Launching the Space Economy
The Space Age dates back to the 1950s and was primarily funded by the Soviet Union and United States governments. The two rivals raced to launch objects into space to demonstrate national superiority in technology. This led to dramatic advances in many fields ranging from materials science to microelectronics and humans walking the moon. But, as the national rivalry dissipated in the late 20th century alongside a series of human spaceflight disasters, fascination with space began to wane. Flash forward to today and new financial opportunities for outer space exploration and private spaceflight have galvanized a new Space Economy.
Private spaceflight got a jolt in 2004 by the late Paul Allen, a co-founder of Microsoft, when his SpaceShipOne claimed the Ansari X-Prize. The $10 million dollar prize was awarded for achieving the first privately funded human spaceflight capable of carrying three passengers to 100 km.
Since then, many now billionaires including Elon Musk, Jeff Bezos, and Richard Branson have built companies that seek to shape the Space Economy for years to come. Musk’s SpaceX has led the way by orbiting a reusable rocket, launching a satellite internet constellation, and developing an interplanetary spaceflight system. Jeff Bezos’s Blue Origin is also making “partially and fully reusable launch vehicles that are safe, low cost and serve the needs of all civil, commercial and defense customers.” While Richard Branson’s Virgin Galactic is focusing on suborbital spaceflights for space tourists. These pioneers of launch technology have opened the doors for aspiring start-ups to build factories in outer space.
Exponential cost per kilogram declines for space launches has enabled space manufacturing startups.
However, a few prohibitive factors have long complicated the economics of the space industry: launch cost, technical expertise, and availability of capital. The combination of improvements in engine and propulsion design alongside new rocket fabrication techniques continue to significantly reduce rocket launch costs year over year (see the image above). Also, the technical expertise from the pioneering companies combined with leading universities have created a critical mass of skilled engineers and scientists that are able to collaborate with simulation tools and information systems to rapidly assess the feasibility of new Space Economy ideas. With these two critical factors addressed, the last need for space manufacturing startups is capital. Due to unique circumstances that are beyond the scope of this post, venture capital has been readily available for this new generation of space manufacturing startups.
The Startups Making Outer Space A Manufacturing Hub
Similar to the trajectory of launch objectives, in-space manufacturing plans originate within governmental space agencies but do not end there. NASA’s plans discuss building an additive manufacturing facility and performing multi-material fabrication with printed electronics. While recent a European Union funded project, PULSAR, seeks to “construct in orbit the primary mirror of a telescope from separate parts.” These worthy missions primarily seek to build and consume products in outer space to advance governmental goals. On the other hand, private enterprises have begun to push the boundaries to manufacture in space for use in terrestrial applications including zany ideas like dropping artificial human organs from space. A number of startups have made traction towards more tractable goals which will be detailed below.
Space Tango’s mission is to manufacture health and technology products in space that create value and transformational solutions. As a leader in automated systems, Space Tango pursues pathways to on-orbit production. Our vision is to inspire, innovate and create a better future for humanity by utilizing the environment of space.
Space Tango founded in 2014, was among the first companies to try manufacturing in space. Through its partnership with the International Space Station (ISS), “Space Tango streamlines the process of conducting experiments in the unique environment that microgravity offers.” Its ISS TangoLab facilities offer “autonomous, configurable ecosystems designed for microgravity research and small-scale manufacturing.” Additionally, Space Tango has developed its own re-entry free-flying orbital platform, ST-42, which uses “microgravity to manufacture health and technology products.”
GITAI is a space robotics startup that will develop robots that can conduct tasks in all realms of space development, and cut down costs for operations by the Moon and Mars and construct space colonies.
GITAI established in 2016 also started on the International Space Station with an autonomous robot arm. Its robot was able to “succeed in executing two tasks: assembling structures and panels for In-Space Assembly (ISA), and operating switches & cables for Intra-Vehicular Activity (IVA).” They seek by 2040 to “be an equal partner with the world’s leading space launch companies, providing cheap and safe labor to build cities and space colonies on the moon and Mars.”
Varda Space Industries
Varda Space Industries is building the world’s first commercial zero-gravity industrial park at scale. Reusable rockets have lowered the cost of access to space and opened up a range of in-space activities. From more powerful fiber optic cables to new, life-saving pharmaceuticals, there is a world of products used on Earth today that can only be manufactured in space. Varda is accelerating innovation in the space industry and creating products that will benefit life on Earth. Our mission is to expand the economic bounds of humankind.
