AIMS5.0 - The next big step in digital transformation

AIMS5.0 partners and reviewers at the final review meeting, hosted by TTTech in Vienna, 8–9 October 2026.

Partners

Countries

Use cases

Average TRL

Exploitable results

Publications

53

12

20

4.8 → 7.2

179

331

AIMS5.0 (Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0) has concluded after 41 months. Funded by the Chips Joint Undertaking and national funding authorities and coordinated by Infineon Technologies AG, the project brought together 53 partners from 12 countries to apply artificial intelligence to production in nine industrial domains, from semiconductor fabs and automotive logistics to machine tools, consumer electronics and indoor farming.

Across 20 use cases, the average technology readiness level rose from 4.8 at the start to 7.2 at the end. Of the 179 exploitable results registered by the consortium, 154 are already implemented or under test in industrial environments, and 39 have been selected as Key Exploitable Results. The final results were presented to the Chips JU and independent experts at the closing review, hosted by TTTech in Vienna on 8 and 9 October 2026.

"When AIMS5.0 started, most of our use cases were at an early research stage. Today the majority have been demonstrated in real production environments, and several results are already in daily use at partner sites. That is what becomes possible when 53 partners from industry and research work on the same problems together, from the chip to the shop floor."

Thomas Gutt, Infineon Technologies AG, AIMS5.0 coordinator

Edge hardware for AI on the shop floor (WP1)

Work package 1 developed the hardware, firmware and middleware that allow AI to run directly next to the machine. The components were designed together with the AI, architecture and platform teams and then tested in the industrial use cases.

In a semiconductor fab, an improved RFID system reached 99.68% read accuracy over more than 18 million reads, and acoustic fault detection on the ceiling transport system reduces manual recovery work. Thales completed miniature RF MEMS leakage sensors with considerably lower insertion loss and power consumption than the reference design.

The StreamAnalyze edge analytics engine now runs on x86, ARM and RISC-V from a single code base. For autonomous lawnmowers, this reduced the model lifecycle effort from about 40 days to just over three. Further results include a mobile sensor platform for cleanrooms that processes 15 frames per second instead of 3.5, a perception system that lets mobile robots detect people within 5 m with more than 95% accuracy, and an EEG- and EMG-based controller for industrial exoskeletons.

AI methods and the AI Toolbox (WP2)

Work package 2 produced 54 reusable AI technologies, covering computer vision, anomaly detection and predictive maintenance, robotics, scheduling and optimisation, and large language models. Most of them were validated directly in the project's use cases.

The use cases provide concrete figures. A vision system for robotic conveyor feeding locates sockets with 98.7% accuracy and a position error of 2 mm. New sensors in the cleanroom cut the reaction time to contamination from eight hours to under one. At the Foundation for Research and Technology – Hellas (FORTH), machine learning halved the redesign time for RF components and reduced consumables and chemical waste by 45%. Control scripts for new robot tasks can now be generated in 30 to 45 minutes, and more than 90% of them run correctly.

The methods are documented in the AIMS5.0 AI Toolbox, a public wiki with 41 tools and 17 industrial examples that helps companies select and deploy AI. The partners have also compiled a book, AI in Industry 5.0: from Machine Learning to LLM applications.

An open architecture based on Eclipse Arrowhead (WP3)

Work package 3 extended Eclipse Arrowhead, the open-source framework for service-oriented industrial automation, so that AI functions can be integrated and deployed at the edge. The project contributed to release 5.2.2, including the migration of five support systems, among them the DataManager, EventHandler and Gatekeeper, from version 4.6.

The AI-Gym, an environment for testing and validating AI components, is now available as open source within Eclipse Arrowhead. Together with the Arrowhead fPVN project, the team also developed an Arrowhead modelling language for SysML v2, which CEA, Luleå University of Technology and PTC presented at the OMG technical meeting in Reston in April 2026.

Arrowhead is already used in industry, for example in a manufacturing execution system (MES) at Scania. It is also taught in bachelor's and master's courses in Sweden, Hungary, Italy and Finland.

Digital Reference and Open Access Platform (WP4)

Work package 4 maintains the Digital Reference, an ontology designed to become the common semantic standard for semiconductors and the supply chains that contain them. During AIMS5.0 it gained three new lobes, including one for quality management, and the use cases added 641 classes to the wider ecosystem. The model can be browsed and downloaded on a public website, and a learning tool lets users explore it class by class.

The Open Access Platform builds on this model. It hosts the ontologies of 17 use cases and provides working tools on top of them. A carbon handprint tool, aligned with the Digital Product Passport and the Corporate Sustainability Reporting Directive (CSRD), compares emissions and CO₂ savings along the value chain. A simulation-based planning tool for wafer fabs was presented at the Winter Simulation Conference 2025.

