Students needing preparatory work may take one or more of the following, which can count toward an undergraduate but not a graduate degree:
| SSIE 400. Fundamentals of Mathematics | 3 credits |
| SSIE 410. Fundamental Structures | 3 credits |
| CS 210. Logic Design | 4 credits |
| CS 140. Introduction to Computer Programming | 4 credits |
General Systems Sequence. The general systems sequence provides
the student with firm conceptual foundations and tools for solving systems
problems of universal nature through a well-organized general systems methodology.
Emphasis is given to balanced use of mathematical and computational tools
in the study of problems associated with complex systems. In addition to
the courses required of all students in the systems science specialization,
the student takes the following courses:
| SSIE 606. Systems Problem Solving Workshop | 2 |
| SSIE 517. Fuzzy Sets, Uncertainty, and Information | 3 |
| or alternatively
SSIE 516. Fuzzy Set Theory and Information Theory |
2 |
| SSIE 650. Systems Optimization | 3 |
1. Four required courses:
SSIE 561. Quality Assurance
SSIE 520. Modeling and Simulation
SSIE 510. The Science of Manufacturing
SSIE 512. Integrated Manufacturing Systems
2. Four courses in an area of specialization or from a list of approved courses outside the department.
3. Complete either of the following independent study options:
a. Thesis: oral presentation and defense of the thesis are required.
b. Non-thesis: with departmental approval, the thesis requirement may
be replaced by two approved elective courses and a project. Normally only
allowed for part-time students.
SSIE 400. FUNDAMENTALS OF MATHEMATICS
Basic concepts of logic: truth tables, tautologies, valid arguments.
Set theory: subsets, product sets, cardinality, functions and relations.
Basic concepts of probability; real functions of real variable; derivative,
integral, limit, conti nuity; interpolation, approximation; vectors and
matrices.
SSIE 410. FUNDAMENTAL STRUCTURES
Covered concepts: sets, fuzzy sets, graph theory, trees, finite automata,
Turing machines, formal languages, algebraic structures, semigroups, monoids,
lattices, Boolean algebras, homomorphisms, isomorphisms, etc. Presented
in terms applicable to modelling and simulation in systems and computer
science. This class is available to under graduate students as SSIE 310.
Graduate students complete additional assignments. Prerequisite: SSIE 400
or equivalent.
SSIE 500. COMPUTATIONAL TOOLS
Prepares the student for the computer demands and opportunities involved
in the design, analysis, modeling, and simulation of complex systems. Each
student develops a specific artificial life system demonstrating complex
behavior. This system serves as the focal point for investigating modern
tools associated with advanced research. Students develop proficiency in
using object-oriented paradigms, contemporary programming languages (Java,
C++, Smalltalk), symbolic computation (Mathematica, Maple, MathCad), spreadsheet
analysis (Lotus, Excel, QuattroPro), discrete and continuous simulation
languages (SIMAN, ARENA, Stella), and the Internet as research tools to
enhance their computer modeling techniques and understanding. Emphasis
is placed on integrating the results of these tool applications to produce
a comprehensive, professional report and presentation using word processing
and presentation graphics packages. Prerequisite: graduate standing or
consent of the department chair.
SSIE 501. INTRODUCTION TO SYSTEMS SCIENCE
Course includes: a general characterization of systems science as a
field of study; intellectual roots, philosophical assumptions, and historical
development of the field; an overview of fundamental systems concepts,
principles, and laws; and a survey of application areas of systems science
and its implications for other fields of study.
SSIE 502. SIMPLE MODELS OF COMPLEX SYSTEMS
Course explores and illustrates dynamic processes, such as growth,
evolution, diffusion, aggregation, chaos, and bifurcation that produce
patterns and structures occurring in many natural systems. Systems modeling
techniques such as Cellular Automation Models (CAM), Movable Finite Automate
Models (MFA), Lindenmeyer Systems (L -systems), and Fractals, will be introduced,
and applied to biology, physics, chemistry, computer science, engineer
ing, etc. The treatment will be kept mathematically simple; instead microcomputer-based
graphics will be generously used in the course. Course consists of lectures
as well as hands-on experience on microcomputers. A key requirement for
satisfactory completion of the course is the development of a computer
model of a dynamic process, and graphic display of the results.
