By Patricia Deflorin and Reik Leiterer, databooster, Photos by Industrie 2025
Mastering current challenges with foresight
On the 9th of May, the 10th edition of the “Industrieforum 2025” by Industrie 2025 focused on challenges and solutions related to digital transformation and innovation in the industry sector. Adam Gontarz, President of Industrie 2025, opened the event (btw fantastically moderated) with a look back at 10 years of the Industrieforum and why the topics of that time are still highly relevant today.
One of the program highlights was already reached with the keynote by Dr. Thomas Zurbuchen, several years head of science at NASA. In a convincing manner, he got to the heart of the drivers of innovation without forgetting to discuss the related challenges from different perspectives. With his personal lessons learned and a 500-year-old quote by H. Cortez (1519), which is remarkable in its actuality regarding disruptive innovation, he gives an extremely inspiring start to the day:
“To lead change, be willing to burn your ships in the harbour.”
From our perspective as a network for data innovation and data-driven value creation, the subsequent presentations offered an exciting insight into the increasing importance of data and the associated fields of application in industry/manufacturing. Johann Hoffman from MR Maschinenfabrik Reinhausen, for example, highlighted the need for data governance, without which Industry 4.0 cannot be successfully implemented. From cybersecurity and digital, economically sustainable services in mechanical engineering to the concept of meta factory and the use of AI – the data reference was strongly present in almost all presentations. That’s why the databooster program exists – to encourage the development of innovative ideas in this area!
On the exhibitor side, there were exciting players in the data field to discover. CLUE Security Service AG, for example, presented operational approaches for early detection of IT threats and the protection against attacks – both for critical local infrastructure and for web-based infrastructure. OCTOTRONIC GmbH offers comprehensive solutions in the frame of an Analytics Landscape for process monitoring, data management and planning optimization. And akenza.io supports the manufacturing industry by adding remote monitoring and predictive maintenance capabilities to existing products and equipment based on their low-code IoT platform with visualization and data processing capabilities.
The event convinced with the awesome atmosphere, the very good speakers, open-minded participants interested in exchange and cooperation and a perfect organization. Therefore: we are looking forward to the 11th edition!
May 3, 2023 – By Gundula Heinatz Bürki and Reik Leiterer, data innovation alliance. Photos Markus Burren, Oracle
How can the databooster, the innovation program of data innovation alliance powered by Innosuisse, help to smooth the path for the first steps of innovative ideas – and most importantly, lead to the right direction in the process?
10 innovation teams presented their Databooster-funded ideas on the 3rd of May, directly opposite the Zurich airport at the beautiful Oracle venue. At this point – many thanks to Oracle, our host on this day. After the amiable welcome by the Oracle team, the participants got insightful presentations about the process and the first outcomes of the individual innovation journeys as well as the future path and direction now being taken.
The first block of presentations covered the potential of customized holistic energy solutions (Endaprime), challenges around the complexity of manufacturing process data (CSEM), and the development of tools for the automated detection of fake news (ZHAW). Following a Q&A session, the participants particularly appreciated the exchange of experiences on the problems encountered and the related solutions, as well as the open communication about wrong directions and obstacles that still exist.
This lived and shared culture of failure is very much in line with our understanding of innovation. The block was concluded with a presentation by Andreas Steiner and Patrick Jung from TEK, an organization that facilitates the transfer of knowledge from universities to SMEs in the industrial sector and supports the rapid and economically sustainable implementation of innovation projects.
After a short interactive sequence on the concept of future thinking and foresight, another block of presentations followed. These included a presentation on intelligent energy systems in the field of e-mobility (eneXan), a framework for standardized and automated ESG reporting (Ascentys), and the ethical and social requirements for the use of AI in law enforcement (Eraneos).
The lively discussions during the networking coffee break about the presented projects and ideas had to be interrupted at some point, however, as the last block of presentations also provided exciting insights into the work of the innovation teams.
Starting with a radical approach for achieving the optimum in terms of collaboration and operational efficiency from a company’s workforce (Peerdom), through automated risk analysis in data projects (Xurce) and the support of companies in the digitization process via an independent and open consulting network composed by agile and specialized consulting cells (Swiss Digital Network), to support decision tools for health care providers (Rewoso).
