Department of Systems Engineering
603 Crawford Hall
Phone 368-4033; Fax 368-3123
Kenneth Loparo
The Department of Systems Engineering of the Case School of Engineering offers the following degree programs: Bachelor of Science in Engineering degree in Systems and Control Engineering; Bachelor of Science in Engineering degree in Industrial Engineering; Master of Science degree in Systems Engineering; and Doctor of Philosophy degree in Systems Engineering.
The Bachelor of Science in Engineering degree in Systems and Control Engineering is accredited by the Accreditation Board of Engineering and Technology, Inc. (ABET) and we are planning to apply for accreditation of the Bachelor of Science in Engineering degree in Industrial Engineering at the next available opportunity.
Marcus R. Buchner, Ph.D. (Michigan State University)
Associate Professor
Simulation of complex Systems; control of industrial systems;
analysis of discrete event and combined systems.
Vira Chankong, Ph.D. (Case Western Reserve University)
Associate Professor
Large-scale optimization; multiobjective optimization; decision theory; risk analysis.
Howard Chizeck, Sc.D. (Massachusetts Institute of Technology)
Professor
Adaptive, stochastic and nonlinear control theory; biomedical control engineering.
Benjamin F. Hobbs, Ph.D. (Cornell University)
Associate Professor
Energy systems;water resources systems; multiple-criteria decision making.
Irving Lefkowitz, Ph.D. (Case Western Reserve University)
Professor Emeritus
Computer control of industrial systems; expert systems applications of industrial control; hierarchical and multilevel systems.
Kenneth A. Loparo, Ph.D. (Case Western Reserve University)
Professor and Chairman
Stability and control of nonlinear and stochastic systems; analysis and control of discrete event systems; intelligent control systems.
Behnam Malakooti, Ph.D. (Purdue University)
Associate Professor
Computer-aided manufacturing; man-machine systems; multiple-criteria decision making and optimization.
Mihajilo D. Mesarovic, Ph.D. (Serbian Academy of Science)
Cady Staley Professor of Engineering
Large-scale systems theory; multilevel systems; world and regional modeling.
N. Sreenath, Ph.D. (University of Maryland)
Assistant Professor
Nonlinear systems: modeling, stability, and control; multibody systems; symbolic computation; large scale systems; global climate change problems.
Coleman B. Brosilow, Ph.D. (Brooklyn Polytechnic Institute)
Professor of Chemical Engineering and Systems Engineering
Process control; inferential control; systems simulation.
Patricia Brennan, Ph.D. (University of Wisconsin, Madison)
Associate Professor of Nursing and Systems Engineering
Decision support systems, organizational modeling.
Otomar Hajek, Rer. Nat. Dr. (Caroline University, Prague, Czechoslovakia)
Professor of Mathematics and Systems Engineering
Ordinary differential equations; optimal control.
Joseph Koonce, Ph.D. (University of Wisconsin, Madison)
Associate Professor of Biology and Systems Engineering
Systems control and application of systems concepts to biological and ecological systems, aquatic ecology and systems ecology.
The systems and control engineering programs provide the student with the basic concepts, analytical tools, and methods which are useful in dealing the complex technological and non-technological systems. Problems relating to modeling, decision making, control, and optimization are studied. Although the system is approached as a single unit with regard to the functions and tasks which are to be performed, the system generally includes components of various types: technological, human, biological, environmental, industrial, social, political, and economic. The relationship and interaction among the various components in the system need to be understood and modelled. This information is then used to determine the best way of coordinating and regulating their individual contributions to achieve the overall goal of the system. What may be best for an individual component of the system may not be best for the system as a whole, and compromises and tradeoffs are often required in determining a feasible solution to the system problem. This is a common occurrence in business and governmental organizations, and also occurs in many other types of systems. The computer plays a central role in the systems and control curriculum not only for engineering and mathematical computations but also for simulation, automatic control, real-time data acquisition and signal processing, and other information processing and automation tasks.
Some examples of systems problems which are studied include computer control of industrial plants, development of multilevel regionalized world models, development of decision models for control of pollution, control of physiological processes, and optimal planning and management of energy resources in large-scale systems. At the undergraduate level, there are two elective sequences: control and systems.
The control sequence is directed toward developing the skills in dynamic analysis and feedback control that are used in aerospace, process control, energy systems, and water treatment systems, for example.
The systems sequence focuses on modeling, optimization, and decision and planning methodologies which are useful in a variety of engineering and socioeconomic applications. Both sequences use the concepts of modeling, data analysis, computer simulation, automation and remote control, real-time data acquisition and optimization.
In addition to a basic engineering background, the curriculum provides preparation in computational methods, mathematical modeling and characterization of dynamic systems, data analysis, computer simulation, automatic control, optimization, applications of realtime computers and methodd for systems analysis. Students from this program may find positions in private industry or in the public (governmental) sector , or may enter graduate school for specialization.
A five-year Bachelor of Science (engineering or mathematics)/Master of Science (systems engineering) program is available for qualified students. A minor in Systems Engineering is also available.
A total of five courses (15 credit hours) are required to obtain a minor in Systems and Control Engineering. Three (3) out of the five (5) courses must be selected from the following list: ESYS 212, ESYS 304/305, ESYS 315 or ESYS 346.
