Robotics and Automation: Automation and robotics can contribute to faster scaling of production, safer production, and more accurate results. We work with everything from the underlying mathematics to the robotics themselves. We have extensive experience in gripping and handling and are now also building expertise in upcoming techniques such as curved hot-wire cutting of polystyrene, roboforming, and laser welding.
3D Printing: Additive manufacturing (3D printing) is a production method where a product is built layer by layer based on a digital model. This enables the creation of complex geometric shapes that are difficult—or impossible—to produce with traditional subtractive methods (where material is typically removed). By only adding material where it is needed, material consumption can be reduced, and internal cavities can be integrated to save weight and resources.
The material properties of the finished product largely depend on the parameters controlling the process (such as laser intensity, laser speed, stripe density, etc.), providing great flexibility and the ability to tailor properties as needed. Additive manufacturing can also be combined with and supplement traditional production technologies, requiring interdisciplinary expertise in mathematics, physics, numerical calculations, materials technology, and production technology. Read more about 3D printing here.
Artificial Intelligence (AI): Modern production is increasingly based on digital value chains in line with the principles of Industry 4.0—from digital design to sensor-based production. With the data stream comes significant potential for the use of artificial intelligence (AI) in both design and production phases. Areas such as generative design are well advanced, while the use of AI in production faces challenges.
Access to relevant production data can be limited when digital solutions related to machines and equipment are proprietary, and a lack of relevant sensor data and interoperability (seamless communication between systems) makes it difficult to apply AI effectively. Additionally, creating trust in AI models can be challenging if they do not meet the necessary precision or indicate uncertainty in their predictions.
At SINTEF, we work towards smarter data that can be utilized better and used in multiple places simultaneously, as well as reliable AI models through a combination of domain knowledge and machine learning.
Sensors: These are the senses of computers, collecting information. It is therefore important that the sensors are as good as possible so that decisions are made on the best possible basis. SINTEF is world-leading in sensors, which play important roles in advanced production. We also have solid expertise in the processing of sensor data and the interpretation of this type of information.
Tracking technology for automatic data capture (QR codes, RFID, Bluetooth tags) is central to many production operations. This ensures efficient monitoring, progress, and control of material flow in factories. Sharing tracking data in real-time between suppliers and customers is necessary to ensure efficient flow and logistics between companies. Resilience in value chains, including the supplier side, is necessary to ensure the supply capability of production companies. Access to tracking data can contribute to increased resilience in the event of unexpected serious incidents that may affect delivery capability and can be used as decision support in replanning.
Internet of Things (IoT): Smart products containing sensors enable new business models, including data-based services and collaboration through digital platforms with many actors in ecosystems. Production companies have greater opportunities to utilize data from products in operation to develop new services, product-service systems, and to utilize condition monitoring for predictive maintenance, as well as for learning and developing better products. Physical products with built-in digital technologies also provide better opportunities for leasing or rental and new, more flexible pricing models. Such solutions also offer opportunities for circular strategies, both to extend lifespan and strengthen reuse, remanufacturing, and recycling.
Digital Twins: A digital twin is a digital representation of a physical object (such as a product or machine), a process, or a service. The representation is so precise that it can be used for decision support. The digital twin is often connected to the physical world through real-time data streams, enabling monitoring, analysis, and optimization of performance and operation.
Digital twins are particularly important for the effective use of artificial intelligence (AI) in production. Unlike previous digital solutions, which mainly contained static and nominal information, digital twins are dynamic models that evolve throughout the object's lifecycle. This enables continuous condition monitoring, predictive maintenance, and ongoing improvement of production processes.
Digital twins can be used for modeling and analysis of material flow and processes as important decision support in the development or design of new production lines or factories and value chains. Digital twin models can be used for simulation/optimization to contribute to increased efficiency and productivity.
Materials: New materials with unique properties offer new business opportunities. This involves improving production techniques and product performance. In state-of-the-art laboratories, we work along the entire value chain—from raw materials and environmentally friendly production processes to casting and forming, joining, and other advanced production processes. Here you can read more about the research area of materials in SINTEF and the opportunities it can provide.
Connection to Humans: Industry 5.0 focuses on the interaction between humans and technology to exploit the full potential of new digital solutions. Human-machine interaction and enhanced work among skilled workers and operators are emphasized to ensure the use, utilization, and value creation of digital technologies in production companies.
Not sure about what suits your type of production best? Contact us, and we will find answers to what works and what doesn't for your company.
