Relativity Space, a California-based company that can 3D print an entire rocket and can build large metal 3D printers, has now secured $300 million in a Series D funding round. Relativity Space is founded by Tim Ellis in the year 2015. It combines 3D printing, autonomous robotics, and Artificial Intelligence to build a rocket in less than 60 days. The company is as of now on its way to launch an entirely 3D printed rocket to orbit. The company has a team size of 230 employees.

AI Has Cracked a Key Mathematical Puzzle for Understanding Our World Karen Hao MIT Technology Review "Partial differential equations can describe everything from planetary motion to plate tectonics, but they're notoriously hard to solve. Physicists 3D Print a Boat That Could Sail Down a Human Hair John Biggs Gizmodo "Researchers at Leiden University have 3D printed the smallest boat in the world: a 30-micrometer copy of Benchy the tug boat, a well-known 3D printer test object. This boat is so small, it could float down the interior of a human hair. The 3D-printed boat is part of an exploration of microswimmers, microscopic organisms or objects that can move through liquids." Record-Smashing Hybrid Drone Stays Airborne for a Crazy 10 Hours, 14 Minutes Luke Dormehl Digital Trends "i'HYBRiX is an innovation, inspired by hybrid cars, that combines the best of both technologies,' a spokesperson for Quaternium told Digital Trends, referring to the drone's clever gasoline and battery-electric hybrid power system.

Scientists claim to have created the first ever synthetic tongue using 3D printing. The'biometric tongue', developed in the UK, mimics the elasticity, wettability and unique rough texture of a real human tongue with its synthetic silicone structure. Experts took digital scans of real human tongues to 3D-print their artificial material, which could be used to test the oral processing properties of some foods. It could also fight against adulteration in food and orally administered pharmaceuticals and lead to new nutritional technologies. The printed synthetic silicone structure mimics the topology, elasticity and wettability of a real tongue's surface'Recreating the surface of an average human tongue comes with unique architectural challenges,' said study author Dr Efren Andablo-Reyes at the University of Leeds.

I-nteract is a cyber-physical system that enables real-time interaction with both virtual and real artifacts to design 3D models for additive manufacturing by leveraging on mixed reality technologies. This paper presents novel advances in the development of the interaction platform I-nteract to generate 3D models using both constructive solid geometry and artificial intelligence. The system also enables the user to adjust the dimensions of the 3D models with respect to their physical workspace. The effectiveness of the system is demonstrated by generating 3D models of furniture (e.g., chairs and tables) and fitting them into the physical space in a mixed reality environment.

CHICAGO (Reuters) - Question: How can a company like Caterpillar CAT.N try to counter a slump in sales of bulldozers and trucks during a pandemic that has made every human a potential disease vector? Caterpillar's autonomous driving technology, which can be bolted on to existing machines, is helping the U.S. heavy equipment maker mitigate the heavy impact of the coronavirus crisis on sales of its traditional workhorses. With both small and large customers looking to protect their operations from future disruptions, demand has surged for machines that don't require human operators on board. Sales of Caterpillar's autonomous technology for mining operations have been growing at a double-digit percentage clip this year compared with 2019, according to previously unreported internal company data shared with Reuters. By contrast, sales of its yellow bulldozers, mining trucks and other equipment have been falling for the past nine months, a trend that's also hit its main rivals including Japan's Komatsu Ltd 6301.T and American player Deere & Co DE.N .

Hitachi Construction Machinery (HCM) and its consolidated subsidiary, Wenco International Mining Systems, have jointly developed "ConSite Mine", a new technology platform that helps resolve problems at mine sites by remotely monitoring mining machines on a 24/7 basis through the use of IoT and AI based analysis of equipment operations data. According to Hitachi, it has developed this technology to help customers and HCM dealers predict costly maintenance issues before they occur, such as the occurrence of cracks in excavator booms or arms, by utilising machine learning and applied analysis technologies. Detailed information from these predictive alerts are provided on the web-based ConSite Mine dashboard and other items. Currently, Hitachi is piloting the technology in Australia, Zambia and Indonesia. "ConSite Mine" will be further modified based on customer feedback before wider commercial release in 2021.

Hitachi Construction Machinery Co. Ltd and its consolidated subsidiary, Wenco International Mining Systems Ltd have jointly developed ConSite Mine, which helps resolve problems at mine sites by remotely monitoring mining machines on 24/7 basis through the use of Internet of Things (IoT) and artificial intelligence (AI) based analysis of equipment operations data. Hitachi Construction Machinery has developed this technology to help customers and Hitachi Construction Machinery dealers predict costly maintenance issues before they occur, such as the occurrence of cracks in and excavator boom or arm by utilising machine learning and applied analysis technologies. Currently, Hitachi Construction Machinery Group is piloting the technology in Australia, Zambia and Indonesia. The system will be further modified based on customer feedback before wider commercial release in 2021. ConSite Mine will enable the maintenance professionals for customers and Hitachi Construction Machinery dealers to monitor equipment health in real time and anticipate issues before they occur.

The integration of AI and 3D printing in manufacturing can help increase unit production rate, detect defects, and provide real-time control over the manufacturing process. As the name suggests, additive manufacturing is a method of building products by adding layers of components on one another. AI, on the other hand, as everyone knows, can automate monotonous tasks and bring accuracy in those tasks. The manufacturing sector has many repetitive labor tasks that make AI a perfect match for the manufacturing and 3D printing process.. AI can increase the production rate and accuracy of 3D production. Using computer vision, manufacturers can reverse engineer the existing models and create a new and improved product design.

Additive Manufacturing (AM) processes offer unique capabilities to build low-volume parts with complex geometries and fast prototyping from a variety of materials. Metal-based AM has become increasingly more popular over the last decade for manufacturing and repairing functional parts in automotive, medical and aerospace industries. Despite the great potential in metal-based AM market, the state-of-the-art practices involve rigorous trial and errors before achieving consistent parts with the desired geometric and material properties, which is mainly due to the sensitivity of the build on process parameters. While the influence of process parameters such as laser power, powder parameters, and scan speed on the microstructure and final properties of the AM build are extensively studied in the literature, the influence of toolpath strategies yet to be fully investigated. Authors in [Steuben et al., 2016] considered three different toolpath patterns for building a part using a fused deposition modeling process and demonstrated that the pattern has a significant effect on the ultimate strength and elastic modulus of the build. Akram et al. [Akram et al., 2018] formulated a microstructure model using a Cellular Automata (CA) and demonstrated a strong correlation between the toolpath pattern (i.e., unidirectional and bidirectional) and the grain orientations.

In this installment of the AI in Supply Chain series (#AIinSupplyChain), we explore the topic of industrial supply chains and factories of the future since this is where the AI applications we are covering will primarily be used. According to the German Federal Ministry for Economic Affairs and Energy, "Industrie 4.0 refers to the intelligent networking of machines and processes for industry with the help of information and communication technology." Industrie 4.0 is a term that is closely related to the terms Factory of the Future and Fourth Industrial Revolution. Industrie 4.0 envisions a future in which: Factories produce goods in fluctuating quantities based on real-time demand rather than preset production quotas. Production lines are modularized and can be reconfigured easily to enable the production of different types of products in small lots.