Human augmentation technologies are transforming healthcare,rehabilitation, industrial ergonomics, assistive living, sports, and personal mobility by improving human capabilities and enhancing quality of life.
Autodesk · MedTech / BioTech / HealthTech · Hardware
The CAD is the easy half and the CAM is the assignment — without a team member who understands machining strategy and can defend a process choice, this is not winnable, and mechanical students will be doing it from coursework.
What it actually is
Exoskeletons, prosthetics and assistive devices extend what a body can do. The ask is to design one of your choosing in Autodesk Fusion, then take a single critical component from it all the way through a machining workflow to G-code. The manufacturing half is the real assignment — this tests CAM knowledge as much as design.
What to build
A complete Fusion assembly of a human augmentation device — an exoskeleton joint, a prosthetic component, a rehabilitation mechanism or a wearable assistive support — from which one critical mechanical component is identified and justified as manufacturable by either three-axis CNC milling or two-axis CNC turning, then carried through the full digital manufacturing chain in Fusion: manufacturing setup, tool selection, toolpath generation, machining simulation, toolpath optimisation and G-code output, presented with assembled and exploded renders and a six-to-eight slide deck.
Smallest thing that wins the room
Show the assembled device, isolate the chosen component and explain why its geometry suits turning rather than milling, then run the machining simulation and show the optimised toolpath with the cycle time reduction and the generated G-code.
How crowded this one gets
A guess, projected from the 2025 statements — the last year where both the submission counts and the winners were published.
Quieter than 86% of the 226 · #33 of 226 by expected field
Few teams are likely to go here. The best odds on the board come from statements like this.
Why: company-sponsored statements drew the smallest fields of all; hardware halves the field a software statement gets.
This is a guess, not a fact
Nobody has published 2026’s numbers yet. This is an analysed estimate from last year’s pattern, so please do not take it as the truth — check the live counter on the SIH portal before you decide anything. The range covers the middle half of likely outcomes, so one statement in two lands outside it. Entry closes at 500 ideas per statement, so no range goes past that — a statement that reaches the cap fills and shuts rather than drawing an unlimited crowd. The model reads only three things a team can see before choosing — software or hardware, the theme, and what kind of body posted it — and those explain about a quarter of the variation in last year’s field sizes (R² 0.25 on held-out statements). Trust the band more than the number, and the ordering more than either. It cannot see how good your idea is, which is the part that actually decides it.
The scores
The number is the shorthand. The line under it is the reason.
Acceptance potential
2/5The CAM requirement is a hard skill gate — justifying why a component suits three-axis milling over turning and optimising a toolpath is manufacturing engineering, and a software team attempting it will be transparently out of its depth beside mechanical students.
Feasibility
2/5The design half is approachable but the CAM half is not — manufacturing setup, tool selection, toolpath strategy and machining simulation are specialist skills taught in mechanical manufacturing courses, and a team without that background cannot produce a defensible workflow.
Innovation scope
4/5The device itself is entirely your choice across six named application areas, so the concept is wide open even though the manufacturing workflow that follows is prescribed step by step.
Clarity
5/5The Expected Outcomes section enumerates every required deliverable from the CAD model through justification, machining strategy, simulation, optimisation and renders, leaving nothing about the submission ambiguous.
Effort
HeavyA full device assembly plus a complete CAM workflow with simulation and optimisation is two distinct bodies of work, and the CAM half has a steep learning curve if it is new to you.
Demo-ability
MediumMachining simulation is genuinely satisfying to watch and renders present well, but the judging is on manufacturing sophistication in a deck rather than on a working device.
In its favour
- Green flag: The application area is completely open, so you can choose a device that matches whatever domain knowledge your team already has
- Green flag: Fusion integrates CAD and CAM in one tool, so the workflow is learnable end to end without switching software
- Green flag: Machining simulation gives you a quantitative optimisation result — cycle time or tool load reduced — which is concrete evidence rather than an aesthetic claim
- Green flag: Assistive and rehabilitation devices carry an easy, sincere impact narrative
Against it
- Red flag: The core assignment is CAM, not design — you must justify a manufacturing process choice and optimise a toolpath, which is specialist knowledge a software team does not have
- Red flag: Choosing a component that is not genuinely manufacturable by the stated processes undermines the entire submission, and that judgement requires manufacturing experience to get right
- Red flag: AI-generated content is explicitly prohibited and only Fusion may be used, closing off the usual shortcuts
- Red flag: Medical and assistive devices invite questions about biomechanical loading and fit that a purely CAD-driven concept cannot answer
What you will be writing
- Autodesk Fusion CAD + CAM (mandatory)
- 3-axis milling / 2-axis turning toolpath strategies
- Machining simulation and collision checking
- Tool library selection and feeds-and-speeds
- G-code post-processing
- Rendered assembled and exploded views
- Assistive device design
- Computer-aided manufacturing
- Mechanical engineering
Prior art to read before you start
human augmentation device design · CNC machining workflow development · design for manufacturability
Analysed by Claude Opus. Every score above is a judgment call with its reasoning attached — kindly cross-check this against the official statement on the SIH portal before your team commits to it.