The new quality model is now being evaluated for product traceability and the handling of customer complaints.

Use cases at OEMs and Tier 1 suppliers (WP5)

In work package 5, 24 partners from eight countries tested AI in eight industrial use cases. Four of the results are already in industrial use or being rolled out.

Use case

Partners

Result

UC1 Green AI lifecycle

AI Digi+ Solutions, Cetto

CO₂ and energy monitoring tool piloted at Cetto; scenario analysis of route and e-truck options shows potential to reduce transport emissions and energy cost

UC2 AI-enhanced value chain

Philips, University of Groningen, TU Eindhoven, Semaku

Quality dashboard in daily use on the OneBlade line to find the root causes of defects earlier; generative AI makes robotic testing of intense pulsed light (IPL) devices more human-like

UC3 Servitization

Husqvarna, Skandinaviska Enskilda Banken (SEB), Stream Analyze

Edge AI service running at Husqvarna, cutting administration effort by more than 80%

UC4 Production and logistics

BMW, IPH Hannover, Universidad Politécnica de Madrid

Autonomous drone scanning and much faster map creation for mobile robots, now in regular operation

UC5 Machine tools

IDEKO, Soraluce, Goimek, Savvy Data Systems, Multiverse

Tool breakage detected within 1.5 seconds; validated on industrial milling machines

UC6 Robotic conveyor feeding

EDI (Latvia), Harokopio University of Athens

Robot picks randomly piled bottles and places them on a moving conveyor; sockets detected with 98.7% accuracy

UC7 Luminaire manufacturing

Signify, TU Eindhoven, University of Groningen

Metal 3D printing developed as a lower-cost alternative to die casting for luminaire parts

UC8 Human-centric AI

Smart Universal, TÜBİTAK BİLGEM

Human-aware mobile robots and an exoskeleton controlled by brain signals; task time cut by at least 20%

AI in semiconductor manufacturing (WP6)

Work package 6 was the largest in AIMS5.0. Thirty partners worked on 12 use cases, most of them inside European semiconductor fabs, where AI was applied to production planning, material handling, maintenance, quality control and the supply chain. Every use case delivered results, and several exceeded their targets.

Use case

Partners

Result

UC9 Energy-aware scheduling

FernUniversität in Hagen, Infineon, Systema, Virtual Vehicle

Electricity cost down of 750 kWh a day saved at high energy consuming peak situations ; anomalies in the cooling network predicted with 98.6% accuracy

UC10 AI-based manufacturing execution system

Systema, Infineon

AI-enabled MES that connects five fab use cases; cycle time and training targets met

UC11 Indoor food production

TTTech, AIT Austrian Institute of Technology, Research Studios Austria, Zelos Plant, Gdańsk University of Technology

Plant irregularities detected with more than 90% accuracy; adaptive antennas improve signal quality about fourfold; cybersecurity of the farm architecture assessed with ThreatGet

UC12 Human-centred AI for fab networks

WU Wien, HSZG, TU Dresden, Systema, Infineon

Higher equipment effectiveness and less repair variability; study on how transparent AI affects workers' trust

UC13 Sensors for automated wafer transport

Hochschule Stralsund, Fabmatics, TU Dresden, Universität zu Lübeck, Infineon

Early fault detection on transport vehicles and a mobile sensor platform for predictive maintenance lowering maintenance efforts

UC14 Virtual commissioning

Fabmatics, Hochschule Stralsund, Infineon

Digital twins cut commissioning time by about a third; a next-generation storage system and mobile robots tested in a fab

UC15 Machine learning at scale

Infineon, University of Padova, Statwolf, LFoundry, KAI

Shared MLOps platform: about 75% faster model development and about 25% less data needed for new machines

UC16 RF transceivers

FORTH, Thales

Redesign time halved and chemical waste cut by 45%; all four targets met

UC17 Contamination management

Fraunhofer IISB, Pfeiffer Vacuum, Systema, Infineon

New methods andsensors for contamination control in semiconductor factories and pilot fabs; reaction time cut from eight hours to under one hour

UC18 Carbon handprint in the supply chain

Infineon, NXP, DAC.digital, TU Eindhoven, Semaku, University of Groningen

Semantic carbon handprint model added to the Digital Reference; around 1,000 people trained on digital supply chains

UC19 Business planning and quality incidents

NXP, Infineon, TU Eindhoven, Semaku

Master plans generated in about three minutes with up to 40% fewer replanning changes; LLM prototype for root cause analysis

UC20 Harmonised equipment control

Infineon

Test wafer data harmonised between two fab sites, a step towards running them as one virtual fab

Many of these results also support sustainability: less energy at peak load, fewer test wafers, less scrap and fewer chemicals. The teams agreed on one main lesson: data availability and quality remain the biggest obstacle when AI moves from pilot to high-volume production.