The remaining two courses can be chosen from available courses in the Department of Systems Engineering and require written approval by the faculty member in charge of the minor program. A suggested list of courses is:
- ESYS 202, Systems Modeling<
- EIND 352/353, Engineering Economics/Accounting for Engineers
- ESYS 313, Signal Processing
- ESYS 306, Control Engineering II
Six (6) of the fifteen (15) credits required for the minor program can be used to satisfy the B.S. requirements for the major degree program, so a total of nine (9) credit hours of additional course work are required for the minor program.
The program in industrial engineering provides the student with methods and techniques useful in solving problems related to production and manufacturing systems, for example, computer-aided manufacturing, engineering economics, facility layout and design, man-machine systems, quality control, production planning and scheduling, automation, inventory control, resource management, etc. The program draws upon the curricular strengths in the departments of systems engineering, mechanical engineering, and operations research. The curriculum represents a modern systems and computer-oriented approach to production/manufacturing engineering, with strong emphasis on the role of computers and microprocessors in the industrial environment for real-time data collection and processing, on-line control, system simulation, management information, automation, computer-aided design, and computer-aided manufacturing.
A focus of the program is on the use of decision support and intelligent systems for computer integrated manufacturing planning. Students are encouraged to participate in the co-op program with industry. A five-year Bachelor of Science (industrial engineering)/ Master of Science (systems engineering) program is available for qualified students. A minor in Industrial Engineering is also available.
A qualified engineering student can receive a minor in industrial engineering by satisfying the following requirements:
- EIND 250, Production Systems Engineering
- EIND 350, Manufacturing Systems Engineering
- EIND 315, Decision Making
- EIND 346, Engineering Optimization
Choose two courses from one of the following lists:
Area I: Operations Analysis:
- EIND 315, Decision Analysis
- OPMT 351, Design of Logistical Systems
- EIND 346, Engineering Optimization
- ORBH 250, Introduction to Organizational Behavior and Management.
Area II: Engineering Economics
- EIND 352, Engineering Economics
- ECON 326, Econometrics
- ECON 361, Managerial Economics
- ECON 369, Economics of Industrial Production and Technology
Area III: Business Administration
- ACCT 303, Basic Accounting
- BAFI 355, Corporation Finance
- MKMR 301, Marketing Management
A total of 15 credits are required. Six of these credits can be used to satisfy the B.S. degree requirement, so a total of 9 additional credits are required for the minor in industrial engineering.
Bachelor of Science in Engineering Degree
FRESHMAN
FALL SEMESTER
Open elective or humanities/social science (3-0-3)(a),(j)
CHEM 105, Principles of Chemistry I (3-0-3) or
CHEM 107, Properties and Structure of Matter I (3-0-3)
CMPS 131, Elementary Computer Programming (2-2-3)
MATH 121, Calculus for Science and Engineering I (4-0-4)
ENGL 150, Expository Writing (3-0-3)
PHED 101, Physical Education Activities (0-3-0)
Total (15-5-16)
SPRING SEMESTER
Humanities/social science or open elective (3-0-3)(i)
CHEM 106, Principles of Chemistry II (3-0-3) or
CHEM 108, Properties and Structure of Matter II (3-0-3)
CHEM 113, Principles of Chemistry Laboratory (1-3-2)
MATH 122, Calculus for Science and Engineering II (4-0-4)
PHYS 120, General Physics I, Mechanics (4-0-4)(c)
PHED 102, Physical Education Activities (0-3-0)
Total (15-6-16)
SOPHOMORE
FALL SEMESTER
Humanities or Social Science Sequence I (3-0-3)
MATH 223, Calculus for Science and Engineering III (3-0-3)
PHYS 219, General Physics II, Electricity and Magnetism (4-0-4)
EMAE 172, Mechanical Manufacturing (1-3-3)
ECIV 110, Mechanics (3-0-3)(d)
Total (14-3-16)
SPRING SEMESTER
Humanities or Social Science Sequence II (3-0-3)
MATH 224, Elementary Differential Equations (3-0-3)
PHYS 220, General Physics III, Modern Physics (3-0-3)
EMSE 101, Introduction to Material Science (3-0-3)(d)
EIND 250, Production Systems Engineering (3-0-3)
STAT 385, Statistical Methods (3-0-3)
Total (18-0-18)
JUNIOR
FALL SEMESTER
Humanities or Social Science Sequence III (3-0-3)
EMAE 150, Thermodynamics I (3-1-3)(d)
ORBH 250, Introduction to Organizational Behav. and Management (3-0-3)
ESYS 301, Systems and Control (3-0-3)(d)
ESYS 302, Systems and Control Laboratory (0-3-1)
EIND 352, Engineering Economics (3-0-3)
OPMT 351, Logistical Systems (3-0-3)
EIND 353, Accounting for Engineers (1-0-1)
Total (19-3-20)
SPRING SEMESTER
Humanities or Social Science Sequence IV (3-0-3)
EEAP 240, Electronic Circuits I (3-2-4)(d)
OPRE 432, Computer Simulation (3-0-3)
EIND 346, Engineering Optimization (3-0-3)
EIND 321, Optimization Laboratory (0-3-1)
OPMT 352, Design of Production Systems (3-0-3)
Total (15-5-17)
SENIOR
FALL SEMESTER
Humanities or social science elective (3-0-3)(d)
EIND 355, Production Engineering (1-3-2)
EIND 350, Manufacturing Systems Engineering (3-0-3)
EIND 351, Manufacturing Systems Laboratory (0-2-1)
ECMP 251, Numerical Methods (2-2-3)(d)
ESYS 322, Simulation Laboratory (0-3-1)
Technical elective (3-0-3)(h)
Total (12-10-16)
SPRING SEMESTER
Humanities or social science elective (3-0-3)
EIND 398, Senior Project (0-6-3)
ENGL 398, Professional Communication (2-0-2)
Technical elective (3-0-3)(h)
Open elective (3-0-3)(f)
EIND 315, Decision Analysis (3-0-3)
Total (14-6-17)
Hours required for graduation: 136 plus Graphics Proficiency.
