The University of Arizona  1993-95 General Catalog

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Systems and Industrial Engineering (SIE)
Engineering Building, Room 111
(520) 626-8181

Professors Pitu B. Mirchandani, Head, Ronald G. Askin, A. Terry
Bahill, Lucien Duckstein, William R. Ferrell, Marcel F. Neuts,
John S. Ramberg, Donald G. Schultz (Emeritus), Soroosh
Sorooshian, Ferenc Szidarovszky, A. Wayne Wymore (Emeritus),
Sidney J. Yakowitz

Associate Professors Robert L. Baker (Emeritus), Duane L.
Dietrich, Jeffrey B. Goldberg, Julia L. Higle, Suvrajeet Sen

Assistant Professors Emmanuel Fernandez, Sanjay Jagdale, Renato
Monteiro, Fei-Yue Wang

Instructor Frank W. Ciarallo, John R. Lyon

Adjunct Professor Walter Arnell

Adjunct Associate Professor Sandra Newsome

Adjunct Assistant Professor Kenneth L. Head, William Thompson

The Department of Systems and Industrial Engineering in the
College of Engineering and Mines offers the degrees of Bachelor
of Science in Systems Engineering, Bachelor of Science in
Industrial Engineering, Master of Science with a major in
systems, industrial, or reliability and quality engineering, and
Doctor of Philosophy with a major in systems and industrial
engineering. For specific undergraduate program requirements, see
the College of Engineering and Mines section of this catalog.

230. Introduction to Engineering Probability and Statistics (3) I
II S Axioms of probability, discrete and continuous
distributions, sampling distributions. Engineering applications
of statistical estimation, hypothesis testing, confidence
intervals.. P, MATH 125b.

250. Introduction to Systems Engineering (3) I System modeling;
the elementary constructs and principles of system models
including discrete-time, discrete-state system theory; finite
state machines; modeling components, coupling, modes, and
homomorphisms. System design; requirements, life-cycle,
performance measures, costs, tradeoffs, alternative design
concepts, testing plan, and documentation. Applications and case
studies from engineering. 2ES, 1ED. P, ENGR 102, MATH 125b.

260. Introduction to Industrial and Manufacturing Systems (3) I
Analysis, design and control of manufacturing and production
systems, including topics in facilities layout and location,
materials handling, inventory control, computer-integrated
manufacturing, information systems, and simulation. 2ES, 1ED. P,
ENGR 102, MATH 125b.

265. Engineering Economic Analysis (3) I II S Methods and modern
techniques of engineering economic analysis for decision making.
Topics from evaluations of economic alternatives, cost control,
capital budgeting, managerial cost accounting and deterministic
inventory theory and decision-making under uncertainty. 3ES. P,
ENGR 102, MATH 125b. (Identical with ENGR 265)

270. Computer Methods for Engineering (3) I II S Application of
numerical methods and computer programming techniques to the
solution of numerical problems of engineering systems. 1.5ES. P,
ENGR 102, MATH 125b and PHYS 110.

321. Probabilistic Models in Operations Research (3) II
Probability, Markov chains, Poisson processes, queueing models,
reliability models. 3ES. P, 230.

330R. Engineering Statistics (3) I II Design of engineering
experiments and associated analytical and graphical data analysis
methods, including tests of significance, confidence intervals,
multiple regression, and probability plots. 1.5ES, 1.5ED. P, MATH
254, SIE 230, CR 330L.

330L. Engineering Statistics Lab (1) I II Problem solving in the
applications of engineering statistics. 0.5ES, 0.5ED. CR, 330R.

340. Deterministic Operations Research (3) I Deterministic models
and methods of operations research linear programming, including
models, theory and algorithms. 3ES. P, MATH 254.

350. Deterministic Systems (3) II Analysis and design of linear
deterministic systems in both the time and frequency domains
using Fourier analysis, Laplace transforms and state space
methods. Attention will be given to modeling physical and
engineering systems. 3ES. P, MATH 254.

370. Microcomputer Systems (4) I II Boolean algebra,
combinational and sequential logic circuits, state machines,
simple computer architecture, assembly language programming, and
real-time computer control. The computer is used as an example of
systems engineering design; it is analyzed as a system, not as a
collection of components. 3R, 3L. 1ES, 3ED. P, ENGR 102, ECE 207.

