Agent skill

trade-study

Structured skill for conducting engineering trade studies and concept selection

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Forks 31

Install this agent skill to your Project

npx add-skill https://github.com/majiayu000/claude-skill-registry/tree/main/skills/data/trade-study

Metadata

Additional technical details for this skill

phase
7
domain
science
category
design-development
priority
medium
specialization
mechanical-engineering
tools libraries
[
    "Decision analysis tools",
    "MATLAB",
    "Spreadsheets"
]

SKILL.md

Trade Study Skill

Purpose

The Trade Study skill provides structured capabilities for conducting engineering trade studies and concept selection, enabling systematic evaluation of design alternatives against requirements.

Capabilities

  • Trade study framework setup
  • Evaluation criteria definition and weighting
  • Concept generation support
  • Pugh matrix implementation
  • Quantitative scoring methods
  • Sensitivity analysis
  • Decision documentation
  • Stakeholder consensus building

Usage Guidelines

Trade Study Framework

Trade Study Types

Type Application Complexity
Screening Eliminate non-viable options Low
Pugh matrix Comparative evaluation Medium
Weighted scoring Quantitative ranking Medium
Multi-attribute utility Complex decisions High
Optimization Parameter selection High

Process Overview

1. Define objectives and scope
2. Establish evaluation criteria
3. Generate alternatives
4. Collect data for each alternative
5. Score alternatives against criteria
6. Analyze results and sensitivity
7. Make recommendation
8. Document decision

Criteria Development

Criteria Categories

Category Example Criteria
Performance Power output, efficiency, accuracy
Physical Size, weight, volume
Cost Development cost, unit cost, life cycle cost
Schedule Development time, lead time
Risk Technical risk, schedule risk, cost risk
Manufacturability Complexity, process capability
Reliability MTBF, failure modes, redundancy
Maintainability Access, service intervals, spares

Criteria Weighting

Methods for weight assignment:

1. Direct assignment
   - Assign percentages directly
   - Total must equal 100%

2. Pairwise comparison
   - Compare each pair of criteria
   - Calculate weights from preferences

3. Swing weighting
   - Consider range of performance
   - Assign weights based on swing importance

4. AHP (Analytic Hierarchy Process)
   - Structured pairwise comparison
   - Consistency check included

Concept Generation

Brainstorming Guidelines

1. Define the function to be achieved
2. Generate alternatives without judgment
3. Consider:
   - Prior art and benchmarks
   - Different technologies
   - Component variations
   - Configuration options
4. Combine and refine ideas
5. Screen for feasibility

Concept Representation

Method Detail Level Use
Sketch Low Initial brainstorm
Block diagram Low-Medium Functional layout
Layout drawing Medium Spatial arrangement
CAD model High Detailed evaluation

Pugh Matrix Method

Matrix Setup

Pugh Matrix:
- Rows: Evaluation criteria
- Columns: Concept alternatives
- Datum: Baseline or best-known solution
- Scoring: + (better), - (worse), S (same)

| Criteria | Weight | Datum | Alt-A | Alt-B | Alt-C |
|----------|--------|-------|-------|-------|-------|
| Crit 1   | 0.30   | 0     | +     | -     | S     |
| Crit 2   | 0.25   | 0     | S     | +     | +     |
| Crit 3   | 0.20   | 0     | -     | +     | +     |
| Crit 4   | 0.15   | 0     | +     | S     | -     |
| Crit 5   | 0.10   | 0     | S     | +     | S     |

Results Analysis

Calculate for each alternative:
- Sum of positives
- Sum of negatives
- Weighted sum of positives
- Weighted sum of negatives
- Net score

Use results to:
- Eliminate weak concepts
- Identify best features
- Create hybrid concepts
- Iterate evaluation

Weighted Scoring Method

Scoring Scale

Example 5-point scale:
5 = Excellent, exceeds requirements significantly
4 = Good, exceeds requirements
3 = Acceptable, meets requirements
2 = Marginal, partially meets requirements
1 = Poor, does not meet requirements
0 = Unacceptable, disqualifying

Or numerical scale tied to requirements:
Score = (Performance - Threshold) / (Goal - Threshold)

Weighted Score Calculation

Total Score = Sum(Weight_i x Score_i)

Example:
| Criteria | Weight | Alt-A Score | Alt-A Weighted |
|----------|--------|-------------|----------------|
| Crit 1   | 0.30   | 4           | 1.20           |
| Crit 2   | 0.25   | 3           | 0.75           |
| Crit 3   | 0.20   | 5           | 1.00           |
| Crit 4   | 0.15   | 3           | 0.45           |
| Crit 5   | 0.10   | 4           | 0.40           |
| Total    | 1.00   |             | 3.80           |

Sensitivity Analysis

Analysis Methods

1. Weight sensitivity
   - Vary weights +/- 10-20%
   - Identify crossover points
   - Determine robust winner

2. Score sensitivity
   - Vary scores +/- 1 point
   - Consider uncertainty in data
   - Identify close decisions

3. Tornado diagram
   - Show impact of each factor
   - Prioritize data improvement

Decision Documentation

Trade Study Report

Required sections:
1. Executive summary
2. Objectives and scope
3. Evaluation criteria and weights
4. Alternatives description
5. Data sources and assumptions
6. Scoring rationale
7. Results and analysis
8. Sensitivity analysis
9. Recommendation
10. Appendices (detailed data)

Process Integration

  • ME-002: Conceptual Design Trade Study

Input Schema

json
{
  "study_objective": "string",
  "scope": {
    "system": "string",
    "decision_type": "concept|configuration|supplier|technology"
  },
  "requirements": "array of requirement references",
  "alternatives": [
    {
      "name": "string",
      "description": "string",
      "data_sources": "array"
    }
  ],
  "stakeholders": "array of reviewers",
  "constraints": {
    "budget": "number",
    "schedule": "string",
    "must_meet": "array of requirements"
  }
}

Output Schema

json
{
  "trade_study_report": {
    "document_number": "string",
    "revision": "string"
  },
  "criteria": [
    {
      "name": "string",
      "weight": "number",
      "rationale": "string"
    }
  ],
  "results": {
    "scoring_matrix": "2D array",
    "weighted_scores": "array",
    "ranking": "array"
  },
  "sensitivity_analysis": {
    "robust_criteria": "array",
    "sensitive_criteria": "array",
    "crossover_points": "array"
  },
  "recommendation": {
    "selected_alternative": "string",
    "rationale": "string",
    "risks": "array",
    "next_steps": "array"
  }
}

Best Practices

  1. Define clear objectives before starting
  2. Include diverse stakeholder perspectives
  3. Document all assumptions and data sources
  4. Use consistent scoring across alternatives
  5. Perform sensitivity analysis on close decisions
  6. Get stakeholder buy-in on recommendation

Integration Points

  • Connects with Requirements Flowdown for evaluation criteria
  • Feeds into CAD Modeling for selected concept
  • Supports Design Review for decision documentation
  • Integrates with Risk assessment for technical risks

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