Message from the Editors
The fifteenth issue of InnovatieNU explores production intelligence, where AI, IoT, and data analytics transform manufacturing. It highlights enhanced efficiency, smart planning, and human-AI collaboration, while addressing ethical concerns like privacy and transparency. The issue promotes responsible, human-centred adoption of technology to drive sustainable, innovative, and trustworthy industrial progress.
Featured
Production Intelligence in Action
Artificial intelligence is reshaping manufacturing by enabling predictive, autonomous, and data-driven processes. This shift goes beyond automation. It’s a transformation in how decisions are made and products are designed. As organisations navigate this complex landscape, structured guidance like the AI Guide helps bridge the gap between potential and practical application, offering a strategic approach to sustainable innovation in smart manufacturing.
Lessons Learned
From Data Streams to Strategic Value
SME manufacturers are sitting on valuable production data, but without proper integration and context, it remains underused. This article explains how digital tools like AI and digital twins only add value once a structured data foundation is in place. With practical guidance and real-world examples, it shows how SMEs can turn fragmented data into faster decisions, fewer delays, and smarter operations.
AI-hub East Netherlands at the Heart of Industrial AI
AI-hub East Netherlands is turning industrial AI from vision into action. Focused on data readiness, organisational strategy, and real-world applications, the region is helping SMEs adopt AI for smarter production, predictive maintenance, and new business models. Through hands-on support and cross-sector collaboration, East Netherlands is positioning itself as a frontrunner in Europe’s digital and green industrial transformation.
AI-Enhanced Order Scheduling of High-End Components for the Semiconductor Industry
Mintres B.V., in collaboration with Fraunhofer IPT and FIP-AM@UT, has developed an AI-optimised planning module for their ERP system. This intelligent tool enhances production efficiency and flexibility in manufacturing thermal components for the semiconductor industry. By leveraging evolutionary algorithms, complex planning processes are automated—reducing response times and optimising resource allocation.
Sustainability
The Future of Smart Factories through Artificial Intelligence (AI)
Artificial intelligence (AI) is no longer just a technological trend, but a force that helps companies stay competitive. From smart maintenance to automated quality control, AI is changing how factories work and transforming production planning. In this article, Limis shares insights on why integrating AI into manufacturing is no longer optional, but essential in today’s rapidly evolving industry.
AMC NU
AMC NU
Read more about what’s happening with the Circular Manufacturing Program and our Advanced Manufacturing Centre, and discover the many innovation topics we can help you with to support your business.
Technology & Innovation
Step by Step to the AI Summit
Many SMEs want to adopt AI but don’t know where to start. This article outlines why now is the time to act, not with major investments but with focused steps. With technology ready and employees eager, the real barrier is leadership hesitation. Discover how strategic thinking and small-scale pilots can help your business climb the AI ladder today.
Get a Grip on Your Production
transAI helps factories become smarter by digitally connecting machines, systems, and staff onto one simple platform. It reduces manual tasks, improves productivity, and cuts errors by automating processes and using AI to provide real-time insights. Certified secure (ISO 27001), transAI makes production easier and more efficient, helping companies stay competitive and prepared for future challenges in manufacturing.
Steps to take for adoption of AI in manufacturing industry
AI adoption in manufacturing is not a simple solution. This article outlines four essential steps for successful integration: define clear goals, follow a structured methodology, embed AI into organisational processes, and collaborate with others. Drawing on real-world examples, it highlights both the potential and the challenges of AI, showing that understanding your process is the first step to meaningful innovation.
Shaping the Future of Research in the AI Era
Artificial intelligence is changing not just how research is conducted, but how it begins. This article examines how artificial intelligence is reshaping the research landscape from labour-intensive processes to platforms like SCIONS that use predictive tools to assess early-stage ideas. By integrating AI analysis with human judgment, SCIONS illustrates a shift toward more collaborative, transparent, and forward-looking research practices.
AI for defect detection on AM
Additive Manufacturing using FDM often faces print failures like spaghetti defects. This research applies AI and computer vision, notably YOLO11, to detect issues in real time. A new metric improves stopping accuracy, reducing waste and enhancing reliability across diverse printing scenarios.
AI at design firms: from curiosity to strategy
Design firms are exploring how generative AI can enhance creativity and efficiency. This project reveals that AI tools like ChatGPT, Vizcom, and Midjourney support idea generation, visualisation, and prototyping, but are limited in detailed design. Successful adoption depends on company culture, experimentation, and open dialogue. The key to AI integration lies in collaboration, reflection, and learning by doing.
High-tech laser and AI for increased steel recycling
Tata Steel Nederland is working every day to recycle steel. The company increases the use of scrap from 17% in 2022 to 30% in 2030. By integrating laser analysis, AI, and digital twins, Tata Steel and its partners are pioneering smarter recycling methods that reduce CO₂ emissions, improve material efficiency, and advance the transition to green steel.
Prognostics & Health Management in the Era of AI
Prognostics and Health Management (PHM) enables us to anticipate and manage system failures. With the advent of AI, technologies like intelligent agents and large language models (LLMs) are transforming PHM into adaptive, intelligent frameworks. This article explores how AI-driven PHM enhances safety, efficiency, and sustainability by enabling autonomous action and clear communication across a wide range of systems.
Generative Design in Manufacturing
Generative design offers manufacturers powerful tools to automate and accelerate product development. By leveraging techniques like topology optimisation, parametric modelling and neural networks, businesses can reduce lead times and enhance adaptability. The key lies in identifying repeatable, time-consuming tasks and applying the right design automation technology to improve efficiency, sustainability, and innovation within competitive markets.
From Downtime to Uptime
GraphRAG is an AI-powered system that converts unstructured maintenance data into structured knowledge graphs to streamline fault diagnosis in manufacturing. By integrating multilingual logs and technical manuals, it enables accurate and context-aware troubleshooting. GraphRAG preserves expert knowledge, reduces downtime, and boosts operational efficiency. It empowers engineers with intelligent support and helps organisations build long-term resilience in maintenance practices.
AI for process optimisation in a manufacturing company
Pentas Moulding, a Dutch manufacturing company, is embracing AI for process optimisation with support from Novel-T and EDIH. By integrating AI into machines and daily workflows, they’ve created personalised digital assistants for employees and set the foundation for a smarter, more sustainable factory—one that’s efficient, connected, and ready for the future of industry.