Trust, acceptance and regulation (WP7)

Work package 7 examined how workers and organisations accept AI and how companies can meet the regulatory requirements. Based on 27 interviews and a survey answered by all partners, the team combined four established models into one AI assurance framework. It links each risk to a trustworthiness requirement, a control and a measure of user acceptance, and was published at IDIMT 2026.

For day-to-day use, the team developed a chatbot that checks industrial AI applications against the AI Act, the GDPR, the Cyber Resilience Act and relevant standards. Seventeen of the 20 use cases used it for self-assessment. In a comparison with legal experts on five use cases, the chatbot proved useful for a first orientation but no substitute for legal advice.

In a final survey, users rated the AIMS5.0 tools positively, with scores between 6.9 and 7.7 out of 10. Six recommendations for digital workspaces are published in the public deliverable D7.3.

Publications, standards and exploitation (WP8)

The project produced 331 publications and other dissemination outputs, more than twice as many as at the second review, and 82% of them are already published or accepted. They include 38 journal articles, 13 of them in Q1 and Q2 journals, 116 conference papers and 55 bachelor's, master's and doctoral theses. Citations of AIMS5.0 work have risen from 37 to 178.

Partners also contributed to standardisation, including IEC TC56 on dependability, IEC TC65 on human–machine collaboration and a new ISO/IEC group on Physical AI. AIT Austrian Institute of Technology leads the international work on ISO/DTS 5112, a guideline for auditing cybersecurity engineering in road vehicles.

The final exploitation register lists 179 results, 85 of them developed jointly by two or more partners. Universities and research organisations own 78. Thirty-one results are to be licensed and 13 released as open source. From the register, the consortium selected 39 Key Exploitable Results. Eight of them are shared enablers that other use cases build on, among them the Digital Reference, Eclipse Arrowhead 5.2, the Open Access Platform, the AI Toolbox and the AI-Gym.

Coordination and outlook (WP9)

The technical work was completed on 15 September 2026, and all 15 deliverables of the final period have been submitted. At the final General Assembly in Madrid in June 2026, the partners showed their results at more than 40 demonstrator stands. Throughout the final year, AIMS5.0 worked closely with the Chips JU projects SC4EU and Arrowhead fPVN.

The results remain publicly available on aims50.eu, including 26 articles, 17 public deliverables and 27 videos, and further use case videos will follow in the coming weeks. AIMS5.0 will present its results at its own booth at EFECS 2026 in Helsinki on 2 and 3 December.

Explore the results

About AIMS5.0

AIMS5.0 ran from May 2023 to September 2026 under the Chips Joint Undertaking. Coordinated by Infineon Technologies AG, a consortium of 53 partners from industry, SMEs, research organisations and universities in 12 European countries developed and validated AI-based hardware, software and methods for sustainable, resilient and human-centric manufacturing. Public deliverables, use case videos and project news are available at aims50.eu.

The AIMS5.0 project is supported by the Chips Joint Undertaking and its members, including top-up funding by National Funding Authorities from involved countries under grant agreement no. 101112089. The participating countries are Austria, France, Germany, Greece, Hungary, Italy, Latvia, Netherlands, Poland, Spain, Sweden and Turkey.

News Grid

Project Results
Oct 22 2026

Faster planning for semiconductor fabs: AIMS5.0 use case 12

AIMS5.0 Use Case Spotlight · UC12: Human-centred AI for the optimisation of robust and competitive semiconductor manufacturing networks

A semiconductor fab is one of the most complex production systems in industry. Wafers pass through hundreds of process steps, many tools serve several products at once, and an automated transport system moves material between them around the clock. Every shift, planners decide which lot runs next, which tool needs attention and when material leaves the warehouse for the cleanroom. Many of these decisions still rely on long-term models and on the experience of the people on the shop floor.

Use case 12 (UC12) of AIMS5.0 set out to improve planning, decision-making, digitalisation and automation in semiconductor manufacturing and intra-logistics. WU Vienna, Hochschule Zittau/Görlitz, TU Dresden, Systema and Infineon worked together in three sub-use cases: short-term forecasting of work in progress, fast simulation of production and transport, and a digital Kanban system for material delivery.

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Project Results
Oct 22 2026

Scheduling with the energy bill in mind: AIMS5.0 use case 9

AIMS5.0 Use Case Spotlight · UC9: Energy-aware scheduling of batch processing machines in wafer fabs

In a wafer fab, a small number of process steps account for a large share of the electricity bill. Diffusion and oxidation furnaces are a typical example. They process many wafers in one batch, at high temperatures and often for several hours. Around them, cooling, air handling and ultrapure water supply run day and night to keep the cleanroom stable.