During the subsequent aperitif, new contacts were made and the next steps and possible collaborations were discussed. The variety of project ideas and their high degree of innovation, the noticeable motivation and enthusiasm of the various innovation teams, and the number of already successfully implemented solutions have shown that we have taken the right path with the databooster approach of sharpening the ideas and providing financial support for the first steps of innovation. Maybe next time you are one of the presenting teams? – If you are interested, please contact us or visit our website!
The construction industry has been undergoing a digital transformation, with data science playing an increasingly important role in improving efficiency, reducing costs, and enhancing safety. However, to fully realize its potential, it’s essential to promote open innovation and collaboration between data scientists and construction experts.
For this purpose, the first open innovation workshop on “Construction & Data Science” was recently held in Zurich, Switzerland, bringing together 40 participants from both fields to explore the intersection of construction and data science.
Findings
To improve cooperation between the construction industry and data science, the workshop formulated central key findings:
Focus on creating structured data sets across projects, teams, and companies and move away from managing data in CAD systems.
Don’t wait for new standards to be defined, learn to combine information from different sources and standards by mapping it.
Consider using other ways of pulling data from CAD tools, like Speckle or an IFC-based modeling tool like Blender.
Engage in open source or open data projects and learn from others, especially in rapidly evolving technology.
Check out sites like www.opensource.construction/ to proactively work towards changing the status quo and improving the industry.
The summary is also nicely put together in the Linkedin post by opensource.construction’s President, Maximilian Vomhof.
The Event The workshop aimed to identify potential problems and solutions in this area and to promote open innovation and collaboration between data scientists and construction experts. In this blog post, you will find a report on the insights gained from the workshop and highlight the importance of open innovation in these industries.
The workshop was organized jointly by opensource.construction, bauen digital Schweiz, and the data innovation alliance at Amstein + Walthert in Oerlikon. After a short introduction to the Databooster program, the passive part for the participants was over!
The workshop was structured according to the double diamond framework from design thinking, which consists of four stages: discover, define, develop, and deliver. After the four groups got to know each other, they explored the problem space at the intersection of construction and data science or data engineering. In this phase, the focus was on generating a wide range of ideas and potential solutions by asking “why” questions and understanding the workings of the construction industry as a data scientist – essentially, “falling in love” with the problem.
At this workshop, “love” was certainly in the air, with many questions generated. Of these, five problems were identified as most relevant:
Optimized building scans
Open-source door planning configurator
Linked product data
GIS data linked with building laws
Open data environment for storing and linking element-independent information
In the second part of the workshop, powerful teams were formed around the ideas generated. They not only focused on potential solutions but also on related business cases, which added a practical, pragmatic dimension to the ideation process.
One of the solutions produced was standardization, particularly in the light of data formats. However, it was agreed that establishing standards and achieving consensus could take a long time – a luxury that the construction industry simply doesn’t have. It was essential to identify quick and effective solutions that could be implemented without major delay.
Despite the apero long being ready, the teams were still deeply engaged in finding innovative solutions that could be launched swiftly. The teams agreed to follow up on their ideas and continue pushing for change, possibly using the Innovation Booster Databooster, something we are particularly happy to hear.
In conclusion, we believe that the Innovation Booster Databooster initiative is a valuable resource for teams to develop and implement their solutions generated using the double diamond design thinking structure. We look forward to seeing how these ideas will shape the future of construction and data science!
By Michael Opieczonek, Innobooster Robotics and Reik Leiterer, Innobooster Databooster
Joint Event by Innovation Booster Robotics and Innovation Booster databooster March 16th, Biel/Bienne
The event was organized on premises of Switzerland Innovation Park Biel/Bienne. As this is a center of innovation, premises of a smart-factory and cobotics center, the symbolic meaning of this location resonated well with the event. The event started with keynote talks, addressing the topics of smart factory, cobotics, human-machine-interaction and general trends in the field of robotics and data-driven value-added services. After a networking lunch, an interactive, moderated design thinking workshop for identifying challenges and developing ideas and solutions was organized.