a Students are encouraged to take ECON 101, 102, and 361 in their social science sequence.<
c Selected students may be invited to take PHYS 125, 126, General Physics I, II-Honors (3,3) in place of an open elective (3) and PHYS 120 (4).
d Engineering Core Elective.
f 400-level courses must be approved by the M.B.A. Office in Weatherhead School.
g Courses used for engineering economics (technical elective) cannot be used for social science sequences.
h Technical elective to be selected from one of the specialty areas listed.
j One of these courses must be a humanities/social science course.
Students may focus their programs in one of several specialties by carefully selecting elective courses in consultation with their faculty adviser. Suggested elective courses in each specialty are shown on the facing page.
Production Management/Operations
- ESYS 450, Integrated Production Systems (3-0-3)
- OPMT 477, Production Planning and Inventory Control (3)
- OPRE 452, Materials Management and Hospital Clinics (3)
Human Factors/Organizational Behavior
- ORBH 402, Behavioral Sciences in Management (3)f
- ORBH 412, Organizational Analysis (3)f
- ORBH 418, The Management of Work: Sociotechnical Systems (3)f
Mechanical/Manufacturing Engineering
- EMAE 250, Computers for Engineering (3)
- EMAE 354, Design of Mechanical Elements (3)
- EMAE 181, Dynamics (3)
- EEAP 489, Robotics (3)
Engineering Economics
- ECON 326, Econometrics (3)
- ECON 361, Managerial Economics (3)
- ECON 369, Economics of Industrial Production and Technology (3)
Data Management and Information Systems
- MIDS 309, Management Information System II (3)
- MIDS 327, Data Base Management (3)
- MIDS 310, Technology of Information Systems (3)
Artificial Intelligence
- CMPS 391, Introduction to Artificial Intelligence (3)
- ECMP 491, Intelligent Systems I (3)
Bachelor of Science in Engineering Degree
FRESHMAN
FALL SEMESTER
Open elective or humanities/social science (3-0-3)(a),(b)
CHEM 105, Principles of Chemistry I (3-0-3) or
CHEM 107, Properties and Structure of Matter I (3-0-3)
CMPS 131, Elementary Computer Programming (2-2-3)
MATH 121, Calculus for Science and Engineering I (4-0-4)
ENGL 150, Expository Writing (3-0-3)
PHED 101, Physical Education Activities (0-3-0)
Total (15-5-16)
SPRING SEMESTER
Humanities or social science/open (3-0-3)(h)
CHEM 106, Principles of Chemistry II (3-0-3) or
CHEM 108, Properties and Structure of Matter II (3-0-3)
CHEM 113, Principles of Chemistry Laboratory (1-3-2)
MATH 122, Calculus for Science & Engineering II (4-0-4)
PHYS 120, General Physics I, Mechanics (4-0-4)(a)
PHED 102, Physical Education Activities (0-3-0)
Total (15-6-16)
SOPHOMORE
FALL SEMESTER
Humanities or Social Science Sequence I (3-0-3)
EEAP 240, Electronic Circuits I (3-2-4)(e)
MATH 223, Calculus for Science and Engineering III (3-0-3)
PHYS 219, General Physics II, Electricity & Magnetism (4-0-4)
EIND 352, Engineering Economics (3-0-3)
EIND 353, Accounting for Engineers (1-0-1)
Total (17-2-18)
SPRING SEMESTER
Humanities or Social Science Sequence II (3-0-3)
ESYS 202, Systems Modeling (3-0-3)
MATH 224, Elementary Differential Equations (3-0-3)
PHYS 220, General Physics III, Modern Physics (3-0-3)
Technical elective (3-0-3)(d)
STAT 380, Intro. to Probability and Statistics I (3-0-3)(g)
Total (18-0-18)
JUNIOR
FALL SEMESTER
Humanities or Social Science Sequence III (3-0-3)
MATH 201, Linear Algebra (3-0-3)
ESYS 212, Signals and Systems (3-0-3)(e)
ESYS 322, Simulation Lab (1-3-2)
ENGL 398, Professional Communication (2-0-2)
ECMP 251, Numerical Methods (2-2-3)
Total (14-5-16)
SPRING SEMESTER
Humanities or Social Science Sequence IV (3-0-3)
ESYS 313, Signal Processing (3-0-3)
ESYS 304, Control Engineering I (3-0-3)
ESYS 305, Control Engineering Laboratory (0-3-1)
ESYS 346, Engineering Optimization (3-0-3)
ESYS 321, Optimization Laboratory (0-3-1)
Technical elective (3-0-3)(e)
Total (15-6-17)
SENIOR
FALL SEMESTER
Humanities or social science elective (3-0-3)
Technical elective (3-0-3)(e)
Technical elective (3-0-3)(d)
Technical elective (3-0-3)(d)
ESYS 306, Control Engineering II (control option)
or technical elective (3-0-3)(e)
Open elective (3-0-3)(e)
Total (18-0-18)
SPRING SEMESTER
Humanities or social science elective (3-0-3)
ESYS 307, Control Laboratory(control option) (1-6-3)
or Technical elective (3-0-3)(e)
OPRE 432, Computer Simulation (systems option)
or Technical elective (3-0-3)(e)
ESYS 398, Engineering Projects Laboratory (1-6-3)
ESYS 315, Decision Analysis (3-0-3)
Total (11-12-15) control option
(13-6-15) systems option
Hours required for graduation: 134 plus graphics proficiency.
