1. Graduate Work – Systems Engineering
Lynn Coupal
Description of the education (courses etc.) and practical training or skills in my
background that are relevant to my success in Systems Engineering.
Most of my education and background has been primarily in Mathematics. My Undergraduate
degrees were Mathematics and Secondary Mathematics Education. I pursued my Masters degree
in Systems Engineering.
I studied the book entitled Case Studies in Reliability and Maintenance. There were a lot of
topics covered in Probability and Statistics, including but not limited to: modeling, reliability
assessment and prediction, simulation, testing, failure analysis, statistical process control,
regression analysis and reliability growth modeling and analysis. Most cases consisted of
mathematical modeling.
At the undergraduate level, I took a few Probability and Statistics courses. One was an advanced
Probability and Statistics class that was Calculus based. Additionally, one of the first classes
completed towards my master’s program was entitled Probability and Statistics for Scientists
and Engineers (NMTH 6701). My Calc. based Probability and Statistics class helped to prepare
me for the type of mathematics necessary for mastery of this course. In the Probability and
Statistics for Scientists and Engineers class, probability models and statistical methods were used
to analyze data. This course provided a comprehensive introduction to the use of models and
methods most likely that I will encounter in my future career as an engineer.
NSPP6325 – Integrated Design and Manufacturing - This course introduced me to a process
approach to engineering design, manufacturing, and service applications. Models, modeling
tools, solution approaches, and methodologies for analysis and improvement of processes,
including the product development and manufacturing processes were discussed. The science of
process modeling and analysis was illustrated with case studies – which appears to have some
similarities with the layout of System Testing and Reliability.
NSYS6120 – Systems Engineering and Analysis - This course introduced me to an organized
multidisciplinary approach to designing and developing systems. I was able to explore concepts,
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2. Graduate Work – Systems Engineering
Lynn Coupal
principles, and practices of systems engineering as applied to large integrated systems.
Discussion topics included requirements development, life-cycle costing, scheduling, risk
management, functional analysis, conceptual and preliminary design, testing and evaluation,
optimization, and modeling. This time, the approach is where the similarity lies with System
Testing and Reliability.
NSYS6140 – Systems Optimization and Analysis - This course introduced me to the theory and
practice of optimal system design as an element of the engineering design process. I learned how
to apply optimization as a tool in the various stages of product realization and management of
engineering and manufacturing activities. The course stressed the importance of application of
nonlinear programming methods. Topics included optimality criteria, gradient- and nongradient-
based unconstrained methods, and modern nonlinear programming methods such as penalty
functions, method of multipliers, generalized reduced gradient, and successive quadratic
programming. Special attention was given to large structured problems that naturally occur in
engineering practice. We were exposed to modern optimization software (e.g., OPTLIB, OPT,
BIAS) and extensive comparative results. Examples were cited from mechanical, electrical, civil,
and chemical engineering, as well as from engineering management. There was quite a lot of
mathematical formulation involved.
NSYS6160 – Systems Engineering Management - This course provided me the necessary
techniques for planning and controlling systems, including evaluating the schedule and
operational effectiveness of systems management strategies. Performance measurement, work
breakdown structures, cost estimating, and quality management were discussed. This course also
briefly covered configuration management, standards, and case studies of systems from different
applications areas. The employment of case studies is a commonality amongst many of the
courses.
NSYS6163 – Integrated Risk Management - This course provided an introduction to the theory
and methodology of risk management in the context of systems engineering. It addressed topics
including risk identification, risk ranking and filtering, performance metrics, event and fault
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3. Graduate Work – Systems Engineering
Lynn Coupal
trees, theory of extreme values, decisions on extreme events, combinatorial optimization,
systems configuration, network modeling, and system interdependencies. Knowledge of
probability and statistics was assumed. Once again, there is a commonality with the mathematics
involved.
NMGT8750 - Total Quality Management and Improvement - This course provided a historical
overview and a fundamental understanding of the subject including: statistical thinking, the 7
basic tools, quality systems, managing operations for quality, product quality, process quality,
customer satisfaction, the role of quality as a competitive tool, critical elements that differentiate
high performing organizations from their competitors, the quality improvement process and how
organizations deliver ever-improving value to customers, Daily Work Management, Quality
Function Deployment, Six Sigma, the psychology of quality, and managing people in a quality
environment.
NMBA6130 - Leadership and Teamwork - This course provided an overview of leadership and
teamwork with an emphasis on how leaders and teams manage change in a dynamic technology
and business environment. The course was structured into four broad modules: Level-Three
Leadership, Creating and Sustaining Collaboration, Leading in the New Workplace, and Leading
Change. In each module, I considered various frameworks and perspectives, and applied them to
case studies and other examples. By engaging with the class and its online learning community, I
gained critical expertise in navigating this new leadership landscape.
NMBA6313 - Supply Chain Management - This course provided a simulation to try to achieve a
strategic advantage that was required for effective design and integration of multiple players and
activities throughout the supply chain. I gained an understanding of the definition and scope of
supply chain management and an appreciation of the potential for businesses to improve bottom-
line performance through an integrated, strategic approach to the management of supply chains.
Managing the simulation gave a basic understanding of the roles of the various entities in
managing the supply chain, the interrelatedness of critical activities, and a strategic view of the
importance of supply chain management. The LINKS Supply Chain Management Simulation
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4. Graduate Work – Systems Engineering
Lynn Coupal
provided me with hands-on experience with the cross-functional impact of supply chain
decision-making: analyzing complex data; evaluating the costs and benefits of cross-functional
trade-offs; making critical supply chain decisions; evaluating the consequences of those
decisions; and working to continuously improve based on experience.
NSYS6152 - System Testing and Reliability - This course provided classical techniques and
concepts necessary for evaluating the long-term and short-term reliability of engineering
systems. Strategies were explored for integrating, testing, and validating products and systems.
This course provided an in-depth coverage of tasks, processes, methods, and techniques for
achieving, testing, and maintaining the required level of system reliability considering
operational performance, customer satisfaction, and affordability. Specific topics included the
integration of established system requirements, establishing system reliability requirements,
reliability program planning, system reliability modeling and analysis, system reliability design
guidelines and analysis, system reliability test and evaluation, verification and validation of a
system, and the maintenance of inherent system reliability during production and operation.
NEEC6501- Random Processes for Engineering Applications - This course provided a
background on communication systems and computer networks and how they are designed to
provide high performance consistently and reliably in the presence of noisy communication
channels; equipment faults; a wide range of media applications that combine voice, images and
video; and high variability in user demand. Probability models provided the mathematical
framework for characterizing random variability and formed the basis for tools to design systems
that perform predictably in the face of random inputs and environments. The concept of a
random variable and its characterization using a probability distribution function and associated
moments was reviewed. The focus was on characterizing the joint behavior of multiple random
variables to understand their interdependence and to enable prediction of likely outcomes. The
joint distribution function as well as the correlation and the covariance functions were essential
tools in achieving these objectives. Random processes described signals and dynamic behavior
encountered in engineering systems. The utility of probability models was demonstrated through
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5. Graduate Work – Systems Engineering
Lynn Coupal
applications in communication systems, reliability, digital signal processing, and
communications networks.
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