With our Technology Circle events, we bring industry 4.0 technology topics to the Basel Area. As the industrial transformation team of the Basel Area, our main focus in this section of the event is on the manufacturing industry.

“The industrial metaverse is not merely a single technology. Rather, it represents an integrated ecosystem.”
—Isabel Steinhoff, Transformation & Metaverse Strategist, Co-Founder at Dimenteers

Isabel shows us the positive impact of metaverse on the manufacturing industry with three examples.

For Nestlé, ensuring that all manufacturing safety procedures are followed correctly is critically important. With its digital twin of the Nescafé factory in Girona, northern Spain, Nestlé teaches safety, hygiene and traffic rules of the large facility in a safe, virtual environment. Employees can go through vital safety training without endangering themselves or the factory without even being on the premises.

Swissgrid faced challenges with outsourcing and risk management. With the help of Rimon, one of our former i4Challenge winners, they digitized their monthly inspection process and enabled untrained people to execute it using augmented reality (AR). They streamlined inspections, improved quality, standardized the process and enhanced know-how management.

BMW built a digital twin of a factory before actually building it and simulated 6 months of production. Thanks to the learnings of this simulation, BMW changed the design before construction. This made the planning process 30% more efficient, saved 10% in production costs and about 80% of meetings could be skipped or streamlined due to high information availability.

There are many more opportunities that save cost, improve safety and efficiency and have an overall positive impact on people, the environment and the company’s bottom line.

As Europe’s leading life sciences ecosystem, healthcare is most dear to our hearts and was our primary focus in this event. The opportunities for healing in the metaverse are endless.

Philippe Gerwill presented a few apt use cases, followed by a tour of the Avalon health city by Aimedis, where he is Executive Advisor.

Personal fitness and mental health

Healthcare is most often sick care. We tend to treat people instead of preventing illnesses. But this trend is shifting towards wellness and preventive care, especially with the younger generation.

A way to nudge people towards preventive care is by giving them incentives. Today, these incentives already exist as tokens or NFTs. With the metaverse, we can gamify preventive healthcare even more.

For example, with a fun home workout:

The metaverse also offers interesting opportunities for one’s mental health.

Imagine doing a yoga exercise in an immersive environment that makes you feel like you’re on a beach rather than in your own room. The same goes for meditation.

The idea is not only to transport yourself elsewhere but also to access the expertise of people anywhere in the world. You could experience guided meditation by monks in Tibet, or join a workout session with your favorite fitness star.

Telemedicine

The COVID-19 pandemic forced us to minimize doctor visits to avoid potential exposure to the virus. Telemedicine was heavily worked on before, but COVID accelerated its acceptance across the board.

With the metaverse, people from all over the world could walk into a virtual hospital and receive care from the best health professionals around the globe – neither of them would even have to leave their living rooms.

While cameras and a conversation are a start, they often aren’t enough to diagnose health issues accurately. That’s why we need to use new sensor technology like smartwatches, home medical equipment and even smart pills.

Medical training

Someone has to be a doctor’s first patient. Aspiring doctors can practice as many procedures as they want inside the metaverse without risk to an actual patient.

Students can gain hands-on experience or learn in an immersive, reactive environment instead of reading books in a cold classroom.

Medical procedures

In the metaverse, we can access the best technology and expertise from top professionals worldwide. We’re not limited by our physical surroundings. For example, in surgical procedures, we can pilot robots from afar and have as many steady hands as we need:

Few hospitals are equipped with this kind of technology. But even with normal VR goggles, you can effectively use the metaverse for medical procedures. For example, distracting children with games during injections has proven effective.

The Titan-e project ran for the past three years. It aimed to bridge the gap between scientific institutions and entrepreneurs, fostering collaboration, knowledge exchange and technological advancements in the Upper Rhine region, encompassing Switzerland, Alsace, and Baden.

The project focused on advancements in innovation and technology. Academic institutions, entrepreneurs and various organizations came together to advance the region’s economy and contribute to overall well-being.

As part of Titan-E, ADEUS has developed a cross-border network on health technologies in the Upper Rhine. This cartography takes the form of a dynamic visualization of the ecosystem through the representation of its actors and the interactions in which small and medium-sized enterprises are involved.

Under Titan-e, we also brought the i4Challenge to live. It provides mentoring, support and visibility to startups and SMEs with promising ideas in various industry 4.0 topics like robotics, AI and sustainability.

In the years 2021 and 2022, a total of 71 projects applied to the competition. A tri-national jury of experts from both industry and academia evaluated these projects to identify the best ones and offer them further development opportunities.

