomes are what students are expected to gain from this course.
IE 345 – REGRESSION APPLICATIONS AND FORECASTING IN ENGINEERING
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSIE and BSME Major
Course (catalog) description
COURSE DESCRIPTION: IE 345 Regression Applications and Forecasting in Engineering. 3
Hours. Single and multiple regression analysis of variance, examination of residuals,
introduction to time series analysis, and analytical forecasting techniques; application to
engineering system. Prerequisite: IE 342 Probability and Statistics for Engineers.
Prerequisite(s)
PREREQUISITE(S): IE 342 Probability and Statistics for Engineers, 3 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCES MATERIALS: Introduction to Time Series Analysis
and Forecasting by Douglas C. Montgomery, Cheryl L. Jennings and Murat Kulahci, 1st Ed.,
John Wiley & Sons, 2008.
1. Introduction to Forecasting and Regression: An applied Approach, by Bruce L.
Bowerman, Richard T. O’Connell and Anne B. Koehler, 4th Ed., Thomson Books/Cole,
Belmont, CA 2005.
2. Introduction to Time-Series Modeling and Forecasting in Business Economics, by
Patricia E. Gaynor and Rickey C. Kilpartick, McGraw-Hill, New York, NY, 1994.
3. Statistics, Data Analysis and Decision Modeling, by Evans and Olson, Prentice Hall,
Upper Saddle River, NJ, 2000.
4. Data, Statistics, and Decision Models with Excel, by Harnett and Horrell, John Wiley &
Sons, New York, 1998.
Course objectives
COURSE OBJECTIVES: This course studies the essentials of effective regression analysis and
forecasting methods. In a very general sense, all decisions are based upon forecasts. Many
decision makers are unscientific methods of forecasting to arrive at decisions. However, if the
decision maker possessed the knowledge of more scientific approaches, the effectiveness of his
or her decisions should be enhanced. It is for these reasons that managers, engineers, economists,
and analysts should study statistical regression and forecasting methods. This course tries to
refine and stimulate your interest and success in regression analysis and forecasting.
While this course covers a full range of regression analysis and forecasting methods, it
concentrates on the most widely used methods of regression analysis and forecasting in
engineering applications. These methods are important tools in production, marketing, finance,
engineering, and economics. The emphasis of the course will be on the principles and
applications of successful regression analysis and forecasting. The course will also stress the
importance of communicating regression analysis and forecasting results through written report
and verbal presentations. Data analysis and approaches to presenting results will also be
introduced. Upon completion of this course, the students will be expected to be able to apply
regression analysis and forecasting methods for solving engineering system problems.
Topics covered
MAJOR TOPICS:
1
Introduction
2
Time-Series Analysis
3
Simple Regression Analysis
4
Multiple Regression Analysis
5
Exponential Smoothing
6
Winters’ Exponential Smoothing
7
Box-Jenkins Methodology: Non-seasonal Models
8
Box-Jenkins Methodology: Seasonal Models
9
Examinations
Total
Hrs
1
5
7
9
7
5
3
3
8
48
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Type of Instruction
Contact Hours/Week
Lecture/Discussion
3
Laboratory
0
Contribution of course to meeting the professional component
This course studies the essentials of effective regression analysis and forecasting methods. While
this course covers a full range of regression analysis and forecasting methods, it concentrates on
then most widely used methods of regression analysis and forecasting in engineering
applications. These methods are important tools in production, marketing, finance, engineering,
and economics. The emphasis of the course will be on the principles and applications of
successful regression analysis and forecasting. The course will also stress the importance of
communicating regression analysis and forecasting results through written report and verbal
presentations. Data analysis and approaches to presenting results will also be introduced. Upon
completion of this course, the students will be expected to be able to apply regression analysis
and forecasting methods for solving engineering system problems.
Relationship of course to program outcomes
As shown in the BSME Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
E.
Ability to identify, formulate, and solve engineering problems
G.
Ability to communicate effectively
K.
Ability to use techniques, skills, and modern engineering tools necessary for engineering
practice.
Person(s) who prepared this description and date of preparation
David He, Associate Professor of Industrial Engineering, January, 2011
Updated by Dr. David He, Professor of Industrial Engineering, August 2013
Comments on outcomes
A.
Use of fundamental knowledge of probability and statistics in regression analysis,
engineering, problem formulation, modeling, and solution generation.
E.
Throughout the course, the students are required to analyze different engineering
application problems, identify the problem parameters, formulate and modeling the
problems, and find solutions to these problems using regression and forecasting methods
to thermodynamic fundamentals, and finally how to express them in mathematical terms.
G.
Students are provided with opportunities to present their learning experience in oral and
written format through their homework and projects.
K.
After this course, the students will be able to use effectively the regression analysis and
forecasting tools to solve engineering problems.
These outcomes are what students are expected to gain from this course.
IE365 – WORK PRODUCTIVITY ANALYSIS
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE and BSEM Majors
Course (catalog) description
COURSE DESCRIPTION: IE365 Work Productivity Analysis. 4 hours
Operations analysis, man-machine relationship, motion study, micro-motion study, time study,
predetermined time systems, performance rating, standard data techniques, work sampling, and
wage payment plans.
Prerequisite(s)
PREREQUISITE(S): Credit or Concurrent Registration in IE 342 – Probability and
Statistics for Engineers, 3 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: Methods, Standards and Work Design,
Nibel, B.W. and Freivalds, A., 12th Edition, McGraw Hill, 2009.
