Breaking the Bottleneck | Issue 37
[1/16/2023] Sony XR for 3D Design, Microsoft's New Material Discovery, Nvidia Isaac Updates, & 2023 Automotive Readiness for Software Defined Vehicles
Breaking the Bottleneck is a weekly manufacturing technology newsletter with perspectives, interviews, news, funding announcements, manufacturing market maps, and a startup database!
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News:
Sony Launches XR HMD for 3D Design [Sony]
Siemens and Sony have introduced a new system that brings together virtual reality (VR) and industrial software, enabling engineers and designers to collaborate seamlessly in a "borderless immersive workspace" within the industrial metaverse. The platform combines Siemens' Xcelerator software with Sony's spatial content creation system, which includes a high-quality VR headset and controllers. This technology offers features like 4K OLED displays, spatial recognition with cameras and sensors, and video 'see-through' functionality, allowing users to overlay virtual designs onto their physical environment. The system includes controllers for manipulating objects and precise pointing in virtual space while wearing the headset. Siemens' software powers this system, allowing designers and engineers to create and explore design concepts in this immersive environment. The product is known as Siemens' NX Immersive Designer and is set to be available later this year.
Robots Execute Complex Plans More Accurately w/Multiple AI Models [MIT]
The MIT Improbable AI Lab developed a new framework called Compositional Foundation Models for Hierarchical Planning (HiP) to help robots perform complex tasks that involve multiple steps. Unlike traditional approaches that require paired vision, language, and action data, HiP uses three different foundation models, each trained on different data modalities removing the need for access to expensive paired data and making the decision-making process more transparent. HiP operates as a hierarchy with three components:
A large language model (LLM) that captures symbolic information and develops an abstract task plan based on common-sense knowledge.
A video diffusion model that collects geometric and physical information about the world from internet footage and generates an observation trajectory plan.
An egocentric action model that uses first-person images to determine how to execute each task within the long-horizon goal.
HiP has been tested on various manipulation tasks and outperformed comparable frameworks. It has the potential to assist with household chores, construction, and manufacturing tasks.
Microsoft Discovered New Battery Material Using AI [Microsoft]
Microsoft, in partnership with the Pacific Northwest National Laboratory (PNNL), leveraged AI and advancements in chemistry and materials science to rapidly explore and discover a novel battery material. The AI model efficiently evaluated a vast array of potential materials and was identified through a series of filters, such as stability, reactivity, and energy-conducting potential. The model significantly reduced the initial pool of 32 million candidates to about 500,000, with only 800 remaining after subsequent filtration steps. The HPC component, known for its accuracy but computationally intensive nature, played a vital role in narrowing the selection further. Molecular dynamics simulations, a combination of AI and HPC, scrutinized the movements of atoms and molecules within each material, ensuring the most suitable candidates were retained. This multi-tiered process culminated in a shortlist of 150 promising materials, which were further assessed for practicality, including factors like cost and availability. Ultimately, 23 candidates emerged from this accelerated material discovery journey, with five among them already known. the newfound material is a solid-state electrolyte, offering the promise of greater safety & efficiency, and is noteworthy for its reduced lithium content, which could potentially decrease lithium usage by as much as 70%. Furthermore, what’s surprising is that this material incorporates both lithium and sodium ions, two elements typically considered incompatible due to their similar charges and different sizes.
Generative AI Powers Smarter Robots With NVIDIA Isaac Platform [NVIDIA]
Siemens and Voltaiq Collaborate to Optimize Battery Manufacturing [Voltaiq]
Siemens and Voltaiq have joined forces to create a solution aimed at accelerating battery manufacturing. Siemens' Insights Hub and Voltaiq's battery-specific monitoring, visualization, and advanced analytics capabilities provide an end-to-end solution for managing and optimizing battery cell manufacturing. The solution focuses on the critical finishing stage of battery production, helping to reduce the risk of discovering problems late in the process, which can impact yield and profitability. Voltaiq's technology allows for early detection of cell anomalies, improving product quality and reducing scrap rates. The solution is compatible with existing equipment and can be implemented quickly reducing the burden on the workforce.
