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IME Graduate Courses

MS and PhD Courses 

EEL 5606. Introduction to Mobile Robotics and Unmanned Systems (3). This course provides a thorough technical overview of autonomous vehicles for engineering students interested in understanding the basics of unmanned systems. The principles and methodology involved for the systems development is discussed. The course uses practical examples of developing autonomous unmanned vehicle systems. 

EEL 5688. Principles of Autonomous Systems (3). Prerequisite: EEL 5605. This course provides an in-depth review of the principles of autonomy by reviewing probability theory and covering topics in pattern recognition, computer vision/perception, localization/SLAM, planning, and unsupervised/supervised learning. 

EGN 5444. Big Data Analytics in Engineering (3). Prerequisites: EGN 3443. This course introduces the fundamentals of big data analytics, including data loading, cleaning, transformation, visualization, predictive analytics and data-driven decision making, with an emphasis on computer implementation and engineering applications. 

EIN 5020. Research Methodology (3). This course provides a structured and easily understandable step-by-step approach for students to learn the key components that compromise a sound research process. 

EIN 5182. Engineering Management (3). Prerequisite: EIN 5353. Course in modeling existing and future organizations, with emphasis on organizations for the 21st century. Special consideration is given to flat matrix models. 

EIN 5328. Environmentally Conscious Design and Manufacturing (3). Prerequisite: Graduate standing. This course offers a review of basic concepts and fundamentals of environmentally conscious design and manufacturing. The topics include ecology and environment; review of environmental laws and regulations pertaining to design and manufacturing; the global picture of environmental concerns; integration of environmentally conscious design and manufacturing within a company; and life-cycle analysis for product and process design. 

EIN 5353. Engineering Economic Analysis (3). Prerequisites: EGN 3443 and MAP 3305. This course includes feasibility science, mathematics and engineering focused on the engineering economic analysis of design and system alternatives for high technology operations. 

EIN 5356C. Cost Estimating for Engineering Economic Analysis (3). Prerequisite: Instructor permission. The course provides students with an improved understanding and application of engineering economics and cost analysis which are critical in a Systems Engineer's toolkit. The course includes cost aspects of systems engineering, exploring cost from a decision-making perspective. 

EIN 5392. Manufacturing Processes and Systems (3). Prerequisite: EGN 4000. Material forming, material removal and material joining processes. Shop floor layout topics. Material flow topics. Information system topics. System integration topics. Manufacturing system evaluation topics. Case studies and design exercises. 

EIN 5398. Manufacturing Materials Processing (3). Prerequisite: EIN 5392. Review of basic concepts and fundamental results of materials science. Fundamentals of casting processes and applications. Nontraditional methods in materials processing. Microscale material processing, with applications to microelectronics and similar structures. Industrial byproduct processing. Automation issues. Case studies and design exercises. 

EIN 5445C. Technology Entrepreneurship and Commercialization (3). This course simulates, in an academic environment, the process of creating and analyzing business models and commercialization plans for technology-based products or services. 

EIN 5524. System Modeling and Simulation (3). Prerequisites: CGS 3460, EGN 3443, and ESI 3443. Discrete event, continuous, and process simulation. Combined discrete/continuous simulation. Manufacturing systems modeling. Event graphs. Simulation languages and systems. Experimentation with models. Introduction to simulation-specific statistical problems. Model validation and verification issues. Design exercises. 

EIN 5622. Computer-Aided Manufacturing (3). Prerequisite: EIN 3390C. CAD/CAM. Numerical Control (NC) and Computer Numerical Control (CNC). Programmable automation. Computer-aided process planning. 

EIN 5905r. Directed Individual Study (1–3). (S/U grade only). Prerequisite: Instructor permission. May be repeated to a maximum of six semester hours. 

EIN 5930r. Special Topics in Industrial Engineering (3–6). Prerequisite: Instructor permission. This course discusses topics in industrial engineering with particular emphasis on recent developments. May be repeated to a maximum of six semester hours. 