In form of impulse presentations. 5 speakers give inspiring insights into their research and application areas as well as highlighting current challenges to solve within their respective fields:
Prof. Dr. Sarah Dégallier Rochat, Lead of Humane Digital Transformation at Bern University of Applied Sciences delivered a presentation on Robots as tools: New approaches to robot integration for SMEs. She highlighted that Swiss SMEs are the makers and can turn workers into makers via the concept of augmented worker. Dr. James Hermu, Postdoctoral Researcher in the Learning Algorithms and Systems (LASA) Laboratory at EPFL, delivered a presentation on Real Time Adaptive Systems for Human Robot Collaboration. He talked about methods to teach robots to perform skills with the level of dexterity displayed by humans in similar tasks. Philipp Schmid, Head Industry 4.0 & Machine Learning at CSEM (Swiss Center for Electronics and Microtechnology), delivered a presentation on Industry 4.0 and Machine Learning. He highlighted the need of how machine learning and robots can automate processes at industrial sites and hence increase future of smart-factories. Dr. Renaud Dubé, CTO and Co-Founder of Sevensense Robotics, delivered a presentation on Visual AI: Empowering a new generation of mobile robots. We learned about robots visual capabilities and challenges: lighting and viewpoints changes and understanding semantics.
Prof. Dr Marc Pollefeys, Professor of Computer Science at ETH Zurich and the Director of the Microsoft Mixed Reality and AI Lab in Zurich, delivered a presentation on spatial computing and the industrial metaverse. He gave interesting examples how metaverse can be used for instructional trainings of workers at industrial settings and how spatial computing is contributing to more sophisticated mapping and localization of robots.
The ideation workshop followed in the afternoon and was moderated by the facilitators Prof. Dr. Patricia Deflorin and Dr. Jürg Meierhofer. The workshop took the format of sequences that build on each other – from identifying and understanding the problem to designing the right solutions. The workshop sessions were closed with the presentations of the devleoped ideas and solutions.
The identified challenges could be roughly clustered into 3 categories.
Cluster 1 relates to the general challenges of integrating automation (both on software and hardware side) into existing processes. On the one hand, this includes the necessary technological knowledge and understanding of WHAT one wants to implement – on the other hand, it also includes the expertise or competence development within the company on HOW it can ultimately be integrated. Decision-makers, employees and customers must all be integrated into this process,
and employee acceptance and training/up-skilling must be ensured – all while considering the short- and long-term cost-benefit relations, ethical and moral issues, and cultural acceptance.
Cluster 2 refers to machine learning systems that react more flexibly/dynamically to process changes. On the one hand, regarding rapidly changing environmental conditions,
on the other hand, related to highly dynamic process sequences (small batch manufacturing). This requires not only innovative approaches in human-machine interactions (intuitive, ease-of-use handling, no-code environments etc.) but also standardization in processes and interfaces as well as further developments in modular and self-learning ML systems. In this context, the challenge also arises as to how and whether the individual, experience-based knowledge of experts in a company can be transferred to (semi-)automated processes, e.g., the transformation of human intuition in process understanding to rule-based robot-supported systems.
Cluster 3 concerns the (extended) use of cobots/robots in the field of maintenance. This concerns the large area of logistics/ergonomics, from pick-up, sorting and movement of highly divers component categories, to complex processes in material/surface inspection, automated damage repair/replacement, and assembling and dismantling of large rail vehicles. In these processes, the reliability/accuracy requirements are a major (technical) challenge and addressing them would often involve very high costs.
For each cluster, the workshop participants focused on some of the identified challenges and discussed possible solutions.
Solutions Cluster 1:
Guideline/framework for the integration of automation processes into existing workflows, considering management, customer, and employee’s perspectives (at the meta-level).
Framework for integration and regular assessment of compliance with ethical and moral guidelines and legal framework conditions.
Guideline/framework for the practical implementation of automation processes in the company regarding the involvement of employees: internal acceptance, considering employee’s needs, training/education (up-skilling) and empowering.
Needs assessment for automation solutions in industry (standardization, interfaces, usability/interactivity).