a Selected students may be invited to take PHYS 125, 126, General Physics I, II-Honors (3,3) in place of an open elective (3) and PHYS 120 (4).
b Students are encouraged to take ESYS 101 for their open elective.
c Engineering Core course.
d Three technical electives must be choosen from EFTS 150, Thermodynamics or EMAC 171, Physical Chemistry I; EFTS151, Fluid Mechanics or ECHE 360, Trasport Phenomena; ECIV 110, Mechanics; EMCH 181, Dynamics; EEAP 210, Fields/Energy Conversion I.
e Technical electives to be taken from the same elective sequence listed below.
f Selected students may be invited to take ESYS 416 in place of ESYS 346. B.S./M.S. students should take ESYS 416 in place of 346.
g STAT 385 may be taken in place of STAT 380.
h One of these courses must be a humanities/social science course.
- ESYS 340, Introduction to Global Issues
- ESYS 404, Digital Control Systems
- ESYS 408, Modern Control Engineering
- ESYS 414, Complex Systems Modeling and Analysis
- ESYS 416, Optimization Theory and Techniques
- ECMP 280, Digital Electronics I
- EEAP 383, Microprocessor Applications to Control
- ECMP 315, Computer Design I
- ESYS 306, Control Engineering II
- ESYS 307, Control Laboratory
- ESYS 340, Introduction to Global Issues
- ESYS 408, Modern Control Engineering
- ESYS 414, Complex Systems Modeling and Analysis
- ESYS 426, Water and Energy Systems Engineering
- ESYS 427, Approaches to Risk Assessment
- ESYS 435, Legal, Economic and Social Aspects of Resource Management
- EIND 250, Production Systems Engineering
- EIND 350, Manufacturing Systems Engineering
- STAT 381, Theoretical Statistics I
Approved courses in operations research
Graduate programs in systems engineering include the following areas of concentration: large-scale systems, energy systems, control theory, computer control of industrial systems, computer control of biomedical systems, and global studies.
All the research carried out in the department is associated with graduate programs and research funds are used to provide assistantships that support the thesis research of graduate students. Current research funding is provided by the Ameritech Corporation, Amoco, Apogee Research Inc., The Bailey Controls Company, BP America, Centerior Energy Corporation, Cleveland Advanced Manufacturing Program (CAMP), Edison Biotechnology Center, Ford Motor Company, NASA, NASA-Lewis Research Center, National Institutes of Health, National Institute of Disability Research and Rehabilitation, National Regulatory Research Institute, National Science Foundation, Ohio Air Quality Development Authority, Society of Manufacturing Engineering, U.S. Army Corps of Engineers, U.S. Veterans Administration-Rehabilitation Research and Development.
Thesis research may be directed to theory, methodology, or techniques useful in systems applications for planning, design, control, or management. Some representative thesis subjects are: Distributed computer control, mathematical programming and optimization, global and regional modeling, computer-aided design for manufacturing, facility layout and design, flexible manufacturing systems, stability and control of stochastic systems, geometric theory of linear and nonlinear control, man-machine systems, intelligent control systems, large-scale optimization, risk assessment and management, dynamic simulation of hybrid systems, discrete event systems, fault detection and process diagnostics, parameter estimation and adaptive control, energy system planning and management, hierarchial control, inferential control, and dual control theory.
General areas of current research interest include the following:
Control Systems
Focusing on technological systems, control systems research considers problems of modeling, information processing and control of complex systems. Topics include optimal control theory and design, stochastic control and estimation, direct digital control, analysis and design of systems affected by failures and probabilistic events, real-time computer systems and software for control, computer-aided design of control systems, hierarchial control systems, and adaptive control theory. Several projects center on the control of biomedical systems, electric power systems, industrial systems, avionic systems and intelligent and autonomous systems.
Control of Industrial Systems
Oriented toward applications in industry, this research is concerned with the development of concepts, techniques, and methodology for the control of complex industrial systems. The control function is considered in its broadest sense-the on-line implementation of decisions and actions that improve performance. Thus, the research includes a broad range of topics: inferential control, dynamic simulation of large-scale process systems, design methodologies for distributed and hierarchical control systems, adaptive control, process diagnostics, intelligent control and discrete manufacturing. The program is interdisciplinary, with active participation by students and faculty from the departments of systems engineering, chemical engineering, computer engineering, and others.
Mathematical Systems Theory
Work on mathematical systems theory focuses on the characterization of systems, their structure and behavior, and system oriented problems. Topics include stability of dynamical systems, stochastic estimation and control theory, differential geometric methods in systems and control theory, complicated dynamics and chaos, communication and control under uncertainty, analysis and control of discrete event systems.