377. Software for Engineers (3) I FORTRAN and C. Modular design,
program verification, data structures, and development of
algorithms. Credit is allowed for this course or C SC 342, but
not for both. 1.5ES, 1.5ED. CR, 321.

383. Integrated Manufacturing Systems (3) II Introduction to the
integrated manufacturing enterprise and automation. Topics
include computer-aided design, process planning, computer
numerical control machining, machine vision, application of
robots and automation. 2R, 2L. 2ES, 1ED. P, 260, MSE 331.

406. Engineering Quality Control (3) II Quality planning, on-line
statistical process control techniques for monitoring and
improving the quality of manufactured products, acceptance
sampling, and government standards. 2ES, 1ED. P, 230 or A ME 474,
CR, 330R, 330L.

408. Reliability Engineering (3) I Time-to-time failure, failure-
rate, and reliability determination for early, useful and wear-
out lives; equipment reliability predictions; spare parts
provisioning; reliability growth; reliability allocation. Credit
for this course or A ME 472. P, 330 or A ME 413a, MATH 223.
1.5ES, 1.5ED. May be convened with 508.

410. Industrial Ergonomics (4) I Human performance and well-being
as affected by workplace, environment and task. Analysis and
design for prevention and solution of ergonomic problems. Basic
measurements and design methods. 2ES, 2ED. P, 230, PSYC 101.

411. Human Interaction with Computers and Software (4) II The
interaction of technical requirements with the characteristics of
computer users and programmers as they affect the design of
software, and the physical and cognitive interfaces between
people and computers. 1ES, 3ED. May be convened with 511.

422. Engineering Decision Making Under Uncertainty (3) I
Application of principles of probability and statistics to the
design and control of engineering systems in a random or
uncertain environment. Emphasis is placed on Bayesian decision
analysis. 1ES, 2ED. P, 330R-330L or equivalent. May be convened
with 522.

430. Engineering Statistics (3) I II Statistical methodology of
estimation, testing hypotheses, goodness-of-fit, nonparametric
methods and decision theory as it relates to engineering
practice. Significant emphasis on the underlying statistical
modeling and assumptions. P, 330R, 330L. May be convened with

431. Digital Systems Simulation (3) I II Simulation modeling of
systems using digital computer languages, emphasizing random
variate generation, modeling, timekeeping structures and
statistical design and analysis of simulation experiments. 1.5ES,
1.5ED. P, 321, 330R, 330L. May be convened with 531.

440. Survey of Optimization Methods (3) II Survey of methods
including network flows, integer programming, nonlinear
programming, and dynamic programming. Model development and
solution algorithms are covered. 3ES. P, 340. May be convened
with 540.

442. System Design Projects (3) I II Practical application of
engineering knowledge by student teams to actual system design
problems in industry or business. Development of report writing
and oral presentation skills. 3ED. P, 431. Writing-Emphasis
Course. P, satisfaction of the upper-division writing-proficiency
requirement (see "Writing-Emphasis Courses" in the Academic
Policies and Graduation Requirements section of this catalog).

453. Deterministic Control Systems (3) I The analysis and
synthesis of deterministic linear control systems, with emphasis
on design using both frequency-domain and state-variable
approaches. 1.5ES, 1.5ED. P, 350.

462. Production Systems Analysis (3) I Production systems,
quantitative methods for forecasting, aggregate planning,
inventory control, materials requirement planning, production
scheduling, manpower planning and facility design. 3ES. P, 340.

463. Facilities and Production Systems Design (3) I Case studies
emphasizing aspects of production systems design such as facility
location, facility layout, group technology, product and process
design, material handling, and automated assembly. The student
will be required to work in groups. Solutions will be presented
using both written and oral reports. 3ED. CR, 462.

464. Facilities Layout and Location (3) II Modeling and solution
of continuous and discrete, single and multifacility location
problems for various objectives. Relative location and layout of
facilities/departments for minimizing material handling and
interaction costs. Emphasis on quantitative methods. 2ES, 1ED. P,
321, 340. May be convened with 564.

473. Concepts in Information and Communication Systems (3) II
Modeling and analysis of information and communication,
systems/networks for applications in telecommunication, systems
and computer communication networks. Topics selected from the
following: signal representation, sampling, coding and error
detection, modulation, OSI network architecture, network
protocols, delay models of performance, routing and flow control.
3ES. P, 321, 340. May be convened with 573.