EIN 5931. Leadership and Communications (3). Prerequisites: Graduate standing and EGN 3613. Course topics include leadership theories, motivation, goal setting, planning, proposal writing and technical presentations. Presentations given by business leaders are planned. 

EIN 5936r. Graduate Seminar (0). (S/U grade only). Research presentations by faculty, students, and guests from industry. 

EIN 6901r. Master's Thesis (1–12). (S/U grade only). Prerequisite: Approval by department. This course provides a means of registering for thesis research work and recording progress towards its completion. May be repeated to a maximum of forty-five (45) credit hours; repeatable within the same term. 

EIN 8976r. Master's Thesis Defense (0). (P/F grade only.) 

EMA 5015C. Nanomaterials and Nanotechnology (3). This course is designed to provide students the basic understanding and up-to-date knowledge on nanostructured materials, characterization methods, nano-devices, and nano-fabrication through class lectures, literature reading, and hands-on lab experiments. 

EMA 5182. Composite Materials Engineering (3). Prerequisite: Instructor permission. Course provides basic understanding of composite materials. Topics include introduction to composite materials, properties and forms of constituent materials, consideration of composite behavior and failure modes, characterization of material performance and testing, introduction to available manufacturing techniques, laboratory demonstrations, and case studies. 

EOC 5518. Marine Vehicles Engineering Principles (3). This course provides a thorough technical overview of naval architecture of advanced marine vehicles. As an introduction to naval architecture and marine vehicles, this course provides the practicing systems engineer the basic knowledge and skills necessary to lead a team of engineers with marine vehicles as part of the mission and project. 

EOC 5519. Marine Systems Engineering Principles (3). In this course, students apply strategic and critical thinking principles to the development of marine systems, and develop a comprehensive approach to the integration of hull, propulsion, and mission systems into marine vehicle design. 

ESI 5000. Design Considerations for Systems Engineering (3). This course provides students with knowledge and practical experience in quality and reliability measures for systems engineering. The course covers principles of Failure Mode and Effects Analysis (FMEA), reliability specifications, design for reliability, human centered design, accelerated testing, mechanical stress and analysis, software reliability, cybersecurity, supplier reliability, mathematical and statistical models for process control, life distributions and concepts, design for quality, focus on customers, six sigma, total quality, and the importance of quality in design. 

ESI 5001. Systems Test and Evaluation (3). This course provides students with knowledge and practical experience in system test and evaluation (T&E) as practicing systems engineers. The course discusses how tests are defined, designed, conducted, and how data from the tests are evaluated against the system requirements. Test and evaluation techniques of system design and performance are analyzed throughout the course. Feedback loop of data analysis is introduced to identify the need for design changes in order to improve safety, correct failures, verify supportability of the systems, and support investment decisions. 

ESI 5223. Statistical Process Control (3). Prerequisite: ESI 4234. Advanced methods of statistical process control for univariate and multivariate processes, methods for change point detection and estimation, control chart performance comparisons, process capability studies. 

ESI 5228. Introduction to ISO 9000 (3). Prerequisite: Instructor permission. Introduction to the ISO 9000 quality system standards. Quality auditing. Audit report writing. Documenting the requirements. Case studies and demonstrations. 

ESI 5243. Engineering Data Analysis (3). Prerequisite: EGN 3443 or equivalent. Analysis of experimental and observational data from engineering systems. Course focuses on empirical model building using observational data for characterization, estimation, inference and prediction. 

ESI 5247. Engineering Experiments (3). Prerequisites: EGN 3443 and ESI 5243. This course provides an introduction to designing experiments and analyzing the results. It is intended for engineers and scientists who perform experiments or serve as advisors to experimentation in industrial settings. Students must have an understanding of basic statistical concepts. A statistical approach to designing and analyzing experiments is provided as a means to efficiently study and comprehend the underlying process being evaluated. Insight is gained that leads to improved performance and quality. 

