Levitation at Room Temperature: The Race to Replicate
Shop Talk
Capturing this week's zeitgeist
Korean scientists have uncovered a room temperature superconducting material, dubbed LK-99.
How big of a deal is this? Picture everything from sci-fi-esque devices like levitating trains to electronics and computers that respond significantly faster to ultra-efficient continent-spanning power lines that could help address climate change. They’d take a big leap forward with a room temperature superconductor.
Other uses include MRI machines that wouldn’t need to be cooled so tremendously. Desktop quantum computers could become a reality. And the days of your computer or smartphone overheating? Those could be history.
The race to reproduce the results are setting Twitter, err X, ablaze. Follow Ate-a-Pi and Andrew McCalip from Varda Space for the latest.
More can’t miss content on X:
- A candid interview of Ford CEO, Jim Farley, explains the difficulty in transforming a car company into a software company.
- CNN interview with Kurt House on how mining startup KoBold Metals is utilizing AI to pinpoint key metals for clean energy.
Assembly Line
This week's most influential Industry 4.0 media
📦 A Soap Maker Cracks the Code to ‘Made in America’
Bath & Body Works decided it needed to get new products to market more quickly. The result was a production initiative with little parallel in corporate America.
Now every step of production occurs at plants just feet from each other on the company’s dedicated “beauty park” on the outskirts of Columbus. One factory makes the foaming pump and mechanism. Another makes the bottle itself, a third makes the label, a fourth makes the soap, fills the bottle, attaches the label and screws on the top. A fifth packages it. Getting a bottle to distribution is down to 21 days and a few miles. A majority of Bath & Body Works products, which are sold in its own stores, are made on site.
One challenge to replicating BBW’s model is that factories don’t operate in bubbles, but rely on networks of suppliers, parts and expertise—and moving those networks is costly. Once such a network has been established, it tends to get stuck there. Semiconductor manufacturers and raw steel producers require massive upfront investment and economies of scale. The BBW model is better suited to exploiting economies of scope, in which a manufacturer produces a variety of products. Bath & Body Works can roll out around 7,000 new scented products a year.
The Race to Automate Aerospace: A Talk with JPB Système CEO Damien Marc
“I took the decision to incorporate manufacturing into our core business. And that was a tough decision — our business is global, our competition is global, so we need to produce at the best quality and the best price,” explained Marc. “France was not necessarily the best choice in that sense, so I was going to look around and maybe buy a company. I didn’t find what I was looking for, but then I realized there was one other way I might be able to do it.”
Marc’s plan was to use CNC machines, with the business logic behind the idea that the equipment cost more or less the same no matter the country, but hiring the higher-salary workers in the French market could allow JPB to get the most value out of each machine. Marc quickly ran into trouble with this idea, as well. Much like in many of the other most heavily industrialized nations, good CNC operators that don’t already have jobs are just hard to come by. He finally settled on using CNC robots for the low-value tasks, so he could “center the operators in high-value operations.” This was a promising turning point, although it came with its own set of challenges.
“When I put two different machines in the workshop, they weren’t able to communicate with each other,” Marc said, referring attempts to connect his first CNC robot to an inspection machine. “There is no protocol. I was really surprised because my background is computer skills and electronics.” JPB ended up having to make its own programmable logic control (PLC) language in order to get the machines synced: “So, we created the communication between those two machines, and at the end, the machine for production was producing, the machine for inspection was inspecting, and the inspection machine was sending the offsets corrections to the production machine. We successfully created our first closed-loop.”
Full factory furnishing with Edwards Vacuum
IBM and AWS partnering to transform industrial welding with AI and machine learning
IBM Smart Edge for Welding on AWS utilizes audio and visual capturing technology developed in collaboration with IBM Research. Using visual and audio recordings taken at the time of the weld, state-of-the-art artificial intelligence and machine learning models analyze the quality of the weld. If the quality does not meet standards, alerts are sent, and remediation action can take place without delay.