Course objectives
COURSE OBJECTIVES: The course is designed to provide students with an opportunity to
follow the evolution of Industrial Engineering and offers traditional tools of industrial engineers
that have been developed for methods engineering and time study. Students get hands-on
experience with some of these tools through laboratory projects. With the successful completion
of the course, students will be equipped with a broad understanding of professional and ethical
responsibility of a method engineer as well as a palette of traditional tools of methods engineers
for productivity and quality improvements.
Topics covered
MAJOR TOPICS:
1.
Introduction to motion and time study
2.
Tools of methods analyst
3.
Operations analysis
4.
Worker-and-machine relationship
5.
Motion and micromotion study
6.
Job analysis and evaluation
7.
Time study requirement
8.
Elements of time study
9.
Standard time and standard data
10.
Basic motion times
11.
Formula Construction
12.
Work sampling studies
13.
Follow-up method and uses of time standards
14.
Lab meetings
15.
Exams
Total
Hrs
3
4
3
3
4
3
3
3
4
4
3
2
2
30
4
75
Class/laboratory schedule, i.e., number of sessions each week and duration of each session.
CREDIT HOURS: 4 Hours
Type of Instruction:
Contact Hours/Week
Lecture-and-discussion
3
Laboratory
2
Contribution of course to meeting the professional component
The course deals with the subject that industrial engineering has been most identified with:
motion and time study, and productivity improvement. Through the course, students get a chance
to view the evolution of industrial engineering and learn traditional methods engineering tools
that have been developed for improving quality and productivity at large. Owing much to the
peculiar subject matter, students are exposed to and better understand professional and ethical
issues on ‘fair wage,’ ‘objective performance rating,’ and allocation of ‘proper allowances’ for
standard time, to name a few.
Relationship of course to program outcomes
As shown in the BSIE Course Outcomes Matrix:
B.
Design and conduct experiments, as well as analyze and interpret data
D.
An Ability to function on technical teams.
F.
Understanding of professional and ethical responsibility
G.
An ability to communicate effectively
J.
A knowledge of contemporary issues
Person(s) who prepared this description and date of preparation
Hong Seo Ryoo (Assistant Professor) of Mechanical & Industrial Engineering, January 31, 2002
Rao Kodali (Lecturer), October 6, 2006
Houshang Darabi, Professor of Industrial Engineering, January 15, 2013
Comments on outcomes
B.
Through the use of exemplary problems in the text as well as through lab projects,
students learn to analyze, simplify, and formulate problems and apply the techniques
learned in course for their solution.
D.
Students participate in team projects where they work in groups of 3-4 to satisfy project
requirements.
F.
Owing to the subject matter, students are exposed to professional and ethical issues
centered on ‘fair wage,’ ‘objective performance rating,’ and allocation of ‘proper
allowances’ for standard time throughout the semester. Chapters of text on standard time
basically deal with this issue.
G.
Lab projects require technically written lab reports that are graded based upon not only
the accuracy of results but also for the contents, the format, and the efficacy of
presentation. Depending upon instructor, oral presentations may be required for some of
the lab reports.
J.
Students are required to create a presentation on their choice of contemporary issue and
share their findings with their classmates.
These outcomes are what students are expected to gain from this course.
ME 380 / IE 380 – MANUFACTURING PROCESS PRINCIPLES
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSME AND BSIE Majors
Course (catalog) description
COURSE DESCRIPTION: Manufacturing Process Principles. 3 Hours. Introduction to basic
manufacturing processes such as casting, bulk deformation, sheet metal forming, metal cutting.
Interaction between materials, design, and manufacturing method. Economics of manufacturing.
Prerequisite: CME 203.
Prerequisite(s)
PREREQUISITE(S): CME 203 Strength and Materials, 3 Hours.
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCES MATERIALS: Mikell P. Groover, Fundamentals of
Modern Manufacturing. 3rd Edition. John Wiley & Sons, Inc., 2006.
Course objectives
COURSE OBJECTIVES: This course is designed to introduce students to engineering materials,
manufacturing methods, and the importance of design and economic considerations in the
selection of engineering materials and manufacturing processes to produce a desired part or a
component. The course description is concerned mainly with the metals and manufacturing
processes of metals, as outlined above, a course description which is a leftover-from-the 1960’s,
when metals, then, were indeed the backbone of the manufacturing industry. However, since
then, immense advances have been made in other materials, such as ceramics, polymers, and
composite materials. Therefore, in order to be current in manufacturing industry and competitive
in the domestic and global
marketplace, metals, as well as engineering materials other than metals, namely, ceramics,
polymers, and composite materials – metal matrix composites, ceramic matrix composites, and
polymer matrix composites are presented to students. In addition to new engineering materials,
manufacturing processes for these new engineering materials, such as plastic injection molding,
filament winding, pultrusion are also presented to students. Accordingly, this course is aimed to
maintain a fine balance between not overwhelming the students with details and yet not
overlooking essentials that the students should be familiar with as they enter the business world.
Topics covered
MAJOR TOPICS:
1
Introduction to engineering materials and manufacturing processes
2
Metals and manufacturing processes for metals
3
Ceramics and manufacturing processes for ceramics
4
Polymers and manufacturing processes for polymers
5
Composite materials and manufacturing processes for composite materials
6
Metal casting
7
Powder metallurgy
8
Bulk deformation processes – rolling, forging, extrusion, and drawing
Hrs
1-1/2
3
3
3
3
3
1-1/2
6
9
Sheet metalworking – cutting, bending, and deep drawing
10
Material removal processes by cutting tools – turning, drilling, and milling
11
Material removal processes by abrasives and non-traditional processes
12
Joining-welding, brazing, soldering, adhesive bonding
and mechanical assembly
13
Examinations
14
Final examinations
Total 47
3
6
3
6
3
2
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Type of Instruction
Contact Hours/Week
Lecture/Discussion
3
Laboratory
0
Contribution of course to meeting the professional component
Selection of engineering materials and manufacturing processes for an intended product do not
only involve teams of engineers from various branches of engineering but in a broader sense they
also involves purchasing, production, human resources, finance, sales, and marketing,
complexity of the product, annual production rate, safety, quality, and environmental concerns.