Adaptive Control of Physiological Systems
Research on the adaptive control of physiological systems focuses on the development of techniques for the real-time estimation of the dynamical parameters of physiological processes and the design, based on these estimates, of controllers with the ability to adapt on-line to changes in system behavior. Current interest centers on the cardiovascular system, electrically stimulated muscle and the mechanisms of hydrocephalus.
Control of Neuroprosthetic Devices
The work on the control of neuroprosthetic devices involves the design and analysis of controllers which regulate the force, position, and stiffness of paralyzed muscle tissue. There is intense current activity investigating the coordination and control of muscles using microprocessor-based neuroprosthetic devices in order to provide functional walking for paraplegic patients and functional hand use for quadriplegics.
Systems Analysis
Simulation, data gathering, optimization, and decision making in large-scale systems are the central concerns of systems analysis. Emphasis is on non-technological and technical factors as well as policy analysis. Research activity includes modeling and management of energy systems, environmental models, optimization, multicriteria decision making, decision theory, risk assessment and management, hierarchical multiobjective methodology, decision support systems, and computer design-aided manufacturing.
The Systems Computer Laboratory provides computing facilities for simulation, optimization, control system design, system analysis, production control, manufacturing analysis, general engineering computations and real-time data acquisition, signal processing, and control. The laboratory offers a wide variety of mono- and hi-resolution color workstations ranging from IBM compatible, APPLE Macintosh, DEC VAX, SUN SPARC, TI LISP, through to NeXT computers. Operating systems include UNIX, MAC, DOS, WINDOWS, and VMS. Extensive software library and application packages are available including standard scientific languages like FORTRAN, C, C++, PASCAL; AI languages such as LISP and PROLOG; symbolic computational systems such as MACSYMA and MATHEMATICA; and control, signal analysis, and optimization packages such as MATRIX-X, MATLAB, CC, LINDO, GINO.
CWRUnet is a state-of -the-art high-speed fiber optic campus-wide local area computer network which interconnects laboratories, faculty and student offices, classrooms, and student dormitories at CWRU. Through this network, users have access to a variety of on-campus and off-campus resources. Access to major programming languages, application packages, is available over the network. On-line databases such as EUCLID (the University Libraries' circulation and public access catalog), and CD-ROM based dictionary, thesaurus and encyclopedias are available. Many regional and national institutional library catalogs are accessible over the network as well. Links between CWRUNET and local, state, national, and international data communications networks such as USENET and BITNET provide gateways to other institutions, to regional resource centers such as supercomputer facilities (the Ohio Supercomputer Center, the Pittsburgh Supercomputer Center and the NASA Lewis Center Supercomputing facilities), and to a wide range of international resources.
The Control Laboratory has a variety of physical pilot processes which are used in the undergraduate program. These include liquid level systems, electromechanical servo systems, robots and manipulators, material handling systems, pneumatic and hydraulic systems, and thermal processes. The laboratory also includes industrial components (actuators and sensors) commonly used in process control, programmable logic controllers and a number of computers with Analog/Digital and Digital/Analog hardware for realtime control experiments. These computers also have computer aided control system analysis and design software as well as state-of-the art DSP (digital signal processing) software for student use in the laboratory. A basic Bailey Network 90 Distributed Control Systems (DCS) configuration (I/0 unit, operator interface, Multifunctional Controller, and local microprocessor-based controllers) is also available. The Bailey configuration is representative of an advanced, state-of-the-art, flexible controller for a small-to-medium scale industrial process. Several experimental process systems (liquid level, temperature, velocity and position servo units, etc) are tied into the computer and control equipment for studies of realtime applications of direct digital control, optimizing and adaptive control, and modeling and simulation of dynamic systems.
The Production and Manufacturing Engineering Software Laboratory provides various software packages for different phases of production control and manufacturing analysis. The packages include production management, project management and scheduling, optimization, decision making, work measurement, computer-aided process planning and computer-aided manufacturing, facilities layout and design and simulation of manufacturing systems.
This laboratory consists of several pick and place robots, conveyors, programmable logic controllers, a teachable robot, and several NCR computers. A supervised computer control system coordinates material movement from an automatic storage and retrieval system. Simulation software packages are used to simulate the material movement and to analyze the effectiveness of different plant layouts and the associated materials handling system.
Industrial Engineering (EIND)
EIND 101. Introduction to Industrial Engineering (3).
The profession of industrial engineering; areas of application as well as methodologies of problem solution. Project management, facilities analysis, manufacturing processes, materials equipment selection and investment, planning and control, and work measurement and design. Optimization methods, applied probability and statistics, simulation, information systems, human systems, and computer models. Representatives from local industry discuss industrial engineering practice with students.
EIND 250. Production Systems Engineering (3).
Time and motion study, human factors and safety engineering, man-machine systems, quality control and reliability, project management, scheduling, sequencing, inspection and maintenance, and the relationship of these topics to the integrated operations of industrial processes. The inherent variability of the process variables and outputs and the role of multiple-objective analysis; the trade-offs among cost, reliability, product quality, and safety in the design of a system. Prerequisite: Consent of instructor.
EIND 315. Decision Analysis.
See ESYS 315.
EIND 321. Optimization Laboratory (1).
See ESYS 321.
EIND 346. Engineering Optimization (3).
See ESYS 346.
EIND 350. Manufacturing Systems Engineering (3).
Step-by-step and cohesive account of concepts, theories, and procedures for solving modern manufacturing problems; computer applications. Production automation, computer-aided manufacturing, computerized manufacturing processes, computerized discrete production systems, numerical control, process control, industrial robots, flexible manufacturing systems, group technology, materials handling systems, man-machine requirements, and computerized facility layout design. Prerequisite: EIND 250 or consent of instructor.