SSIE 505. APPLIED PROBABILITY AND STATISTICS
Basic concepts in probability and statistics required in the modeling
of random processes and uncertainty. Bayes formula, Bayesian statistics,
independence of events; random variables and their descriptive statistics;
distribution and moment generating functions; Bernoulli trials, normal
binomial hypergeometric, Poisson, exponential and multi nomial distributions,
Chebyshev's theorem; sampling, con fidence intervals, estimation of parameters,
Students-t, gamma X squared and F distributions; hypothesis testing, contingency
tables, goodness of fit, nonparametric statis tics, curve fitting, least
squares, regression, correlation; maximum entropy principle. Prerequisites:
SSIE 400 and one year of calculus.
SSIE 506. SYSTEMS PROBLEM SOLVING
A comprehensive conceptual framework for systems problem solving is
introduced. Methods applicable to broad classes of problems discussed.
Prerequisites: SSIE 410 and 505, and CS 340 or equivalent.
SSIE 510. THE SCIENCE OF MANUFACTURING
Manufacturing has become increasingly critical to our standard of living
and to our competitive market position. Little has really been published
and analyzed as to the underlying science of manufacturing. This course
is designed to study the manufacturing literature and the manufacturing
process and to investigate the underlying principles that govern manufacturing.
Prerequisite: SSIE 505 or equivalent.
SSIE 511. ADVANCED PRODUCTION AND SCHEDULE CONTROL
Production scheduling and control. Design/production interface, bills
of material, engineering revision control, and general concepts of production
planning and control for the engineer. Prerequisite: SSIE 510 or consent
of department chair.
SSIE 512. INTEGRATED MANUFACTURING SYSTEMS
Integration of equipment, people, and information re quired in total
manufacturing systems. Product/process design, planning and support, procurement
support, software/hardware. Prerequisite: graduate standing or consent
of department chair.
SSIE 513. ADVANCED DESIGN FOR MATERIAL SYSTEMS
Material and material-related costs represent as much as one half to
two thirds of today's manufacturing cost. The focus for a competitive manufacturing
enterprise must be upon controlling and reducing these costs. This control
and reduction will be brought about through an analysis of the total system,
from purchase through the facility and out to the customer. Specific topics
include: relationship buying, just-in-time, workstation design, handling
systems design, facility design, and distribution systems. Prerequisite:
SSIE 510 or consent of department chair.
SSIE 516. FUZZY SET THEORY AND INFORMATION THEORY
2 credits
Overview of basic concepts of fuzzy set theory. Difference between
probability theory and fuzzy set theory. Foundations of information theory.
Uniqueness of information measures, maximum and minimum principles of information,
fundamental properties of information. Prerequisites: SSIE 500 and 505,
or equivalents.
SSIE 517. FUZZY SET, UNCERTAINTY, AND INFORMATION
Same subject areas as SSIE 516 (Fuzzy Set Theory and Information Theory),
but some topics are covered at greater depth.
*SSIE 518. GENERALIZED INFORMATION THEORY
Several new theories of uncertainty are introduced, including possibility
theory, evidence theory, and fuzzy set theory. Measures of information
based on uncertainty reduction within these theories are examined in detail
and compared with the classical measure of information formulated within
the framework of probability theory (the Shannon entropy). Three important
principles of uncertainty-based information are introduced, and their role
in classical science, systems science, computer science, engineering, and
other areas of human affairs is discussed. Prerequisite: calculus and basic
probability theory (e.g., SSIE 505).
SSIE 520. MODELING AND SIMULATION
4 credits
Approaches, methodologies, and specific tools required in the modeling
of complex systems. Stochastic systems, discrete event simulation, experimental
statistics, and elementary queuing theory. Dynamic behavior of continuous
models. GPSS, Stella II, SAS, Minitab, SPSS, or JMP. Decision, utility,
and game theory. Meta-modeling, adaptive linear machines. Sensitivity analysis,
validity, and precision of model. Prerequisites: SSIE 410, 505, and CS
541, or equivalents.
SSIE 521. ANALYSIS OF SIMULATION RESULTS
Ability to analyze, understand, and control complex manufacturing systems
is enhanced through usage of simulation techniques. Topics include model
development, theory, model validation, evaluation and analysis of the results,
etc. Major emphasis on projects which are development models for actual
manufacturing systems. Prerequisite: graduate standing or approval of department
chair.
