56:091 – Professional Seminar
(Spring Semester, 2009)
Thursdays, 4:30P - 5:20P, C131 PC
There are different and individual reasons
Graduate with better initial pay
Don’t know what else to do
Defers student loan payback
Parents say so
Realizes that there is more to learn
There are 34 graduate students Fall 2009 in IE.
Number of students receiving externally sponsored program
funding as RAs
22 RA's are supported by Kusiak, Thomas, Schnell, Y Chen, Krokhmal
Number of graduate students receiving TA funding and for which
10 TA's are supported by 59:005, 56:032, 56:134, 56:144, 56:162,
Number of students receiving tuition waivers or direct tuition
All of our RA's and TA's receive tuition waiver ($2,615/semester)
5+ are receiving full tuition
Typical program duration, Post BS
MS: 2 years
PhD: 5 years
Research Focus Areas
Human Factors—The Human Factors area specializes in exploring how systems fit the people who
must operate them, determining the roles of people with the systems, and selecting those people
who can best fit particular roles within these systems. Students who focus on Human Factors will
be able to work with a multidisciplinary team of faculty with strengths in understanding cognitive
behavior as it relates to automation, air and ground transportation, medical studies, and space
Production Systems—The Production Systems area develops new solutions in areas such as
engineering design, supply chain management (e.g. supply chain system design, error recovery,
large scale systems), manufacturing (e.g. system design, planning and scheduling), and medicine
(e.g. disease diagnosis, discovery of medical knowledge). Students who focus on production
systems will be able to work on topics related to computational intelligence theories for
applications in industry, healthcare, and service organizations.
Reliability Systems—The objective of the Reliability Systems area is to provide students with
advanced data analysis and decision making techniques that will improve quality and reliability of
complex systems. Students who focus on system reliability and uncertainty will be able to work
on areas related to contemporary reliability systems including integration of quality and
reliability, simultaneous life cycle design for manufacturing systems, decision theory in quality
and reliability engineering, condition-based maintenance and degradation modeling, discrete
event simulation and decision analysis.
Virtual reality, robotics, human-computer interaction
Aviation human factors, flight test, training systems,
Matt Rizzo (secondary appointment)
Data mining, evolutionary computation, healthcare
systems, medical technology, reengineering, engine
manufacturing, process modeling
Intelligent Systems Lab
Supply chain design, large scale networks,
collaborative systems for design and manufacturing,
financial engineering and distributed design.
Kurt Anstreicher (secondary appointment)
Linear and nonlinear programming, interior-point
algorithms, nonlinear integer programming.
Maintenance decision making, process
monitoring and diagnosis, reliability modeling and
analysis, manufacturing system design
Stochastic optimization, risk analysis,
probabilistic combinatorial optimization,
cooperative control, optimal trading strategies
and pricing of derivatives.
Center of Computer Aided Design (CCAD)
IIHR- Hydroscience & Engineering
National Advanced Driving Simulator
Injury Prevention Center
In many ways easier than UG
Requires tight collaboration with an advisor
Requires focus on research
Pays for itself and then some
Master of Science
Students from ABET accredited U.S. universities
From any engineering discipline or the mathematical, physical, or
computer science disciplines
Minimum undergraduate grade point average of 3.00 (based on 4.00)
and/or an acceptable score on the Graduate Record Examination
(minimum score of 650 Q and 4.5 W).
Entering students need strong verbal and written skills in the English
language and a background in computer programming, (e.g., C++, C,
VB), probability, statistics, and mathematics equivalent to that
required in an accredited undergraduate engineering program.
Other background requirements are helpful depending upon the
emphasis of the individual's program of study. Students with
insufficient background are expected to take additional courses
beyond those normally required in a plan of study.
Why would anyone do non-thesis ?
Minimum of 30 semester credits of coursework in l00 or 200 level courses
including a maximum of six semester credit hours of research.
requires a minimum of 36 semester credits of course work in 100- or 200-level
courses, and cannot include any credit hours of research.
May cause extra work if student decides to go for PhD
Both options require at least 21 graduate-level semester credits in
Industrial Engineering, including research credits
MS degree candidates must
take at least nine semester credits at the 200 level from the Industrial
Take at least one 100- or 200-level course from each of three focus areas,
Human Factors, Operations Research, and Reliability and Systems Design.
M.S. thesis applicants who wish to pursue a PhD degree at The University of
Iowa may wish to select two 200-level courses in each of the focus areas to
complete their PhD breadth requirement before entering the PhD program.
A special combined Bachelor of Science/Master of Science (BS/MS) degree
program for qualified Industrial Engineering undergraduate students is available
to enable a student to complete a Master of Science degree in two or three
semesters after completion of the Bachelor of Science degree.