EIND 351. Manufacturing Systems Laboratory (1).
Application of techniques developed in EIND 350 using available software packages, small scale robots and equipment, and real-time mini- and micro-computer facilities. Prerequisite: EIND 350.
EIND 352. Engineering Economics (3).
Economic analysis of engineering projects, focusing on financial decisions concerning capital investments. Present worth, annual worth, internal rate of return, benefit/cost ratio. Replacement and abandonment policies, effects of taxes, and consideration of inflation. Benefit/cost analysis of public sector projects, including nonmarket effects.
EIND 353. Accounting for Engineers (1).
Overview of corporate accounting practice and how they contribute to engineering economic analyses. Cost accounting. Preparation and interpretation of financial reports. Corequisite: ESYS 352.
EIND 355. Production Engineering Laboratory (3).
Development of experimental techniques for measuring costs, human activities, and the physical characteristics of industrial systems. Hands-on experience with industrial and manufacturing computer software packages to solve simulated and real-world problems. Experimental design and error analysis. Field trips to selected local industries to provide exposure to modern machine, tools, and manufacturing systems. Prerequisite: EIND 250, 350, and 351.
EIND 396. Special Topics in Industrial Engineering (credit as arranged).
Prerequisite: Consent of department chairman.
EIND 398. Engineering Projects Laboratory I (3).
Senior project with emphasis on research and design.
Systems and Control Engineering (ESYS)
ESYS 101. Introduction to Systems Engineering (3).
Use of systems engineering methods to design, analyze, operate and control phenomena. Problem solving methods, mathematical modeling. Computer simulation. Basic concepts of feedback, subsystem interconnections, block diagrams. Examples from transportation, environmental, biomedical, electrical, economic systems. Strong course emphasis on group project.
ESYS 202. Systems Modeling (3).
Process of model building; classes of models far both structured and unstructured problems; guideline, tools, and basic building blocks for model buildings integrated processes for building models of complex, poorly understood problems; class projects in building models of realistic systems. Prerequisite: Sophomore status.
ESYS 212. Signals and Systems (3).
Characterization of continuous and discrete time signals and dynamic analysis of linear systems described by differential and difference equations. Convolution, impulse response and step response for linear time-in-variant systems. Laplace transforms and z-transforms with application to differential and difference equations. Prerequisite: MATH 224.
ESYS 214. Fourier Methods (1).
Fourier series and Fourier transforms for continuous parameter (time) systems with applications to frequency response analysis of linear time invariant systems. Corequisite: ESYS 212.
ESYS 301. Systems and Control (3).
Characterization of signals in time and frequency domains, linearization, modeling of simple dynamic elements, Laplace transforms, linear time-invariant systems. Feedback control; closed-loop relationships, stability criteria, analysis and design techniques in time and frequency domains, compensation methods. For students not taking ESYS 212. Prerequisite: MATH 224.
ESYS 302. Systems and Control Laboratory (1).
Methods of computer simulation, transient and frequency response testing, analysis and design of feedback control systems, analog and digital process controllers, Corequisite: ESYS 301.
ESYS 304. Control Engineering I (3).
Similar in scope and objectives to ESYS 301 except that, presuming prior background in ESYS 212, this course goes further in the development of analysis and control techniques specific to servo and press control applications. Sampled-data systems and digital computer control; feed forward and multiloop control configurations consideration of disturbance inputs. Design studies of selected control applications. Prerequisite: ESYS 212 or consent of instructor.
ESYS 305. Control Engineering Laboratory (l).
Methods of computer simulation, transient and frequency response testing, analysis and design of feedback control systems, analog and digital process controllers. Corequisite: ESYS 304.
ESYS 306. Control Engineering II (3).
(Continuation of ESYS 304) Advanced techniques for control of dynamic systems. State-space modeling, analysis, and controller synthesis; introduction to nonlinear control systems: phase plane methods, bang-bang control, time-optimal control; describing functions analysis and design techniques; discrete time systems and controllers. Prerequisite: ESYS 304.
ESYS 307. Controls Laboratory.
Modeling and control experiments of multivariable systems; sensor, actuator and plant nonlinearities; discrete time control of continuous-time systems and computer implementation of digital controllers; and control systems analysis/design packages. Prerequisite: ESYS 305 and 306.
ESYS 313. Signal Processing (3).
Fourier series and transforms. Analog and digital filters. Fast-Fourier transforms, sampling, and modulation for discrete time signals and systems. Consideration of stochastic signals and linear processing of stochastic signals using correlation functions and spectral analysis. Prerequisite: ESYS 212.
ESYS 315. Decision Analysis (3).
Decision problem formulation, goals and objectives. Decision making under certainty. Decision making under uncertainty, Bayesian approach, risk analysis, fuzzy situation. Stochastic multistate decision making, multiobjective decision making. Stochastic models including Markov chains, with applications to inventory problems. Prerequisite: ESYS 202 and STAT 380, or STAT 385, or consent of instructor.
ESYS 321. Optimization Laboratory (1).
Practical experience in computer applications of optimization technique. Use of computer package in linear and nonlinear optimization. Problem solving in multiobjective and multilevel optimization. Corequisite: ESYS 346 or ESYS 416.
ESYS 322. Simulation Laboratory (2).