For production planning, these batch machines bring a recurring trade-off. A furnace can start with a partly loaded batch, which keeps urgent lots on schedule but uses energy and capacity less efficiently. Or it can wait for more wafers, which fills the batch but delays lots that are already due. Planners face this decision many times a day, and in most cases the delivery date decides.

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Project Results
Oct 22 2026

54 AI technologies, one open toolbox: AIMS5.0 work package 2

AIMS5.0 Deep Dive, part 2 of 9 · Work package 2: AI tools, methods and algorithms for sustainable industrial processes

Companies that want to use AI in production can choose from thousands of models and libraries online. What they usually miss is guidance: which method fits a given production problem, and what it takes to get it running on the shop floor. Work package 2 (WP2) of AIMS5.0 worked on both questions. It was led by Pál Varga of the Budapest University of Technology and Economics (BME) and Kārlis Freivalds of the Institute of Electronics and Computer Science (EDI) in Latvia.

The work package had a practical brief. It collected the requirements of the 20 industrial use cases, developed and refined AI algorithms to meet them, supported their integration into the use cases, and measured the gains. At the same time, it built a repository of AI methods, tools and algorithms that companies outside the consortium can reuse. The final results are documented in deliverable D2.4.

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Project Results
Oct 22 2026

AI at the edge: what AIMS5.0 built in work package 1

AIMS5.0 Deep Dive, part 1 of 9 · Work package 1: Components for the Edge

Before an AI model can improve a production process, the data has to come from somewhere. It has to be measured reliably, processed fast enough on site and passed on without delay. In AIMS5.0, this was the task of work package 1 (WP1). Led by the University of Lübeck, the partners developed hardware, firmware, middleware and tools that allow AI to run close to the machine, where the data is created.

WP1 started with clear targets: higher quality and reliability of hardware components, faster and more efficient low-latency communication in the industrial internet of things, higher overall productivity, and better predictive maintenance and lifecycle management of silicon. The work was organised in five tasks, from cross-WP co-design to processing and communication hardware, sensors, firmware and deployment tools, and test and validation. Four deliverables document the results, from the first exploration of edge hardware (D1.1) to the final summary of AI-ready edge hardware and systems (D1.4).

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Project Results
Oct 9 2026

AIMS5.0 concludes: 179 results bring AI from pilot to production in European manufacturing

AIMS5.0 partners and reviewers at the final review meeting, hosted by TTTech in Vienna, 8–9 October 2026.

AIMS5.0 (Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0) has concluded after 41 months. Funded by the Chips Joint Undertaking and national funding authorities and coordinated by Infineon Technologies AG, the project brought together 53 partners from 12 countries to apply artificial intelligence to production in nine industrial domains, from semiconductor fabs and automotive logistics to machine tools, consumer electronics and indoor farming.

Across 20 use cases, the average technology readiness level rose from 4.8 at the start to 7.2 at the end. Of the 179 exploitable results registered by the consortium, 154 are already implemented or under test in industrial environments, and 39 have been selected as Key Exploitable Results. The final results were presented to the Chips JU and independent experts at the closing review, hosted by TTTech in Vienna on 8 and 9 October 2026.

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Project Results
June 16 2026

AIMS5.0 General Assembly in Madrid: From Project Results to Industrial Impact

A final General Assembly focused on outcomes

On 16-17 June 2026, the AIMS5.0 consortium met in Madrid for the project’s General Assembly. The meeting brought partners together for two days of technical exchange, Work Package updates, selected Use Case presentations, poster sessions and demonstrator discussions.

As the project approaches its final phase, the meeting provided a concentrated view of the results achieved over three years of European collaboration. The focus was not only on reporting progress, but also on connecting these results with the industrial challenges addressed by AIMS5.0: competitiveness, resilience, sustainability and the practical use of artificial intelligence in manufacturing.

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Project Results
April 10 2026

AIMS5.0: How AI and Digitalisation Strengthen the European Manufacturing Supply Chain

From technical work packages to measurable impact across devices, manufacturing, OEMs, and EU markets

Introduction

Europe’s manufacturing sector is under growing pressure to become more competitive, resilient, and sustainable at the same time. In this context, AIMS5.0 contributes by developing and connecting technologies and methods from the fields of digitalisation and artificial intelligence. The project does not focus on isolated technical improvements alone. Instead, it addresses the broader industrial value chain and supply chain, from devices and architecture systems to manufacturing, OEMs, and ultimately the EU market.

The ambition behind AIMS5.0 Within AIMS5.0, the central objective is to make manufacturing in Europe more competitive and more sustainable through the targeted use of digital technologies and AI. What makes this approach especially relevant is its end-to-end perspective. Rather than improving only individual process steps, the project aims to generate benefits across an interconnected industrial ecosystem.