Students in the joint degree program are allowed to take up to 12 semester hours
(sh) of 100- or 200-level graduate courses and attend one of the program's
graduate seminars in place of the undergraduate seminar before the conferral of
the Bachelor of Science degree.
Of these courses, 6 sh may be counted towards both the B.S. and M.S. degrees.
The requirements for admission to the program are:
completion of at least 80 sh of credits
a cumulative grade point average (GPA) of 3.25 or higher
a letter of application submitted to the Department of Mechanical and Industrial Engineering
A student in the combined program receives a B.S. degree when all requirements
for that degree have been completed, and then becomes a regular M.S. level
graduate student in the program. Students in the program may begin working
with a faculty member on an M.S. thesis project during the senior year of
A series of written and oral examinations is required, as well as written dissertation based upon the results of the original
The PhD degree recognizes a broad academic background with considerable depth in at least one area of specialization
and that clearly demonstrates the capability of the student to do high level research.
At least two semesters of residence and include a minimum of 72 hours of total graduate study including research for the
Graduate studies towards a M.S. degree are included in the minimum requirements, with a maximum of 36 hours
transferred in from a M.S. program in Industrial Engineering (or closely allied area) at a recognized institution.
A minimum grade point average of 3.25 (based on 4.00) is required on all graduate work taken at The University of Iowa.
Each PhD student must pass at least two 200 level IE formal courses in each of three focus areas: Human Factors,
Operations Research, and Reliability and Systems Design.
Continuing M.S. students may already satisfy this requirement in full or in part.
Each student has to satisfy the Qualifying Exam in two of the three focus areas.
The requirement can be satisfied for a focus area by:
▪ Passing a written Qualifying Exam in that focus area.
▪ Achieving a grade of A- or better in each of two 200 level IE formal courses in that focus area.
The student will have to demonstrate their capability for creative individual research achievement by completing and
defending his or her dissertation research proposal in a Comprehensive Examination conducted by an Examining
Committee consisting of at least 5 members of the Graduate College faculty, with at least three faculty who are
predominately IE faculty, and with a chair or co-chair of the Examining Committee who is a predominately IE faculty.
Having satisfactorily completed this examination, the student is accepted as a candidate for the PhD degree.
The student then has to complete and defend his or her dissertation in a final examination conducted by the Examining
Committee, with a composition as described in the section on the Comprehensive Examination.
Semester Human Operations
Course Title Production
Offering Factors Research
56:131 Manufacturing Systems Spring X
56:132 Introduction to Industrial Robotics TBD X
56:134 Process Engineering Fall X
56:138 Knowledge Discovery and Management TBD X
56:144 Human Factors Fall F
56:147 Ergonomics Spring X
56:150 Information Systems Design Spring X
56:153 Engineering Administration I Fall X
56:162 Quality Control Spring X
56:166 Stochastic Modeling Spring X
56:171 Operations Research Fall F
56:176 Applied Linear Regression Fall X
56:178 Digital Systems Simulation Fall F
56:181 Internet Systems Design TBD X
56:186 Health Informatics I Fall X
Semester Human Operations
Course Title Production
Offering Factors Research
56:230 Innovation Science and Studies (Kusiak) Spr (10, 12) X
56:235 Computational Intelligence (Kusiak) Spr (11, 13) X
56:236 Decision Making in Supply Chain Management Engineering Fall (10, 12) X
56:237 Operational Issues in Supply Chain Management Engineering Fall (09, 11) X
56:240 Human Performance in Engineering Systems Spr (10, 12) X
56:241 Research Methods in Human Factors Engineering Spr (10, 12) X
56:242 Human Computer Interaction (Thomas) Fall (09, 11) X
56:243 Modeling Operator Performance Spr (11) X
56:244 Airborne Design of Experiments (Schnell) Fall (09, 11) X
56:245 Human Factors in Aviation (Schnell) Fall (10, 12) X
56:246 The Design of Virtual Environments (Thomas) Fall (10, 12) X
56:248 Analytical Methods in Human Factors Engineering Spr (11) X
56:270 Linear Programming (same as 06K:286; ) Fall X
56:271 Nonlinear Programming (Chen) Fall (09, 11) X
56:272 Integer Programming and Network Flows Spring X
same as (06K:287: Discrete Optimization; )
56:275 Statistical Pattern Recognition (Chen) Fall (09, 11) X X
56:274 Stochastic Optimization (Krokhmal) Fall (09, 11) X
56:276 Game theory (Krokhmal) Fall (10, 12) X