Discrete event systems and simulation concepts. Discrete event simulation with SLAM II. Batch and interactive languages. Prerequisite: STAT 380 or 385; Corequisite: ENGL 398.
ESYS 340. Introduction to Global Issues (3).
Methods for analysis and assessment of issues of world scope, and implications for United States policies and interests. Technology, environment, economic growth, health and value transformations. An intensive report required on one or more of the issues considered, with the use of a world system model, when appropriate. (Also listed as UNIV 301.)
ESYS 346. Engineering Optimization (3).
Examination of well-known optimization techniques including linear programming and extensions; transportation and assignment problems; network flow optimization; quadratic, integer, and separable programming; geometric programming and dynamic programming. Nonlinear optimization topics: optimality criteria, gradient and other practical unconstrained and constrained methods. Computer applications using engineering and business case studies. Strategies for optimization studies.
ESYS 396. Special Topics in Systems Engineering (credit as arranged).
Prerequisite: Consent of department chairman.
ESYS 398. Engineering Projects Laboratory I (3).
Elective projects with emphasis on research and design.
ESYS 401. Digital Signal Processing (3).
Characterization of signals, basic processing approaches. Fourier analysis of time functions:c Fourier series and transform, discrete Fourier transform, fast algorithms. Discrete transfer function, discrete representation of continuous systems. Digital filter design: frequency response of discrete systems, digital realization of analog filters. Random signals: discrete correlation sequences and power density spectra, response of linear systems. Prerequisite: ESYS 313.
ESYS 404. Digital Control Systems (4).
Analysis and design techniques for computer based control systems. Sampling, hybrid continuous-timed discrete time system modeling; sampled data and state space representations, controllability, observability and stability, transformation of analog controllers, design of deadbeat and state feedback controllers; pole placement controllers based on input/output models, introduction to model identification, optimal control and adaptive control. Prerequisite: ESYS 304 and STAT 380.
ESYS 408. Introduction to Linear Systems (3).
Analysis and design of linear feedback systems using state-space techniques. Review of matrix theory, linearization, transition maps and variations of constants formula, structural properties of state-space models, controllability and observability, realization theory, role assignment and stabilization, linear quadratic regulator problems, observers, and the separation theorem. Prerequisite: ESYS 304 or consent of instructor.
ESYS 410. Multivariable Control (3).
Analysis and design of linear feedback systems using frequency domain techniques. Matrix fraction description of linear time invariant systems, mathematical theory of polynomial matrices, poles and zeroes of multivariable systems, canonical realizations, frequency domain analysis, and design techniques. Prerequisite: ESYS 408.
ESYS 414. Complex Systems Modeling and Analysis (3).
Complexity and uncertainty are principal obstacles to deriving solutions in many situations, in particular those situations which require multidisciplinary considerations and are "poorly defined." This course deals with multilevel, hierarchical system theory applied to complex systems including the use of an interactive software support system for dealing with uncertainties. Global climate change will be used as the case study. Global models and the software support system will be used in the course. Prerequisite: Consent of instructor.
ESYS 416. Optimization Theory and Techniques (3).
Underlying theory of linear, nonlinear, multilevel, and multiobjective optimization. Techniques include linear programming and extensions, quadratic programming, dynamic programming, unconstrained and constrained nonlinear programming, decomposition coordination scheme for multilevel optimization. Methods for generating Pareto optimal solutions in multiobjective optimization. Applications to engineering problems. Prerequisite: MATH 201 or consent of instructor.
ESYS 417. Introduction to Stochastic Control (3).
Analysis and design of controllers for discrete time stochastic systems. Review of probability theory and stochastic properties, input-output analysis of linear stochastic systems, spectral factorization and Wiener filtering, minimum variance control, state-space models of stochastic systems, optimal control and dynamic programming, statistical estimation and filtering, the Kalman-Bucy theory, the linear quadratic Gaussian problem, and the separation theorem. Prerequisite: ESYS 408, STAT 380 or consent of instructor.
ESYS 418. Identification and Adaptive Control (3).
Parameter identification methods for linear discrete time systems: maximum likelihood and least square estimation techniques. Adaptive control for linear discrete time systems including self tuning regulators and model reference adaptive control. Consideration of both theoretical and practical issues relating to the use of identification and adaptive control methods in applications. The use of identification and control system design software will be emphasized in the course. Special topics include deadtime estimation, jump linear systems, and dual control. Prerequisite: ESYS 417 or consent of instructor.
ESYS 421. Optimization of Dynamic Systems (1).
Fundamentals of dynamic optimization with applications to control. Variational treatment of control problems and the Maximum Principle. Structure of optimal systems; regulators, terminal controllers, time-optimal controllers. Sufficient conditions for optimality. Singular controls. Computational aspects. Selected applications. Prerequisite: ESYS 408 or consent of instructor.
ESYS 426. Water and Energy Systems Engineering (3).
Art and science of large-scale systems engineering is explored using water resources and energy supply systems as examples. Applications of optimization and simulation methods to the planning and management of water and energy systems. Simulation of supply systems reliability and water quality, using analytical and Monte Carlo methods. Optimal control of reservoirs and power generation. Optimization in design: location, timing, and sizing of power and water supply facilities. Portfolio analysis of supply alternatives. Policy analysis, including market simulation and national energy planning. Co-requisite : ESYS 416 ESYS 346, or consent of instructor.
ESYS 427. Risk and Reliability Analysis for Engineering (3).