The shortcomings of traditional design-manufacturing engineering teams are compared with the
benefits of concurrent engineering in addressing to Design for Manufacturability problems.
Recycling of materials, conservation of energy, product liability suits, affordability, and social
responsibility as engineers, safety, quality, and reliability, and affordability are stressed
throughout the course.
Relationship of course to program outcomes
As shown in the BSME/BSIE Course Outcomes Matrix:
a. Ability to apply knowledge of mathematics, science and engineering
e. Ability to identify, formulate, and solve engineering problems
j. Knowledge of contemporary issues.
Person(s) who prepared this description and date of preparation
Jeremiah Abiade, Assistant Professor of Mechanical and Industrial Engineering, January 15,
2014
Comments on outcomes
a. Students are able to use mathematical calculations in solving engineering problems. Students
learn theory and applications of engineering problems concerning manufacturing processes
through out-of-class assignments and examinations.
e. Ability to understand what is needed, ability to formulate problems mathematically, and
ability to build on fundamental knowledge and apply it to new situations through out-of-class
assignments.
j. Knowledge of major technological issues facing society and the world and appreciation of
the society’s concerns with security in technology. The textbook is supplemented by the
latest information from the latest publications, conferences, and trade shows. The planned
tour of a steel plant had to be scrapped because of the adverse economic affect of dumping
steel imports on the domestic steel producers.
These outcomes are what students are expected to gain from this course.
IE/ME 394 – SENIOR CAPSTONE DESIGN
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSME and BSIE Majors
Course (catalog) description
COURSE DESCRIPTION: IE/ME 396 Senior Design I. 4 Hours. Systematic approach to the
design process. Creative problem solving. Design methodology and engineering principles
applied to open-ended design problems with inherent breadth and innovation.
Prerequisitie(s)
PREREQUISITE(S): Senior standing with the department. Completion of core courses and
consent of the instructor.
Textbook(s) and/or other required material
None.
Course objectives
COURSE OBJECTIVES: This course integrates the knowledge acquired in the various courses
of the undergraduate curriculum to an open-ended design effort and applies the knowledge
gained to the solution of a contemporary engineering problem. Students improve oral and written
communication skills, gain familiarity with available technical literature, and experience the life
cycle of a design project within a group environment. Many projects include practice in the use
of computers and relevant support software while solving a design problem. Students work
together as a team to accomplish common goals. Issues of professional ethics are also discussed.
Topics covered
MAJOR TOPICS:
1
Systematic approach to the design process; project management
2
Recognition/elicitation of customer needs
3
Translation of customer needs to functional specifications
4
Systematic aids to creativity
5
Student design projects:
Formation of teams, development of design needs and specifications,
Solution concept generation, analysis, concept selection, concept
Development including analysis and optimization, detail design,
Possible prototyping, design reviews, written formal reports
6
Engineering workplace issues: intellectual property, liability, ethics
7
Style and substance of reports and oral presentations
8
Presentations (in lieu of examinations)
Total 60
Hrs
4
1
1
1
48
2
1
2
Class/laboratory schedule, number of sessions each week and duration of each session
CREDIT HOURS: 4 Hours
TYPE OF INSTRUCTION:
Type of Instruction:
Contact Hours/Week
Lecture-Discussion
4
Laboratory
0
Contribution of course to meeting the professional component
This course is a capstone design course, and is intended to expose students to many of the
aspects of working in a professional environment. Students work in teams on projects for
industry or other clients. It includes open-ended design, teamwork, communication, and
customer interaction. Analysis of the designed system is required, with application of whatever
technical content from the entire curriculum is relevant to the team’s problem. Process
documentation with approval mechanisms at significant gates is also required.
Relationship of course to program outcomes
As shown in the BSME Course Outcomes Matrix, this course contributes to:
C.
Ability to design a system, component, or process to meet desired needs
D.
Ability to function on multi-disciplinary teams
E.
Ability to identify, formulate, and solve engineering problems
F.
Understanding of professional and ethical responsibility
G.
Ability to communicate effectively
I.
Recognition of the need for, and ability to engage in life-long learning
Person who prepared this description and date of preparation
Michael J. Scott, Assistant Professor of Mechanical Engineering, January 28, 2002;
Constantine M. Megaridis, Professor of Mechanical Engineering, August 27, 2011.
Michael Brown, Department of Mechanical Engineering, January 16, 2014
Comments on outcomes
C.
Project course with open-ended problems requiring creativity and new ideas.
D.
Semester projects are performed in teams of three undergraduates.
E.
Design projects require teams to determine which problems to analyze and solve.
F.
Ethical considerations inherent in design decisions.
G.
Teams give oral and written presentations at midterm and semester end.
I.
Many projects have clients or technical advisors from industry; interacting with
professional engineers further along in their careers, students learn first-hand the need to
keep current.
The above outcomes are what students are expected to gain from completing this course.
