Elisa Industriq to showcase AI-powered solutions helping manufacturers to unlock the value in their existing data at Hannover Messe.
Artificial intelligence is the next frontier for manufacturers, providing tools to generate insights and value from their existing data to help them optimise operations, reduce costs and improve product quality, all while increasing efficiency and speed to market. Elisa Industriq is at the forefront of this revolution, and we will be showcasing our powerful portfolio of tools utilising AI and machine learning at Hannover Messe, 17–21 April in Hannover, Germany.
“Our vision has always been to revolutionise manufacturing by harnessing the power of AI and advanced analytics”, says Lasse Nordlund, Managing Director of Elisa Industriq. “We’re excited to demonstrate how our AI-powered solutions can help manufacturers unlock the value buried in their existing data and achieve greater efficiencies.”
Elisa Industriq was established two years ago to harness the potential of AI, machine learning and advanced analytics for the manufacturing industry. It has expanded into a family of five companies dedicated to delivering innovative solutions across various sectors, including camLine, CalcuQuote, TenForce and our strategic partner sedApta. Elisa Industriq empowers a diverse range of customers to unlock the value hidden in their existing data and processes, enhancing their competitiveness in today’s dynamic markets.
Visitors to Hannover Messe will be able to see some of Elisa Industriq’s cutting-edge AI solutions in action. These solutions enable manufacturers to optimise production schedules, reduce waste and improve product quality, all by leveraging the data they already have at their disposal.
The solutions being demoed in Hannover include:
- ML-powered anomaly detection for semiconductor manufacturers, developed with camLine, which streamlines quality control processes, swiftly identifies and addresses production issues, and boosts overall manufacturing efficiency. The adaptable deep learning model minimises design analysis work and showcases operational excellence.
- Enhanced demand sensing empowers customers with accurate demand forecasts by integrating both historical data and external factors. Developed in collaboration with sedApta, this solution uses advanced machine learning algorithms to consider variables like fuel costs, annual festivities and global scenarios such as pandemics. Customers benefit from more precise predictions, better decision-making and improved supply chain management.
- AI-enhanced bill of materials optimization for electronics manufacturers, developed with CalcuQuote, addresses supply chain challenges in the electronics sector by optimising component selection and reducing lead times. It utilises sophisticated machine learning algorithms to identify patterns and relationships, streamlining part numbering and inventory management, leading to significant cost savings and efficiency improvements.
- AI-PROFICIENT: an R&D project combining AI, the IIoT and augmented reality to enhance plant productivity, created together with TenForce in collaboration with INEOS and Continental France, offering early fault detection and prediction of quality problems, digital twin-based simulation, transparent decision-making and optimised control, and personalised shop-floor assistance with XR and conversational interfaces for connected workers.
If you’re coming to Hannover Messe, stop by Elisa Industriq’s stand (hall 15, stand E05) to see first-hand how our AI-powered solutions can help your organisation achieve greater success and gain a competitive advantage in the manufacturing industry by unleashing the potential of your existing data.
Elisa Industriq is a leading provider of AI-powered solutions for manufacturers and is committed to building a sustainable future through digital technologies that enable human–machine collaboration. We help companies track quality and supplier performance, integrate their disconnected services, and enhance sustainability and flexibility in their supply chains.