474. Expert Systems (3) I Building, testing and evaluating expert
systems, computer systems that emulate the human and draw
conclusions based on incomplete or inaccurate data. Each student
will build an expert system using commercially available expert
system shells. 1ES, 2ED. P, familiarity with computers. May be
convened with 574.

475. Computational Methods for Games, Decisions, and Artificial
Intelligence (3) II An introduction to automata, computer
representation and optimal solution of games and decision
problems. Principles of heuristic programming and machine
learning. A programming project is to be selected from areas such
as game strategies, graphics, recreational mathematics, and
manufacturing simulation. Microcomputer experience is emphasized.
1.5ES, 1.5ED. P, 270 or C SC 227. May be convened with 575.

476. Numerical Analysis (3) I An intermediate-level introduction
to numerical methods and error analysis for function
approximation and interpolation, integration, solution of linear
and nonlinear equations, and differential equations. 3ES. P, ENGR
102, MATH 254. May be convened with 576.

485. Introduction to Robotics (3) I Methods of design and
operation of general purpose and industrial manipulation systems.
Kinematic and dynamic models of mechanical manipulators.
Trajectory planning. Manipulator control. Robotic vision and
sensors. Computer software, languages and simulation methods for
robotics systems. Mathematical theory of intelligent machines and
application to automation. 3ES. P, 350. May be convened with 585.

486. Modeling Manufacturing Systems (3) II An intermediate-level
introduction to topics in hierarchical design, planning, and
control of manufacturing systems. Topics include modeling
automated transfer lines, cellular manufacturing, and flexible
manufacturing systems. Emphasis on material flow and analysis of
throughput rate. 2ES, 1ED, P, 321, 340. May be convened with 586.

495. Colloquium
s. Senior (1) I Open to majors only. P, senior standing.

507. Advanced Engineering Quality Control (3) II Advanced
techniques for statistical quality assurance, including
multivariate control charting, principal components analysis,
economic design of acceptance sampling plans and control charts,
inspection errors, and select papers from the recent literature.
P, 530.

508. Reliability Engineering (3) I For a description of course
topics, see 408. Graduate-level requirements include a special
report of 30 pages on a specific reliability engineering topic.
Credit for this course or A ME 572. May be convened with 408.

510. Behavioral Judgment and Decision Making (3) II Models and
theories of human judgment and decision from an engineering
perspective. Subjective probability, value and utility. Methods
for aiding and supporting decision making. P, 330R, 330L or 530.

511. Human Interaction with Computers and Software (4) II For a
description of course topics, see 411. Graduate-level
requirements include separate examinations and a major project.
May be convened with 411.

513. Environmental Risk Analysis (3) I 1994-95 (Identical with
HWR 513)

518. Reliability Testing (3) II Mean-time-between-failure and
reliability confidence limits; sequential testing; sampling;
accelerated, sudden-death, and suspended-items; non-parametric,
and Bayesian testing. Credit for this course or A ME 575. P, 408,

520. Stochastic Modeling I (3) I Modeling of stochastic processes
from an applied viewpoint. Markov chains in discrete and
continuous time, renewal theory, applications to engineering
processes. P, 321.

521a-521b. Advanced Systems Modeling and Simulation (3-3)
(Identical with MIS 521a-521b)

522. Engineering Decision Making Under Uncertainty (3) I For a
description of course topics, see 422. Graduate-level
requirements include a semester research project. P, 330R, 330L.
May be convened with 422.

525. Queueing Theory (3) II Application of the theory of
stochastic processes to queueing phenomena; introduction to semi-
Markov processes; steady-state analysis of birth-death,
Markovian, and general single- and multiple-channel queueing
systems. P, 520.

528. Maintainability Engineering (3) II Complex systems
reliability; maintainability engineering; reliability and
availability of maintained systems; operational readiness; system
effectiveness; maintainability demonstration. Credit for this
course or A ME 577, but not for both. P, 408, 530.

529. Advanced Decision-Making Under Uncertainty (3) II 1993-94
Review of statistical decision theory; utility, games, Bayesian
decision theory. Conjugate priors, worth of data, worth of
information sequential decision making. Engineering and water
resource applications. P, 422.