Inside Boeing’s Manufacturing Mess [WSJ]
“The performance of the prime manufacturer can never exceed the capabilities of the least proficient of the suppliers,” Hart-Smith wrote. “These costs do not vanish merely because the work itself is out-of-sight.”’
Boeing's outsourcing strategy for its aircraft components, which was in place before engineer John Hart-Smith's above warning in 2001, has become a subject of scrutiny. Boeing's approach involves having numerous factories around the world produce key pieces of aircraft components, which are then assembled by Boeing. This decentralized manufacturing system has created challenges in maintaining consistent quality and oversight, with the prominent example being Spirit AeroSystems. Spirit was once praised by Boeing as an exemplary partner, but it has faced its share of production problems and quality lapses since taking on a substantial portion of Boeing's work. It is the sole supplier of fuselages for many Boeing aircraft, including the one involved in the Alaska Airlines emergency landing. Spirit's financial difficulties, exacerbated by the MAX grounding and the COVID-19 pandemic, led to layoffs, which left the company short of experienced workers when demand for its products rebounded. Some Spirit employees have reported that production problems were common, and internal complaints about quality were often ignored. The pressure to meet production quotas and deadlines led to a rushed work environment, potentially resulting in undetected defects in aircraft components. The Federal Aviation Administration (FAA) announced this week that it has decided to increase oversight of Boeing's manufacturing processes.
3D Printing Technology Launched at CES [3D Printing Industry]
Companies like Creality, Formlabs, Siemens, Goofoo, and Doser presented new 3D printers and manufacturing solutions at CES 2024.
Formlabs' Resin-Based 3D Printing: Formlabs introduced a resin pumping system and two new materials (Polypropylene Powder and Premium Teeth Resin) to improve efficiency, versatility, and scalability in prototyping.
DoserRx1 for Personalized Medication: Doser unveiled the DoserRx1, a desktop 3D printer designed for producing personalized pharmaceutical pills. It uses semi-solid extrusion (SSE) technology to produce custom dosages efficiently, offering potential benefits in medication production.
New 3D Printers from Creality: Creality launched two new FDM 3D printers, the K1C and Ender-3 V3, with high 3D printing speeds and unique features like carbon fiber filament printing for the K1C.
More 2024 Manufacturing Predictions
2024 Manufacturing Trends to Watch [Manufacturing Dive]
Predictions for the Manufacturing Industry [Manufacturer]
Research:
Automakers Readiness for Software Defined Vehicles [AlixPartners]
A survey of 180 senior executives in the automotive and technology industries conducted by AlixPartners predicts a major shift towards software-defined vehicles (SDVs) by the end of the decade. Key findings from the survey include:
Roughly two-thirds of Tier-1 auto suppliers are targeting collaboration with tech companies. That number drops to 46% for tech firms and 38% for automakers, which most plan to strengthen SDV capabilities through partnerships and relationships with Tier-1 suppliers, respectively.
For risk mitigation, 49% of automakers favor early-phase testing, while 43% of tech firms and 30% of automotive Tier-1s prefer modular-platform software design testing
38% of automakers favor model-based systems engineering for integration of software and hardware; tech companies, meanwhile, largely prefer AI for testing
To attract and retain SDV talent, automakers focus on compensation and investing in leading-edge capabilities, while tech firms and Tier-1 auto suppliers prefer a more balanced approach, including reskilling and redesigning internal processes
Podcasts:
Steel & Rubber [Industrial Revolutions]
Manufacturing Deals
Nanotronics - An industrial AI company focused on quality control and precision manufacturing for health care and biotech
[Strategic] - Strategic Partnership with OrbiMed
Xaba - An ideveloper of an AI-powered cognitive software solution to automate programming and deployment of robotics and CNC machines
$2m [Seed Extension] - BDC Capital’s Deep Tech Venture Fund and Hitachi Ventures
Weekly Planned Downtime
How Olive Oil Is Produced in Spain
Trailer For The Final Season of Curb Your Enthusiasm