Capturing this week's zeitgeist
This week's most influential Industry 4.0 media.
Custom Machine Builder Develops Automation Solution That Increases Production Capacity Four-Fold
While the metal housing and circuit boards were made efficiently and cost-effectively in high numbers, adhering three plastic covers to each housing with a quality seal was slow and labor-intensive. When this electronic component was first introduced, low output was not a problem. As demand for the component increased, however, the bottleneck of plastic cover application became a concern. The manufacturer asked KAMP Automation to design an automated machine that would significantly expand capacity and ensure quality seals for the adhered plastic covers.
In the new automated process, the machine operator places two die-cast metal housings on fixtures and six plastic covers on a cover fixture (three covers for each housing). Vacuum holds the metal housings and plastic covers in place. Manually loading the machine made sense from a cost standpoint and only required seconds. Housings and covers in place, the operator starts the machine.
‘Revolutionary’ digital printing technology uptake expected to accelerate for packaging
The whir of a digital inkjet printer that spits out crisp, vibrant documents in mere seconds is a familiar reference to most Americans. Just as this innovation transformed home and office printing when it replaced legacy tools like the dot matrix printer, industrial-scale digital inkjet technology is now transforming the packaging space. Digital printing, on the other hand, does not rely on plates. Designers develop the desired image in a computer program and send the digital file to the inkjet mechanism that sprays ink droplets directly onto the packaging medium.
“Print is the traditional bottleneck in a converting facility, and if you remove that bottleneck you can streamline both upstream and downstream processes,” Wettersten said. “That’s where transformation begins to occur with digital printing, aligning systems and workflow and enabling new capabilities around responsiveness and flexibility.”
“What we’re seeing today is large corrugated companies starting to invest in web presses to totally change workflow,” he said. “The impact on lead times is rather eye-opening: You can take conventional lead times of 18 to 20 days for repeat orders down to fewer than five days on a digital press.”
Predictive Maintenance 3D Simulation Use Case
OT-IT Integration: AWS and Siemens break down data silos by closing the machine-to-cloud gap
AWS announced that AWS IoT SiteWise Edge, on-premises software that makes it easy to collect, organize, process, and monitor equipment data, can now be deployed directly from the Siemens Industrial Edge Marketplace to help simplify, accelerate, and reduce the cost of sending industrial equipment data to the AWS cloud. This new offering aims to help bridge the chasm between OT and IT by allowing customers to start ingesting OT data from a variety of industrial protocols into the cloud faster using Siemens Industrial Edge Devices already connected to machines, removing layers of configuration and accelerating time to value.
Customers can now jumpstart industrial data ingestion from machine to edge (Level 1 and Level 2 OT networks) by deploying AWS IoT SiteWise Edge using existing Siemens Industrial Edge infrastructure and connectivity applications such as SIMATIC S7+ Connector, Modbus TCP Connector, and more. You can then securely aggregate and process data from a large number of machines and production lines (Level 3), as well as send it to the AWS cloud for use across a wide range of use cases. This empowers process engineers, maintenance technicians, and efficiency champions to derive business value from operational data that is organized and contextualized for use in local and cloud applications, unlocking use cases such as asset monitoring, predictive maintenance, quality inspection, and energy management.
Generative AI for Process Systems Engineering
LLM-based Control Code Generation using Image Recognition
LLM-based code generation could save significant manual efforts in industrial automation, where control engineers manually produce control logic for sophisticated production processes. Previous attempts in control logic code generation lacked methods to interpret schematic drawings from process engineers. Recent LLMs now combine image recognition, trained domain knowledge, and coding skills. We propose a novel LLM-based code generation method that generates IEC 61131-3 Structure Text control logic source code from Piping-and-Instrumentation Diagrams (P&IDs) using image recognition. We have evaluated the method in three case study with industrial P&IDs and provide first evidence on the feasibility of such a code generation besides experiences on image recognition glitches.