Solutions Cluster 2:
Development of automatization solutions that can meet the requirements of low volume/small batch production or highly variable process flows.
Development of ML systems with improved flexibility in terms of self-learning/self-optimizing components so that they can better adapt to changing environments and high-complex processes.
Development of monitoring systems to capture unconscious, intuitive human components in the manufacturing process and convert them into a rule-based, machine-executable program (e.g. ViT).
Solutions Cluster 3:
Development of a tunnel scanning and cleaning system to identify and remove paint from vehicles – a combination of intelligent optical sensing for detection and characterization of paint and non-destructive automatization for cleaning/removal of paint while preserving the underlying paint/coating etc.
Development of a tunnel scanning system to identify and characterize surface damages/deformations on large vehicles – a combination of intelligent passive and active optical sensing, resulting in a digital 3D-representation and classification of surface damages/deformations.
System development of an automation solution for different tasks as a mobile implementation which works inside of large vehicles.
Conceptual development of a holistic system (identifying segments, sub-processes, requirements) to support logistics/ergonomics, both in terms of the potential of autonomous (e.g., for, sorting, transport) and worker assistance systems (e.g., exoskeleton, human-robot collaborations).
If you are interested in the ideas and/or you want to further explore these challenges and ideas, we welcome your submission for proposals during the calls by both boosters:
In a distinguished group of highly experienced people, we discussed how value is created in business ecosystems and differentiated between the individual and the organizational perspective. It was very inspiring to have diverse industry representatives in the same room and to create a common understanding. Departing from economic value creation, we extended our scope to the ecological dimension. An intense discussion arose how ecological value can be created without negatively impacting the economic value. There were statements that economic value creation is still the predominant requirement, and that in many cases, also a slight reduction of economic value for the sake of ecological value would not be accepted. However, the increasing relevance of sustainability and upcoming regulations might change this balance in the near future.
The Data Innovation Alliance’s second Expert Day in March 2023 was a hub of activity as experts from four key areas – Smart Maintenance, NLP & AI Technology, Spatial Data, and Smart Services – gathered to share their insights and mingle with researchers and industry professionals. The event kicked off with leaders from each Expert Group pre-discussing their plans for 2023, generating a wealth of innovative ideas for joint events and initiatives, and paving the way for exciting collaborations in the (near) future.
But that’s not all! The NLP and Digital Health groups are teaming up to bring you joint events that will revolutionize the way we approach data. And with the next Expert Day set for August 2023, featuring four expert groups once again, get ready for even more ground-breaking discussions and initiatives, organized jointly with other Innovation Boosters. Keep an eye on our events calendar for more information.
While the keynote speech may not have met expectations in terms of insights, it set the stage for what was to come – dynamic discussions and collaborations in the expert group break sessions. To ensure everyone had access to the wealth of information shared, short summaries of the discussions were written by participants in each room.
In short, the second Expert Day was a superb success, bringing together a diverse group of experts to debate their ideas and shape the future of data innovation.
Smart Services for Sustainability – Circular Servitization by Jürg Meierhofer
The Smart Services for Sustainability – Circular Servitization discussion was a dynamic conversation among highly experienced individuals from different industries. They explored how value is created in business ecosystems, focusing on both individual and organizational perspectives.
It was inspiring to have diverse industry representatives in the same room and to create a common understanding. Departing from economic value creation, the group extended its scope to ecological factors. An intense discussion arose about how environmental value can be created without negatively impacting economic value. Statements that economic value creation is still the predominant requirement were made, meaning that in many cases, even a slight reduction of economic value for the sake of ecological value would be treated with suspicion. As sustainability becomes increasingly relevant and regulations loom, the balance between economic and ecological value may shift in the near future.
Overall, the Smart Services for Sustainability – Circular Servitization discussion was thought-provoking and left participants eager to continue exploring the intersection of business and sustainability.
