Swedish AI company Cetasol has raised €2.3m ($2.7m) in a seed funding round to scale its AI-driven decision support and digital twin technology to reduce fuel use for ships. The investment was co-led by BackingMinds and Shift4Good, with ongoing support from existing investor Sarsia. Cetasol’s primary product, iHelm, is designed to collect data from vessels and uses the company’s digital twin technology for both vessel and engine. The system processes information through edge computing and provides the c ...

Summary of SKF Tech and Innovation Summit 2025 Company and Industry Overview - **Company**: SKF (OTCPK:SKFR.Y) - **Industry**: Engineering and manufacturing, focusing on bearings and sealing solutions across various sectors including food and beverage, agriculture, and mining Key Trends and Innovations 1. **Industry Trends**: - Electrification, automation, and agile workforce are reshaping customer operations [7] - Shift from just-in-time to just-in-case supply chains emphasizing resilience and localization [9] - Demand for adaptability, strategic collaboration, and long-term value from customers [9] 2. **Emerging Technologies**: - Advanced materials and artificial intelligence are enhancing durability and sustainability [10] - Digital twin technology is revolutionizing product development and performance monitoring [29][30] Product Innovations and Solutions 1. **Food and Beverage Industry**: - SKF Food Line ball bearing units designed for high hygiene standards, reducing cleaning water usage by up to 33% [20] - Fully sealed and greased for life, minimizing maintenance and contamination risks [19][20] 2. **Agricultural Solutions**: - Introduction of AgriHub T400, designed for harsh conditions, featuring a super mud block seal that offers four times the sealing performance of conventional solutions [65] - Modular designs allow OEMs to customize solutions for various agricultural needs [68] 3. **Mining and Conveyor Systems**: - Development of a compact conveyor pulley housing with improved sealing to withstand extreme conditions, reducing downtime and maintenance [115][117] - Over 5,000 units delivered globally, showcasing scalability and adaptability [117] Sustainability and Efficiency - Emphasis on reducing environmental impact through innovative designs that lower lifecycle costs and resource consumption [25][81] - Digital solutions like the SKF Observer Pi Connector enhance data utilization for better decision-making and operational efficiency [83][89] Customer Collaboration and Value Creation - SKF aims to transition from being a supplier to a long-term partner, focusing on lifecycle costs and sustainability [27][50] - Collaborative design processes with customers to enhance product development and operational efficiency [54][106] Conclusion - SKF is committed to driving innovation that combines performance with sustainability, addressing the evolving needs of various industries while minimizing environmental impact [118][126]

Core Insights - DXC Technology has partnered with ISA Vías to implement a Digital Twin platform aimed at enhancing road safety on the Ruta del Maipo in Chile, which serves over 7 million vehicles monthly [1][3][4] Group 1: Collaboration and Technology Implementation - The Digital Twin technology creates a real-time virtual model of the roadway, allowing ISA Vías to simulate various emergency scenarios without disrupting traffic [3][4] - This collaboration is seen as a significant advancement in modernizing Chile's infrastructure, improving safety protocols, and optimizing traffic management [4][5] Group 2: Benefits and Future Plans - The Digital Twin platform provides real-time insights for better traffic flow, predictive maintenance, and data-driven decision-making, ultimately enhancing operational efficiency and safety [4][5] - Plans for expansion include additional highways and tunnels, setting a new standard for critical infrastructure protection in Latin America [4][5] Group 3: Company Overview - DXC Technology specializes in helping global companies modernize IT and optimize data architectures while ensuring security and scalability across various cloud environments [6][7] - The company operates with a workforce of over 120,000 professionals across more than 70 countries, delivering innovative solutions that reshape industries [5][6]

Investment Rating - The report assigns an "In-Line" investment rating to the Capital Goods sector in Europe [4]. Core Insights - The report emphasizes that early adopters of AI with pricing power in the Capital Goods sector are likely to capture significant benefits, particularly in margin expansion [3][7]. - Six key use cases for AI adoption are identified, which include enhancing sales processes, utilizing AI chatbots, predictive maintenance, product design and testing, inventory management, and energy management [7][32]. Summary by Sections Investment Rating - The Capital Goods sector is rated "In-Line" [4]. AI Adoption Overview - AI adoption in the Capital Goods sector has seen a notable increase compared to the previous year, with a focus on identifying companies that have made significant strides in AI integration [3][27]. - The report highlights that only 9% of global industrial companies classified as AI adopters possess high pricing power, indicating a substantial opportunity for early adopters in the sector [29]. Key Use Cases - **Sales Processes**: AI is used to automate customer quotes and enhance sales strategies, with Rexel implementing an automated request for quotes system [9][34]. - **AI Chatbots**: Both internal and external chatbots are deployed to improve efficiency in customer service and internal operations, with Schneider Electric utilizing chatbots for customer inquiries [10][41]. - **Predictive Maintenance**: Companies like KONE leverage AI to enhance maintenance processes, significantly reducing unscheduled call-outs and improving fault identification [11][52]. - **Product Design and Testing**: AI tools are integrated into R&D to streamline product development, as seen with KONE's use of generative AI for rapid prototyping [12][47]. - **Inventory Management**: AI is applied to optimize inventory levels and supply chain efficiency, with Rexel reporting increased sales through AI-assisted inventory management [13][53]. - **Energy Management**: AI technologies are utilized to forecast and optimize energy consumption, with Schneider Electric achieving significant energy savings through AI integration [14][55]. Company Highlights - **Rexel**: Recognized for its extensive AI use cases, including customer churn algorithms and automated pricing models, which have led to substantial revenue increases [15][34]. - **KONE**: Noted for its proactive application of AI in maintenance and service offerings, enhancing operational efficiency and customer satisfaction [18][52]. - **Schneider Electric**: Acknowledged for its strong focus on energy management and inventory optimization through AI, contributing to significant productivity savings [19][55].

Group 1: Infrastructure Challenges - Traditional infrastructure is facing systemic shortcomings in risk resilience and emergency response efficiency due to outdated design standards and insufficient disaster resistance [1] - Current infrastructure design standards are primarily based on historical disaster data, which are inadequate for the increasing frequency of extreme weather events [1] - Monitoring methods are lagging, with low coverage of intelligent monitoring systems, making it difficult to detect structural damage in aging infrastructure [1] Group 2: Advancements in Urban Infrastructure - The acceleration of new urban infrastructure construction, particularly through the application of artificial intelligence, is reshaping urban disaster prevention systems [2] - The integration of digital construction, smart facilities, and information platforms significantly enhances data collection, analysis, and forecasting capabilities for urban infrastructure [2] - Technologies like digital twins are enabling simulation-based urban governance, allowing managers to optimize emergency response plans in virtual environments [2] Group 3: Disaster Management in Zhejiang - Zhejiang faces significant risks from typhoons and secondary disasters, necessitating advanced disaster management strategies [3] - The province has developed the first national resilience disaster prevention model, integrating comprehensive risk assessment and decision support systems [3] - This model can provide real-time forecasts of various risks and assist in decision-making for population relocation and resource allocation [3] Group 4: Resilience of the Power Grid - The extensive power grid system in Zhejiang is vulnerable to natural disasters, making it crucial to enhance its disaster resilience [4] - The State Grid Zhejiang Electric Power Company has established a comprehensive disaster resilience model that incorporates advanced technologies for risk forecasting and assessment [4] - This model enables dynamic risk predictions for power grid equipment during disasters and supports optimal decision-making across various stages of disaster management [4]