IE 442 – DESIGN AND ANALYSIS OF EXPERIMENTS IN ENGINEERING
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSIE Major
Course (catalog) description
COURSE DESCRIPTION: IE 442 Design and Analysis of Experiments in Engineering, 4 Hours
(1 hour for Lab using Minitab Software). Simple comparative experiments, single factor
experiment, randomized blocks, Latin squares, and related designs, factorial design, regression
model, response surface method and other approach to optimization, robust design, random
factors, nested/split-plot designs, course project, and lab Session.
Prerequisite(s)
PREREQUISITE(S): IE342 – Probability and Statistics for Engineers, 3 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS:
1. Design and Analysis of Experiments, 8th Edition, by Douglas C. Montgomery, ISBN
978-1-1181-4692-7, John Wiley, 2012.
2. Design and Analysis of Experiments: MINITAB Companion, 7th Edition, by Douglas C.
Montgomery, Scott M. Kowalski, ISBN 978-0-470-16990-2, John Wiley, 2011.
Course objectives
COURSE OBJECTIVES: Develop the ability to appropriately analyze experimental data and
communicate the results, the ability to translate industrial problems into an appropriate
experimental design. Students also are given an introduction to techniques for variance reduction
through robust parameter design.
Topics covered
MAJOR TOPICS:
1.
Introduction to Probability and Sampling Distribution
2.
Simple Comparative Experiments
3.
Experiment with Single Factor
4.
Randomized Blocks and Latin Squares
5.
Factorial Design
6.
2k Factorial Design
7.
Blocking and Confounding in 2K Factorial Design
8.
Two-level Factorial Design
9.
Response Surface Methods and Design
10.
Robust Parameter Design
11.
Experiments with Random Factors
12.
Labs Training with Minitab
13.
Course Projects
14.
Exams
Hrs
2
5
4
3
3
4
3
8
4
3
3
15
15
3
Total
75
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Contact Hours/Week
Type of Instruction
3 Hrs
Lecture/Discussion
Outcomes
B
Ability to design and conduct experiments, as
well as analyze and interpret data.
Comments on outcomes
Students are able to design and conduct
experiments, solving real problems, especially in
engineering. Students are also able to analyze
and interpret data based on scientific and
engineering principles. Students use fundamental
knowledge of design and analysis of experiments
to solve real problems through class learning and
course project.
Person(s) who prepared this description and date of preparation
Professor Lin Li, Assistant Professor of Mechanical Engineering, August 1, 2014
These outcomes are what students are expected to gain from this course.
IE 446 – QUALITY CONTROL AND RELIABILITY
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE Major
Course (catalog) description
COURSE DESCRIPTION: IE 446 Quality Control and Reliability. 3 Hours. Principles of
statistical quality control including control by variable and by attribute, construction and use of
control charts for variables, fraction defectives and number of defects and use of standard plans,
reliability and life cycle testing. Prerequisite: IE 342.
Prerequisite(s)
PREREQUISITE(S): IE 342 Probability and Statistics for Engineers, 3 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: D. C. Montgomery, Introduction to
Statistical Quality Control, 7th Edition, John Wiley & Sons, 2013.
Course objectives
COURSE OBJECTIVES: This course introduces students to concepts and methods of modern
statistical quality control. Students learn to apply standard quality control tools. They learn the
theoretical statistical concepts that justify the use of particular quality control tools in particular
situations. They learn theory and methods for analyzing the performance of different quality
control tools. The use of appropriate software for statistical and quality analysis is taught, and is
necessary for successful completion of some homework assignments. Issues of ethics and
professional responsibility and their relation to product quality are discussed.
Topics covered
MAJOR TOPICS:
1
Statistical and computational background
2
Concepts and history of quality control
3
Informal tools for quality control
4
Control charts for variables
5
Control charts for attributes
6
Theoretical performance of control charts
7
EWMA and CUSUM control charts
8
Process capability analysis
9
Acceptance sampling
10
Reliability concepts and measures
11
Measurement, tolerance, and specifications
12
Examinations
Total
Hrs
4
3
2
8
5
3
4
3
5
2
4
2
45
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 Hours
TYPE OF INSTRUCTION:
Type of Instruction
Contact Hours/Week
Lecture-Discussion
3
Laboratory
0
Contribution of course to meeting the professional component
This course shows how to use modern statistical quality control tools, such as control charts and
process capability measures, to monitor quality characteristics of manufacturing processes.
Students also learn the underlying basic probability and statistics so that they will choose
appropriate quality control tools and will be able to implement specialized tools for non-textbook
situations, as well as to analyze the theoretical performance of those tools. The importance of
product quality in the contemporary global economy and the relationship between quality and
professional ethics are also discussed.
Relationship of course to program outcomes
As shown in the BSIE Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
E.
Ability to identify, formulate, and solve engineering problems
F.
Understanding of professional and ethical responsibility
K.
Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice
Person(s) who prepared this description and date of preparation
Dr. Lin Li, Professor of Industrial Engineering, August 22, 2013
Comments on outcomes
A.
Students are able to use mathematical calculations in solving engineering problems and
able to formulate engineering problems based on scientific and engineering problems.
Use of fundamental knowledge of probability and statistics in statistical quality control,
process capability and acceptance sampling are introduced.
E.
Students develop the ability to understand what is needed, are able to formulate problems
mathematically and are able to build on fundamental knowledge and apply it to new
situations. Throughout this course, the students are required to analyze different quality
control and process environment application problems, identify the problem parameters,
formulate and modeling the problems, and find solutions to these problems using
statistical quality control methods.
F.