ipolog Factory Viewer: Revolutionieren Sie Ihre 3D-Planung
Explainable generative design in manufacturing for reinforcement learning based factory layout planning
Generative design can be an effective approach to generate optimized factory layouts. One evolving topic in this field is the use of reinforcement learning (RL)-based approaches. Existing research has focused on the utilization of the approach without providing additional insights into the learned metrics and the derived policy. This information, however, is valuable from a layout planning perspective since the planner needs to ensure the trustworthiness and comprehensibility of the results. Furthermore, a deeper understanding of the learned policy and its influencing factors can help improve the manual planning process that follows as well as the acceptance of the results. These gaps in the existing approaches can be addressed by methods categorized as explainable artificial intelligence methods which have to be aligned with the properties of the problem and its audience. Consequently, this paper presents a method that will increase the trust in layouts generated by the RL approach. The method uses policy summarization and perturbation together with the state value evaluation. The method also uses explainable generative design for analyzing interrelationships between state values and actions at a feature level. The result is that the method identifies whether the RL approach learns the problem characteristics or if the solution is a result of random behavior. Furthermore, the method can be used to ensure that the reward function is aligned with the overall optimization goal and supports the planner in further detailed planning tasks by providing insights about the problem-defining interdependencies. The applicability of the proposed method is validated based on an industrial application scenario considering a layout planning case of 43 functional units. The results show that the method allows evaluation of the trustworthiness of the generated results by preventing randomly generated solutions from being considered in a detailed manual planning step. The paper concludes with a discussion of the results and a presentation of future research directions which also includes the transfer potentials of the proposed method to other application fields in RL-based generative design.
New Product Introduction
Highlighting new and innovative products and services
Universal Robots continues its innovation journey by launching new 30 kg collaborative robot
Universal Robots, the Danish manufacturer of collaborative robots (cobots), has announced that it will expand its leading product portfolio with a new 30 kg payload cobot. UR30 is the second in Universal Robot’s new series of innovative, next generation cobots and is built on the same architecture as the award-winning UR20. Despite its compact size, UR30 offers extraordinary lift, and its superior motion control ensures the perfect placement of large payloads allowing it to work at higher speeds and lift heavier loads.
This makes UR30 ideal for several applications, including machine tending, material handling and high torque screw driving. For machine tending, the high payload brings new possibilities as it allows the cobot to use multiple grippers at the same time. This means it can remove finished parts and load more material in one single pass, shortening changeover times and maximizing productivity. UR30 will also effectively support high torque screw driving as it can handle larger and higher-output torque tools, and thanks to a steady mode feature UR30 delivers straight and consistent screw driving. This will be beneficial in, for example, the automotive industry.
Fast and efficient PLC code generation and more with artificial intelligence
TwinCAT Chat was developed to offer users a clear advantage over the conventional use of, for example, ChatGPT in the web browser. The key added value lies in its deep integration, especially with regard to the specialized requirements of the automation industry. The core features include the direct integration of the chat function into the development environment (IDE). This greatly simplifies the development process, as communication and code exchange are seamlessly integrated. Furthermore, the basic initialization of our model has been tailored specifically to TwinCAT requests. This way you can ask your specific questions directly and don’t have to tell the model that you are using TwinCAT and expect the code examples in Structured Text. Another highlight is the ability to easily adopt generated code. This not only saves developers time, but also reduces human errors that can occur during manual transfers. Interaction with TwinCAT Chat has been designed in such a way that the need to type commands is reduced to a minimum. Instead, the user can simply click on pre-tested requests that are specifically designed to improve their workflow. These requests include actions such as:
- Optimize: The system can make suggestions to increase the performance or improve the efficiency of the code.
- Document: TwinCAT Chat helps to create comments and documentation so that the code is easier for other team members to understand.
- Complete: If code fragments are missing or incomplete, our system can generate suggestions to complete them to ensure functionality.
- Refactoring: TwinCAT Chat can refactor code according to certain guidelines and policies so that it is more in line with company guidelines.
Overall, this system provides an efficient and intuitive user interface that greatly facilitates the development process.
How governments are shaping the future industrial landscape.
