Design and Systems Reliability (DSR)

ENME 600 – ENGINEERING DESIGN METHODS (3 credits) Prerequisites: Graduate standing or permission of instructor. Meets the Core Course Requirement for DSR students.

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.

ENME 607 – ENGINEERING DECISION-MAKING (3 credits) Prerequisite: Graduate standing or permission of instructor.  Meets the Core Course Requirement for DSR students.

In the course of engineering design, project management, and other functions, engineers have to make decisions, almost always under time and budget constraints. This course covers material on individual decision-making, group decision-making, and organizations of decision-makers. The course will present techniques for making better decisions and for understanding how decisions are related to each other. Specific topics include the role of models, decision-making heuristics, decision analysis, sequential decision-making, decision processes, search, decomposition, project management, decision-making systems and product development organizations.

ENME 610 – ENGINEERING OPTIMIZATION (3 credits) Prerequisite: Graduate standing or permission of instructor.  Meets the Core Course Requirement for DSR students.

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.

ENME 625 – MULTIDISCIPLINARY OPTIMIZATION (3 credits) Prerequisite: Graduate standing or permission of instructor. 

Overview of single– and multi–level design optimization concepts and techniques with emphasis on multidisciplinary engineering design problems. Topics include single- and multi-level optimality conditions, hierarchic and non-hierarchic modes, and multi-level post optimality sensitivity analysis.   Students are expected to work on a semester-long project.

ENME 690 – MECHANICAL FUNDAMENTALS OF ELECTRONIC SYSTEMS (3 credits) Prerequisites: None. Meets the Core Course Requirement for DSR students.

This course will provide the student with an understanding of the fundamental mechanical principles used in the design of electronic devices and their integration into electronic systems. It will focus on the effect of materials compatibility, thermal stress, mechanical stress, and environmental exposure on product performance, durability, and cost.  Both electronic devices and package assemblies will be considered.  Analysis of package assemblies to understand thermal and mechanical stress effects will be emphasized through student projects.

ENME 695 – DESIGN FOR RELIABILITY (3 credits) Prerequisites: None.  Meets the Core Course Requirement for DSR students.

This course will present classical reliability concepts and definitions based on statistical analysis of observed failure distributions. Techniques to improve reliability, based on the study of root-cause failure mechanisms, will be presented; based on knowledge of the life-cycle load profile, product architecture and material properties. Techniques to prevent operational failures through robust design and manufacturing practices will be discussed.  Students will gain the fundamentals and skills in the field of reliability as it directly pertains to the design and the manufacture of electrical, mechanical, and electromechanical products.

ENME 722 – EQUILIBRIUM MODELING IN ENGINEERING (3 credits) Prerequisites: None. 

Provide motivation and introduction to equilibrium models involving economics and engineering.  We will concentrate on models involving markets (Nash-Cournot, etc.) those wherein the activities are spatially diverse, those involving energy activities or traffic flow, as well as selected other examples in mechanical engineering.  Areas that will be covered include: Review of relevant optimization theory, presentation of the mixed complementarity problem (MCP) and variational inequality problem (VIP) formats to solve equilibrium problems as well as introduction to existence and uniqueness results, relevant game theory notions, presentation of specific models for engineering-economic applications, presentation for algorithms to solve these equilibrium problems.

ENME725 – PROBABILISTIC OPTIMIZATION (3 credits) Prerequisites: An advanced undergraduate course in probability and a graduate course in optimization or permission of the instructor. 

Provide an introduction to optimization under uncertainty.  Chance-constrained programming, reliability programming, value of information, two stage problems with recourse, decomposition methods, nonlinear programming theory, probability theory.  The objectives of this course are to provide understanding for studying problems that involve optimization under uncertainty, learn about various stochastic programming formulations (chance constrained programs, two stage methods with recourse, etc.) relevant to engineering and economic settings, present theory for solutions to such problems, and present algorithms to solve these problems.

ENME 737 – PROGNOSTICS AND HEALTH MANAGEMENT (3 credits) Prerequisites: None. 