Essay assignment and class discussion on relationship between product quality, public
safety, liability, and professional ethics.
K.
Students demonstrate the knowledge of computing tools in engineering analysis and
technical approaches in engineering experimentation. After this course the students will
be able to effectively use the computing tools to solve statistical quality control and
reliability problems.
These outcomes are what students are expected to gain from this course.
IE 461 – SAFETY ENGINEERING
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSIE AND BSEM Majors
Course (catalog) description
COURSE DESCRIPTION: Safety Engineering. 3 undergraduate hours; 4 graduate hours;
Accident losses; standards and codes; hazards control; accident investigations; mechanical
injuries; heat, pressure, and electrical hazards; fires and explosions; toxic materials and radiation;
vibration and noise; course project for graduate level.
Prerequisite(s)
PREREQUISITE(S): IE 342 Probability and Statistics for Engineers, 3 hours; or consent of the
instructor.
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS:
1. Safety and Health for Engineers, 2nd Edition, R. Brauer. Wiley-Interscience, 2006, ISBN
978-0-471-29189-3.
Course objectives
COURSE OBJECTIVES: This course is designed to introduce students to the principles of
health and safety engineering, with an emphasis on the application to the occupational setting.
Both quantitative and qualitative tools are discussed.
Topics covered
MAJOR TOPICS:
1
Health Protection Fundamentals
2
Mechanical Hazards and Control
3
Electrical, Thermal, Pressure Hazards and Control
4
Fire, Explosion Hazards and Control
5
Ionizing/Non-ionizing Radiation, Noise Hazards and Control
6
Chemical, Biological Hazards and Control
7
Ventilation Control Systems and Personal Protective Equipment
8
Accident investigation, emergencies
9
Examination
Total
Hrs
6
7.5
4.5
3
7.5
6
4.5
3
3
45
.
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
TYPE OF INSTRUCTION:
Contact Hours/Week
Type of Instruction
3 Hrs
Lecture/Discussion
0
Contribution of course to meeting the professional component
This course provides a fundamental understanding of health and safety engineering with an
emphasis as it pertains to the occupational environment. Identification of hazards and their
associated methods of control are discussed. The underlying theme throughout the course is that
worker health protection may be afforded through prevention by the anticipation, recognition,
evaluation, and control of workplace hazards.
Relationship of course to program outcomes:
Outcomes
A
E
F
Comments on outcomes
Ability to apply knowledge of mathematics,
science and engineering.
Students are able to integrate health protection
principles, the physical environment, and
engineering solutions. Also, students work in
small groups to develop quantitative and
qualitative control strategies for problems
presented during lecture. For example, students
develop control strategies for worker hazards in
grain handling facilities in agricultural settings.
An ability to identify, formulate, and solve
engineering problems.
Students are able to formulate quantitative
problems for health protection evaluation and
control, solve quantitative problems for health
protection evaluation and control and utilize
quantitative formulas and problems based on the
content of the course and provide quantitative
solutions to demonstrate their ability to apply
standard equations used in practice. For example,
students develop and solve explosion, thermal,
radiation, and noise problems for comparison to
thresholds of concern.
Understanding of professional and ethical
responsibility
Students are able to understand their
responsibility as engineers for the protection
of worker health in the industrial environment
as well as the surrounding community, the
fact that society values these responsibilities,
as demonstrated through professional work
ethic, litigation, and legislation. Students
develop this sense of responsibility to the
public through lecture, conversation, and
reading on the social, political, and economic
implications of health protection. For
example, we discuss the tension between
engineers’ duties to employers and clients vs.
duties to the general public.
The broad education necessary to understand
H the impact of engineering solutions in global
and societal context.
I
A recognition of the need and ability to engage
in life-long learning.
Students were able to apply a framework with
which they are able to approach health and safety
concerns in any occupational environment.
Students are able to integrate and apply their
understanding of the physical environment, heath
and safety hazards, and engineering solutions to
an assortment of potential hazards, settings and
applications. Students apply heath and
fundamentals along with engineering control
solutions to problems that extend to global and
societal concerns. For example, students examine
health and safety issues related the infectious
diseases (TB or Legionellosis in Basic concepts
lecture & assignment), learn to read regulations &
Standards and Bureau of Labor Statistics Tables
that describe rates of injury by occupation (S&H
Regulations assignment), learn about disposal of
hazardous waste and process safety relative to
community and worker health impacts in US vs.
developing countries. One lecture is devoted to
ethics in engineering S&H practice and
professional certification process, which includes
the requirement for professional development and
continuing education.
Students are able to recognize the continuous
development of health protection technology,
continuous development of standards and
legislation that affect heath protection. Students
learn through lecture and safety control
technologies along with new standards and laws
that affect the practice of health protection. They
also learn to research multiple sources of
recommendations, guidelines and professional and
legal standards relevant to design and
performance. For example, students learn about
the annual review of documentation for the
continuous development of occupational exposure
thresholds such as OSHA PELs, ACGIH TVLs &
NIOSH RELs. One lecture is devoted to ethics in
engineering S&H development and continuing
education.
Person(s) who prepared this description and date of preparation
Professor Salvatore Cali, UIC Instructor, August 2013
These outcomes are what students are expected to gain from this course.
IE 463 – FACILITIES PLANNING AND MATERIAL HANDLING
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE Major
Course (catalog) description
COURSE DESCRIPTION: Facilities design functions, computer-aided plant layout, facility
location, warehouse layout, Minimax location, deterministic and probabilistic conveyor models.
