Aerospace and Electronic Systems Magazine February 2018 - 43

Ahmadi, Kosari, and Malaek

Figure 5.

The cubesat passive optical payload design structure matrix.

mance and DPs. Complementary parameters are aligned such that
increasing the value of one increases the value of the other whereas
competing parameters demonstrate the converse of this situation.
Neutral parameters are uncorrelated [24].
Here the uncorrelated DPs are removed and the resulting correlation between PP and the corresponding DPs should be formulated. In order to formulate the relationship between a PP and the
corresponding DPs, fuzzy logic and the Sugeno inference approach
can be applied [25].
Each of the developed formulas should be examined looking
for possible hidden parameters. Hidden parameters are factors affecting more than one PP or may appear in more than one formula.

Step 6. Identification of system MDPs.
After extracting a formula which could define a PP based on the
corresponding DPs, the MDPs should be identified. Other than the
two principal properties of the DPs, the main ones have four additional properties that make them distinguishable from the others.
The MDPs have the strongest effect on system performance; they
are independent of each other. Other DPs are dependent on them,
and they are the output of sizing and the input of the next phase.
Based on this definition, each of the DPs in the extracted formula
should be examined. The final goal is to select the three MDPs
FEBRUARY 2018

among the DPs identified in the previous step. These parameters
can be named as follows:
C

One DP of Information (I);

C

One DP of Energy (E);

C

One DP of Matter (M).

To do this, at first, all the PPs and DPs should be arranged in
the form of a parameter-based design structure matrix according
to Figure 5 [26]. The arrangement of the parameters in this form
requires determining their category that must be done in this step.
The relations between PPs and DPs have been identified based on
an Excel code that has been developed and published in [1].
Removal of the dependent parameters must be based on one of
the following criteria:
C

The number of times that the parameter appears in different
formulas;

C

Sensitivity analysis;

C

The physical nature of the problem;

C

The underlying logic of the process

C

The simplicity of calculations.

IEEE A&E SYSTEMS MAGAZINE

43



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