The last iteration of the i4Challenge is now closed. And while the Interreg project Titan-e is over, we’re still committed to providing the latest insights and promote collaboration in the community of the Basel Area and across its borders.

So stay tuned for our next Technology Circle event. We’ll announce its topic soon via email.

The AI4SME Guide is your first step to implementing AI in your manufacturing SME. It contains the combined knowledge our partners and us have gained in the past three years of developing AI projects.

The AI4SME Guide…

• provides insights on the need for innovation in manufacturing SMEs.
• helps you determine the relevance of AI adoption for your SME.
• contains information about support options in the Basel Area.
• addresses progress blockers like skepticism, resource limitations and uncertainty.
• gives step-by-step instructions to start your AI journey.
• explores the do’s and don’ts when implementing AI in a business.
• showcases inspirational success stories.
• links sustainability and AI.
• showcases future technologies.
• summarizes goals, successes, and learnings from the AI4SME Program.

The two following companies have gone through the AI4SME Program to develop a proof of concept for their AI project that can meaningfully transform how they operate.

KETAG uses AI to enhance energy efficiency

Küffer Elektro-Technik AG has more than 70 years of experience in auditing, repairing and improving drive systems of all kinds.

Through AI4SME workshops, KETAG developed an app called TSapp. It makes it easy for workers to find the most suitable and energy-efficient replacement electric motor.

According to EnergieSchweiz, electric motors consume about 20% of Switzerland’s electricity. Due to a lack of expertise and time pressure, broken motors get replaced by the same models instead of more energy-efficient ones.

With TSapp, anyone can scan the data of a motor embossed on its type plate. A matching algorithm compares this information with the IEC standard and automates the search for a suitable new motor. A corresponding list of recommended electric motors is provided, and thanks to the interconnection of suppliers, ordering them is quick and easy.

The solution is independent of the manufacturer and can read type plates of various ages up to 40 years old.

Liebherr-France uses AI to improve operational efficiency

The Liebherr Group is a Swiss conglomerate known for its diverse range of products, including construction machinery, aerospace components, and domestic appliances.

Through AI4SME workshops, Liebherr developed a solution for the early detection of dysfunctions in their production machines.

Production machines sometimes break down. When that happens, they need to be repaired, which costs money and creates downtime in production. Liebherr found that in around 5% of cases, spare parts are missing, which delays immediate repairs.

To anticipate failure, Liebherr identified collecting more (and the right) data as key.

Liebherr uses various sensors to record all relevant machine variables. The collected data is stored on a server hosted by Liebherr and accessible through a secure connection.

As a result, Liebherr prevented a lengthy machine shutdown in a quick intervention that lasted only 10 minutes.

Get the full AI4SME Guide

In the last three years, we’ve helped eight companies to develop a proof of concept for an AI solution that could meaningfully transform their businesses. We brought together stakeholders from private individuals to companies and governments over three nations to exchange knowledge and innovate together.

The full AI4SME Guide contains all the information you need to develop and implement AI in your manufacturing SME.

Sébastien Trillat, Innovation Global Domain Manager at Forvia, introduces his company and explains why they partnered with the AIARD Industrial Chair. Forvia is a leading global automotive technology company. It’s based on the long-established company Faurecia and is the 7th global automotive supplier.

A few years ago, Sébastien wanted to start working with TRIZ. Forvia partnered with AIARD Industrial Chair to train its employees in the TRIZ methodology. Soon, Forvia saw the potential benefits of dedicating resources specifically to the methodology. That’s when the company hired a young engineer to develop an internal network on TRIZ. Meanwhile, Forvia is already implementing many TRIZ principles to reap the benefits early on. And with great success! A tool they’ve developed together with AIARD Industrial Chair is expected to bring benefits in the double-digit millions.

Prof. Dr. Bernhard Kölmel from the Hochschule Pforzheim & WFG Wirtschaftsregion Nordschwarzwald taught us how decision makers can implement AI in their organizations. He started with a quote from Lord of the Rings.

ChatGPT has created a lot of hype around AI. It’s an important topic and experts say that while the hype is at its peak, they don’t expect a bust following it. It’s important to see the big picture. ChatGPT-4 is very impressive but the competition isn’t sleeping. China, for example, has developed a language model even larger than ChatGPT-4! AI is also becoming even more interesting thanks to the Internet of Things (IoT). Almost every machine — even fridges and toasters — collect data that we can use to formulate problems and find solutions.

Companies aren’t used to dealing with easily accessible AI yet. Many think that there are dangers to AI. They try to find these “AI heroes” with the idea of trusting them on every business decision that involves AI. We need to demystify AI and get rid of the “heroes”. Bernhard made a great example why it’s so important.