Prerequisite(s)
PREREQUISITE(S): IE 471 (Operations Research I), 3 hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS:
1) Facilities Planning (4th edition), J. A. Tompkins, J. A. White, Y. A. Bozer, J. M. A.
Tanchoco, John Wiley & Sons, 2010.
Course objectives
COURSE OBJECTIVES: This course introduces students to various aspects of facilities
planning process. The objective is to provide the students with basic tools and methodologies
used in this process, and to expose the students to the application of such tools. Both quantitative
and qualitative tools (methods) are discussed.
Topics covered
MAJOR TOPICS:
1.
Introduction
2.
Computer-aided plant layout
3.
Facilities location problems
4.
Warehouse layout problems
5.
Minimax layout and location problem
6.
Deterministic and probabilistic conveyor models
Total
Hrs
3
8
8
8
8
10
45
IE 463 Instruction Notes on Relevant ABET Outcomes:
A
C
E
Ability to apply knowledge of mathematics,
science and engineering.
Students are able to use mathematical calculations
in solving engineering problems and are able to
formulate engineering problems based on
scientific and engineering principles. They also
use operation research techniques to formulate
and solve facilities planning problems. For
example, they apply Integer Programming to
design an optimal layout of a facility.
Ability to design a system, component, or
process to meet desired needs.
Students develop the ability to define and follow
an iterative design procedure and think creatively.
Also, students are supposed to decide and design
the right layout and material handling equipment
for their projects.
Ability to identify, formulate, and solve
engineering problems.
Students develop the ability to understand what is
needed, formulate problems mathematically and
build on fundamental knowledge and apply it to
new situations. In addition, operations research
techniques are taught in the lecture portion of this
course. The students select the right technique and
interpret the mathematical solution of their model
to provide answers for their engineering problem.
For example, graph theory is used to investigate
the adjacency of production departments of a
facility.
G Ability to communicate effectively.
Students develop the ability to present effectively
in senior design, write laboratory reports and
course project reports, develop good interview
skills, and create engineering drawings. In
addition, students have to present their project
results by two oral and two written presentations.
J
Students acquire the knowledge of major
technological issues facing society and the world
and develop an appreciation for the society’s
concerns with security in technology. In the
feasibility study phase of the term projects, the
students are encouraged to select a facility, which
is economically, technologically and operationally
feasible.
Knowledge of contemporary issues.
Ability to use the techniques, skills, and
K modern engineering tools necessary for
engineering practice.
Students develop the ability to utilize computers
for engineering analysis purposes and technical
approaches in engineering experimentation.
Simulation software, LP packages and other
mathematical programming software tools are
used to find the optimal design of material
handling systems, plant layout and location.
Person(s) who prepared this description and date of preparation
Houshang Darabi, Assistant Professor of Industrial Engineering, March 03, 2003.
Houshang Darabi, Associate Professor of Industrial Engineering, September 5, 2013.
These outcomes are what students are expected to gain from this course.
IE 466 – PRODUCTION PLANNING AND INVENTORY CONTROL
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE and BSEM Majors
Course (catalog) description
COURSE DESCRIPTION: IE466 Production Planning and Inventory Control. 3 undergraduate
hours; 4 graduate hours. Principles of demand forecasting, production planning, master
scheduling, job sequencing, design and control of deterministic and stochastic inventory systems,
and material requirement planning
Prerequisite(s)
PREREQUISITE(S): IE342 Probability and Statistics (3 hrs), IE 345: Regression and
Forecasting (3 hrs) and IE 471 –Operations Research (3 Hours)
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: Production and Operations Analysis
(6th Edition), S. Nahmias, McGraw Hill, 2009
Course objectives
COURSE OBJECTIVES: To teach students to apply basic optimization techniques to formulate
and solve problems that arise in production systems. With the successful completion of the
course, students are equipped with a general understanding of (integrated) production systems
and a palette of optimization tools for solving commonly encountered production planning and
control problems, including aggregate and disaggregate planning, job shop scheduling, and
inventory control.
Topics covered
MAJOR TOPICS:
1.
Introduction to production system
2.
Forecasting techniques
3.
Aggregate and disaggregate planning
4.
Inventory system and control
5.
Material planning requirement
6.
Job shop scheduling
7.
Integrated production systems: push vs. pull systems, JIT
8.
Exams and/or quizzes
Total
Hrs
1
8
7
7
7
7
5
3
45
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 undergraduate hours; 4 graduate hours.
Type of Instruction
Contact Hours/Week
Lecture-and-discussion
3
Contribution of course to meeting the professional component
Students are exposed to various bottleneck problems of various production systems and learn to
formulate and solve them by using theoretical foundation of operations research and basic
scientific/engineering principles. Through illustrative examples and discussions in class as well
as problems from text and the literature, students get hands-on experience with optimization of
commonly encountered production planning and control problems, including aggregate and
disaggregate planning, job shop scheduling, and inventory control, and obtain a general
understanding of (integrated) production systems. Contemporary issues and examples are
presented and discussed in detail to provide students with insights as to how the class materials
learned l are related and can be used for their solution. Through the course, students learn the
merits and shortcomings of local vs. heuristic vs. exact solution procedures and, through
illustrations and discussions, learn how simple tools learned in class may be extended and
modified to solve real-world production system-related problems.
Relationship of course to program outcomes
As shown in the BSIE Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
E.
Ability to identify, formulate, and solve engineering problems
Comments on outcomes
A.
Use of linear algebra, calculus, optimization techniques, etc. to problems arising in
production systems
E.
