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Course Criteria
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3.00 Credits
Covers relatively new approaches to machine intelligence known collectively as soft computing. Introduces various types of fuzzy inference systems, neural networks, and genetic algorithms, along with several synergistic approaches for combining them as hybrid intelligent systems. Emphasis is on applications, including modeling, prediction, design, control, databases and data mining. Offered as a dual level (graduate/undergraduate) course with SSIE 519. The undergraduate students are not required to do projects on the same level as the graduate students, and are not required to place the degree of emphasis on hybrids. Prerequisites: senior standing, basic knowledge of calculus and discrete mathematics and competence in at least one programming language, or consent of department chair.
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3.00 Credits
Operations Research (OR) is devoted to the determination of the optimal course of action of a decision problem given resource restrictions. This course is intended as a second course in an Optimization and OR sequence and builds upon the material presented in the ISE 320 course. ISE 320 primarily restricts attention to deterministic OR models. In addition to covering additional deterministic techniques, ISE 420 will cover probabilistic and advanced OR topics such as Dynamic Programming, Queuing Systems, Monte Carlo Simulation, Nonlinear Programming, and Markovian Decision Processes. Prerequisite: senior standing in ISE or consent of department chair.
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3.00 Credits
Model building, nature of simulation and material on the full range of simulation activities, such as input analysis, output analysis, verification and validation, and model animation. Includes random number generation; distribution functions and random variates; applications of discrete event simulation methods to queueing, inventory control and production planning problems; Markov processes, queuing theory and decision analysis. Prerequisites: ISE 362 and ISE 320 or consent of department chair. fall
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3.00 Credits
Course provides a broad foundation in decision models and techniques used in industry and research for technical and managerial problems. Topics include: decision theory, risk and uncertainty, value of information, preference measurements, prioritization of alternatives, multiple objectives and hierarchical decisions. This is offered as a dual-level course with SSIE 522. The undergraduate students will not be required to do some of the course work on the same level as the graduate students. Prerequisite: ISE 362 or permission of the department chair.
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3.00 Credits
One of the growing systems in our society is that of the healthcare delivery system. The purpose of this course is to introduce the concepts behind the healthcare delivery systems and to focus upon the systems improvement or continuous improvement techniques available for complex systems. Topics would include improvement to, and problems with: organizational structure, managing change, the financial structure, the responsibility structure, quality data and implications of quality measures, use of clinical decisions support systems and the care giver?s role in the system. There will also be a focus upon suppliers to the healthcare delivery system and the unique requirements placed upon their products and processes.
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3.00 Credits
Includes the following: 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.
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3.00 Credits
Computer-based decision-making tools in which a domain expert?s knowledge is embedded are known as knowledge-based expert systems (KBESs). Expert systems allow such expert knowledge to be widely disseminated (e.g., throughout a company or throughout different facilities that a company has). This course introduces the student to all steps of development (e.g., knowledge representations, knowledge acquisition, and expert system development, among others) with special emphasis on manufacturing applications. The course will culminate with the students developing functioning prototype expert systems in a manufacturing area of their choice. Prerequisite: senior standing in ISE or consent of department chair.
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3.00 Credits
Changes in our society have resulted in major changes in manufacturing to the point at which labor costs are no longer the controlling cost, or even the major cost. Major costs have shifted to the material and material-related costs, with the overhead and burden costs almost as significant. While innovative design is critical to engineering, being profitable is also critical, and profit starts with determining the proper costs for a product or idea. Topics include costs of labor, equipment, material, overhead or burden, volume/cost relationships, use rates, collection, build-up of costs, costing of manufacturing operations, standard costs and variances. Prerequisite: senior standing or consent of department chair.
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3.00 Credits
Managing engineering projects from design through completion. Topics include project scope definition, budgeting, planning, scheduling, monitoring and completion. In addition, people issues, risk analysis and contracting are addressed. The course will emphasize early stages of project development, which have a great impact on the quality, cost and schedule of a project. Principles and functions of industrial project management will be illustrated with case studies. Appropriate computer tools will be used. Prerequisite: ISE 362 or consent of department chair. fall, 3 cr.
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3.00 Credits
Simple introduction to basic elements of fuzzy logic and fuzzy set theory, including an overview of classical logic and classical set theory. Included are basic concepts and properties of classical sets and fuzzy sets, classical relations and fuzzy relations, classical logic and fuzzy logic, and fuzzy arithmetic. The practical utility of fuzzy logic and fuzzy set theory is illustrated by describing selected applications in various areas of human affairs. Prerequisite: ISE 361 or consent of the instructor. spring, 3 cr.
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