🇰🇷 South Korean defence industry rides global order wave
South Korea, was the world’s ninth-largest seller of arms in 2022 up from 31st place in 2000, according to the Stockholm International Peace Research Institute. Because South Korea produces armaments at a larger scale than many of its western competitors, it can offer better value for money on assets such as tanks and howitzers and lower-end fighter jets.
Korean exporters are also assisted by the government, including its willingness to step in and place orders so as to keep production lines “hot” in the absence of orders from abroad.
Seoul has devised a “niche marketing strategy for countries newly seeking to invest and develop their own defence industrial bases”, setting up production in the buying country while offering generous terms on tech transfer, said Haena Jo, research analyst at the International Institute for Strategic Studies (IISS) in London.
🇲🇽 The city where Mexico’s nearshoring hype is becoming reality
Monterrey, a business-friendly city a few hours’ drive from Texas, is a bellwether for Mexico’s ability to reap the rewards of nearshoring — a shift that is taking place thanks to the coronavirus pandemic, trade tariffs between the US and China, and geopolitical instability since Russia invaded Ukraine. “A week doesn’t go by for us without meeting Chinese, Korean, Japanese executives, looking to open offices or a plant,” said Lorenzo Barrera Segovia, chief executive of Banco Base, a bank based in the city.
“Monterrey and the rest of the country has a deficit in terms of planning… in terms of giving a strategic direction to economic growth,” said Roberto Durán, professor at the Tecnológico de Monterrey university. Unresolved national structural problems — such as corruption and the lack of competition in the economy — cause some observers, like Jason Tuvey, emerging markets economist at Capital Economics, to doubt that the external forces will be transformative for Mexico.
🇪🇺 ABB signs €500 million EIB financing to further drive smart and sustainable electrification technologies
ABB and the European Investment Bank (EIB), the lending arm of the European Union, have signed a €500 million financing agreement to support ABB’s research and development in its Electrification business area. The EIB financing supports the European Green Deal, the European Union’s plan to become net zero by 2050. Investment in green innovation is necessary for Europe to create a sustainable economy capable of protecting its people and creating high-quality jobs.
This week's top funding events, acquisitions, and partnerships across industrial value chains
Braincube raises €83 million of growth equity investment from Scottish Equity Partners and Bpifrance - Braincube
Braincube, a market-leading manufacturing data software platform with specialist industrial applications, has raised €83 million of growth equity investment. The investment was led by Scottish Equity Partners (‘SEP’).
Braincube’s Industrial Internet of Things (‘IIoT’) platform helps manufacturers increase their profits using data insights to improve quality, productivity, and sustainability in their factories. Production line optimisations, resulting from Braincube’s use-case driven framework and proprietary AI, have already saved customers more than $10 billion, and have reduced carbon emissions by 2.5 million tonnes.
Braincube’s customer base spans several Manufacturing verticals, with a particular specialism in the food and beverage, pulp and paper, building materials, and tires and plastics sectors. Customers include leading global manufacturing companies such as Bridgestone and International Paper.
PhysicsX raises €29.2M to reinvent AI and simulation engineering technologies
London-based PhysicsX, a deep-tech startup building artificial intelligence(s) to power engineering, has secured $32M (approximately €29.2M) in a Series A round of funding. The investment was led by General Catalyst. The round also saw participation from Standard Investment, NGP, Radius Capital, and KKR co-founder and co-executive chairman, Henry Kravis. PhysicsX plans to expedite its growth in customer delivery, product development, and fundamental research.
The startup uses generative AI to facilitate groundbreaking engineering solutions across various advanced industries such as automotive, aerospace, renewables, and materials production.
Expedition Growth Capital and EIFO invest $16 Million in Factbird to boost international growth
The Danish tech company Factbird, which supplies intelligent, cloud-based technology for the optimization of manufacturers production lines, has once again landed a large multi-million dollar investment. This time, it is USD 16 million. The money comes from the English capital fund Expedition Growth Capital and Denmark’s Export and Investment Fund, EIFO. The funds will help Factbird’s international expansion after its 2021 separation from consulting firm Emendo Consulting Group as an independent tech company.
