The hype is all about humanoid robots, but the constant winners are in the background.
I have divided the analysis into two perspectives. 1. the complete value chain of humanoid robots, which shows all the players from the chip to the finished robot, and 2. the blade manufacturers in the background, who always earn money as enablers, regardless of which manufacturer wins the race.
ASML, Applied Materials and Tokyo Electron dominate in manufacturing technology. Quality assurance comes from Keysight, Advantest and Teradyne. Chip design is supported by Synopsys, Cadence and ARM. Data streams are secured by Arista Networks, Cisco and Equinix. The computing basis is created in the cloud by Amazon, Microsoft and Alphabet. Albemarle, Lynas and Umicore play a central role in raw materials and battery materials. These companies monetize their customers' investment waves, have high barriers to entry, service revenues and pricing power, but remain cyclical with risks from export rules, capex cuts and currency movements.
🌐 Value chain of humanoid robots Sector overview
1. research & chip design (IP / EDA)
$ARM (-2,43 %)
ARM Holdings (ARM, UK/USA) - CPU architectures
$SNPS (-1,97 %)
Synopsys (SNPS, USA) - Chip design software
$CDNS (-0,69 %)
Cadence Design Systems (CDNS, USA) - EDA & Simulation
2. manufacturing technology & equipment
$ASML (+0,47 %)
ASML (ASML, NL) - EUV lithography, key monopoly
$AMAT (-0,84 %)
Applied Materials (AMAT, USA) - Process equipment
$8035 (-0,33 %)
Tokyo Electron (8035.T, JP) - Wafer equipment
$KEYS (-3,65 %)
Keysight Technologies (KEYS, USA) - Test & RF measurement technology
$6857 (-4,62 %)
Advantest (6857.T, JP) - Semiconductor test systems
$TER (-1,06 %)
Teradyne (TER, USA) - Test systems + robotics (Universal Robots)
3. chip production (Foundries)
$TSM (-1,82 %)
TSMC (TSM, TW) - Largest contract manufacturer
$005930
Samsung Electronics (005930.KQ, KR) - Memory + Foundry
$GFS (-1,05 %)
GlobalFoundries (GFS, USA) - Specialized production
4. computing & control unit ("brain")
$NVDA (-0,19 %)
Nvidia (NVDA, USA) - GPUs, AI accelerators
$INTC (-6,76 %)
Intel (INTC, USA) - CPUs, FPGAs
$AMD (-0,14 %)
AMD (AMD, USA) - CPUs/GPUs
$MRVL (-1,41 %)
Marvell Technology (MRVL, USA) - Network/data center chips
5. sensors ("senses")
$6758 (-0,95 %)
Sony (6758.T, JP) - CMOS image sensors
$6861 (-1,7 %)
Keyence (6861.T, JP) - Vision systems, sensors
$STM (+0,45 %)
STMicroelectronics (STM, CH/FR) - MEMS sensors
6. actuators & power electronics ("muscles")
$IFX (-1,29 %)
Infineon (IFX, DE) - Power semiconductors, SiC
$ON (-1,51 %)
N Semiconductor (ON, USA) - SiC/Power Chips
$STM (+0,45 %)
STMicroelectronics (STM, CH/FR) - Motor control & power
$TXN (+2,57 %)
Texas Instruments (TXN, USA) - Motor control, power ICs
$ADI (+6,03 %)
Analog Devices (ADI, USA) - Energy & BMS chips
7. communication & networking ("nerves")
$QCOM (-0,77 %)
Qualcomm (QCOM, USA) - 5G/SoCs
$AVGO (-1,35 %)
Broadcom (AVGO, USA) - Network & radio chips
$SWKS (+0,05 %)
Skyworks Solutions (SWKS, USA) - RF components
8. energy supply
$300750
CATL (300750.SZ, CN) - Batteries
$6752 (+0,27 %)
Panasonic (6752.T, JP) - Batteries for automotive/robotics
$373220
LG Energy Solution (373220.KQ, KR) - Batteries
9. cloud & infrastructure
