Do the Math on Sustainability & Quality
Shop Talk
Capturing this week's zeitgeist
Watch videos about the restoration of Michigan Central Station from Ford, CEO Jim Farley, and executive chair William Clay Ford Jr.
Kaizen Blitz
- 📊 Survey Says
- Top 10 industrial technology trends as showcased at Hannover Messe 2024.
- 🏆 Golden Part
- Ford’s Chicago Assembly Plant Turns 100 !
- Boeing, EOS, Arburg & Westinghouse among winners at TCT Awards 2024.
- 🏭💰 Behemoth Factories
- ‘Silicon Heartland’ construction on schedule at Intel semiconductor plant with investment growing to $28 billion.
- NXP, Vanguard to Build $7.8 Billion Singapore Chip Wafer Plant.
- Zambia Sees KoBold Spending $2.3 Billion on Giant Copper Mine.
- JCB began work on a new $500 million factory in San Antonio.
- Air Liquide plans $250 mln Idaho plant to supply gas for chipmaker Micron.
- Toyota is growing its Huntsville plant production capabilities with a $282 million investment.
- 🏢💸 Corporate Frontier
- Clean Energy Ventures Closes $305M Fund II Aiming to Mitigate 75 Gigatons of Emissions by 2050
- McRock Fund III launches with US $81 million in commitments. Fund III will focus on industrial software.
- 🏛️📜 Industrial Policy
- The Goal for China’s Chip Giant, SMIC: Cut Out the U.S.
Assembly Line
This week's most influential Industry 4.0 media.
Introducing the Revenue-Quality Podium: How Revenue Mix Drives Value for Industrial Tech and Life-Science Tools Companies
Based on a quantitative analysis of publicly-traded industrial technology and life-science tools (ITLST) companies and our own portfolio, we created a new framework — the Revenue-Quality Podium — to help management teams, investors and industry stakeholders track value creation as companies transition to a higher share of high-quality revenue.
In the software world, it is widely accepted that recurring/subscription revenue is a key value driver. Software companies are often valued on a multiple of annual recurring revenue (ARR) — higher ARR generally leads to a higher valuation. This preference for recurring revenue suggests that some types of revenue are considered more valuable or ‘high-quality’ than others in determining the valuation of a business.
We think in parallel terms when evaluating current and prospective ITLST investments, focusing closely on the quality of a company’s revenue. Most of our investments have a wide range of revenue streams, ranging from product sales and recurring consumable sales to service contracts and software/data subscriptions. Our two decades of experience in partnering with ITLST companies has reinforced our thinking that the percentage of higher-quality revenue is a meaningful indicator of current value, and moreover, should serve as a key lever to help our companies increase in value over time.
Former SpaceX engineer invents a “Robotic Blacksmith Army”
Inside Apple’s efforts to build a better recycling robot
Daisy significantly reduces Liam’s overall footprint from 29 robots across 100 feet to four primary modules, while increasing the number of material output streams from 8 to 15. The biggest improvement is the increase in compatibility from a single iPhone model (the 6 in the case of Liam 2.0) to several. Apple has continually updated that figure in the 7.5 years since Daisy arrived. The robot now handles 29 different models, up from 18 a year and a half ago.
The stark difference in cycle times between Liam 1.0 and Daisy is due, in part, to a fundamental rethink of the separation process. Whereas the first robot gingerly unscrewed the various components, newer versions take a kind of brute force approach. The robots “punch out” the component now. Turns out it’s significantly faster to effectively rip a phone apart, and while the result is a lot less pretty, no one cares what discarded phones look like. It’s not being refurbished, after all; it’s being melted down.
Apple sees Daisy as a kind of ambassador for its recycling efforts. It not nearly where it needs to be in terms of speed and efficiency, but it’s something headline grabbing that puts more eyes on the company’s end-of-life efforts. “One metric ton of material recovered from Daisy prevents 2,000 metric tons of mining,” Chandler says.
I Visited Apple's Secret iPhone Testing Labs!
Leveraging Data for Growth
Citrine offers an AI platform designed to enable chemists and materials scientists to develop better products in less time. In big tech companies, data is abundant and there are armies of data scientists to use it primarily because software margins are huge, and these companies have been growing like crazy (maybe not forever). Chemical companies are very different. Data is relatively scarce because experiments take time to conduct, and you need lab space and the people doing the experiments are doing more than just product development. They are supporting the existing business. Citrine essentially allows R&D people to become data scientists through a no-code platform.
Citrine Informatics enables you to not hire a data scientist or two and instead allows someone like me (not a data scientist) to build my own models for whatever system I’m working on. By working on the model yourself, instead of through a data scientist, you can incorporate your expertise directly and iterate quickly. In polymeric products where formulation is essential for product development, like polyurethane foams or waterborne emulsions, I think this approach is the way.