Factbird has grown by 300% since 2021. The customer portfolio today counts more than 250+ companies within the pharmaceutical, packaging, industrial equipment and devices, and food and beverage industries across the key markets in the Nordics, USA, Germany, and England.
Retrocausal Raises Oversubscribed $5.3M Round to Meet Increased Demand for its Generative AI Manufacturing Assembly Optimization Solution
Retrocausal, a leading platform provider for manufacturing process management, today announced a $5.3M financing round co-led by Glasswing Ventures, One Way Ventures, and Indicator Ventures, along with participation from existing investors Argon Ventures, Differential Ventures, Ascend Vietnam Ventures, Incubate Fund US, SaaS Ventures, Hypertherm Ventures, Stage Venture Partners, and Techstars.
Funding will be used to meet the increased market demand for its proprietary generative AI technology, Retrocausal’s Kaizen Copilot software for Manufacturing Assembly Optimization. Retrocausal’s solution simplifies manual assembly operations and the underlying processes to empower the low-skilled workforce to take on high-skill manufacturing jobs. Retrocausal’s Copilot software allows an untrained worker to become productive on a new process within five minutes and deliver the productivity and quality of someone who has had months of training, resulting in 25% greater First Time Yields (FTY) and 90% less assembly-related scrap costs.
Unchained Robotics raises €5.5 M to unlock the future of automation
Unchained Robotics advanced its goal to make plug-and-play robotics accessible in industry with a €5.5 million raise. It brings the company’s funding to €7.7 million. Robotics and automation technology can support and compensate for the lack of skilled workers. However, for German SMEs in particular, automation technology is often too high a barrier to entry. Unchained Robotics wants to change this with its simple, transparent, independent automation solution. Unchained Robotics offers plug-and-play automation solutions that can automate logistics and metalworking processes in factories within a few hours.
Future Industry Ventures, a joint venture between SBI Holdings and Redstone, led the round. Unchained Robotics aims to use the investment to expand its sales and services and to serve the booming demand for its new MalocherBot into a broader range of applications.
AI for industry: Schaeffler and Siemens bring Industrial Copilot to shopfloor
To support engineers with various automation tasks, the AI-powered assistant is connected to Siemens’ engineering framework Totally Integrated Automation (TIA) Portal via the open API TIA Portal Openness. The Industrial Copilot helps Schaeffler’s automation engineers to generate code faster for programmable logic controllers (PLC), the devices that control most machines throughout the world’s factories. Engineering teams can significantly reduce time, effort, and the probability of errors by generating PLC code through natural language inputs.
Siemens Industrial Copilot has access to all relevant documentation, guidelines and manuals to assist shopfloor workers with identifying possible errors. These capabilities enable maintenance teams to identify errors and generate step-by-step solutions more quickly. This will help to significantly reduce machine downtime, make industrial companies more efficient and thus support sustainability efforts.
HP and Materialise Partner to Drive Volume 3D Printing
As an HP preferred partner, Materialise will provide the industry with an end-to-end manufacturing solution that is integrated with an additive technology that is designed for productivity and scale — MJF and Metal Jet systems. As part of this partnership, HP will help customers identify meaningful use cases for the software platform, as well as showcase the solution at HP demo facilities and public events.
The seamless connectivity between HP AM technology and Materialise CO-AM enables users to create workflows that improve traceability, quality control, and machine utilization. Optimized 3D print job management allows production leads to track planned and actual printer activities and optimize machine time. To ensure continuous production, real-time machine monitoring provides operators and engineers with critical process data, including build status, material usage, and machine sensor data. This data can be collected and stored in log files of 3D-printed jobs to enhance traceability and quality control. In addition to their 3D printers, Metal Jet users can connect process-relevant HP machinery to the CO-AM platform, such as the Powder Management Station, Curing Station, and Powder Removal Station. This integration allows Metal Jet users to streamline the post-processing of metal parts within the manufacturing process.