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Project Results
April 02 2026

SysMLv2 Library for SOA: Arrowhead Work Highlighted in the Context of AIMS5.0 Collaboration

At the OMG technology meeting in Reston, Asma Smaoui (CEA), Jerker Delsing (LTU), and Géza Kulcsár (PTC) presented ongoing work on the ‘SysMLv2 library for SOA’, based on MBSE activities in the Arrowhead fPVN and AIMS5.0 projects. The resulting Arorwhead DSL (Domain Specific Language) is applicable to integration of AI and automation into production and products.

What the presentation focused on

The presentation followed a clear technical path. It introduced the background and resources behind the work, revisited the SysML v1.6 version of the Eclipse Arrowhead DSL, reviewed previous and updated versions of the Arrowhead SysMLv2 library, and explained the translation path from Arrowhead DSL based in SysMLv1 to SysMLv2. It also included concrete use cases, current work related to integration with ISO 23726-3, and forward-looking perspectives.

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Project Results
Dezember 18 2025

1. Winter Simulation Conference 2025: Key Insights for AIMS5.0

Introduction

In December 2025, representatives of the Infineon Supply Chain Innovation team participated in the Winter Simulation Conference (WSC) in Seattle, USA. The Winter Simulation Conference is one of the leading global events for simulation experts, researchers, and industry practitioners, with around 1,000 participants from academia and industry.

The participation and research activities were supported by several EU-funded initiatives, including AIMS5.0, SC4EU, and SemiconductorX. This highlights the strong connection between European research projects and global innovation in advanced manufacturing and supply chain management.

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Project Results
Dezember 9 2025

1. AIMS5.0 at EFECS Malta 2025

Roadmaps, Project Presentations and New Paths for European Chips

EFECS 2025 took place on 3–4 December at the Hilton Hotel in St Julian’s, Malta, bringing together Europe’s leading stakeholders in electronic components and systems. The forum is co‑organised by Chips Joint Undertaking together with the industry associations AENEAS, EPoSS and INSIDE, and is recognised as the key annual meeting point for Europe’s semiconductor and digital systems community.

This year’s edition was particularly strategic: it combined high‑level discussions on Europe’s technological sovereignty with concrete project presentations and the official release of new roadmaps that will guide future work in the chips domain.

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Project Results
Dezember 9 2025

1. Deep Tech Collaboration Workshop — Lisbon 2025

AIMS5.0 × SC4EU × Arrowhead fVPN

Strengthening Europe’s Semiconductor Future Through Joint Innovation

At the Deep Tech Lisbon Event 2025, three leading European projects — AIMS5.0, SC4EU and Arrowhead fVPN — met in a coordinated workshop to explore cross-project collaboration, talent development, and future pathways for Europe’s semiconductor ecosystem. The session ran parallel to the SC4EU General Assembly and the Arrowhead fVPN technical meeting, bringing partners together to accelerate knowledge exchange, align priorities and support a more resilient digital Europe.

 

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Project Results
September 19 2025

AIMS5.0 at the European Research & Innovation Days – Reflections from Brussels

The European Research and Innovation Days (RiDaysEU) are always a special moment in Europe’s calendar. For two days each September, policymakers, researchers, industry leaders, and innovators gather in Brussels to exchange perspectives on where Europe stands and where it must go in order to remain competitive in a fast-changing global landscape.

This year, one of the highlights for our team was the invitation to present the AIMS5.0 project, which had been selected by the Chips Joint Undertaking (Chips JU) as one of the flagship initiatives to be showcased at the exhibition. To be chosen from among so many excellent projects was not only an honor, but also a recognition of the importance of AIMS5.0’s work for Europe’s industrial and digital future.

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Project Event
July 10 2025

RIGOLETTO project launched: Strengthening European microelectronics for future vehicles

 

The European research project RIGOLETTO, rigoletto-project.eu, has officially started, bringing together partners from industry and research to develop advanced microelectronics solutions for future vehicle architectures. The project focuses on open RISC-V-based computing platforms for software-defined, electrified and autonomous vehicles.

As vehicles become increasingly software-defined and autonomous, their computing systems must provide higher performance, safety, security and flexibility. RIGOLETTO addresses this challenge by investigating scalable reference processors...

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Project Results
May 20 2025

AIMS5.0 at INSIDE Connect 2025: Showcasing AI for Sustainable Manufacturing

1. Introduction

At INSIDE Connect 2025 in Málaga, the AIMS5.0 project was in the spotlight as leading experts gathered to discuss Europe’s digital transformation. The event brought together innovators in AI, Edge Computing, and sustainable manufacturing to shape the future of European industry.