Supply chain modeling, production planning, and inventory control problems are
described in class and also given to students as homework and exams. These problems
are industrial engineering problems and the students learn how to formulate and solve
those using analytical tools.
Person(s) who prepared this description and date of preparation
Hong Seo Ryoo (Assistant Professor) of Mechanical & Industrial Engineering, January 31, 2002
Nan Ratisoontorn, Visiting Assistant Professor of Industrial Engineering, June 12, 2013.
IE 467 – DISCRETE EVENT COMPUTER SIMULATION APPLICATION
Designation as a ‘Required’ or ‘Elective’ course
TYPE OF COURSE: Required for BSIE and BSME Major
Course (catalog) description
COURSE DESCRIPTION: IE 467 Industrial Systems Simulation. 3 Hours. The solution of
industrial problems by means of computer simulation. Simulation strategies. Simulation
perspectives. In-depth study of some specific simulation programming languages, with projects.
Prerequisite(s)
PREREQUISITE(S): IE 342.
Textbook(s) and/or other required material: Simulation with Arena, by Kelton and Sadowski, 5th
Edition, McGraw-Hill, New York, 2010.
Course objectives
COURSE OBJECTIVES: The primary objective is to become proficient in the use of discrete
event computer simulation as problem solving/system design technique. A systems approach to
problem solving/system design will be stressed. Since proficiency with simulation can only be
achieved from hands on experience, a computer simulation tool (Arena) will be applied to a
progression of projects including manufacturing/production systems, transportation, service,
bank system, etc. The course will also stress the importance of communication of simulation
results through written report and verbal presentations. Data analysis and approaches to
presenting simulation results will also be introduced. Upon completion of this course, the
students will be expected to be able to model complex, real life industrial systems using
computer simulation methods.
Topics covered
MAJOR TOPICS:
1
Introduction to discrete event simulation
2
Basic Modeling Concept
3
Terminating System Analysis
4
Transporters and Routings
5
Entity Flow and Conveyors
6
Non-Terminating System Analysis
7
Advanced Simulation Modeling Concepts
8
Arena Simulation Lab
9
Exams
10
Final Project Presentation
Total
Hrs
1
5
7
9
7
5
3
3
3
2
45
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 hours
Type of Instruction
Lecture-and-discussion
Laboratory
Contact Hours/Week
3
6
Contribution of course to meeting the professional component
The primary objective is to become proficient in the use of computer simulation as problem
solving/system design technique. Since proficiency with simulation can only be achieved from
hands on experience, a computer simulation tool (Arena) will be applied to a progression of
projects including manufacturing/production systems, transportation, service, bank system, etc.
Data analysis and approaches to presenting simulation results will also be introduced. Upon
completion of this course, students will be expected to be able to model complex, real life
industrial systems using computer simulation methods.
Relationship of course to program outcomes
As shown in the BSME Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
B.
Design and conduct experiments, as well as analyze and interpret data
D.
Ability to function on multi-disciplinary teams
E.
Ability to identify, formulate, and solve engineering problems
K.
Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice.
Person(s) who prepared this description and date of preparation
David He, Professor of Industrial Engineering, December 2013
Comments on outcomes
A.
Use of fundamental knowledge of probability and statistics in data analysis, problem
formulation, modeling, and solution generation.
B.
Data collection and curve fitting for input analysis, simulation experiments in
performance analysis, statistical inference of simulation output.
D.
The simulation projects and final simulation project required in this course encourage
students to form their project teams to achieve a better learning experience in the class.
E.
Throughout the course, the students are required to analyze different industrial systems,
identify the problems, formulate and modeling the problems, and find solutions to these
problems using simulation.
K.
After this course, the students will be able to use effectively the industrial simulation tool
to solve problems.
These outcomes are what students are expected to gain from this course.
IE 471 – OPERATIONS RESEARCH I
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE and BSEM Majors
Course (catalog) description
COURSE DESCRIPTION: IE471 Operations Research I. 3 undergraduate hours; 4 graduate
hours. Introduction to operations research, formulation of linear programming problems, simplex
methods, duality theory, sensitivity analysis, network models, and mixed-integer linear
programming. No graduate credit for industrial engineering majors.
Prerequisite(s)
PREREQUISITE(S): MATH 310, Applied Linear Algebra, 3 Hours
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS:
Introduction to Operations Research, Hillier and Lieberman, 8th edition, McGraw Hill, 2005,
Course objectives
COURSE OBJECTIVES: The course is designed to provide students with an opportunity to
learn the theory and techniques of linear programming and its extensions. Students are expected
to learn to formulate real-world problems as linear and mixed-integer programs through
illustrations in class, via numerous problems from text and the literature, and also via an optional
project opportunity. Students also learn to use Excel and CPLEX to solve linear programs. With
the successful completion of the course, students will be equipped with the understanding of a
palette of optimization tools: the simplex algorithm for linear programs and various algorithms
for simple network models.
Topics covered
MAJOR TOPICS:
1.
Introduction to operations research and linear programming
2.
Model formulation, graphical interpretation and computer implementation
3.
Simplex method
4.
Theory of the Simplex method
5.
Duality theory
6.
Sensitivity analysis
7.
Transportation and Assignment problems
8.
Network models
9.
Integer programming formulation
10.
Project presentation
11.
Exams
Total
Hrs
1½
6½
9
3
5
3
5
5-6*
4-5*
2*
3
45
*: The semester project is required for the course at the discretion of an instructor.
**: If an instructor requires the final project, 5 hours are allocated for network models and 4 for
integer programming.
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 undergraduate hours; 4 graduate hours.