SSIE 530. ANALYSIS OF PHYSICAL SYSTEMS I
Modeling and analysis of physical systems described by continuous functions
of single independent variable. Mathematical models formulated; methods
for solution presented. Emphasis on relationships between original system,
mathematical model, and mathematical solution. Prerequisites: one year
of calculus and some ordinary differential equations.
SSIE 531 (also ME 530). MAN-MACHINE SYSTEMS
A systems engineering characterization of the human operator and the
interaction with simple and complex machines, such as airplanes and ground
vehicles. Topics will include human perception, information measurement,
manual control, and mathematical modeling of the human operator. Modern
control theory will be employed to characterize the man-machine system.
Prerequisite: BS in engineering or approval of department chair.
SSIE 535. ANALYTICAL METHODS
A survey and discussion of some of the more important and useful analytical
methods for analyzing a wide variety of engineering and scientific problems.
Topics will include solution of differential equations, including methods
for linear equations, power series, eigenfunction expansions, and separation
of variables, topics in multi-variable calculus, including vector analysis,
and selected topics in linear algebra, integral transforms, and functions
of a complex variable. Each of the methods will be introduced in the context
of real, applied problems and then illustrated with typical "real world"
applications. Prerequisite: two semesters of calculus.
SSIE 538. NUMERICAL MODELING OF PHYSICAL PHENOMENA
Efficient and effective method for solving differential equations numerically.
Single and multi-step methods for initial value problems for ordinary differential
equations, matrix and shooting methods for two-point boundary value problems,
and shooting methods for eigenvalue-eigenfunction problems (for resonant
frequency and mode shape calculations). Finite difference methods for partial
differential equations, including the heat, wave, and potential equations.
Explicit and implicit methods, method of characteristics, Lax-Wendroff
schemes, and various methods to accelerate the convergence of the approximate
solutions. Considerable emphasis is placed on the interpretation of the
numerical solutions in terms of systems they model and the qualitative
(as well as quantitative) insight they provide.
SSIE 541. JUSTIFYING NEW TECHNOLOGY
Traditional methods are reviewed against changes in manufacturing.
Estimating, product cost vs. utilization, risk, sensitivity analysis, and
decision modeling. Prerequisite: basic course in engineering economics
or its equivalent, or approval of department chair.
SSIE 545. HEURISTIC PROBLEM SOLVING
Concept of problem as cognitive dissonance. Methods of problem recognition,
definition, solution, implementation, refinement. Intuitive approaches:
analysis and syntheses; Meta-problem solvingdevelopment of strategies appropriate
to problem type; inventive thinking: deferred judgment, metaphorical and
visual thinking, finding order in chaos. Prerequisite: curiosity of creative
process and genuine desire to innovate.
SSIE 546. THE PSYCHOLOGY OF PROBLEM SOLVING
Current topics in cognitive science including perception, learning,
pattern recognition, creativity, artificial intelligence, neural networks,
brain theory, evolution of function.
SSIE 550. INTRODUCTION TO SYSTEMS OPTIMIZATION
Basic course in engineering optimization with emphasis on algorithms
and applications. Topics: single variable optimization, multi-variable
optimization, Linear Programming (formulation, simplex method, interior
point methods, sensitivity analysis, applications), constrained optimization
(Lagrange multipliers, Kuhn-Tucker conditions, direct search methods),
and time permitting, Quadratic Programming and linearization methods. Students
will gain enough proficiency to build optimization models of practical
problems and solve them using tools learned in class. Use of available
optimization computer codes.
SSIE 555. AUTOMATED SYSTEMS
Basic elements of automating a manufacturing process. Programmable
logic controllers, data networks, parts orientation and feeding, robotics
and systems integration. Prerequisite: SSIE 512 or approval of department
chair.
SSIE 556. EXPERT SYSTEMS IN ELECTRONICS PACKAGING
Role of artificial intelligence (AI)-based expert systems in manufacturing
as related to electronics packaging domain. Expert systems design and development
as applied to electronics packaging. Knowledge acquisition and representation
techniques solution spaces and search tech niques, inference and deduction
mechanism, and design and development of prototype systems. Prerequisite:
graduate standing or approval of department chair.