The solution substantially reduces the time between detection and remediation of defects, as well as the number of defects on the manufacturing line. By leveraging a combination of optical, thermal, and acoustic insights during the weld inspection process, two key manufacturing personas can better determine whether a welding discontinuity may result in a defect that will cost time and money: weld technician and process engineer.
Sensor Fusion with AI Transforms the Smart Manufacturing Era
Bosch calls its new semiconductor fab in Dresden a smart factory with highly automated, fully connected machines and integrated processes combined with AI and internet of things (IoT) technologies for facilitating data-driven manufacturing. With machines that think for themselves and glasses with built-in cameras, maintenance work in this fab can be performed from 9,000 kilometers (about 5,592 miles) away.
STMicroelectronics (STMicro) has added compute power to sensing in what it calls an intelligent sensor processing unit (ISPU). It combines a DSP suited to run AI algorithms and MEMS sensor on the same chip. The merger of sensors and AI puts electronic decision-making on the edge, while enabling smart sensors to sense, process and take actions, bridging the fusion of technology and the physical world.
Using ML For Improved Fab Scheduling
The exact number of available tools for each step varies as tools are taken offline for maintenance or repairs. Some steps, like diffusion furnaces, consolidate multiple lots into large batches. Some sequences, like photoresist processing, must adhere to stringent time constraints. Lithography cells must match wafers with the appropriate reticles. Lot priorities change continuously. Even the time needed for an individual process step may change, as run-to-run control systems adjust recipe times for optimal results.
At the fab level, machine learning can support improved cycle time prediction and capacity planning. At the process cell or cluster tool level, it can inform WIP scheduling decisions. In between, it can facilitate better load balancing and order dispatching. As a first step, though, all of these applications need accurate models of the fab environment, which is a difficult problem.
The GlobalFoundries group demonstrated the effectiveness of neural network methods for time constraint tunnel dispatching. The relationship between input parameters and cycle time is complex and non-linear. As discussed above, machine learning methods are especially useful in situations like this, where statistical data is available but exact modeling is difficult.
Interesting Engineering on UVeye – The MRI for Cars
Robots Automate Assembly of Auto Parts
AMG is Husco’s in-house factory automation arm. It designs and builds most of the manufacturing lines for Husco, and it recently began offering its services to outside clients as well.
While many manufacturers, including Husco, have been devoting more and more of their efforts to EVs, increasing the efficiency of internal combustion engines remains important. One crucial development has been the use of variable-force solenoids in car and truck engines. These small devices optimize the opening of the valves that let fuel and air into the cylinders at the heart of each engine, helping to increase both fuel efficiency and horsepower.To reach its goal, the plant would have to produce a fully assembled and tested solenoid every 6.1 seconds. To make that possible, the AMG team developed a modular automated assembly system consisting of a pallet-transfer conveyor and 10 Epson SCARA robots for most of the material handling. They settled on one Epson G6, two G3, and seven T-Series systems.
Husco and AMG most often use Epson T-Series robots for pick and place operations, but upgrade to the G-Series when they need higher speed and accuracy.
The Czingers disrupt manufacturing at top speeds — 253 mph, specifically
With a combination of innovative software and 3D metal printing, the Czingers have created a system to radically speed up and streamline the process of making vehicles, and potentially transform the automotive industry. It applies artificial intelligence to develop car parts, and 3D printing to manufacture them.
The Los Angeles-based company’s own Divergent Adaptive Production System (DAPS) was developed by a team that includes engineers formerly from Tesla, Apple, and other tech heavyweights. It’s a complete software-hardware solution designed to replace traditional vehicle manufacturing. With artificial intelligence, it can computationally design any structure, no matter how complex. The system then additively manufactures and assembles these parts, optimizing every component for minimum weight and maximum strength. And it can seamlessly switch from manufacturing cars to drones and beyond.
“That software designs the parts and designs it to be its most efficient and to print in the most effective way on our hardware,” said Lukas Czinger, who majored in electrical engineering as a student at Yale College. “Then it also designs it to be assembled in the lowest possible cycle time while meeting all the requirements of our modular, fully fixtureless assembly process. Those three things together — design software, printing, and assembly — is really what Divergent is.”