Varda Space Industries emerged in late-2021 after a couple years in stealth. According to TechCrunch, “Varda separates itself [from Space Tango and others] by its loftier ambition — to manufacture commercially viable products at scale in space.” They seek to manufacture products with high dollar per-unit-mass value that can be transported back to Earth. But that’s not all, Varda hopes to “build the first infrastructure that can harvest source materials for new products in-space via asteroid mining.”
The Rest of The Stars
- Rocket Lab (NASDAQ: RKLB), incorporated 2006 - “Rocket Lab is an end-to-end space company delivering reliable launch services, spacecraft, satellite components, and on-orbit management.”
- Relativity Space, 2015 - “As a vertically integrated technology platform, Relativity is at the forefront of an inevitable shift toward software-defined manufacturing. By fusing 3D printing, artificial intelligence, and autonomous robotics, we are pioneering the factory of the future. Leading an unrivaled team to solve problems never solved before, our leadership includes seasoned veterans and experts from the world’s most renowned aerospace, 3D printing, and technology companies. Together, we are revolutionizing how rockets are built and flown.”
- Astra (NASDAQ: ASTR), 2016 - “Today, Astra offers one of the lowest cost-per-launch dedicated orbital launch service of any operational launch provider in the world. Astra delivered its first commercial payload into Earth orbit in 2021, making it the fastest company in history to reach this milestone, just five years after it was founded in 2016. Astra was the first space launch company to be publicly traded on Nasdaq.”
- Launcher, 2017 - “Launcher is the only company with dedicated launch + orbital transfer or rideshare. Our orbital transfer vehicle and satellite platform compatible with SpaceX Rideshare and Launcher’s small launch vehicle.”
- Redwire (NYSE: RDW), 2020 - “Decades of flight heritage and innovation of world-class technologies combined with our mission success and focus on customer satisfaction have positioned Redwire Space as a leader in advancing the future of space infrastructure. Redwire’s operating units are organized into broad business areas focusing on space commercialization, digitally engineered spacecraft, on-orbit servicing, assembly, and manufacturing, advanced sensors and components, and space domain awareness and resiliency.”
- Sierra Space, 2021 - “Sierra Space is building a shared ecosystem in space for scientific collaboration and innovation to enhance life on earth. With technologies that make space more affordable and accessible, we’re dedicated to creating a prosperous and secure space economy that will benefit all of humanity. Rapidly advancing toward the launch of the next generation of space transportation, the world’s only winged commercial spaceplane, the Dream Chaser, will perform cargo supply and return missions for NASA, set to begin in 2023 - delivering up to 12,000 pounds of cargo to the International Space Station at a time. Sierra Space is also the developer of the Large Integrated Flexible Environment (LIFETM) Habitat, a modular, three-story commercial habitation and science platform. The unique structure will provide opportunities for multiple businesses including manufacturing, pharmaceuticals, and other sectors, to optimize zero gravity benefits. The Dream Chaser Spaceplane and LIFE platform are central components of the joint partnership Orbital Reef commercial space station and mixed-use business park being developed in partnership with Blue Origin.”
Back on Earth, traditional companies are also targeting the emerging space economy. STMicroelectronics has developed radiation hardened integrated circuits fit for use on next generation satellites. Additive manufacturing companies, like Velo3D and Desktop Metal, are driving the new rocket fabrication and repair techniques mentioned earlier.
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NVIDIA Omniverse Ecosystem Expands 10x, Amid New Features and Services for Developers, Enterprises and Creators
There are also new connections to industrial automation and digital twin software developers. Bentley Systems, the infrastructure engineering software company, announced the availability of LumenRT for NVIDIA Omniverse, powered by Bentley iTwin. It brings engineering-grade, industrial-scale real-time physically accurate visualization to nearly 39,000 Bentley System customers worldwide. Ipolog, a developer of factory, logistics and planning software, released three new connections to the platform. This, coupled with the growing Isaac Sim robotics ecosystem, allows customers such as BMW Group to better develop holistic digital twins.
At GTC, NVIDIA announced NVIDIA OVX, a computing system architecture designed to power large-scale digital twins. NVIDIA OVX is built to operate complex simulations that will run within Omniverse, enabling designers, engineers and planners to create physically accurate digital twins and massive, true-to-reality simulation environments.