SSIE 561. QUALITY ASSURANCE FOR ENGINEERS
Statistical quality control, designing for quality, process control,
vendor and customer quality issues, quality costs and production. Prerequisites:
BS in engineering (any field), and probability and statistics coursework,
or consent of department chair.
SSIE 562. RELIABILITY
Reliability networks, failure mode and effect analysis, apportionment,
fault trees, and human reliability. Prerequisites: SSIE 561 and probability
and statistics, or consent of department chair.
SSIE 566. DESIGNING WITH EXPERIMENTS
(crosslisted with ME 566)
Basics of applying statistical design, and the design function, statistical
experimental design, control of experimen tal setting, Taguchi methods,
and analysis of results. Prerequisites: SSIE 561 and 505 or equivalents,
or approval of department chair.
SSIE 570. BIOLOGICAL SYSTEMS THEORY
Models of biological organizations that complement structural, analytic
concepts of molecular biology, and abstract, mathematical concepts of theories.
Extension of these principles to ecological, social, cognitive levels of
biological organizations.
SSIE 571. MODELING OF BIOLOGICAL SYSTEMS
Computer-based modeling of biological systems such as protein folding,
protein biosynthesis, aggregation of cells into tissue, self-assembly of
bacteriophages, origin of life and evolution, and neuron systems. Prerequisites:
SSIE 400 or equivalent and equivalence of sophomore physics.
SSIE 575. SYSTEMS DESIGN
Systems approach to design process. Complex poorly defined, interdisciplinary
problems. Design viewed as problem solving and opportunity development
activity. User identification and satisfaction, adaptive design, design
by attribute, design consciousness, models of design process. Prerequisite:
open to students with advanced standing or professional experience.
SSIE 576. MANUFACTURING PROCESSING I
(crosslisted with ME 571)
Equilibrium and non-equilibrium microstructure arising from liquid-solid
processing of materials. Casting of metal alloys, fusion welding of metals,
injection molding of polymers, and brazing/soldering of metals. Prerequisite:
BS in engineering or equivalent, or consent of department chair.
SSIE 577. MANUFACTURING PROCESSES II
(crosslisted with ME 572)
Role of mechanical and thermal forces on solid state fabrication of
materials; extrusion, forging, particulate (powder) processing, rolling,
sheet forming, wire drawing, heat treating, and sintering. Prerequisites:
strength of materials and heat transfer, or consent of department chair.
SSIE 578. PROCESSES FOR ELECTRONICS MANUFACTURING
The electrical content of manufactured products is increasing in all
areas. To prepare the engineer for manufacturing these electrical assemblies,
this course has been structured to cover topics in soldering, wire bonding,
TAB, printed wiring board production, PCB assembly and population processes
(through hole and SMT), and associated environmental issues. Prerequisite:
undergraduate course in manufacturing processes, related experience, or
consent of department chairman.
SSIE 580. SPECIAL TOPICS 1-4 credits
Topics vary from semester to semester.
SSIE 590. SPECIAL TOPICS-INDUSTRIAL ENGINEERING SPECIAL PROBLEM
This course will be based upon a basic understanding of industrial
engineering. The course will vary and will cover decision making in industrial
or manufacturing engineer ing situations. Major emphasis is expected to
be in manufacturing systems. Prerequisite: consent of department chairman.
SSIE 592. PROFESSIONAL SEMINAR 2 credits
Weekly seminar course conducted by faculty and outside speakers. Topics
of current research. Each student goes into details of at least one of
topics of seminar; through term paper, demonstrates in-depth understanding
of topic to satisfaction of faculty. Prerequisite: student should be in
last semester of master's program and have completed 12 credit hours.
SSIE 594. INDUSTRIAL INTERNSHIP
Industrial engineering, systems science, and other professional experience.
Daily log book, memo progress reports, and a formal final report required.
The internship may replace no more than one lecture course for the MSIE
or MSSS degree. Prerequisite: permission of department chair.
SSIE 595. TERMINATION PROJECT: SYSTEMS SCIENCE
2 credits
Project acceptable both to student and to a faculty committee. Inquire
at our Watson Advising Office to complete proper documentation. Prerequisite:
consent of instructor and committee members.