2. AI for Sustainable Manufacturing

Professor Pal Varga from the Budapest University of Technology and Economics presented AIMS5.0’s advances in developing AI tools and algorithms for industrial processes. The project integrates a wide spectrum of approaches—from statistical models and Bayesian methods to state-of-the-art deep neural networks and reinforcement learning—providing powerful solutions for sustainable and efficient manufacturing.

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Project Results
May 20 2025

AIMS5.0 General Assembly in Gdansk: A Resounding Success

The AIMS5.0 consortium has once again demonstrated the power of European collaboration as 53 partners from across the continent converged in the historic city of Gdansk for our most productive General Assembly to date. Over two intensive days, our diverse team of researchers, industry experts, and technology leaders advanced our shared mission of transforming European manufacturing through artificial intelligence.

Two Days of Strategic Progress

The carefully structured agenda maximized both collaboration and concrete outcomes:

Day 1: Building Momentum

  • Opening plenary sessions setting the stage for strategic discussions
  • Public presentations showcasing our latest achievements
  • Networking lunch fostering cross-partner collaboration
  • Productive evening sessions deepening work package coordination

    • Day 2: Driving Results

  • Deep-dive technical sessions across all nine work packages
  • Extended plenary meetings addressing consortium-wide priorities
  • Strategic closing discussions charting our path forward
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    Project Results
    Mar 28 2025

    A Glimpse into the Future - Modern Conveyor Systems and Virtual Robotics

    The AIMS5.0 team at Stralsund University of Applied Sciences is working on the monitoring of very slow-rotating ball bearings as well as complex simulations for mobile robots.

     

    Predictive Maintenance for Modern Conveyor Systems

    In wafer cassettes or FOUPs, silicon wafers, the "blanks" for microchips and other electronic components, are transported over long distances through the cleanrooms of semiconductor factories. This transport is done using conveyor systems. These conveying systems are extend over kilometers, have a large number of drive units, and almost countless ball bearings. Robustness against failure is essential for conveyor systems, as a failure of a conveyor can quickly lead to a backlog of material flow, thus blocking large areas of production. Methods for predictive maintenance are therefore in high demand to avoid costly downtimes. This is where Use Case 13: "Intelligent Sensors improving Robustness of Automated Wafer Transportation and Storage Systems" comes in. In this use case, Stralsund University of Applied Sciences is explicitly focusing on roller conveyors. With this type of conveyor system, the drive units only rotate when needed, i.e., when a FOUP passes, and at a very slow rotational speed. A commonly used approach for detecting damage in rotating ball bearings or rolling element bearings is the detection of vibrations. In many systems, the frequency of these vibrations is within a range audible to humans, so damage detection works with acoustic analyses. The challenge with the investigated conveyors lies in the maximum shaft speed of approximately 120 rpm and less. The vibrations that occur here are low in energy and, in combination with the low frequency and short running times, difficult to detect. The simultaneously occurring ambient noise level is significantly louder at approximately 70 dB(A), dominates the sound signals recorded by the sensors, and further complicates the evaluation.

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    Project Results
    May 15 2025

    Building Trust in AI Through Visual Storytelling – KAI and Infineon

    We advance and enhance sustainability in semiconductor manufacturing by leveraging AI-powered defect image classification. Our project's core concepts are explained through visual storytelling in an engaging and dynamic explainer video. Our goal is to make the AI project accessible and relatable for everyone, ensuring that all stakeholders can grasp the technology's significance. Through clarity and transparency, we aim to foster trust in our AI initiatives, showcasing our commitment to trustworthy AI. The explainer video serves not only to inform but also to engage both internal and external audiences. By sharing this video across social media platforms and within our organization, we are promoting our AI project with a modern twist, captivating our viewers while emphasizing our sustainability goals. The video is now available on the AIMS5.0 YouTube channel. We invite you to view it and gain further insights into how AI is driving innovation in semiconductor manufacturing. In developing the video, we carefully selected the tools and techniques best suited for our needs. Utilizing Adobe Creative Cloud, including tools like Adobe Illustrator and Adobe After Effects, allowed us to create high-quality visuals that align with our storyline. We also drew on the illustration libraries provided by Infineon to enrich the video content.  

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    Project Results
    Mar 28 2025

    NEW ARROWHEAD CLI UTILITIES ACCELERATE INTEGRATION AND DEVELOPMENT

    A new Command Line Interface (CLI) utility developed in Go has been introduced to support faster, easier development with the Eclipse Arrowhead framework. The tool was recently showcased at the March 2025 Arrowhead bi-weekly meeting by Johan Kristiansson from Luleå University of Technology, a key partner in the AIMS5.0 project.

     

    Purpose and Design

    The CLI was designed to simplify key developer workflows in Arrowhead-based systems. Inspired by popular tools in cloud-native ecosystems, the CLI brings familiar efficiency to Arrowhead integration—ideal for both newcomers and experienced users working on AIMS5.0 and similar industrial automation projects.


