There’s Nothing More Manual than Industrial Automation
Shop Talk
Capturing this week's zeitgeist
What a time to cover the technological transformation of manufacturing. Who, what, where, and how products will be produced has never been more uncertain.
- (How/What) China’s BYD has begun to flex its technological advantages with an outstanding 25% cost advantage over comparable Western models like Tesla’s Model 3.
- (Who/How/Where) Stateside, U.S. automakers and U.A.W. Remain Far Apart on labor talks, prompting the question of whether the U.S. automakers will be able to navigate platform shifts.
- (Where) China’s EV battery manufacturers are flocking to Hungary due to strong bilateral relations.
- (What) A relative laggard in electrification, Toyota, flexes its generative AI capabilities (more below).
- (Who/What) Software-defined vehicles require a new skill set.
- (Who) Huawei released its Mate 60 Pro+ smartphone, demonstrating success in beating back against U.S. sanctions.
- (Where) TSMC races to secure its future by focusing on localizing its supply chain while running into challenges getting a small-scale test production line started in Arizona.
- (How/Where) Apple hopes 3D printing technology is ready for prime-time and ramp up its key manufacturing partners, Foxconn and Luxshare, in Vietnam.
- (How) EDA technology remains a costly bottleneck to advanced chip designs (more below).
Assembly Line
This week's most influential Industry 4.0 media
🧠 AI PCB Design: How Generative AI Takes Us From Constraints To Possibilities
Cadence customers are already reaping the benefits of generative AI within our Joint Enterprise Data and AI (JedAI) Platform. Chip designers are realizing Cadence Cerebrus AI to design chips that are faster, cheaper, and more energy efficient. Now, we’re bringing this generative AI approach to an area of EDA that has traditionally been highly manual—PCB placement and routing.
Allegro X AI flips the PCB design process on its head. Rather than present the operator with a blank canvas, it will take a list of components and constraints that need to be satisfied in the end result and sift through a plethora of design possibilities, encompassing varied placement and routing options. This is hugely powerful for hardware engineers focused on design space exploration (DSE). This has long been par for the course in IC design yet it has more recently become critical to PCB due to the fact that today’s IC complexity doesn’t reduce when it gets onto the PCB—it increases.
However, it’s important to understand that this isn’t Cadence replacing traditional compute algorithms and automation approaches with AI. We remain as committed to accuracy and “correct by construction” as we’ve ever been, and while Allegro X AI is trained on extensive real-world datasets of successful and failed designs, we don’t use that data to determine correctness.
How Cloud-Native CAE Simulation Boosts Growth & Savings
From CFD analyses of aerodynamics, turbomachinery, and urban microclimates to FEA simulations of structural mechanics in automotive and consumer products, all the way to thermal analyses for indoor environments and electronics cooling, the applications for engineering simulation are numerous and can involve multiple physics. In this article, we dive into cloud simulation and CAE and find out how it strategically impacts business growth and helps optimize financial resources, enabling sustainable growth and profitability while minimizing risks. We explore in numbers how various companies from different industries have benefited from SimScale’s cloud-native simulation platform and how you can, too.
One example is ITW, a global design and engineering firm and a leading global supplier of auto parts. Using SimScale, ITW engineers conducted nonlinear static simulation and analysis to accelerate the development of plastic automotive fastening components, allowing them to minimize the insertion force of their fasteners by up to 85% while saving 10% of their R&D costs.
🧠 Toyota and Generative AI: It’s Here, and This is How We’re Using It
Toyota’s initial goal in 2016 was to engineer a resilient cloud safety system, and that led to the development of Safety Connect, a service powered by Drivelink from software company Toyota Connected North America (TCNA). The Safety Connect service is designed to leverage key data points from the vehicle to identify when a collision has occurred and send an automatic notification to call center agents. Should the driver become unconscious, telematics information can provide a more complete picture of the situation, enabling agents to contact authorities faster when it’s needed most.
Vehicle maintenance has also been a focus of AI-driven enhancements. Connected vehicles have hundreds of sensors, and we have been using data from these vehicles to build machine learning models for the most common maintenance items, including batteries, brakes, tires, and oil, and are currently investigating dozens of other components, using daily streaming data from millions of connected and consented vehicles. This suite of predictive maintenance models will help make customers aware of potential maintenance needs prior to component failures, so they can enjoy more reliable mobility experiences.
