A generational opportunity in manufacturing and robotics
The renaissance in robotics and manufacturing is propelled by four major forces:
- Secular global forces to invest in infrastructure, on-shore manufacturing , and de-risk supply chains across the Western nations due to concerns about national security and lessons from the global pandemic.
- The shrinking labor cost advantage of China over US from 44X in 1995 to 4X in 2023 favors automation and inflationary nature of on-shore manufacturing.
- Lack of innovation in manufacturing machinery, precision equipment, and automation creates opportunities for startups.
- The emergence of key enabling technologies, notably widespread access to GPUs, advancement in AI (transformer model, digital twin, language interface), and rapid motor adaptation to solve navigation, perception, control, and interface problems in robotics.
Areas of opportunity ****
- Industrial digitization and automation to improve productivity, optimize manufacturing processes, and automate backend operations, specifically:
- Manufacturing digitization platforms take advantage of hardware and software integration, the Internet of Things (IoT), advanced sensors, and optical inspection to collect imagery, machine, and people data. These systems will simulate, monitor, and optimize processes and integrate resources, providing end-to-end manufacturing as a service.
- Extended manufacturing systems (EMS) marrying data from design tools (electronic design automation (EDA)), machineries (e.g., lithography), and processes (such as wafer prober test) to improve quality and optimize manufacturing. Enabling technologies include artificial intelligence (AI), hardware and software integration, and advanced probing machinery.
- Advanced maintenance monitoring solutions through novel applications of advanced sensors (e.g., sonar), AI, and digital processing to accurately forecast performance and monitor the condition of machinery and equipment.
- Robotics training platforms simulate factory and assembly lines with cameras and generative AI, creating virtual environments to train robots and RLHF robots by controlling them using VR.
- Next-generation manufacturing machinery and precision equipment to improve manufacturing output, quality, and flexibility.
- Lithography technologies through innovations in extreme ultraviolet (EUV), directed assembly, and next-generation scanners to develop high-volume, high-resolution, low-cost lithography machinery.
- Ultra-precision automated manufacturing machinery using laser manufacturing, scanners, robotics, and software.
- Scalable custom manufacturing machinery for personalized drugs, jewelry, and apparel is enabled by innovations in robotics, 3D printing, material science, laser, optical inspection, AI, and digital twin.
- High-precision and cost-efficient additive manufacturing of metal and liquid is achieved through innovations in nozzle performance, melt and solidify material control (e.g., laser-assisted additive manufacturing), and advanced feedstock and powder composition.
- Robotic automation to increase productivity, decrease cost, and fill labor gap for the following verticals:
- Manufacturing cobots navigating and moving materials and products inside factories and robotic arms automating repetitive, human-intensive tasks.
- Construction software and cobots to assist and automate specific tasks, including surveying, painting, flooring, insulation, etc.
- Automated mining machinery and software to improve productivity, monitor performance, and decrease carbon footprint.
- Marine robots for inspection, pollution and hull cleaning, exploration of underwater resources, and autonomous navigation systems.
- Unmanned electric agriculture machinery and drones to automate irrigation, planting, dispensing water and fertilizer, cultivating soil, and picking and sorting products.
- Health care robots for laboratory automation, service hospitals, and assistance for common surgeries.
- Warehouse suite of robots from inventory drones to moving robots, sorting and packaging robots, and autonomous forklifts.
Core risks and de-risk mechanisms
- Commercialization: The upfront cost of purchasing a robot is high, and the return on investment (ROI) is not always clear. New business models to share risks and upsides, such as manufacturing as a service or shared savings agreements, are necessary to flatten the sales learning curve and boost adoption.
- Integration: Integrating robots with existing tools and machinery often disrupts processes and workflows. Startups should design an intuitive interface to ease control and collaboration. In addition, startups that can create asymmetric advantage through automation should consider vertical integration.