Deposition & etch equipment
The machines that build a chip layer by layer — laying thin films down (deposition) and carving them away (etch). Three companies dominate the market.
Ranks moderate (58/100) — set apart by structural importance (78) and strategic relevance (78).
Why it matters
Every new fab and every node transition needs thousands of deposition and etch chambers installed and qualified; they are the bulk of fab capex after lithography.
Why now
Wafer-fab-equipment spending is at record levels — SEMI forecasts ~$116B in 2025 growing toward ~$135B by 2027 — driven by AI logic and HBM-related memory investment, with etch intensity rising as chips go 3D.
If Deposition & etch equipment runs short
Export-control expansion or an order collapse at the big three stalls fab ramps — and shows up in their guidance before it shows anywhere else in the chain.
In depth · editorial + model
Deposition and etch machines build a chip layer by layer — laying thin films down, then carving them away with atomic precision, hundreds of process steps for every advanced wafer. That step count makes these tools the volume backbone of wafer-fab-equipment spending, a market running at record levels as AI logic and high-bandwidth memory investment push fabs to buy more of them per line. Three companies dominate the category — Applied Materials, Lam Research and Tokyo Electron — an allied-nation oligopoly whose segment shares shift between film types but whose collective grip does not. As chips go three-dimensional, with stacked memory and new transistor architectures, etch intensity per wafer keeps rising and the dependence deepens.
Because fabs order these tools years before capacity comes online, the big three's order books are the cleanest leading indicator of the global buildout — trouble shows up in their guidance before it shows up anywhere else in the chain. An export-control expansion or a demand collapse at the top three stalls fab ramps worldwide; there is no meaningful second tier to absorb the volume. The exposure is direct: Applied Materials, Lam Research and Tokyo Electron on the supply side, with TSMC, Samsung and Intel as the buyers whose expansion plans ride on delivery schedules.
Who makes Deposition & etch equipment
The companies exposed to Deposition & etch equipment
How to think about it
- Oligopoly toll booth on every fab
- Equipment orders lead capacity by years
What to watch
- SEMI WFE forecasts and revisions
- China share of tool shipments under export rules
- Etch-intensity growth from 3D NAND and HBM stacking
- Applied Materials / Lam / TEL order books and guidance
Key figures
Frequently asked
What is Deposition & etch equipment?
The machines that build a chip layer by layer — laying thin films down (deposition) and carving them away (etch). Three companies dominate the market.
Why does Deposition & etch equipment matter for AI?
Every new fab and every node transition needs thousands of deposition and etch chambers installed and qualified; they are the bulk of fab capex after lithography.
Who makes Deposition & etch equipment?
The companies the model tags as producers or suppliers of Deposition & etch equipment: Applied Materials, Lam Research, Tokyo Electron.
Which companies are most exposed to Deposition & etch equipment?
Applied Materials, Lam Research, Tokyo Electron, TSMC, Samsung Electronics, Intel — 6 companies in total are mapped to Deposition & etch equipment.
What happens if Deposition & etch equipment runs short?
Export-control expansion or an order collapse at the big three stalls fab ramps — and shows up in their guidance before it shows anywhere else in the chain.
Where does Deposition & etch equipment sit in the AI value chain?
Deposition & etch equipment sits in the Chips layer of the AI value chain.
Go deeper on Deposition & etch equipment
- The materials, geographies and policies it depends on — heat-mapped
- Substitutes, relief valves and the domino chains if it tightens
- The live tension score, momentum and news drivers
- Four levels of analysis — from plain-English to strategic
model v0.7.0 · research, not advice
Model scores are illustrative reads from our model of the AI value chain — not investment advice.