    Core Features

    • Certificate Automation: Streamlines the process of generating and registering certificates
    • Service & System Registration: Allows direct interaction with Arrowhead core services
    • Environment-Based Configuration: Uses environment variables instead of property files—perfect for Kubernetes and containerized deployments
    • Rapid Prototyping: Enables creation of producers and consumers in minutes

     

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    Project Results
    Mar 19 2025

    AIMS5.0 Project Video Released: Showcasing AI-Powered Manufacturing Innovation

    We're excited to announce the release of our official AIMS5.0 project video! This short but comprehensive overview highlights how our collaborative initiative is revolutionizing European manufacturing through AI-enabled technologies.

    What's in the Video?

    Our new 2-minute video takes viewers on a journey through the AIMS5.0 project, illustrating how we're strengthening European digital sovereignty in sustainable production. The video showcases:

    The challenges facing European industries in adopting advanced AI and IoT technologies

    How AIMS5.0 brings together 53 partners across Europe to transform manufacturing
    Our approach to creating shorter supply chains and greener production methods
    The structure and purpose of our nine integrated work packages Key project outcomes, including 20% faster time-to-market and 20% reduced environmental footprint

    Why This Matters

    As Europe faces increasing global competition, AIMS5.0 represents a critical step in maintaining and enhancing our industrial competitiveness. The video demonstrates how our €70 million initiative is driving the shift from Industry 4.0 to Industry 5.0, creating human-centric workplace conditions while enabling the transformation toward climate-friendly production. From AI-enabled sensors to sustainable semiconductor supply chains, the video offers a glimpse into how AIMS5.0 is building a more resilient, efficient, and eco-friendly manufacturing future for Europe.

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    Project Results
    Mar 18 2025

    SC4EU Launches Official Project Video: See Our Vision for Resilient Semiconductor Supply Chains

    We are delighted to announce the release of our official SC4EU project overview video, providing a comprehensive look at our groundbreaking initiative to revolutionize semiconductor supply chain management across Europe and beyond.


    Visualizing Our Mission

    Our newly released video "SC4EU: True Demand-Driven Semiconductor Supply Chains for Europe" encapsulates the essence of our ambitious project in just two minutes. It highlights how we're addressing one of the industry's most pressing challenges – the unpredictability of demand in semiconductor supply chains and the resulting bullwhip effect that leads to chip shortages and inefficiencies.


    As illustrated in the video, SC4EU brings together 14 partners, including leading semiconductor manufacturers Infineon Technologies AG (coordinator), NXP, and STMicroelectronics, along with equipment manufacturer ASML, software giant SAP, and academic institutions from Germany, Netherlands, Greece, France, and Austria.


    Key Project Elements Showcased


    The video provides insights into our core innovative approaches:

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    Project Results
    Dec 09 2024

    Unlocking Sustainable Manufacturing and Supply Chains: The Power of Semantic Technologies


    The AIMS5.0 EU funded project stands for “Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0” and is a Collaborative Innovation Action between multiple domains with a consortium of over 50 academic and industry partners.

    Its main goals consist of strengthening the European digital sovereignty in comprehensively sustainable production, and boosting the economy by adopting, extending and implementing AI-enabled hardware and software components and systems across the whole industrial value chain. Its aim is to create human-centric workplace-conditions and a climate-friendly production. The AIMS5.0 project supports AI-enabled fabs to be more productive and eco-efficient. It advocates shorter supply chains, better resilience, global competitiveness and higher sustainability.

    The global semiconductor manufacturer Infineon Technologies AG has several contributions to the AIMS5.0 funded project, with one of them being Work Package Four. Work Package Four, “The Open Access Platform” is co-lead by Infineon Technologies and FernUniversität Hagen with contributions from DAC.digital and NXP. The primary objective of the Open Access Platform is to create a consistent and modular semantic description of the semiconductor industry containing industrial domains and supply chains based on the Digital Reference Ontology (DRO), which will be elaborated in the following.

    The Semantic Web and Ontologies

    To define the concept and strengths of ontologies, one first needs to understand the Semantic Web. The Semantic Web was coined from T. Berner Lee as an extension of the World Wide Web that enables machines to understand and interpret meaning behind data. It is founded on the concept of data interoperability allowing information to be easily shared, reused, and combined across different organizations and systems. As a result, a more connected and integrated digital ecosystem is enabled. Traditionally, data on the web has been structured in a human-centric manner, with information presented in formats like HTML text documents that are easily comprehensible to humans. However, these formats are not machine-friendly, making it challenging for computers to interpret and process the data efficiently.
     