530. Engineering Statistics (3) I II For a description of course
topics, see 430. Graduate-level requirements include additionally
more difficult homework assignments. P, 330R, 330L or equivalent.
May be convened with 430.

531. Digital Systems Simulation (3) I II For a description of
course topics, see 431. Graduate-level requirements include a
library research report. May be convened with 431.

532. Statistical Models in Engineering (3) Statistical
distributions applicable in engineering, with emphasis on quality
and reliability problems. Topics include model selection,
parameter estimation, and approximations for large-scale systems.
P, 530.

536. Experiment Design for Engineering I (3) I Design and
analysis of experiments for engineering design and manufacture.
Topics include classical designs, Japanese approaches, analysis
of variance and regression analysis. P, 530 or STAT 566a.

537. Experiment Design for Engineering II (3) II Continuation of
536. Topics include response surface analysis, related empirical
optimization methods, random effects models and nested designs.
P, 536.

540. Survey of Optimization Methods (3) II For a description of
course topics, see 440. Graduate-level requirements include
additional assigned readings and a project paper. P, 340, May be
convened with 440.

541. Dynamic Programming (3) II 1993-94 Application of the art
and theory of dynamic programming to common stochastic and
deterministic sequential decision problems, including equipment
replacement, capacity expansion, inventory planning and decision
analysis. P, 321, 340.

544. Linear Programming (3) I Linear and integer programming
formulations, simplex method, geometry of the simplex method,
sensitivity and duality, projective transformation methods. P,

545. Nonlinear Programming (3) II Unconstrained and constrained
optimization problems from a numerical standpoint. Topics include
variable metric methods, optimality conditions, quadratic
programming, penalty and barrier function methods, interior point
methods, successive quadratic programming methods. P, 340.

546. Algorithms and Heuristics for Graphs and Networks (3) II
1994-95 State-of-the-art solution methods for several practical
problems that may be formulated on graphs and networks. Emphasis
on obtaining good solutions in reasonable time when optimization
proves intractible. P, 544.

550. Theory of Linear Systems (3) II An intensive study of
continuous and discrete linear systems from the state-space
viewpoint, including criteria for observability, controllability,
and minimal realizations; and optionally, aspects of optimal
control, state feedback, and observer theory. P, 350.

551. Modeling Physiological Systems (3) Development and
validation of models, sensitivity analyses, and applications of
systems engineering techniques to physiological systems.

552. Analysis and Optimization of Discrete Event Dynamical
Systems (3) Introduction to Discrete Event Dynamical Systems
(DEDS) and the associated modeling and analysis tools.
Generalized semi-Markov process model of DEDS. Elementary
queueing model operational analysis. Mean value analysis.
Perturbation analysis. Supervisory control methodology of DEDS.
Applications to computer and manufacturing systems. P, linear
algebra and vector calculus; basic probability and statistics.

554. Mathematical Systems Engineering Design (3) I Tools for
modeling and concurrent engineering of large-scale, complex
systems: documentation, a system design language, quality
function deployment, system coupling, subsystems, and

558. Fuzzy Sets in Systems Analysis and Analysis, and Decision
Making (3) I 1993-94 Fuzzy numbers' definition, operations; fuzzy
regression, interpolation and reliability, fuzzy logic,
optimization and control; fuzzy events and decision-making
applications in areas such as systems, civil, industrial,
electrical, computer engineering and water management.

559. Multi-Objective Analysis of Engineering Systems (3) I 1994-
95 Systems design versus operation; multi-objective programming
distance-based and outranking techniques; multi-attribute
utility; techniques with qualitative criteria; interactive,
quasi-interactive and dynamic approaches; model choice; resource
and industrial engineering applications. P, 321, CR, 544.

562. Scheduling Theory (3) I 1993-94 Introduction to sequencing
and scheduling. Algorithms for single, multiple, and parallel
processor scheduling problems. Special purpose methods, discrete
programming and heuristic methods. Complexity of scheduling
problems. Industrial practice.

564. Facilities Layout and Location (3) II For a description of
course topics, see 464. Graduate-level requirements include
additional assigned readings and an in-depth research paper on a
course topic. P, 340, 462. May be convened with 464.