🧠 SpartanNash Leveraging AI Technology to Predict Shopper Demand, Decrease Waste
Food solutions company SpartanNash is expanding its use of Upshop’s Magic™ inventory and replenishment optimization application, to consolidate its ordering systems, maintain planogram integrity and assist with merchandising reset planning in both the center store and the produce department. The system also provides store Associates with a real-time, comprehensive view of the store’s stock to maximize assortment for guests, while at the same time reducing waste. The Magic application is specifically designed for the grocery industry, reviewing seasonal trends, promotional activity, display allocation and real-time sales data to offer actionable insights that enhance inventory accuracy and guest satisfaction
🖨️ Redwire BioFabrication Facility Successfully Prints First Human Knee Meniscus on ISS
Redwire Corporation announced that it has successfully 3D bioprinted the first human knee meniscus on orbit using its upgraded 3D BioFabrication Facility (BFF) on the International Space Station (ISS). This milestone opens the door to improved treatments for meniscal injuries, one of the most common injuries for U.S. Service Members.
The print returned to Earth onboard the SpaceX Crew-6 Mission for analysis following successful print operations in July. Before returning to Earth, the print was cultured for 14 days on the ISS in Redwire’s Advanced Space Experiment Processor (ADSEP). The print was conducted as part of the BFF-Meniscus-2 Investigation with the Uniformed Services University of the Health Sciences Center for Biotechnology (4D Bio3), a biomedical research center that explores and adapts promising biotechnologies for warfighter benefit. The investigation was conducted by NASA astronauts Frank Rubio, Warren “Woody” Hoburg, and Stephen Bowen, and UAE astronaut Sultan Al Neyadi.
🖨️ Apple Tests Using 3D Printers to Make Devices in Major Manufacturing Shift
The new technique uses a type of 3D printing called binder jetting to create the device’s general outline at close to its actual size, or what is known in manufacturing as the “near net shape.” The print is made with a powdered substance, which afterward goes through a process called sintering. That uses heat and pressure to squeeze the material into what feels like traditional steel. The exact design and cutouts are then milled like in the previous process.
Apple and its suppliers have been quietly developing the technique for at least three years. The work is still nascent and, for the time being, will be reserved for lower-volume products. Most Apple Watch casings are aluminum, not stainless steel. The company hasn’t made headway on mass-producing 3D-printed enclosures with that material, which is also used for Macs and iPads, as well as lower-end iPhones. But the company is discussing bringing materials that can be 3D-printed, like steel and titanium, to more devices.
How OSARO used Cognex to solve a tricky barcode reading challenge for Zenni Optical
📷 Making automated visual-inspection systems practical
Using supervised learning to train anomaly localization models has major drawbacks compared to images of defect-free products, images of defective products are scarce; and labeling defective-product images is expensive. Consequently, our benchmarking framework doesn’t require any anomalous images in the training phase. Instead, from the defect-free examples, the model learns a distribution of typical image features.
We have released our benchmark in the hope that other researchers will expand on it, to help bridge the gap between the impressive progress on anomaly localization in research and the challenges of real-world implementation.
🧠 This Neural Net Maps Molecules to Aromas
Using a type of deep-learning algorithm called a graph neural network, researchers have built a model that maps chemical structure to odor descriptors. The model has successfully predicted how a panel of humans would describe new smells, and it could be an important step along a long path toward digitizing smells.
The model used a specific type of graph neural network called a message-passing neural network. It was trained on a combined fragrance industry dataset of over 5,000 molecules with their structures converted into graphs and tagged with professional odor notes. Part of the research group worked at Google when the work began, and a few have since formed an offshoot company, Osmo, in January 2023, supported by Google Ventures, Alphabet’s venture capital arm.