Why 3D Printing Buildings Leads to Problems
Heuristics on the high seas: Mathematical optimization for cargo ships
Google’s Operations Research team is proud to announce the Shipping Network Design API, which implements a new solution to the most efficient routes for shipping. Our approach scales better, enabling solutions to world-scale supply chain problems, while being faster than any known previous attempts. It is able to double the profit of a container shipper, deliver 13% more containers, and do so with 15% fewer vessels. Read on to see how we did it.
There are three components to the Liner Shipping Network Design and Scheduling Problem (LSNDSP). Network design determines the order in which vessels visit ports, network scheduling determines the times they arrive and leave, and container routing chooses the journey that containers take from origin to destination. Every container shipping company needs to solve all three challenges, but they are typically solved sequentially. Solving them all simultaneously is more difficult but is also more likely to discover better solutions.
Solutions to network design create service lines that a small set of vessels follow: for instance, sailing between eastern Asia, through the Suez canal, and to southern Europe. These service lines are published with dates, so that shippers can know when and where to have their containers ready at port.
Unveiling High NA EUV
New Product Introduction
Highlighting new and innovative facilities, processes, products, and services
Introducing Aurora: The first large-scale foundation model of the atmosphere
A recent study by Charlton-Perez et al. (2024) underscored the challenges faced by even the most advanced AI weather-prediction models in capturing the rapid intensification and peak wind speeds of Storm Ciarán. To help address those challenges, a team of Microsoft researchers developed Aurora, a cutting-edge AI foundation model that can extract valuable insights from vast amounts of atmospheric data. Aurora presents a new approach to weather forecasting that could transform our ability to predict and mitigate the impacts of extreme events—including being able to anticipate the dramatic escalation of an event like Storm Ciarán.
Aurora’s effectiveness lies in its training on more than a million hours of diverse weather and climate simulations, which enables it to develop a comprehensive understanding of atmospheric dynamics. This allows the model to excel at a wide range of prediction tasks, even in data-sparse regions or extreme weather scenarios. By operating at a high spatial resolution of 0.1° (roughly 11 km at the equator), Aurora captures intricate details of atmospheric processes, providing more accurate operational forecasts than ever before—and at a fraction of the computational cost of traditional numerical weather-prediction systems. We estimate that the computational speed-up that Aurora can bring over the state-of-the-art numerical forecasting system Integrated Forecasting System (IFS) is ~5,000x.
A new way to decarbonise steelmaking - BioIron
BioIron™ uses raw biomass and microwave energy instead of coal to convert Pilbara iron ore to iron and has the potential to support low carbon dioxide (CO2) steelmaking. Our modelling shows that when combined with renewable energy and carbon-circulation by fast-growing biomass, BioIron™ has the potential to reduce CO2 emissions by up to 95% compared with the current blast furnace method.
We have proven the process works at a small-scale pilot plant, and now we’re planning to test it on a larger scale at our new BioIron™ Research & Development Facility. The development of the BioIron Research and Development Facility in the Rockingham Strategic Industrial Area, south of Perth, follows successful trials of the innovative ironmaking process in a small-scale pilot plant in Germany.
The BioIron facility will include a pilot plant that will be ten times bigger than its predecessor in Germany. It will also be the first time the innovative steelmaking process has been tested at a semi-industrial scale, capable of producing one tonne of direct reduced iron per hour. It will provide the required data to assess further scaling of the technology to a larger demonstration plant.
The plant has been designed in collaboration with University of Nottingham, Metso Corporation and Western Australian engineering company Sedgman Onyx. Fabrication of the equipment will begin this year, with commissioning expected in 2026. These works are expected to support up to 60 construction jobs.
Business Transactions
This week's top funding events, acquisitions, and partnerships across industrial value chains.
Viaduct Raises $10 Million in Series B Funding Round
Viaduct, a developer of pioneering AI technology that identifies, solves and predicts product failures, announces the close of a $10 million Series B funding. The round was led by FM Capital, a venture capital firm which invests in the people and technologies that are transforming the automotive and transportation industries. FM Capital was joined by Innovation Endeavors, Exor Ventures, Stellantis Ventures and Sumitomo Rubber.