567. Advanced Production Control (3) II Quantitative models in
the planning, analysis, and control of multi-level production
systems. Topics include aggregate planning, inventory control,
capacitated and uncapacitated lot-sizing, and Just-in-Time
systems. P, 544, 321.

573. Concepts in Information and Communication Systems (3) II For
a description of course topics, see 473. Graduate-level
requirements include a course project in the subject area. P,
321, 340. May be convened with 473.

574. Expert Systems (3) I For a description of course topics, see
474. Graduate-level requirements include a strong testing and
validation study of student's expert system. P, familiarity with
computers. May be convened with 474.

575. Computational Methods for Games, Decisions, and Artificial
Intelligence (3) II For a description of course topics, see 475.
Graduate-level requirements include a comprehensive and intensive
programming project. P, 270 or C SC 227. May be convened with

576. Numerical Analysis (3) I For a description of course topics,
see 476. Graduate-level requirements include extra reading
assignments and more sophisticated programming assignments. P,
ENGR 102, MATH 254, or equivalent skill in PASCAL or FORTRAN. May
be convened with 476.

583. Computer Integrated Manufacturing Systems (3) I Modern
manufacturing systems with emphasis on information requirements
and data management. Includes CAD, CAM, CAPP, real time
scheduling, networking and system justification.

584. Manufacturing Automation (3) II Current topics in hardware
for automation, selecting and implementing robots, part
orientation, computer vision, automated warehousing and material
handling, programmable controllers, NC machining, on-line
computer control. Laboratory projects.

585. Introduction to Robotics (3) I For a description of course
topics, see 485. Graduate-level requirements include two research
projects. P, 350. May be convened with 485.

586. Modeling Manufacturing Systems (3) II For a description of
course topics, see 486. Graduate-level requirements include
additional assigned readings from the current literature and an
in-depth paper on recent research on a course topic. P, 321, 340.
May be convened with 486.

608. Selected Topics in Reliability (3) I In-depth analysis of
selected advanced topics in reliability engineering from the
recent archival literature. Project required. P, 530, A ME 577.

620. Selected Topics in Probability Modeling (3) II [Rpt./2] An
advanced discussion of a subject in applied probability with
significant interest to engineering. Individual projects in
stochastic modeling. P, 520.

625. Advanced Queueing Theory (3) Study of complex queueing
models of engineering interest. Emphasis on algorithmic methods
for the study of such models. P, 525.

631. Digital Systems Simulation (3) Emphasis on current research
problems including random variate generation, modeling, language
development and statistical analysis of output. P, 431 or MIS
521a or 521b.

640. Topics of Optimization (3) [Rpt./2] I Convexity, optimality
conditions, duality, and topics related to the instructor's
research interests; e.g., stochastic programming, nonsmooth
optimization, interior point methods. P, 544 or 540.

645. Large-Scale Optimization (3) I 1994-95 Decomposition-
coordination algorithms for large-scale mathematical programming.
Methods include generalized Benders decomposition, resource and
price directive methods, subgradient optimization, and descent
methods of nondifferentiable optimization. Application of these
methods to stochastic programming will be emphasized. P, 544.

646. Integer and Combinatorial Optimization (3) 1993-94 Modeling
and solving problems where the decisions form a discrete set.
Topics include model development, brand and bound methods,
cutting plane methods, relaxations, computational complexity, and
solving well-structured problems. P, 544.

654. Mathematical Theory of System Design (3) II Formal
presentation of the system design process. Development of the
system design requirements: input/output, technology,
performance, utilization of resources, tradeoff, and system test.
Defining and specifying the system model requirements. P, 554.

685. Advanced Topics in Robotics (3) II Selected topics covering
recent advances in robotics, to be chosen from a list including
applications, kinematics, dynamics, tactile sensing and vision.
P, 485.

686. Advanced Manufacturing System Modeling (3) I 1993-94 Current
topics in design and analysis of manufacturing systems. Topics
include serial processing lines, queueing networks and FMS.
Student projects. P, 567 or 586.

695. Colloquium
a. Doctoral (1-3) [Rpt./12 units] I II Consult department before

696. Seminar
m. Operations Research Methods to Water Resources Systems (1-3)
[Rpt./1] II P, consult department before enrolling. (Identical
with HWR 696m, which is the home)


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