🧠 Monitoring the misalignment of machine tools with autoencoders after they are trained with transfer learning data
CNC machines have revolutionized manufacturing by enabling high-quality and high-productivity production. Monitoring the condition of these machines during production would reduce maintenance cost and avoid manufacturing defective parts. Misalignment of the linear tables in CNCs can directly affect the quality of the manufactured parts, and the components of the linear tables wear out over time due to the heavy and fluctuating loads. To address these challenges, an intelligent monitoring system was developed to identify normal operation and misalignments. Since damaging a CNC machine for data collection is too expensive, transfer learning was used in two steps. First, a specially designed experimental feed axis test platform (FATP) was used to sample the current signal at normal and five levels of left-side misalignment conditions ranging from 0.05 to 0.25 mm. Four different algorithm combinations were trained to detect misalignments. These combinations included a 1D convolution neural network (CNN) and autoencoder (AE) combination, a temporal convolutional network (TCN) and AE combination, a long short-term memory neural network (LSTM) and AE combination, and a CNN, LSTM, and AE combination. At the second step, Wasserstein deep convolutional generative adversarial network (W-DCGAN) was used to generate data by integrating the observed characteristics of the FATP at different misalignment levels and collected limited data from the actual CNC machines. To evaluate the similarity and limited diversity of generated and real signals, t-distributed stochastic neighbor embedding (T-SNE) method was used. The hyperparameters of the model were optimized by random and grid search. The CNN, LSTM, and AE combination demonstrated the best performance, which provides a practical way to detect misalignments without stopping production or cluttering the work area with sensors. The proposed intelligent monitoring system can detect misalignments of the linear tables of CNCs, thus enhancing the quality of manufactured parts and reducing production costs.
Business Transactions
This week's top funding events, acquisitions, and partnerships across industrial value chains
H2 Green Steel raises €1.5 billion in equity to build the world's first green steel plant
The private placement is co-led by new investor Hy24, together with existing investors Altor, GIC and Just Climate. The transaction also includes new investors Andra AP - fonden and Temasek as well as a group of existing investors that continue to support H2 Green Steel with additional equity funding, including AMF, Cristina Stenbeck, Hitachi Energy, IMAS Foundation, Kinnevik, Schaeffler, Vargas and Wallenberg Investments holding company FAM.
The proceeds will finance the construction and development of H2 Green Steel’s flagship large-scale green steel plant in Boden, Sweden. Groundworks have been ongoing on the site in Boden since summer 2022, and through this transaction H2 Green Steel takes another big leap towards start of operations end of 2025.
The plant will deliver steel with up to 95 percent less CO2 emissions compared to steel produced with traditional blast furnace technology. This is made possible by replacing coal in the production process with hydrogen, produced on-site with Europe’s largest electrolyzer, using electricity from renewable sources. Next-generation technology and digitalization, along with an unmatched approach to both circularity and recycling, will make the steel plant the first of its kind.
🔋 Ascend Elements Raises $542 Million to Accelerate Production of U.S.-engineered Lithium-Ion Battery Materials
Ascend Elements, a U.S.-based manufacturer of sustainable, engineered battery materials for electric vehicles, today announced it has raised $542 million in new equity investments, including $460 million in Series D investments and $82 million of additional investments from earlier this year. Ascend Elements’ Series D round was led by Decarbonization Partners, Singapore-based investment firm Temasek, and Qatar Investment Authority (QIA). Other investors include Tenaska, Alliance Resource Partners, PULSE - CMA CGM Energy Fund, BHP Ventures, Fifth Wall, Hitachi Ventures, Mirae Asset, At One Ventures, Agave Partners, Alumni Ventures and other leading global investors.
The funding will advance construction of Ascend Elements’ Apex 1 facility in Hopkinsville, Kentucky, which will be North America’s first sustainable cathode precursor (pCAM) and cathode active material (CAM) manufacturing facility. CAM and pCAM are engineered materials made to precise microstructure specifications for use in electric vehicle batteries. While most of the world’s pCAM and CAM are made in China from primary (mined) metals, U.S.-based Ascend Elements is commercializing an ultra-efficient method to make sustainable pCAM and CAM from black mass, the traditional output of lithium-ion battery recycling facilities.
Boston Metal Closes $262M Series C Funding Round to Decarbonize Steelmaking and Disrupt the Metals Industry
Boston Metal, a global metals technology solutions company, today announced the close of its Series C fundraising, bringing the series total to $262 million. New investors include Aramco Ventures, the corporate venturing arm of Aramco; global investment manager M&G Investments; natural resource investment firm Goehring & Rozencwajg; and investment management firm Baillie Gifford. Existing investor Breakthrough Energy Ventures also joined the round, and several others made additional investments in the Series C, including Microsoft’s Climate Innovation Fund, BHP Ventures and Prelude Ventures.