Type of Instruction
Contact Hours/Week
Lecture-and-discussion
3
Contribution of course to meeting the professional component
The course is a gateway to optimization and presents a variety of basic operations research
techniques for solving linear programming problems. Foremost, students understand the need for
optimization. Through selectively chosen homework problems and the problems from the
literature as well as extensive discussions in class and/or the final project opportunity (optional,)
students learn to formulate and solve real-world problems as linear programs, network problems
and mixed-integer linear programs. Students also learn to use computer software for solving
linear programming problems and learn how to seek information outside of class materials.
Relationship of course to program outcomes:
As shown in the BSIE Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
E.
Ability to identify, formulate, and solve engineering problems
K.
Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice
Person(s) who prepared this description and date of preparation
Wei Chen (Associate Professor) & Hong Seo Ryoo (Assistant Professor) of Mechanical &
Industrial Engineering, January 31, 2002
Pat Banerjee (Professor) of Industrial Engineering, October 15, 2007
Elodie Adida (Assistant Professor of Industrial Engineering), September 17, 2008
Houshang Darabi, Head of Undergraduate Studies, August 2013
Comments on outcomes:
A.
Use of linear algebra and calculus to learn the theory and methods for linear optimization
problems.
E.
Through homework or/and an optional project.
K.
In addition to developing problem solving capabilities by hand in exam situations,
students are required to use computer software and other mathematics applications for
homework problems and their optional semester project.
IE472 – OPERATIONS RESEARCH II
Designation as a 'Required' or 'Elective' course
TYPE OF COURSE: Required for BSIE and BSEM Majors
Course (catalog) description
COURSE DESCRIPTION: IE472 Operations Research II. 3 undergraduate hours; 4 graduate
hours. Nonlinear programming problems, unconstrained optimization search techniques, Kuhn
Tucker theorems, quadratic programming, separable programming, dynamic programming,
Markov chain, and queuing theory.
Prerequisite(s)
PREREQUISITE(S): IE 471 – Operation Research I (3 Hours)
Textbook(s) and/or other required material
SAMPLE SOURCES AND RESOURCE MATERIALS: Introduction to Operations Research,
Hillier and Lieberman, 9th edition, 2010
Course objectives
COURSE OBJECTIVES: The course will continue to introduce the methods of operations
research for improving design and operations of engineering system. The learning will
emphasize the mathematical procedures of nonlinear programming search techniques,
probabilistic models in operations research (e.g., Markov Chains and Queuing Theory), and
dynamic programming. Students successfully completing this course are expected to be able to
apply a variety of operations research techniques for solving nonlinear programming problems;
to have a good command of probabilistic operations research methods and dynamic
programming techniques; and to be familiar with computer software for solving nonlinear
programming problems.
Topics covered
MAJOR TOPICS:
1.
Introduction to Nonlinear Programming
2.
Unconstrained Single Variable Problem
3.
Unconstrained Multiple Variable Problem
4.
Constrained Multiple Variable Problem
5.
Quadratic Programming
6.
Markov Chains
7.
Queuing Theory
8.
Dynamic Programming
9.
Computer Lab
10.
Review and Examinations (3 tests)
Total
Hrs
3
3
3
6
4½
6
6
4½
3
6
45
Class/laboratory schedule, i.e., number of sessions each week and duration of each session
CREDIT HOURS: 3 undergraduate hours; 4 graduate hours.
Type of Instruction
Contact Hours/Week
Lecture-and-discussion
3
Contribution of course to meeting the professional component
The course extends OR I and presents more advanced topics of operations research, including
nonlinear programming problems and probabilistic models. Through selectively chosen
homework problems and the problems from the literature as well as extensive discussions in
class and/or the final project opportunity (optional,) students learn the trade-off between realistic
formulations of real-world problems and their solvability, learn to seek information outside of
class materials, and realize the need for more sophisticated optimization tools and life-long
learning for more accurate treatment of nonlinear problems and probabilistic models. Students
also learn to use computer software for solving integer and nonlinear programming problems.
Relationship of course to program outcomes
As shown in the BSIE Course Outcomes Matrix:
A.
Ability to apply knowledge of mathematics, science and engineering
E.
Ability to identify, formulate, and solve engineering problems
K.
Ability to use the techniques, skills, and modern engineering tools necessary for
engineering practice.
Person(s) who prepared this description and date of preparation
Hong Seo Ryoo (Assistant Professor) & Wei Chen (Associate Professor) of Mechanical &
Industrial Engineering, January 31, 2002
Pat Banerjee (Professor) of Industrial Engineering, February 12, 2008
Nan Ratisoontorn, Visiting Assistant Professor of Industrial Engineering, June 12, 2013
Comments on outcomes
A.
Use of fundamental knowledge of mathematics such as linear algebra and calculus to
learn the methods in Nonlinear Programming. Use the knowledge of statistics and
probability to study the probabilistic models (Markov Chains and Queuing Theory) in
operations research.
E.
Through homework and computer project assignments, students are required to
demonstrate their understanding of the course material by implementing optimization
algorithms for solving engineering problems.
K.
In addition to developing problem solving capabilities by hand in exam situations,
students are required to use nonlinear programming software for homework problems and
the optional semester project. The optional semester project provides students an
opportunity to learn how to seek information outside of class materials. Through
illustrative examples, students are exposed to the shortcomings of linear programming
approach to real-world problems and the trade-off between realistic formulations of
problems vs. their solvability and understand the need for more sophisticated
optimization tools and life-long learning.
These are the outcomes students are expected to gain from this course.