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Course Criteria
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3.00 Credits
Description: Modern manufacturing systems with emphasis on information requirements and data management. Includes CAD, CAM, CAPP, real-time scheduling, networking, and system justification. Graduate-level requirements include selection of their own topics (not have them assigned by the instructor), and the topics must be on a more advanced level. Grading: Regular grades are awarded for this course: A B C D E. May be convened with: SIE 483. Usually offered: Fall.
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3.00 Credits
Description: 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. Grading: Regular grades are awarded for this course: A B C D E. Usually offered: Spring.
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3.00 Credits
Description: 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 other sensing techniques. Graduate-level requirements include two research projects. Grading: Regular grades are awarded for this course: A B C D E. Credit for: 2 units engineering science, 1 unit engineering design. May be convened with: SIE 485. Usually offered: Fall.
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3.00 Credits
Description: Methods for the design and construction of real-time embedded systems including hardware and software components. Topics include System architectures, operating systems, programming and applications. Grading: Regular grades are awarded for this course: A B C D E. Prerequisite(s): SIE 370. Usually offered: Fall.
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3.00 Credits
Description: Seminar in theory and application of ethics as applies to engineering practice, education, and research. Topics will include rationale behind accepted engineering ethics codes, cultural issues in ethical standards, and intellectual property issues. Each student will lead one or more seminars during the semester, and will present relevant information in their areas of interest regularly. Grading: Regular or alternative grades can be awarded for this course: A B C D E or S P C D E. Typical structure: 2 hours seminar, 1 hour discussion. Usually offered: Spring.
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1.00 - 5.00 Credits
Description: Qualified students working on an individual basis with professors who have agreed to supervise such work. Graduate students doing independent work which cannot be classified as actual research will register for credit under course number 599, 699, or 799. Grading: Alternative grades are awarded for this course: S P F. May be repeated: an unlimited number of times, consult your department for details and possible restrictions. Usually offered: Fall, Spring, Summer.
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3.00 Credits
Description: 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. Grading: Regular grades are awarded for this course: A B C D E. Prerequisite(s): SIE 530, SIE 506. Usually offered: Spring.
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3.00 Credits
Description: Emphasis on current research problems including simulation based control, distributed federation of simulations, and multi-paradigm (system dynamics, discrete event based, agent-based) simulations. Grading: Regular grades are awarded for this course: A B C D E. Prerequisite(s): SIE 431 or MIS 521. Usually offered: Spring.
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3.00 Credits
Description: 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. Grading: Regular grades are awarded for this course: A B C D E. Prerequisite(s): SIE 544 or SIE 545. Usually offered: Fall.
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3.00 Credits
Description: Modeling and solving problems where the decisions form a discrete set. Topics include model development, branch and bound methods, cutting plane methods, relaxations, computational complexity, and solving well-structured problems. Grading: Regular grades are awarded for this course: A B C D E. Prerequisite(s): SIE 544. Usually offered: Fall, Spring.
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