Additive Manufacturing

Students in the Professional Master of Engineering in Additive Manufacturing Program will complete 10 courses or 30 credits. Students will take 5 core courses (out of 7 options listed) and 5 technical electives. The technical electives can be chosen from the remaining core list, the pre-approved technical elective list, or can be another course they wish to take. The curriculum is designed so that students could complete the curriculum in two academic years if pursuing the degree full-time.


Additive Manufacturing

ENME600 Engineering Design Methods (3)
Prerequisites: Graduate standing or permission of instructor.
This is an introductory graduate level course in critical thinking about formal methods for design in mechanical engineering. Course participants gain background in these methods and the creative potential each offers to designers. Participants will formulate, present, and discuss their own opinions on the value and appropriate use of design materials for mechanical engineering.
ENME607 Engineering Decision Making (3)
In the course of engineering design, project management, and other functions, engineers have to make decisions, almost always under time and budget constraints. Managing risk requires making decisions in the presence of uncertainty. This course will cover material on individual decision making, group decision making, and organizations of decision-makers. The course will present techniques for making better decisions, for understanding how decisions are related to each other, and for managing risk.
ENME610 Engineering Optimization (3)
Prerequisite: Graduate standing or permission of instructor.
Overview of applied single- and multi-objective optimization and decision making concepts and techniques with applications in engineering design and/or manufacturing problems. Topics include formulation examples, concepts, optimality conditions, unconstrained/constrained methods, and post-optimality sensitivity analysis. Students are expected to work on a semester-long real-world multi-objective engineering project.
ENME743 Applied Machine Learning for Engineering and Design (3)
Credit only granted for: ENME 743 OR ENME 808E. Formerly: ENME 808E.
Machine learning is a rapidly growing field at the intersection of computer science and statistics that is concerned with finding patterns in data. It is responsible for tremendous advances in technology, from personalized product recommendations to speech recognition in cell phones. The goal of this course is to provide a broad introduction to the key ideas in machine learning. The emphasis will be on intuition and practical examples rather than theoretical results, though some experience with probability, statistics, and linear algebra will be important. Through a variety of lecture examples and programming projects, students will learn how to apply powerful machine learning techniques to new problems, run evaluations and interpret results, and think about scaling up from thousands of data points to billions.
ENME744 Additive Manufacturing (3)
Prerequisite: ENME272 and ENME331; or students who have taken courses with comparable content may contact the department. Also offered as: ENME416. Credit only granted for: ENME 416 OR ENME 744.
Develop a comprehensive understanding of fundamental additive manufacturing-alternatively, "three-dimensional (3D) printing-approaches, including extrusion-based deposition, stereolithography, powder bed-based melting, and inkjet-based deposition. Cultivate a "design-for-additive manufacturing" skill set for combining computer-aided design (CAD) and computer-aided manufacturing (CAM) methodologies to produce successful 3D prints. Fabricate 3D mechanical objects using a variety of 3D printing technologies on campus. Execute a design project that demonstrates how additive manufacturing technologies can overcome critical limitations of traditional manufacturing processes.
ENPM671 Advanced Mechanics of Materials (3)
Formulate and quantitatively state the mechanical/physical responses of structural components and configurations subjected to loads, temperature, pre-strains etc. The two methods of analysis employed are the mechanics of materials approach and the theory of elasticity approach. Analysis and design of components of structural/machine systems as experienced in aeronautical, civil, mechanical and nuclear engineering.

Additive Manufacturing

ENME627 Manufacturing with Polymers (3)
Understand fundamental processes used for polymer processing, including injection molding, extrusion, batch mixing. Determine the effects of processing conditions and viscosity on the microstructure of polymers with and without fillers. Develop fundamental models of polymer processing techniques for control of microstructure.
ENME647 Multiphase Flow and Heat Transfer (3)
Boiling and condensation in stationary systems, phase change heat transfer phenomenology, analysis and correlations. Fundamentals of two-phase flow natural circulation in thermal hydraulic multi-loop systems with applications in nuclear reactor safety. Multiphase flow fundamentals. Critical flow rates. Convective boiling and condensation. Multiphase flow and heat transfer applications in power and process industries.
ENME672 Composite Materials (3)
Micromechanics of advanced composites with passive and active reinforcements, mathematical models and engineering implications, effective properties, damage mechanics, and recent advances in “adaptive” or “smart” composites.
ENME770 Life Cycle Cost and System Sustainment Analysis (3)
This course melds elements of traditional engineering economics with manufacturing process modeling and life cycle cost management concepts to form a practical foundation for predicting the cost of commercial products. Methodologies for calculating the cost of systems will be presented. Product life cycle costs associated with scheduling design, reliability, design for environment (life cycle assessment), and end-of-life scenarios will be discussed. In addition, various manufacturing cost analysis methods will be presented, including process-flow, parametric, cost of ownership, and activity based costing. The effects of learning curves, data uncertainty, test and rework processes, and defects will be considered. This course will use real life design scenarios from integrated circuit fabrication, electronic systems assembly, and substrate fabrication as examples of the applications of the methods mentioned above.
ENPM641 Systems Concepts, Issues, and Processes (3)
Prerequisite: Permission of ENGR-CDL-Office of Advanced Engineering Education. Also offered as: ENSE621. Credit only granted for: ENPM641 or ENSE621.
An introduction to the professional and academic aspects of systems engineering. Topics include: systems engineering activities, opportunities and drivers; case studies of systems failures; models of system lifecycle development; introduction to model-based systems engineering; representations for system structure, system behavior, system interfaces and systems intergration; reactive (even-driven) systems, systems-of-systems, measures of system complexity; visual modeling of engineering systems with UML and SySML; simplified procedures for engineering optimization and tradeoff analysis. Software tools for visual modeling of systems with UML and SySML. Students will complete a project for the front-end development of an engineering system using ULM/SySML.
ENPM808G Additive Manufacturing for Aerospace, Energy and Water Applications (3)
In-depth understanding of Additive Manufacturing (AM) technologies and their applicability and limitations is important for future engineers in developing new engineering systems and identifying emerging opportunities in developing products for mass customization. This course will be given in two parts: Part I focuses on brief introduction of AM technologies and their participial operation, applicability, and limitation areas; enabling features of design optimization for AM; material properties in AM; and advances in computational materials science for AM-fabricated material characterization. Here the aim is to provide in-depth fundamental knowledge and tools to evaluate/develop new opportunities in AM. Part II provides specific case studies and exercises on applications in four targeted industrial sectors, namely: Aerospace, Defense, Energy and Water Harvesting applications. These case studies will demonstrate the potential opportunities and limitations associated with each of the four respective areas.
ENPM809C Applied Statistics (3)
ENPM809E Applied Topology Optimization (3)

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