SSIE 597. INDEPENDENT STUDY
1-4 credits
Independent study supervised by department faculty member. Student
must obtain consent of instructor, who then determines description of study
program, number of credits, frequency of meetings, location.
SSIE 598. MSIE PROJECT
Literature review, manufacturing system development or other projects
as defined by the Project Committee. Formal bound report for SSIE Department
Library.
SSIE 599. THESIS RESEARCH 8
credits
Training in the methods of research. Varied computer modeling, hardware
development, and experimentation as determined by the MSIE thesis committee.
Oral examination required (eight credits total). Bound thesis goes in University
Library.
SSIE 606. SYSTEMS PROBLEM SOLVING WORKSHOP
2 credits
Project-oriented course based on material covered in SSIE 506. Specific
projects selected on basis both of interests of individual students and
composition of group. Prerequisite: SSIE 506.
SSIE 612. ADVANCED TOPICS IN INTEGRATED MANUFACTURING
The continual need to improve quality and productivity and remain competitive
in a global market requires the comprehensive integration of people, equipment,
computers, and information within a manufacturing systems engineering framework.
This course is designed to study and analyze manufacturing integration
issues with a special focus on integrating elements such as process planning,
group technology, concurrent engineering, product quality, cost analysis,
flexible manufacturing, inventory
control, information flow and management, and global computer-integrated
manufacturing (CIM) concept. Prerequisite: SSIE 512 or equivalent, or approval
of department chair.
SSIE 617. FUZZY SETS, FUZZY LOGIC, AND FUZZY SYSTEMS
Course consists of two parts. The first part covers funda mentals of
fuzzy set theory and the associated fuzzy logic. The second part is devoted
to applications of the theory. Topics of the theoretical part include:
basic concepts of fuzzy set theory and fuzzy logic; representations of
fuzzy sets; extension principle that facilitates fuzzifications of classical
mathematical concepts; aggregation operations on fuzzy sets; the concept
of a fuzzy number and arithmetic operations on fuzzy numbers; fuzzy relations;
fuzzy relation equations; basic ideas of fuzzy logic; possibility theory
based on fuzzy sets; and information aspects of fuzzy sets. In the application
part, methods of constructing fuzzy sets in various application contexts
are overviewed and representative applications of fuzzy sets and fuzzy
logic are examined. The application areas to be covered include: systems
science; approximate reasoning in expert systems; database and information
retrieval systems; pattern recog nition and image processing; decision
making; medicine; economics; psychology; and various areas of engineering.
Prerequisites: SSIE 505 or equivalent and calculus and discrete mathematics,
or permission of instructor.
SSIE 618. FUZZY MEASURES: THEORY AND APPLICATIONS
Provides the student with a frame of the general theory of fuzzy measure.
It includes some advanced knowledge on set theory (such as atom, s-compact,
etc.), basic concepts of classical measure and fuzzy measure, structural
charac teristics of fuzzy measure, extension of fuzzy measure, concepts
of "almost" and "pseudo-almost" on fuzzy mea sure space, measurable functions
and convergence of their sequence on fuzzy measure space, concept and properties
of fuzzy integral, convergence theorems of sequence of fuzzy integrals,
application of fuzzy integral in synthetical evaluation. Students will
be asked to explore applications of these and related concepts in their
areas of interest and write a term paper. Prerequisites: SSIE 400 and 410.
SSIE 620. ANALYSIS OF COMPLEX SYSTEMS
Techniques for and their applications to modeling and analyzing complex
systems. Decision trees, graph theory, time series and forecasting, system
identification, and non-linear optimization, optimal allocation of resources,
cluster analysis, queuing theory, analysis of specific complex systems.
Prerequisites: SSIE 410 and 505, familiarity with simple differential equations,
working knowledge of APL and PL/I or FORTRAN.
SSIE 630. NEURAL NETWORK AND GENETIC MODELS
4 credits
The use of autonomous self-organizing models in deducing complex systems
properties, behavior, and relations; intelligence, learning, adaptation,
and emergence in artificial systems; perceptions and threshold logic units,
discriminant functions, general non-parametric training; com mittee, piecewise
linear, layered, and parametric machines; evolutionary programming, genetic
algorithms and satisficing vs. optimizing search strategies.
