Structured skill for conducting engineering trade studies and concept selection
Conducts structured engineering trade studies using weighted criteria and Pugh matrices to evaluate design alternatives.
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The Trade Study skill provides structured capabilities for conducting engineering trade studies and concept selection, enabling systematic evaluation of design alternatives against requirements.
| 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 |
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
| 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 |
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
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
| 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:
- 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 |
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
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)
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 |
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
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)
{
"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"
}
}
{
"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"
}
}
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