The metals and mining sectors are under significant pressure to shift to more sustainable production methods while enhancing efficiency and profitability. Boston Metal is developing a scalable technology platform that uses electricity to produce a variety of metals and alloys from a wide range of feedstocks. The company’s Molten Oxide Electrolysis process is simpler, more energy efficient and has a lower environmental impact than traditional methods. With its high-value metals business, Boston Metal is empowering mining companies to create new revenue streams by deploying MOE to extract high-value metals from complex, low-concentration materials that are currently considered waste.
🦾 Mujin Secures $85M in Series C Funding to Accelerate Intelligent Robotic Automation
Mujin, a leader in intelligent robotics for manufacturing, logistics, and supply chain operations, has successfully raised $85 million in its Series C funding round, reflecting the company’s rise to market leadership. The funding round was led by SBI Investment Co., Ltd. in Japan, along with Pegasus Tech Ventures, a prominent Silicon Valley venture capital firm, 7 Industries from the Netherlands, corporate investor Accenture, and renowned angel investor Dr. James Kuffner. With this fresh infusion of capital, Mujin aims to enhance the accessibility of its revolutionary intelligent robotics platform, the MujinController, to integrators and end users, empowering them to develop new, advanced automation applications and drive further innovation.
Ambient Photonics Raises $30M in Series A2 Funding
Ambient Photonics, a pioneer in low-light energy harvesting technology for connected devices, has secured $30 million in a Series A2 funding round. The round was led by Fine Structure Ventures, affiliated with the parent company of Fidelity Investments, and included new investors Helios Climate Ventures, Regeneration.VC, and Sustainable Future Ventures. Existing investors I Squared Capital, Ecosystem Integrity Fund, and Cthulhu Ventures also joined the raise.
Ambient will leverage the funding to expand its manufacturing capabilities and drive mass-market adoption of its proprietary low-light energy harvesting technology, which replaces disposable batteries in connected devices, such as remote controls, keyboards, mice, electronic shelf labels, and sensors. The company recently inaugurated its flagship manufacturing facility in Scotts Valley, California.
Rockwell Automation signs agreement to acquire autonomous robotics leader Clearpath Robotics
Rockwell Automation, the world’s largest company dedicated to industrial automation and digital transformation, today announced it has signed a definitive agreement to acquire Ontario, Canada-based Clearpath Robotics Inc., a leader in autonomous robotics for industrial applications. Combined with Rockwell’s strong continuing partnerships in fixed robotic arms, solutions such as Independent Cart Technology, and traditional leadership in programmable logic controllers (PLCs), the addition of OTTO Motors’ AMR capabilities will create a complete portfolio of advanced material handling solutions unmatched in the industry.
The acquisition will be funded by a portion of the proceeds from the sale of Rockwell’s investment in PTC.
Anduril Industries Acquires Blue Force Technologies
Defense technology company Anduril Industries announced its acquisition of Blue Force Technologies, a developer of autonomous aircraft with an integrated aerostructures division serving a wide range of defense and commercial customers. This transaction will expand Anduril’s existing autonomous fleet to now include large high performance, group 5 aircraft and significantly increases Anduril’s reach and impact within the Department of Defense. Terms of the deal were not disclosed.
Blue Force Technologies designs and manufactures high-end composite aircraft and their components at its factories in North Carolina. Blue Force Technologies has been developing Fury, a group 5 autonomous air vehicle with fighter-like performance since 2019. Fury leverages proprietary rapid prototyping, digital engineering and an open architecture that is designed to deliver next-generation flight performance with the flexibility to integrate heterogenous sensors and payloads to support air dominance missions.
OSARO and FANUC America Collaborate to Enhance Capabilities of Robotic Warehouse Automation Solutions
OSARO®, a global leader in machine-learning-enabled robotics for e-commerce, is partnering with FANUC America, the leading supplier of CNCs, robotics and ROBOMACHINEs, to expand the capabilities of FANUC’s robotic automation solutions optimized for warehousing and e-commerce fulfillment. The two companies will collaborate on go-to-market strategies, commencing with the installation of an advanced piece-picking demonstration robot at FANUC’s Innovation Center in Rochester Hills, Michigan.