SSIE 632. PERTURBATION METHODS
Course focuses on application of perturbation methods to problems in
engineering mechanics. Regular perturbation expansions, method of mathed
(and composite) expansions, and method of multiple time scales will be
applied to problems drawn from such areas as vibrations, fluid mechanics,
heat conduction, solid mechanics. Emphasis will be on understanding the
various methods discussed (e.g., what method applies to what kind of problem,
what each method does and does not do, etc.) with applications used to
illustrate the ideas. Prerequisites: two semesters of calculus and a course
in ordinary differential equations.
SSIE 645. STATISTICAL MODELING WITH IMPRECISE PROBABILITIES
To deal with the uncertainty and the indeterminacy in systems, this
course covers a new and increasingly important mathematical theory of imprecise
probabilities, including upper probabilities and lower probabilities, based
on three fundamental principles: avoiding sure loss, coherence, and natural
extension. Some useful models and strategies for assessing imprecise probability
are introduced, and some applications to probabilistic reasoning, statistical
inference, and decision are discussed. Prerequisites: SSIE 505 and 516
or 517.
SSIE 650. SYSTEMS OPTIMIZATION
Broad spectrum of models and methods for systems optimi zation. Motivating
examples; classical constrained and unconstrained methods; search techniques;
linear programming; network and transportation systems, introduction to
integer programming. Prerequisite: SSIE 520 or one year of calculus.
SSIE 656. ARTIFICIAL INTELLIGENCE IN MANUFACTURING
Artificial intelligence applied to scheduling, inventory control, process
planning, maintenance; design and development of prototype systems; search
techniques, knowledge representation. Prerequisite: SSIE 551 or equivalent,
or consent of department chair.
SSIE 660. STOCHASTIC SYSTEMS
Discrete-state Markov chains; exponential and Poisson processes; reliability
technology; birth and death processes; queuing models; renewal theory;
continuous random variables; Kalman filters. Emphasis on applications.
Prerequisite: SSIE 505 or equivalent.
SSIE 661. ADVANCED ISSUES IN QUALITY
The topic of quality has taken more and more of a critical nature for
manufacturing systems. This course has two components. The first component
is a practical application of the concepts of quality, including the design
and execution of experiments in a real setting. The second component is
the analysis and study of future issues in the field of quality , such
as the development of loss equations, cost of high quality, and people
and high quality. Prerequisite: SSIE 563 (Designing with Experiments) or
a general design of experiments course.
SSIE 670. SELECTED TOPICS IN COGNITIVE SCIENCE
Topics will focus on current approaches to brain models and machine
intelligence and on the different criteria that are used to evaluate such
models. These approaches presently include programmable rule-based symbol
systems (computationalism), coherent, distributed networks (connectionism),
and models based on neurophysiology of simple and complex organisms. Special
attention is given to the evolutionary and developmental constraints on
the many functions of nervous systems and brains. Prerequisite: second-year
graduate level course.
SSIE 680. ADVANCED SPECIAL TOPICS
1-4 credits
Variable content, credit hours, prerequisites. When offered, covered
topics, credit hours, prerequisites, text specified. NOTE: May be repeated
for credit with consent of instructor. Prerequisite: to be announced.
SSIE 697. ADVANCED INDEPENDENT STUDY
Supervised by department faculty member. Student must obtain consent
of instructor, who then determines description of program, number of credits,
frequency of meeting, and location. Appropriate paperwork must be submitted
to complete registration.
SSIE 698. PREDISSERTATION 1-9 credits
Research for and preparation of PhD dissertation.
SSIE 699. DISSERTATION every semester
Required for and preparation of PhD dissertation.
SSIE 700. CONTINUOUS REGISTRATION
Required to maintain matriculation through any spring or fall semester
when no other courses are taken. If minimal one-credit registration is
not maintained, student must reapply for admission.
SSIE 701. PRACTICUM FOR RESEARCH AND TEACHING ASSISTANTS every
semester
Required for all funded graduate assistants. Research or teaching supervised
by faculty adviser.
SSIE 707. RESEARCH SKILLS
1 credit/semester
Development of research skills required within graduate program. May
not be applied toward course credits for any graduate degree.