Amazon Robotics Builds Digital Twins of Warehouses with NVIDIA Omniverse and Isaac Sim
In a World First, Yokogawa and JSR Use AI to Autonomously Control a Chemical Plant for 35 Consecutive Days
Yokogawa Electric Corporation (TOKYO: 6841) and JSR Corporation (JSR, TOKYO: 4185) announce the successful conclusion of a field test in which AI was used to autonomously run a chemical plant for 35 days, a world first. This test confirmed that reinforcement learning AI can be safely applied in an actual plant, and demonstrated that this technology can control operations that have been beyond the capabilities of existing control methods (PID control/APC) and have up to now necessitated the manual operation of control valves based on the judgements of plant personnel. The initiative described here was selected for the 2020 Projects for the Promotion of Advanced Industrial Safety subsidy program of the Japanese Ministry of Economy, Trade and Industry.
The AI used in this control experiment, the Factorial Kernel Dynamic Policy Programming (FKDPP) protocol, was jointly developed by Yokogawa and the Nara Institute of Science and Technology (NAIST) in 2018, and was recognized at an IEEE International Conference on Automation Science and Engineering as being the first reinforcement learning-based AI in the world that can be utilized in plant management.
Given the numerous complex physical and chemical phenomena that impact operations in actual plants, there are still many situations where veteran operators must step in and exercise control. Even when operations are automated using PID control and APC, highly-experienced operators have to halt automated control and change configuration and output values when, for example, a sudden change occurs in atmospheric temperature due to rainfall or some other weather event. This is a common issue at many companies’ plants. Regarding the transition to industrial autonomy, a very significant challenge has been instituting autonomous control in situations where until now manual intervention has been essential, and doing so with as little effort as possible while also ensuring a high level of safety. The results of this test suggest that this collaboration between Yokogawa and JSR has opened a path forward in resolving this longstanding issue.
Industrial Autonomy on the Horizon
Automation systems in continuous-process plants are constantly evolving due to competitive industry pressures, customer demands, external events, and security requirements. Like it or not, most existing systems have changed as a result of numerous small actions taken over the years. A control system originally installed 25 years ago may include a patchwork of small additions made over time, leading to a system that is difficult to maintain because of all its unique quirks. Only some system owners take a strategic lifecycle approach to their control systems. Others are typically reactive, making changes only as needed to correct problems.
The trends are unmistakable: Autonomy is a critical technology that will lead process industry operations into the future. As technology moves beyond automation, autonomy and autonomous systems will bring improvements in many areas. The latest developments around industrial autonomy provide a timely response to several key industry trends, including the desire for post-COVID-19 preparedness and resilience, growing operational complexity, the aging industrial workforce and upskilling needs.
Autonomous robots will one day assemble telescopes directly in space | EU project Pulsar
Autonomous Design Automation: How Far Are We?
As an industry, we will refine the different levels of Autonomous Design Automation further over the years to come. Eventually, the combination of the different steps of the flow with AI/ML will unlock even further productivity improvements. How long will it be until designers define a function in a higher-level language like SysML and, based on the designer’s requirements, autonomously implement it as a hardware/software system after AI/ML-controlled design-space exploration?
Decentralized learning and intelligent automation: the key to zero-touch networks?
Decentralized learning and the multi-armed bandit agent… It may sound like the sci-fi version of an old western. But could this dynamic duo hold the key to efficient distributed machine learning – a crucial factor in the realization of zero-touch automated mobile networks? Let’s find out.
Next-generation autonomous mobile networks will be complex ecosystems made up of a massive number of decentralized and intelligent network devices and nodes – network elements that may be both producing and consuming data simultaneously. If we are to realize our goal of fully automated zero-touch networks, new models of training artificial intelligence (AI) models need to be developed to accommodate these complex and diverse ecosystems.
Automated Assembly for Waterproof Electrical Connectors, Courtesy of Noble Plastics
YOLO V3 + VGG16-based automatic operations monitoring and analysis in a manufacturing workshop under Industry 4.0
Under the background of Industry 4.0 and smart manufacturing, operators are still the core of manufacturing production, and the standardization of their actions greatly affects production efficiency and quality. However, they have not received enough attention. In view of the monitoring and analysis of operators’ actions in the manufacturing field, this paper proposes the YOLO V3 + VGG 16 transfer learning network. First, the region detection of key operators is realized by using YOLO V3, and an action dataset is constructed. Second, using transfer learning to realize the automatic recognition, monitoring and analysis of small sample data, the recognition accuracy of the proposed method is greater than 96%, and the average deviation of the action execution time is less than 1 s. This research is expected to provide guidance for increasing the degree of workshop automation, improving the standardization of operators’ actions, optimizing action processes and ensuring product quality.
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