Capital Investment
Major factory investments and line commissions. Tracked in the Atlas.
🏭🇹🇼 Driven by AI boom, TSMC to invest $2.9 billion in advanced chip plant in Taiwan
Driven by a surge in demand for artificial intelligence, Taiwanese chip maker TSMC (2330.TW) plans to invest nearly T$90 billion ($2.87 billion) in an advanced packaging facility in in the Tongluo Science Park.
CEO C.C. Wei said last week that TSMC is unable to fulfil customer demand driven by the AI boom and plans to roughly double its capacity for advanced packaging - which involves placing multiple chips into a single device, lowering the added cost of more powerful computing.
🏭🇺🇸 SunGas Renewables Announces Beaver Lake Renewable Energy, a $2B Green Methanol Facility in Central Louisiana
SunGas Renewables Inc. announced the formation of Beaver Lake Renewable Energy, LLC (“BLRE”), which will construct a new green methanol production facility in Central Louisiana. A wholly-owned subsidiary of SunGas Renewables, BLRE is expected to generate from the facility nearly 400,000 metric tons of green methanol per year for marine fuel while creating more than 1,150 jobs during construction and more than 100 local jobs during operation.
Green methanol produced by BLRE is expected to be used to fuel A.P. Moller – Maersk’s (“Maersk’s”) fleet of methanol-powered container vessels and will utilize wood fiber from local, sustainably-managed forests. The methanol will have a negative carbon intensity through sequestration of nearly a million tons per year of carbon dioxide produced by the project, which will be executed by Denbury Carbon Solutions.
🏭🇺🇸 Meyer Burger abandons German solar cell factory plans to build a US factory instead
The company says it’s prioritizing the US over Germany because of “a tax credit under the Inflation Reduction Act and related measures, as well as support from the State of Colorado and the City of Colorado Springs.” It’s also getting a $300 million loan from the US Department of Energy. With an initial targeted production of 2 gigawatts of solar cells and modules in the US, Meyer Burger is potentially eligible for tax credits of up to $1.4 billion from the start of production in 2024 until the end of 2032.
It wants its new Colorado Springs solar cell factory online by the fourth quarter of 2024, so it’s diverting production equipment originally intended for its Thalheim factory to Colorado.
Business Transactions
This week's top funding events, acquisitions, and partnerships across industrial value chains
Collaborative Robotics Raises $30M Series A
Collaborative Robotics, a leader in the development of practical collaborative robots (cobots), announced it has raised $30M in Series A funding led by new anchor investor, Sequoia Capital, bringing the total amount raised to over $40M. The funds will enable Collaborative Robotics to begin scaling early field deployments and manufacturing of its novel cobot. Sequoia Capital led the funding round, with Alfred Lin joining the board. Other contributors include Khosla Ventures and Mayo Clinic, with Calibrate, Neo, and 1984.vc expanding existing investments. Jeff Wilke, former CEO of Amazon Consumer, Fuel Capital, and MVP Ventures added to the pool. The company was founded in 2022 by Brad Porter, former VP of Amazon Robotics.
Ethereal Machines raises $7.3 million funding from Peak XV's Surge, others
Ethereal Machines, manufacturer of multi-axis Computer Numerical Control (CNC) machines, on Monday said it has raised $7.3 million in a funding round from various investors, including Peak XV’s Surge and Blume Ventures. Celesta Capital partner Ganapathy Subramaniam, former Blackstone India head Mathew Cyriac and executive chairman of Cadence Design Systems Lip-Bu Tan, along with Finvolve, 9Unicorns, Venture Catalysts and T2D3 Capital also participated in the round, as per a statement.
Ethereal Machines, manufacturer of multi-axis Computer Numerical Control (CNC) machines, on Monday said it has raised $7.3 million in a funding round from various investors, including Peak XV’s Surge and Blume Ventures.
AI-powered Generative Engineering Platform Motion G Secured Additional US$16 Million
Singapore-based Motion G, Inc. has closed a new round of funding led by Episteme, Inc., securing an additional US$16 million. By leveraging advancements in machine learning, AIGC, data science and digital twin technologies, the firm aims to revolutionize the engineering process to significantly drive productivity.