Every decision maker needs to be competent in making AI-involving decisions. AI projects are more than a code. According to a 2014 research paper by Google, only 3% of all AI activities are about the algorithm. The rest is about the work that needs to be done around the algorithm.

Al technologies are complex and relatively new to the business world. Few decision makers understand them. To truly unlock the value of Al, you have to fully integrate it into the fabric of your company. That requires strategies and approaches that understand the science behind AI, the techniques to implement it and the right metrics to measure it’s success. It’s necessary for every company to develop an AI strategy, broken down into concrete, measurable goals. A few examples of AI successfully improving new product development

Bernhard introduces three examples to showcase the power of AI in product development.

• The Volkswagen Group is using Al to improve the efficiency of its production processes. The company has developed an Al system that uses data from the production process to predict quality defects and improve the production process. This has resulted in significant improvements in production efficiency and reduced defect rates.
• Siemens is using Al to optimize the design of its products. The company has developed an Al platform that uses machine learning algorithms to analyze data from product simulations and tests. This has helped Siemens to optimize product designs, reduce development time, and improve product performance.
• Bosch is using Al to develop new products. The company has set up an Al research center that focuses on developing Al-powered products, such as smart home systems and autonomous vehicles. This has helped Bosch to diversify its product portfolio and stay ahead of the competition.

To decide on what AI project your company should work on, Bernhard recommends the AI Project Canvas, modelled after the famous Business Model Canvas. Here is where you can find it with a detailed explanation:

Dr.-Ing. Darko Katic from ArtiMinds GmbH in Karlsruhe showcased how ArtiMinds uses AI to realize the full potential of advanced robotics. Darko puts his company’s mission simply:

To do that, ArtiMinds has two solutions. First, the Robot Programming Suite (RPS) enables developers and process experts to program industrial robots in an easy, intuitive fashion. Second, the Learning & Analytics for Robots (LAR) collects all data coming from a robot and helps analysts interpret it in a meaningful way.

Currently, a lot of manufacturing happens in low income countries. There’s a risk to that as we’ve seen with the pandemic or the war in Ukraine and the respective production issues. We need to bring production back into our own country. The only way to match the cheap labour cost is by using advanced robots.

Robots are very good if they can repeat the same task over and over again without having to adjust to anything. In reality, manufacturing isn’t that easy.

• No two work pieces are the same: there might just be a mm difference between them, impossible to see with your naked eyes. If a piece doesn’t fit, we adjust it intuitively. A robot can’t.
• Something might be “broken”: if a pin on a circuit board is slightly bent, the robot can never fit anything on it. A human would just bend the pin back.
• Not all pieces are rigid: cables, for example, might fall in a weird position or even tangle up. While a human can untangle them easily, a robot can’t work with them anymore. Those are just three of the many challenges we’re facing in advanced robotics.

The robot needs to be able to understand the problem. With sensors, the robot can see and feel the parts its working with. Almost like a human would. If, for example, it needs to insert one piece into another, it’ll register resistance if the pieces don’t fit. It’ll then adjust the position until there is no resistance anymore. With lasers and cameras, the robot recognizes the parts and their positions to adjust itself, making it possible to automate the production with cables and tubes.

It’s fairly easy to make these solutions work in a controlled setting. But getting them production-ready is a different story. That’s why we introduced data driven analysis and optimization. Everything the robot does generates data which we can attribute to a specific action. We collect and visualize this data to make it possible for engineers to easily identify flaws and mend them. A mistake can take only milliseconds and nanometers. An engineer needs the visualization of the data to see it.

Our AI already generates possible solutions to the problems for the engineers to simply verify and implement. The next goal is to enale the robot to learn from its mistakes and make the adjustments itself with the help of a digital twin.

The Industrial Transformation initiative: Realize digital transformation in your company.

The production industry is a significant economic sector in the Basel Area. To help companies succeed, we bring together stakeholders from industry, academia and startups to collectively advance innovation in the field of Industry 4.0.

Our Industrial Transformation team’s activities include:

• A series of public events for the industry dedicated to technologies important for the innovative development of our tri-national region.
• Promote cooperation between entrepreneurs and academia.
• Technology circles Industry 4.0 Events and workshops on Industrial transformationIoT and advanced technologies for digital transformation.
• An AI4 and SME program for the collective and concrete development of Proofs of Concept with Artificial Intelligence Innovative solutions for the production industry.
• The i4Challenge accelerator for SMEs, startups and new ideas for Industry 4.0.