Alternatives and feasibility

Why this matters

Most teams choose their concept on day one and spend the rest of the time finding reasons to support it. A systematic comparison of alternatives forces the question “is there a better way?” and records why the concept was chosen, which project examiners always ask. UAT 316 covered cost analysis and weighted decision matrices. This module uses a tool suited to the concept stage, when detailed data does not yet exist: the Pugh matrix.

Generating genuinely different alternatives

For the canal inspection problem the team sketched four concepts:

• A (datum) a multirotor flown manually, images reviewed by people
• B a multirotor flying automatic waypoints, with AI finding the damage
• C a VTOL drone flying automatically over a longer range, images reviewed by people
• D fixed cameras installed along the canal

Concept D is not a drone at all. Including a different kind of alternative checks whether a drone really is the right answer.

The Pugh matrix

Pugh concept selection (Pugh, 1991) compares each concept with a datum one criterion at a time: better scores +, worse scores −, the same scores S. It suits the concept stage because it does not need detailed numbers that are not yet available.

criteria = ["survey time", "detection quality", "covers all 2 km", "cost", "ease of permission",
            "weather tolerance", "skill needed", "safety"]
scores = {  # +1 better than A, 0 same, -1 worse
    "B": [1, 1, 0, -1, 0, 0, 1, 1],
    "C": [1, 0, 0, -1, -1, 1, 0, 0],
    "D": [1, -1, -1, -1, 1, 1, 1, 1],
}
for name, s in scores.items():
    plus, minus = s.count(1), s.count(-1)
    weak = [c for c, v in zip(criteria, s) if v < 0]
    print(f"{name}: +{plus} -{minus} net {plus - minus:+d}  weaknesses: {', '.join(weak)}")

B: +4 -1 net +3  weaknesses: cost
C: +2 -2 net +0  weaknesses: cost, ease of permission
D: +5 -3 net +2  weaknesses: detection quality, covers all 2 km, cost

Feasibility gates

A concept that looks good on paper may not be achievable. Pass it through the gates one at a time; if it fails a gate, change it or drop it.

• Technical: how mature is the technology (TRL), and can the team deliver it within one academic year?
• Regulatory: can it be flown under general conditions, or does it need a Specific authorisation? (see UAT 313 and the CAAT PDRA guidance)
• Cost: is it within the project budget? (life-cycle cost methods are in UAT 316)
• Schedule: can it be delivered in time for the next semester?
• Safety: can the risk to people and property be managed?

Module lab

Common mistakes

Summary

• Generate genuinely different alternatives, including non-drone options
• A Pugh matrix compares against a datum with + − S to expose weaknesses and improve concepts over several rounds
• A concept must pass the technical, regulatory, cost, schedule and safety gates
• The selection rationale must trace back to the requirements

Check your understanding

1. A concept scores five + and two −. What is its net score?
2. In a Pugh matrix, what does the datum score on every criterion?
3. Why is concept D eliminated even though its net score is positive?
4. After improving a concept, what does Pugh recommend?
5. Which gate checks whether a Specific flight authorisation is needed?