Research tools for analysing design margins in complex engineered systems
Three integrated modules — parametric margin valuation, top-down margin allocation, and probabilistic margin risk — built around the Margin Value Method.
A step-by-step walkthrough of building a DSM, running CPM, and reading the combined-risk results.
This tutorial walks through a full Probabilistic Margin Analysis on a simple worked example: a six-subsystem fan system, where a redesign in any subsystem may propagate to others through their interfaces.
You only need a modern web browser. The module runs entirely client-side; no installation is required.
Open the DSM editor and add the components of your system as rows/columns. Optionally group them into subsystems for cleaner readability and faster editing.
For each ordered pair of components, enter the probability that a change in the source will require a change in the target. Use a coarse 0–1 scale (e.g. 0.1, 0.3, 0.7, 0.9) elicited from designers' judgement — the CPM is robust to ordinal-style inputs.
For each pair, enter the average severity of the propagated change — how much redesign work the target component would require if the change reached it. Same coarse scale.
Click the analysis button. The module composes direct probabilities along all paths between every pair of components and produces three derived matrices: combined likelihood, combined impact, and combined risk.
Click on any component to see its incoming and outgoing risk profile. Components with high outgoing risk are sources of propagation; components with high incoming risk are absorbers — both can guide where to invest in margins or in interface decoupling.
Edit a direct value, decouple a pair, or insert an interface buffer, and watch the combined-risk matrix update live. Use this to test design decisions before committing to them.