The company will use the proceeds to accelerate both business development and deployments for its solution that helps customers improve product quality, boost customer satisfaction and drive operational efficiency. Viaduct’s patented TSI Engine is the only AI-powered solution that intelligently and automatically analyzes thousands of variables hidden in terabytes of data to discover patterns of health, defects and performance in products across a wide range of industries.
iCOMAT raises $22.5M financing led by 8VC and NATO Innovation Fund to automate composites manufacturing
iCOMAT, a pioneer in advanced composite manufacturing, announced the successful closure of its Series A funding round, securing $22.5 million in capital. The round was led by 8VC, and co-led by NATO Innovation Fund. Other investors joining the round include Syensqo Ventures and existing investors Velocity Partners VC.
iCOMAT’s automated and scalable manufacturing technology, the first of its kind, is delivering lighter, stronger and more sustainable structures for aerospace and automotive vehicles. iCOMAT’s technology leverages a breakthrough in composite materials and carbon fiber. Unlike conventional methods, which produce components by stacking multiple straight fiber layers, iCOMAT has developed the world’s first production technology that enables fiber steering – the ability to steer the fibers to optimise the properties of a structure at any point. This innovative technology can help reduce weight by 10 to 65 percent compared to the state-of-the-art commercial solutions, and can increase production rates by 10x.
SiTration Raises $11.8 Million for Critical Metals Recovery
SiTration, a materials recovery company serving the mining and metals industries, announced it has raised $11.8 million in seed capital. The financing round was led by 2150 with participation from BHP Ventures, Extantia, and Orion Industrial Ventures. Previous investors Azolla Ventures and MIT-affiliated E14 Fund also participated in the oversubscribed round. The funding will be used to scale the company’s novel solution for the recovery of critical metals and minerals and to deploy pilot systems with commercial partners.
Founded as a spinoff from research conducted at MIT, SiTration is working to address the demand for critical materials needed to manufacture technologies that are key to the clean energy transition, including electric motors, wind turbines, and batteries. The company’s innovative solution lowers both the cost and the resource intensity of extracting and recycling materials, contributing to the overall push towards a circular economy.
Momenta leads Investment in Luffy AI, Adaptive AI for Industrial Optimization
Momenta, the leading Industrial Impact® venture capital firm, has announced its latest investment in Luffy AI, a Cambridge, UK-based leader in adaptive AI for industrial control. This strategic funding aims to advance industrial processes and enhance operational outcomes.
Luffy’s Adaptive Intelligence Framework, driven by neuroplasticity, offers unparalleled computational efficiency and supports edge deployments of optimized industrial control applications. This innovative technology enables control systems to continuously learn and adapt, making them more resilient and effective than traditional AI models. By integrating simpler digital twin models with self-optimizing neural networks, Luffy’s solution provides numerous benefits, such as reduced maintenance costs, improved explainability, and a heightened ability to manage uncertainty or unexpected events.
Materialise and ArcelorMittal Announce Partnership to Enhance Metal 3D Printing Capabilities
Materialise, a global leader in 3D printing software and services, and ArcelorMittal Powders, a business unit of ArcelorMittal established to produce high-quality steel powders, have signed a memorandum of understanding (MOU) to create solutions to optimize laser powder bed fusion (LPBF) equipment and metal 3D printing strategies. Through the MOU, ArcelorMittal will use Materialise’s next-gen build processor for 3d printers.
The two companies are partnering to develop solutions that integrate Materialise’s next-gen build processor and ArcelorMittal Powders’ AdamIQTM range of steel powders to enhance LPBF, the most widely used additive manufacturing technology for producing metal parts. Build processors link 3D printers with data preparation software, streamlining the additive manufacturing process from design to print. Materialise’s next-gen build processor supports larger build volumes and more complex geometries than traditional build processors, so users will be able to customize process parameters, streamline workflows and print faster. Combined with the AdamIQTM steel powders made specifically for additive manufacturing applications, these printing solutions help improve setup and production speed, part quality, cost-efficiency, reproducibility and repeatability.
Cognite and Equinor Enter Robotics Collaboration To Accelerate Autonomous Industry
Cognite, a globally recognized leader in industrial software, announced a joint robotics project with Equinor, an international energy company, to improve Health, Safety, and Environment (HSE) initiatives at the company’s onshore facility Mongstad, outside of Bergen, Norway.
Developed in conjunction with Adigo and Createc, the project establishes robust routines, systems, and standards governing the utilization of robots within onshore facilities. To enhance safety in hazardous environments, the project will employ a combination of robots, IP cameras, and IoT sensors for remote inspections throughout Mongstad.
Adigo recently launched the new generation of the versatile robot platform VÅK, capable of handling heavy payloads (30kg) and long working hours (8h) before autodocking for charging. VÅK will be used for autonomous transport of water samples from several points in the water treatment plant, operating 24/7. At each sampling point, Adigo installed a system to deliver fluid samples to the robot. Adigo VÅK will drastically reduce the need and presence of personnel in hazardous areas.