Systems Engineering and Design

DURATION: THREE DAYS
COURSE NO.: 1160

This course focuses on the theory of engineering design. Reduced to its simplest form, engineering design consists of generating design options and selecting the preferred option. But, simple as these steps may sound, they are very complex. Few engineers learn how to think in a systems context that is conducive to option generation, and fewer still are taught formal approaches for comparison of options. Further, while uncertainty and risk pervade all of engineering design, virtually no formal treatment is given to methods from related disciplines to the valuation and comparison of design options. Topics of study include engineering microeconomics, forecasting, utility theory, reliability analysis, decision analysis, probability theory, system modeling and Monte Carlo simulation. Implications will be drawn to program management.

COURSE MATERIALS:
Each attendee will receive a copy of the instructors book, Systems Engineering: An Approach to Information-Based Design, along with extensive notes and reference materials.

This course will be valuable for anyone who does engineering design, but particularly for people who want to manage engineering design, perform systems engineering, evaluate system alternatives, or perform engineering systems studies. For senior managers, the course will provide new insights and methods of squeezing additional value from engineering designs. For engineers beginning their careers, the course will broaden their knowledge base and expand their horizons. The deep theoretical understanding of engineering design that the course provides is also useful to engineering managers and in the management of technology.

Engineering design can be viewed and analyzed as a decision-making process. How to approach engineering design as an opportunity for expression of creativity rather than as a process bound to the satisfaction of constraints. Engineering designs include both physical and nonphysical design choices, and nonphysical choices can be very important to the system performance and cost. Methods for finding nonphysical system alternatives. The objectives of engineering design and methods for determining the worth of a system design. Methods for the estimation and treatment of uncertainty and risk in engineering analysis and design. The theory of system worth functions and methods for the evaluation of system worth and comparison of alternatives under conditions of uncertainty and risk. Decision theory applied to design choices and the need for sequential decision making in complex programs. The phases in the life cycle of an engineering system and how each can be modeled. How competition affects engineering design.

1. Principles and Elements of Systems Engineering and Design.
   

   Fundamentals of engineering design and systems engineering from the point of view that design is a decision-making process guided by information. The three essential elements of decision making are reviewed. Eight axioms of design and their application are presented. It is shown that failure to acknowledge these axioms and stay within the framework they impose can result in substantial loss and that ad hoc methods in common use, such as Quality Function Deployment, can give misleading results. Rigorous methods for the comparison of design and system options are developed, with application to conceptual design. A method for evaluation and comparison of options under uncertainty and risk is presented. Proper use of the techniques presented can lead to gains typically on the order of a doubling of project profitability. Topics include: The concept of engineering design as a decision-making process. Axioms that guide design decision making and comparison of system alternatives. Three key theorems of decision making. Principles of probability theory for systems engineering and engineering design. Concepts of uncertainty in engineering models. Concepts of value and utility for comparison of system alternatives. Decision theory, the method of backward induction. Arrows impossibility theorem and its implications to optimal engineering design. Monte Carlo modeling for engineering systems. The role and principles of optimization in engineering design. Forecasting for engineering design. Concepts of engineering systems modeling. Modeling systems operation.

2. Application of Systems Engineering and Design.
   

   How to compare system alternatives in the presence of uncertainty and risk. You will learn how to incorporate uncertainty explicitly in system models how to create valid measures of system worth, including measures of system worth that are valid under conditions of uncertainty and risk how to make wise system choices based on comparison of alternatives in terms of measures of worth how to recognize and quantify risk in various design alternatives how to control risk how to avoid the pitfalls of system design and optimization that almost all engineers fall prey to.