Examples of what we are interested in include…
Summarize and Analyse Technical and Testing Documentation
Autoliv is exploring solutions that could help with analyzing and summarizing test data in CV/DV/PV testing and writing reports. Managing and reviewing technical customer specifications could be sped up with the help of generative AI.
Optimize Material Use with Product Design
Autoliv is seeking the help of generative AI to optimize the design phase, aiming to find more sustainable solutions and address technical challenges. Optimizing material use can contribute significantly to sustainability efforts. Generative AI could assist in reading and checking CAD drawings/designs.
Enhance Data Management and R&D Efficiency
Epiroc is seeking to optimize data flow and architecture within their R&D and product development processes. They aim to leverage generative AI in areas such as data management, processing, and integration. This can lead to accelerated innovation, faster product ideation, and more robust design solutions.
Analyze and Summarize Technical Documentation
Since 1689, Husqvarna Group has secured over 3,350 patents for various technologies. Given this, Husqvarna Group is interested in generative AI solutions to assist in analyzing and maintaining all internal and external product-related documentation in different languages.
Streamline Idea Evaluations and Comply with Design Standards
KONE is exploring solutions to enhance R&D and product development processes by leveraging generative AI to evaluate and manage inventions and ideas. KONE is also interested in using generative AI to evaluate product designs against codes and standards documentation, ensuring product design compliance and quality in different markets and geographical areas. Generative AI could be pivotal in automating and optimizing these aspects of R&D and product development efforts, ultimately expediting time-to-market.
Improve Sustainability with Product Design
KONE is looking for generative AI solutions to enhance sustainability in product design. The aim is to further optimize various sustainability aspects of the product lifecycle – all the way from product design and manufacturing to lifetime usage and disposal.
Accelerate Testing and Simulation
Munters is exploring AI-assisted solutions to accelerate their testing and simulation processes. With a vast amount of data generated during testing, automating and optimizing the analysis is important. Generative AI solutions could quickly process large datasets, identify patterns, and provide insights to engineers, leading to faster product development and improved safety standards.
Support Product Development Efficiency
Munters is investigating generative AI for generating innovative product ideas, designs, and prototypes. By analyzing vast datasets of market trends, customer preferences, and emerging technologies, the ideal solution could identify market gaps and competitive advantages that guide product development decisions for creating cutting-edge products.
Accelerate Testing and Simulation
Scania is exploring how AI tools can speed up R&D and product development through testing and simulation optimization, particularly for handling large datasets. For instance, this can mean employing AI solutions to automate crucial testing, simulation, and data management tasks, and result in improved product quality, faster development, and cost savings.
Create Scenario-Based Tech Roadmaps
Scania is investigating how generative AI solutions can support anticipating future scenarios and their impact on decision-making for product development. As the scenario analysis process is currently time-consuming and resource-intensive, generative AI has the potential to significantly automate and streamline it.
Enhance Product Development Efficiency
SKF is investigating how generative AI can support them in rapid and accurate access to product information, including product catalogs and data sets. Today, many documents are difficult to search through keywords, resulting in the need to read through multiple documents to collect insights.
Re-utilize Test Data and Reports
SKF wants to leverage generative AI to increase efficiency and reduce human error in testing and development environments. Due to keyword search limitations, testing personnel need to sift through numerous documents to utilize past testing data. Ultimately, SKF wants to utilize historic engineering data to potentially develop a conversational interface that transforms extensive information repositories into an interactive support tool.
Customize Packaging Design
Stora Enso is looking for generative AI solutions to streamline the process of creating new designs and optimizing them for production and transport. They aim to provide sustainable, affordable, and customized 3D-printed designs for clients with shorter lead times. Stora Enso envisions utilizing generative AI to optimize furniture design and packaging for unique and complicated products.
Discover New Materials
Stora Enso envisions leveraging generative AI technologies to speed up lengthy material development processes and optimize physical and/or chemical material development, testing, and screening of possibilities. Ultimately, we want to develop a better understanding of the effects and results of modifications on anode material, polymers such as FDCA, or fiber foams.
Synthesize New Water Barrier Polymers
Stora Enso is looking into utilizing generative AI to find new biodegradable water-barrier polymers and define new material formulations. Starting with revealing the synergism between different types of biodegradable polymer molecules with the most efficient composite construction, Stora Enso envisions finding the best possible combination from group contribution theories from classical polymer science to find the most sustainable material for replacing traditional plastics. By combining composite theories of lignocellulosic materials, the solution could find highly improved composites for new packaging and wood composite products.