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System Trade Study Matrix for Component Selection

Introduction

In any engineering project, selecting the right components is crucial. A System Trade Study Matrix offers a systematic approach to making informed decisions based on multiple evaluation criteria. This article explores what a System Trade Study Matrix is, why it's important, and how to construct one.

What is a System Trade Study Matrix?

A System Trade Study Matrix is a tabular representation that helps in evaluating different components based on various metrics or criteria. It is particularly useful when the selection involves multiple conflicting requirements.

Diagram 1: Basic Structure of a System Trade Study Matrix

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Component A | ... | ... | ... | ... |

Component B | ... | ... | ... | ... |

. | ... | ... | ... | ... |

Component Z | ... | ... | ... | ... |

Why is it Important?

Objective Evaluation: It quantifies subjective criteria, offering an objective basis for selection.
Comprehensive Overview: It provides a snapshot of how different components compare.
Risk Mitigation: By considering various criteria, it helps in identifying and mitigating potential risks.

How to Construct a System Trade Study Matrix

Step 1: Identify Components

List down all the potential components that can be used in the system.

Step 2: Determine Evaluation Criteria

Identify the metrics or criteria based on which the components will be evaluated. These can include cost, performance, reliability, etc.

Step 3: Assign Weights to Criteria

Not all criteria are equally important. Assign weights to them according to their relevance in your project.

Step 4: Evaluate Components

For each component, give a score based on each criterion.

Step 5: Calculate Weighted Scores

Multiply the score of each criterion by its weight and sum these up for each component.

Diagram 2: Weighted System Trade Study Matrix

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Component A | ... | ... | ... | ... | ... |

Component B | ... | ... | ... | ... | ... |

. | ... | ... | ... | ... | ... |

Component Z | ... | ... | ... | ... | ... |

Practical Example on Selecting low-power MCU for IOT device

We are still tasked with selecting a microcontroller for a low-power IoT device. This time, we'll consider not only the technical specifications but also project management factors such as schedule risk.

Criteria for Evaluation

Cost: Total cost including the MCU itself and any required peripherals.
Power Consumption: Average power usage in operation and idle modes.
Area: Physical dimensions, as the device has limited space.
Schedule Risk: Risk of delays, based on factors like availability and community support.
Speed: core clock speed of a MCU is a good indicator for compute performance evaluation.

Assigning Weights

For this example, let's use the following weights:

Cost: 0.25
Power Consumption: 0.25
Area: 0.15
Schedule Risk: 0.15 [Higher score => Lower Risk]
Speed: 0.2

System Trade Study Matrix

Here's how our initial matrix might look:

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MCU Option A | 7 | 9 | 6 | 5 | 8 |

MCU Option B | 5 | 8 | 9 | 7 | 7 |

MCU Option C | 6 | 7 | 8 | 8 | 9 |

Calculating Weighted Scores

To calculate the weighted scores, we'll multiply each score by its respective weight:

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MCU Option A | 1.75 | 2.25 | 0.9 | 0.75 | 1.6 | 7.25 |

MCU Option B | 1.25 | 2.0 | 1.35 | 1.05 | 1.4 | 7.05 |

MCU Option C | 1.5 | 1.75 | 1.2 | 1.2 | 1.8 | 7.45 |

Conclusion and Selection

Upon evaluating the weighted scores, we choose MCU Option C because for it is best suitable for realtime and low power IOT device. However MCU Option A has slightly lower scores, additional factors such as vendor relationships or future scalability could be considered for the final decision.

Summary and Conclusion

Conceptual Foundation: The article introduced the System Trade Study Matrix as a tool for objective evaluation of multiple engineering components.
Key Criteria: Discussed the importance of selecting the right evaluation metrics or criteria, such as cost, power consumption, area, and schedule risk.
Weight Assignment: Emphasized the need to assign weights to criteria based on their relative importance in the project.
Practical Example: Demonstrated the matrix's utility through a real-world example of selecting a microcontroller for an IoT device, incorporating both technical and project management criteria.
Weighted Scoring: Explained the calculation of weighted scores to arrive at a final decision, showing how the matrix helps in making a well-informed selection.
Tie-breakers: Addressed situations where multiple options score equally, suggesting the need for additional criteria or dialogue for final decision-making.

The System Trade Study Matrix stands as an essential framework for making informed decisions, offering a balanced perspective that is crucial for anyone involved in complex engineering projects.

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