Research tools for design margins

MARVIN

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.

Open tool References
Module 2 · MARVIN

Margin Deployment Cascading

Allocate margins top-down, from stakeholder needs through requirements and architecture down to design parameters, using a chain of QFD-inspired matrices.

Overview

Margins are usually decided locally at design parameter level — an extra millimetre of clearance, a slightly larger pump, an additional safety factor. The reason for those margins lives further up: a stakeholder need, a requirement, an architectural choice. Margin Deployment Cascading makes that vertical link explicit.

The module borrows the cascading idea from Quality Function Deployment (QFD): the outputs of one matrix become the inputs of the next, so allocations made at one level of abstraction propagate and refine at the level below. Margins follow the same chain.

The cascade

Each matrix in the cascade relates two levels of abstraction. The output of one matrix — the prioritised items on its bottom edge — becomes the input of the next.

  1. Stakeholder needs → requirements Translate stakeholder needs (the “voice of the customer”) into measurable system requirements, with weights that reflect their relative importance.
  2. Requirements → architecture Map weighted requirements onto the architectural elements (subsystems, functional blocks) that contribute to satisfying them.
  3. Architecture → design parameters Decompose architectural-level allocations into the design parameters that engineers actually set, producing target margins on each parameter.

Key features

What the module gives you on top of pen-and-paper QFD.

Linked matrices

Edits at one level automatically update inputs at the next, so the cascade stays consistent without manual copy-paste between sheets.

Margin allocation

Each cell in a relationship matrix can carry a contribution weight; the module rolls these up to give a target margin on every design parameter.

House-of-quality view

For each pair of levels, optionally view the relationship matrix in classic house-of-quality form, with correlation triangle on top.

Sankey overview

Flow diagram from stakeholder needs to design parameters, so you can read off where any given margin allocation came from at a glance.

Where it fits

This module is most useful early in the design, before there is a parametric model that Margin Value Analysis can act on.

Use the cascade to set where margins should live and how big they should be at each level of abstraction. Once parametric models become available, the targets produced here become the requirements that Margin Value Analysis evaluates against, closing the loop between top-down allocation and bottom-up valuation.