ESI 5249. Response Surfaces and Process Optimization (3). Prerequisite: ESI 5247. This course explores combined statistical experiment designs, empirical model building, and optimization methods. Topics include restrictions on randomization, mixture experiments, and robust design. Emphasis is placed on software tools to build designs and perform appropriate analyses. 

ESI 5353. Engineering Risk Analysis and Decision Making with Uncertainty (3). This course provides students with the knowledge and practical experience in risk analysis, risk identification, risk mitigation strategy development, ethics in risk management, communicating uncertainties, and risk leadership in complex organizations. Stochastic modeling and probabilistic theoretical models are exercised, and students are expected to understand probability basics. 

ESI 5408. Applied Optimization (3). Prerequisite: ESI 3312C. Optimization topics relevant to industrial operations and systems. Emphasis on basic modeling assumptions and procedure implementation. Topics shall include linear programming, nonlinear programming, discrete optimization and large-scale optimization software. Design exercises. 

ESI 5451. Project Analysis and Design (3). Prerequisites: EGN 3613 and ESI 3312C. Project analysis and evaluation, utilizing networks and graph theory, advanced engineering economy, simulation procedures and other evaluation software. Project implementation topics, including resource shortfalls and expediting. Case studies and design exercises. 

ESI 5458. Optimization on Networks (3). Prerequisite: ESI 3312C. Review of basic combinatorics. Basic concepts of graph theory. Matching and covering, and applications. Traversability and path problems on networks and applications. Tree problems. Network flows and applications. Eulerian paths, Hamiltonian paths, and applications. Location problems on networks. Design exercises. 

ESI 5510. Fundamentals of Systems Engineering (3). This course provides students with a fundamental understanding of Systems Engineering (SE). The course introduces multidisciplinary SE technical processes over the life cycle of a system including growing a deep awareness and understanding of analyzing and documenting user needs. 

ESI 5512. System Requirements Analysis and Knowledge Management (3). The course provides students with the knowledge and practical experience in system requirement development and analysis as practicing systems engineers. The course introduces key knowledge management principles and practices along with a thorough understanding of methods to codify intellectual property and tacit knowledge into explicit knowledge for the betterment of the organization and the system people, processes, and products supported. 

ESI 5524. Advanced Simulation Applications (3). Prerequisite: ESI 4523 or EIN 5524. Application of simulation to complex systems, including material handling systems, real time scheduling, high speed/high volume production, modern manufacturing techniques, health-care delivery and logistics. Concurrent use of simulation and other analysis techniques. Use of experimental design, output analysis and validation techniques. Case studies. 

ESI 5525. Modeling and Analysis of Manufacturing and Industrial Systems (3). Prerequisites: EIN 4333, ESI 3312C, ESI 4523, ESI 5408, and ESI 5524. Modeling and analysis of material flow systems, flow-shop and job-shop scheduling, material handling system analysis, mathematical and simulation modeling for general manufacturing and industrial systems. 

ESI 5536. Model Based Systems Engineering and Simulation (3). This course provides students with knowledge and practical experience in Model Based Systems Engineering (MBSE) and simulation. The International Council on Systems Engineering (INCOSE) defines MBSE as the formalized application of modeling to support system requirements, design, analysis, verification and validation activities beginning in the conceptual design phase and continuing throughout development and later life cycle phases. The course introduces de facto industry standard MBSE modeling software and tools, and their use in the design and optimization of systems. 

PhD only Courses 

EIN 6980r. Dissertation (1–12). (S/U grade only). Prerequisite: Admission to doctoral candidacy. This is a mandatory class for all PhD seeking students. May be repeated to a maximum of forty-eight (48) semester hours within the same term. 

EIN 8964. Preliminary Doctoral Examination (0). (P/F grade only.) Prerequisite: Doctoral candidate standing. 

EIN 8985r. Dissertation Defense (0). (P/F grade only.) Prerequisite: Doctoral candidate standing.