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    Project Results
    Jun 24 2024

    The next big step in digital transformation is taking shape


    Aiming at a more sustainable, efficient, and user-friendly production, AIMS5.0 is about to show how artificial intelligence (AI) can take a decisive step towards Industry 5.0 and European digital sovereignty. The ambitious research project started a year ago and is part of the EU programme Horizon2020. Its characteristics represent the self-image of EU funded projects as an intelligent collaboration between partners and other projects, for mutual benefit and growth.

    AIMS5.0, the project title sets the direction. The acronym stands for “Artificial Intelligence in Manufacturing leading to Sustainability and Industry5.0” and aims at the potential of artificial intelligence (AI) in the development and manufacture of hardware and software components. In addition to comprehensive sustainability and user-friendliness, the desired goals include significantly increased efficiency in production.

    Semiconductor production predestined for use of AI

    The semiconductor industry in particular is perfectly suited for exploiting the potential of AI. There are many barely visible data-generating manufacturing processes here. At least 250 systems contribute to the manufacture of a product. Each has 20 parameters and 100,000 wafers with up to 10,000 different design variants run in the factory. Considering these figures could be even higher, it is clear that human beings alone are not able to fully comprehend these highly complex processes, let alone monitor them. This is where it takes the assistance of AI. Automatic error detection, for instance, can ensure fewer rejects and an overall higher quality.
     

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    Project Results
    Feb 06 2024

    Flights for future - autonomous drones on a mission


    With the attempt to take the European Industry to the next level of digitalisation, first fundamental research activities in AIMS5.0 prepare the way to get the 20 use cases off the ground bringing the future of a highly efficient fabrication to life. One of the striking examples is an autonomous indoor drone.

    As a work result of work package 5, the drone will demonstrate an AI based improved connection between production and logistics. Developed by IPH, “Institut für integrierte Produktion Hannover” from Germany it will work as a scan device covering a complete production site of carmaker BMW to create a digital twin of it.

    Daily scans for digital twins

    The drone is able to navigate autonomously through a manufacturing hall catching every corner and measuring each millimetre. Other than a ground bound device, it can measure even closed robot cells or conveyor belts. Together with the metrics from a ground bound automated guided vehicle system (AGV), a robot dog, the gapless data collection enables an accurate three-dimensional reproduction for a digital twin with regular updates.


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    Event
    Feb 02 2024

    Sharing knowledge in Austria


    With regard to collaboration and synergy effects within and across the project, a major event in 2023 is worth being noted, which, in fact, was a two-in-one event. 

    On 27-28 September, the University of Applied Sciences in St. Pölten, Austria, hosted the Deep Tech Workshop as part of the two large-scale European initiatives AIMS5.0 and Arrowhead fPVN, while at the same time, the new Research Studio Smart Digital Industries and Services (SDIS) was opened on the premises of the university.    

    Both Arrowhead fPVN coordinator Luleå  University of Technology (LTU) in Sweden and SDIS founder Research Studios Austria Forschungsgesellschaft (RSA FG) are members of the AIMS5.0 consortium. LTU is co-leader of WP3 working on the cyber architecture, and RSA is co-leader of WP7 dealing with human acceptance, trust and ethics for Digital Workspaces. 

    Deep Tech Workshop for collaboration

    The Deep Tech Workshop’s primary focus was on common technologies and initial use of use-cases in AIMS5.0 and Arrowhead fPVN. The latter project name stands for the Arrowhead framework and implementation platform focusing on flexible Production Value Network (fPVN). The workshop provided a valuable forum for sharing knowledge and exchanging ideas on topics like cyber architecture, data models or AI code generation.

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    Event
    Nov 14 2023

    Collaboration at its best


    AIMS5.0 is one of those projects where major findings from other research initiatives are taken to the next level, thus bringing them to life. The subject in question is a Digital Reference (DR), a holistic ontology for supply chains in the field of semiconductor. Its characteristics in turn, represent the self-image of the complete AIMS5.0 project as an intelligent collaboration between partners and other projects, for mutual benefit and growth. 

    The Semantic Web model will help to clearly interpret and exchange countless information and data in a complex supply chain. This way, ambitious goals in fields like quality management or sustainability can easily be achieved in a new manner. In AIMS5.0, DR and other ontologies are subject to WP4, based on the idea that in the area of the Internet of things (IoT) ontology creates a language that is understood by humans and computers alike with the aim of smooth interaction throughout the entire supply chain.

    Total network

    A targeted open access platform shall improve a comprehensive data exchange, and the DR stems from the previous digitalisation project Productive4.0 forming the backbone for the intended platform. Moreover, AIMS5.0 benefits from the relevant research work in the following smaller but highly specialised project SC³, which exclusively focused on DR and ontology and created the further elaborated theoretical foundation for various industrial use cases in AIMS5.0. 


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