Industrial Robotics Company Ati Motors Secures US$10.85 Million in Series A Funding Led by Silicon Valley's True Ventures
Ati Motors, maker of autonomous industrial robots, today announced the close of its Series A funding round in the amount of US$10.85 million. The investment, occurring alongside the company’s product launch event, will further accelerate the development and deployment of Ati Motors’ robotics technology for automating work in industrial environments and warehouses.
The Series A round is led by True Ventures, a Silicon Valley venture capital firm focused on early-stage technology companies. Athera Ventures Partners, also joined as a new investor, bringing its extensive experience in deep tech investments. The round saw significant participation from previous investors: Blume Ventures, Exfinity Ventures and MFV Partners. The latest funding will empower Ati Motors to expand into markets in the US, South East Asia, Japan, and Europe while exploring untapped opportunities across pharmaceuticals, chemicals, maritime, and injection molding sectors. Ati Motors will continue to invest in research and development to launch new products and capabilities in the market.
Tenerife-based Wooptix closes €10 million Series B to automate its semiconductor metrology business
Wooptix, a company based in Tenerife, Madrid and San Francisco, has announced a €10 million Series B financing round. The round is participated by Bullnet Capital, CDTI (Centre for the Development of Technology and Innovation), Danobatgroup, European Innovation Council Fund (EIC), Fagor Automation, Intel Capital, and Mondragón Promotion. The grant and investment support Wooptix´s product introduction and future technological innovation including the manufacture, delivery, and installation of three semiconductor metrology tools in Japan, the USA, and the Netherlands this year.
Wooptix’s patented technology enables blank and patterned wafer-shape measurement in less time and with higher resolution than current systems being used in the industry.
UK’s Materials Nexus raises €2.3M to discover, develop sustainable climate material
London-based Materials Nexus, a deeptech company that processes quantum calculations, announced on Wednesday that it has raised £2M (approximately €2.33M) in a fresh round of funding. The investment was led by Ada Ventures with further investment from High-Tech Gründerfonds, The University of Cambridge, and National Security specialists MD One Ventures. The company says the funds will be used to launch its “ground-breaking” AI and quantum mechanics technology, which accelerates the discovery and development of sustainable, cheaper, higher-performing materials.
SoftBank Group and Symbotic Establish New Warehouse-as-a-Service Joint Venture
SoftBank Group Corp. (TSE: 9984, “SoftBank”) and Symbotic Inc. (Nasdaq: SYM), a leader in A.I.-powered automation technology for the supply chain, today announced the establishment of GreenBox Systems LLC (“GreenBox”), a new joint venture to address the more than $5001 billion annual warehouse-as-a-service market opportunity. Concurrently, Symbotic also announced an approximately $7.5 billion new customer contract with GreenBox, who will be the exclusive provider of Symbotic systems in the warehouse-as-a-service market, and will make supply chain services available to customers.
SoftBank and Symbotic own 65% and 35% of GreenBox, respectively, with the joint venture established today. GreenBox will initially be funded with $100 million of capital contributed pro rata by Symbotic and SoftBank to fund operating expenses and initial system purchases. After Symbotic’s initial $35 million pro rata capital contribution, the contract is expected to be accretive to Symbotic’s annual free cash flow (net of capital contributions).
Group14 Technologies Acquires Schmid Silicon in Milestone European Expansion
Group14 Technologies, the leading global manufacturer and supplier of advanced silicon battery technology, acquired Schmid Silicon Technology Holding GmbH (Schmid Silicon), the most technologically advanced silane producer in Europe, in a landmark move to strengthen the global battery supply chain and meet demand for silicon battery technology worldwide. As part of the acquisition, Group14 will bring online Schmid Silicon’s state-of-the-art silane factory in Spreetal (Schwarze Pumpe), Germany, to support its expanding European operations. The milestone serves to insulate Group14’s customers and partners from potential supply chain disruptions – particularly in the automotive industry – and sets up the company to localize integrated silicon battery technology manufacturing in Europe.