$AMZN (-1,9 %)
Amazon (AMZN, USA) - AWS
$MSFT (-1,02 %)
Microsoft (MSFT, USA) - Azure
$GOOG (-1,29 %)
Alphabet (GOOGL, USA) - Google Cloud
$EQIX (+0,66 %)
Equinix (EQIX, USA) - Data center operator
$ANET (-1,07 %)
Arista Networks (ANET, USA) - Network infrastructure
$CSCO (+0,4 %)
Cisco Systems (CSCO, USA) - Edge & Data Center Networks
10. software & data platforms
$PLTR (+0,52 %)
Palantir (PLTR, USA) - Data integration, decision software
$DDOG (-0,44 %)
Datadog (DDOG, USA) - Cloud monitoring / observability
$SNOW (+0,92 %)
Snowflake (SNOW, USA) - Cloud-native data platform
$ORCL (+0,26 %)
Oracle (ORCL, USA) - Databases, ERP
$SAP (-0,83 %)
SAP (SAP, DE) - ERP/cloud systems
$PATH (-0,21 %)
UiPath (PATH, USA) - Automation software (RPA)
$AI (-2,41 %)
C3.ai (AI, USA) - Enterprise AI platform
11. end applications / robots
$ABB
ABB (ABB, CH) - Industrial robots
$6954 (-2,91 %)
Fanuc (6954.T, JP) - Industrial robots, CNC
$TSLA (-1,74 %)
Tesla (TSLA, USA) - Optimus" humanoid robot
$9618 (-0,22 %)
JD.com (JD, CN) - E-commerce & automated logistics
🛠️ Shovel manufacturer for humanoid robots
🔹 Hardtech (physical "shovels")
These companies provide the material basis: manufacturing machines, raw materials, semiconductor base.
Semiconductor Equipment & Manufacturing
$ASML (+0,47 %)
ASML (ASML, NL) - EUV lithography (monopoly).
$AMAT (-0,84 %)
Applied Materials (AMAT, USA) - Wafer equipment.
$8035 (-0,33 %)
Tokyo Electron (8035.T, JP) - Process equipment.
Test systems (hardware-side)
$6857 (-4,62 %)
Advantest (6857.T, JP) - Semiconductor test.
$TER (-1,06 %)
Teradyne (TER, USA) - Test systems + industrial robots.
Materials & raw materials
$ALB (-2,77 %)
Albemarle (ALB, USA) - Lithium (batteries).
$LYC (-9,74 %)
Lynas Rare Earths (LYC.AX, AUS) - Rare earths for magnets.
$UMICY (+0 %)
Umicore (UMI.BR, BE) - Cathode materials, recycling.
🔹 Soft/infra (digital "shovels")
These companies supply the infrastructure & toolswithout which development, training and operation would be impossible.
Design Software & IP
$SNPS (-1,97 %)
Synopsys (SNPS, USA) - EDA software.
$CDNS (-0,69 %)
Cadence Design Systems (CDNS, USA) - Chip design & simulation.
$ARM (-2,43 %)
ARM Holdings (ARM, UK/USA) - CPU architectures (license model).
Test & Measurement (software/signal level)
$KEYS (-3,65 %)
Keysight Technologies (KEYS, USA) - Electronics & RF test systems.
Network & data center backbone
$ANET (-1,07 %)
Arista Networks (ANET, USA) - High-speed networks.
$CSCO (+0,4 %)
Cisco Systems (CSCO, USA) - Data center/edge networks.
$EQIX (+0,66 %)
Equinix (EQIX, USA) - Data centers (colocation).
Cloud infrastructure
$AMZN (-1,9 %)
Amazon (AMZN, USA) - AWS (cloud, AI training).
$MSFT (-1,02 %)
Microsoft (MSFT, USA) - Azure.
$GOOG (-1,29 %)
Alphabet (GOOGL, USA) - Google Cloud.
Takeaway: Investing in the infrastructure stack allows you to participate in the robotics trend regardless of the subsequent product winner and reduces the individual product risk, but you have to live with cycles. In your opinion, which stage of the chain offers the best risk/return combination and fits into a disciplined portfolio?
Source: Own analysis based on publicly available company information and IR materials of the companies mentioned.