Prognostics and health management (PHM) is an enabling discipline consisting of technologies and methods to assess the reliability of a product in its actual life cycle conditions to determine the advent of failure and mitigate system risk.  PHM permits the reliability of a system to be evaluated and predicted in its actual application conditions.  In recent years, prognostics and health management (PHM) has emerged as a key enabling technology to provide an early warning of failure; to forecast maintenance as needed; to reduce maintenance cycles; to assess the potential for life extensions; and to improve future designs and qualification methods.  In future, PHM will enable systems to assess their own real-time performance (self-cognizant heath management and diagnostics) under actual usage conditions and adaptively enhance life cycle sustainment with risk-mitigation actions that will virtually eliminate unplanned failures.

ENME 741 – OPERATION RESEARCH MODELS IN ENGINEERING (3 credits) Prerequisites: ENCE 302 OR ENME 271 and ENME 392, and Math 140, MATH 240, or permission of the instructor. 

A survey of the fundamentals of operations research models and methods in engineering including: optimization using linear programming, nonlinear programming, integer programming, as well as equilibrium/game theory via mixed complementarity problems.  Examples of specialized course items include: specifics of optimizing power and gas networks, discussion of other network optimization problems, resource-constrained problems, two-level optimization as an example of mixed integer nonlinear programming (MINLP) programming problems as well as algorithms to solve the above types of problems.

ENME 743 – APPLIED MACHINE LEARNING FOR ENGINEERING AND DESIGN (3 credits) Prerequisites: ENME 392 or equivalent, or permission of the instructor. 

Learn how to apply techniques from Artificial Intelligence and Machine Learning to solve engineering problems and design new products or systems.  Design and build a personal or research project that demonstrates how computational learning algorithms can solve difficult tasks in areas you are interested in.  Master how to interpret and transfer state-of-the-art techniques from computer science to practical engineering situations and make smart implementation decisions.

ENME 765 – THERMAL ISSUES IN ELECTRONIC SYSTEMS (3 credits) Prerequisites: Thermodynamics, fluid mechanics, transfer processes (undergraduate level).  Corequisite: ENME 473 (or equivalent).

This course addresses a range of thermal issues associated with electronic products life cycle. Topics include: Passive, active, and hybrid thermal management techniques for electronic devices and systems. Computational modeling approaches for various levels of system hierarchy. Advanced thermal management concepts, including single phase and phase change liquid immersion, heat pipes, and thermoelectrics.

ENME 770 – LIFE CYCLE COST ANALYSIS (3 credits) Prerequisites: None. 

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 application of the methods mentioned above.


This course will discuss issues related to silicon power device selection (IGBT, MCT, GTO, etc.), the characteristics of silicon device operation at temperatures greater than 125C, and the advantages of devices based on SOI and SiC. It will also discuss passive component and packaging materials selection for distributing and controlling power, focusing on the critical limitations to the use of many passive components and packaging materials at elevated temperatures. In addition it will cover packaging techniques and analysis to minimize the temperature elevation caused by power dissipation. Finally, models for failure mechanisms in high temperature and high power electronics will be presented together with a discussion of design options to mitigate their occurrence.


Knowledge of battery operation, degradation, safety and testing are becoming expected knowledge for all engineers and this new graduate level class will provide the necessary background and advanced coverage on the topics. This is an interdisciplinary course, and students in all science and engineering disciplines are welcome. Students will get the opportunity to learn the basic scientific foundations that enhance battery reliability and safety in field applications. Guest lecturers from industry, academia, and government will supplement the lectures in their specialized fields of

ENME 808N – NANOMECHANICS (3 credits) Prerequisite: None.

The success of nanotechnology depends on unexpected material behavior due to nanoscale phenomena, many of which cannot be explained by conventional continuum mechanics. This course examines the mechanics of nanoscale phenomena, the applicability of conventional continuum mechanics, and the alternate techniques available for addressing nanomechanics. Examples of alternate modeling techniques include discrete models based on molecular dynamics, as well as enriched continuum models (based on strain-gradient effects, non-local effects, surface effects, dipole mechanics, and micro-continuum mechanics). This is an advanced graduate course and assumes some familiarity with conventional continuum mechanics.


To familiarize students with the optical principles and applications, and to help them learn the method details and develop skills for research investigations.