Page 273 - Mechanical Engineers' Handbook (Volume 2)

264 Analysis, Design, and Information Processing

We could also associate feedback and learning steps to interconnect these steps one to an-
other. The systems process is typically very iterative. We shall not explicitly show feedback
and learning in our conceptual models of the systems process, although it is ideally always
there.
Here we have described a three-dimensional morphology of systems engineering. There
are a number of systems engineering morphologies or frameworks. In many of these, the
logic dimension is divided into a larger number of steps that are iterative in nature. A
particular seven-step framework, due to Hall, 5,6 involves:

1. Problem definition, in which a descriptive and normative scenario of needs, con-
straints, and alterables associated with an issue is developed. Problem definition
clarifies the issues under consideration to allow other steps of a systems engineering
effort to be carried out.
2. Value system design, in which objectives and objectives measures or attributes with
which to determine success in achieving objectives are determined. Also, the inter-
relationship between objectives and objectives measures and the interaction between
objectives and the elements in the problem definition step are determined. This es-
tablishes a measurement framework, which is needed to establish the extent to which
the impacts of proposed policies or decisions will achieve objectives.
3. System synthesis, in which candidate or alternative decisions, hypotheses, options,
policies, or systems that might result in needs satisfaction and objective attainment
are postulated.
4. Systems analysis and modeling, in which models are constructed to allow determi-
nation of the consequences of pursuing policies. Systems analysis and modeling
determine the behavior or subsequent conditions resulting from alternative policies
and systems. Forecasting and impact analysis are, therefore, the most important ob-
jectives of systems analysis and modeling.
5. Optimization or refinement of each alternative, in which the individual policies and/
or systems are tuned, often by means of parameter adjustment methods, so that each
individual policy or system is refined in some ‘‘best’’ fashion in accordance with the
value system that has been identified earlier.
6. Evaluation and decision making, in which systems and/or policies and/or alterna-
tives are evaluated in terms of the extent to which the impacts of the alternatives
achieve objectives and satisfy needs. Needed to accomplish evaluation are the attri-
butes of the impacts of proposed policies and associated objective and/or subjective
measurement of attribute satisfaction for each proposed alternative. Often this results
in a prioritization of alternatives, with one or more being selected for further planning
and resource allocation.
7. Planning for action, in which implementation efforts, resource and management al-
locations, or plans for the next phase of a systems engineering effort are delineated.

More often than not, the information required to accomplish these seven steps is not perfect
due to information uncertainty, imprecision, or incompleteness effects. This presents a major
challenge to the design of processes and for systems engineering practice as well.
Figure 4 illustrates a not-untypical 49-element morphological box for systems engi-
neering. This is obtained by expanding our initial three systems engineering steps of for-
mulation, analysis, and interpretation to the seven just discussed. The three basic phases of
definition, development, and deployment are expanded to a total of seven phases. These
seven steps, and the seven phases that we associate with them, are essentially those identified