Models and techniques for performing risk analysis in engineering. Markov, queuing, and other stochastic models. Reliability concepts and applications to engineering design. Bayesian reliability analysis. System reliability and maintenance. Fault tree and event tree analysis. Statistics of Extremes. Risk-based decisions using multiple test results. Brief review of decision analysis and Monte Carlo simulation. Prerequisite: STAT 380 or 385 (ESYS 315 recommended).
ESYS 435. Legal, Economic, and Social Aspects of Resource Management (3).
Interrelationships of three important aspects of resource management - legal, economic, and social - within the framework of the systems approach. How the fundamental concepts in law, economics, and social behavior are integrated in natural resources planning and management. Principles of environmental and social impact assessment. Prerequisite: Consent of instructor.
ESYS 450. Integrated Production/Manufacturing Systems (3).
Fundamental theories and techniques of optimization, decision making, and artificial intelligence for solving production/manufacturing problems. Formulation, modeling, planning, and control of production problems at three levels: strategic, tactical, and operational (long term, medium, and short term).
Specific problems include aggregate planning, project planning, scheduling, line balancing, sequencing, and machine setup. Special emphasis will he given on decomposition and control of computer integrated systems, on-line and off-line supervisory planning, and man/machine systems.
ESYS 463. Techniques of Medel Based Control (3).
(Also listed as ECHE 463.) Strategy of industrial process control centered around the use of process modelsa in control systems. Topics include single loop, feedforward, cascade and multivariable internal model control. Tuning controllers to accomodate process uncertainty. Treatment of control effect and output constraints in model predictive control and modular multivariable control.
ESYS 509. Analysis of Discrete Event Systems (3).
Mathematical analysis of discrete event systems. Analytical frameworks used far modeling and analysis including automata, queuing networks, algebras, and computer based methods. Performance analysis using perturbation, spectral, and simulation techniques. Discussion of current literature and research. A course project is required. Prerequisite: Consent of instructor.
ESYS 510. Advanced Systems Theory (3).
Mathematical foundations of general systems theory. General time systems, algebraic systems; abstract linear systems, algorithmic systems. Mathematical formulations and results of structural and behavioral properties. Open research problems. Prerequisite: ESYS 410 or consent of instructor.
ESYS 515. Decision Theory with Applications (3).
Fundamentals of decision theory and analysis of decision processes in systems. Elementary decision analysis. Single and multiattribute utility theory under both certainty and uncertainty. Bayesian decision analysis. Sequential decision processes including dynamic programming and Markov processes. Analysis of multiperson decision processes and game theory as related to management decisions. Applications to large-scale systems and to decision support systems. Prerequisite: Consent of instructor.
ESYS 516. Large Scale Optimization (3).
Concepts and techniques for dealing with large optimization problems encountered in designing large engineering structure, control of interconnected systems, pattern recognition, and planning and operations of complex systems; partitioning, relaxation, restriction, decomposition, approximation, and other problem simplification devices; specific algorithms; potential use of parallel and symbolic computation; student seminars and projects. Prerequisite: ESYS 416 or consent of instructor.
ESYS 517. Stochastic Control Theory (3).
Analysis and control of continuous-time stochastic systems. Control of diffusion processes. Optimal control of linear systems with quadratic cost, open-loop and feedback controls, linear filtering and prediction, stochastic stability and controllability, nonlinear stochastic systems. Diffusion processes. Probability theory. Prerequisite: ESYS 417 or consent of instructor.
ESYS 518. Nonlinear Systems: Analysis and Control (3).
Mathematical preliminaries: differential equations and dynamical systems, differential geometry and manifolds. Dynamical systems and feedback systems, existence and uniqueness of solutions. Complicated dynamics and chaotic systems. Stability of nonlinear systems: input-output methods and Lyapunov stability. Control of nonlinear systems: pin scheduling, nonlinear regulator theory and feedback linearization. Prerequisite: Consent of instructor.
ESYS 521. System Identification (3).
The theory and practice of parameter identification and adaptive filtering, prediction, and control. Linear discretetime systems reflecting the digital implementation of these methods; nonlinear systems and the analysis of continuous-time systems. New techniques and recent major results in the convergence and performance of adaptive algorithms. Course project. Prerequisites: ESYS 304 and 408, or consent of instructor.
ESYS 523. Multiobjective and Hierarchical Systems (3).
Basic concepts of hierarchical, multilevel systems. Lagrangian decompositions and coordination principles. Fundamentals and recent advances in theory, methodology, and applications of multiple criteria decision making (MCDM) with single and multiple decision makers. Interactive MCDM methods. Multiple objectives for discrete and continuous models. Multiobjective programming methods. Hierarchical overlapping coordination with single and multiple objectives. Multiobjective multistage impact analysis. Applications to large scale systems and to decision support systems. Prerequisite: Consent of instructor.
ESYS 529. Digital Simulation of Dynamic Systems (3).
(Also ECHE 529.) Simulation of ordinary and partial differential equations. Runge-Kutta and predictor corrector techniques, shooting methods, finite difference methods, and stability analysis. Prerequisite: MATH 470 or consent of instructor.
ESYS 620. Special Topics in Systems (credit as arranged).
ESYS 621. Special Projects (credit as arranged).
ESYS 622. Special Projects (credit as arranged).
ESYS 651. Thesis (M.S.)
ESYS 701. Dissertation (Ph.D.)
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