Spatial Data by Reik Leiterer
In a room buzzing with ideas, each data expert chimed into the discussion about the creation of a platform that would benefit cantons, individuals, and service providers. There was a shared understanding that it might not be possible to cater to everyone’s needs and that a simpler visualization and analytics approach may be the way forward. However, some uncertainties still remained, such as identifying where the necessary data is available and how it can be integrated, setting limits, and ensuring that data is not misinterpreted. Despite these challenges, the group remained enthusiastic about the potential benefits of the platform and is looking forward to overcoming these obstacles.
NLP & AI Technology by Lina Scarborough
The group opened the floor with how chatbots are great to answer questions, but what happens when users don’t know where to begin asking questions? This is a common issue in legal situations where the average client may not have the necessary background to understand what information is needed. Retrieval augmented language models like KATIE have emerged as a solution to this problem. These models use grounded reasoning and promote a chain of thought to handle complex queries and create a context for users who may not know what subset of questions to ask.
With the rise of machine-generated text, it’s becoming more difficult to distinguish between human and machine-generated content. While probabilistic token selection and frameworks like SCARECROW can help scrutinize machine-generated text, it can still be difficult, to nigh impossible, to identify. However, ChatGPTZero, an app that uses watermarking to create a statistical fingerprint in the sampling method, claims to be able to detect whether an essay is written by ChatGPT or a human – for instance, ChatGPT generally makes redundancy errors whereas humans make grammatical mistakes. This approach hopes to maintain the integrity of human-generated content in the face of increased machine-generated text.
The discussion then flowed into a lively and engaging presentation on how AI technology can make the tricky SQL “minefield” as easy to navigate as a soccer player scoring a goal – literally, by demonstrating SQL prompts on the soccer World Cup!
Smart Maintenance by Melanie Geiger
The five use case presentations highlighted the versatility of data technology in different applications, showcasing how it can be adapted to meet various needs. With input data ranging from domain knowledge to error log data, these use cases demonstrated how AI models can process and analyze complex data sets to provide valuable insights and decision support.
One of the key themes that emerged was the use of AI for diverse condition-based maintenance, specifically anomaly detection and fault diagnosis. By leveraging ML algorithms, these use cases were able to detect potential issues and predict equipment failures for timely maintenance and preventing downtime.
The highlight of the event was not only the apèro treats, but the opportunity to engage with the 60 participants and learn about their projects, challenges, solutions, and ideas for collaboration. Many attendees seemed to share this sentiment, as numerous participants were still engrossed in conversation at the end of the event, and some discussions had to be continued elsewhere. Those who wish to follow up on these conversations have the option to do so at SDS2023. On a more lowkey note, maybe you wanted to add someone on LinkedIn and send them a message. Here you go, this is your reminder!
Our conclusion of the event: the Alliance has many experts in various subtopics of data-driven value creation, but only together we can move faster.
How has Switzerland managed to top the Global Innovation Index rankings for years? State and cantonal funding agencies and regional think tanks play a decisive role. But what is an innovation anyway and how is the degree of innovation measured? What is the difference between an idea, an invention, and an innovation? And what entrepreneurial prerequisites does “real” innovation need?
These and other questions were discussed during the Lunch & Lecture series at the Paulus Academy in Zurich on 1st of February. Gundula Heinatz Bürki, the managing director of the data innovation alliance, took the participants on a journey through the history of innovation in Switzerland and showed how ideas, inventions and innovation are connected. Using the example of various global innovation rankings, she explained the multitude of criteria that go into such rankings and why Switzerland benefits from the innovative large enterprises with a high rate of patent applications.
It became clear that there is still room for improvement related to innovation promotion at SME and start-up level and how the federal government, cantons and regional associations have been active in this area in recent years. The possibilities of the Innosuisse programs such as the Flagship Initiative or Innovation Booster were presented, cantonal initiatives in Zurich, Vaud, and Grisons analysed and the ideas behind the regional research clusters driven by Switzerland Innovation discussed. Bottom line: Interested participants, exciting discussions and the conclusion that Switzerland has an enormously high innovation potential, but that it still needs programs and initiatives such as the Databooster in order to keep top positions in the rankings in the future. Because there is one thing that does not exist in the innovation process: stagnation.
By Nicolas Lenz, Xurce and Gundula Heinatz Bürki, data innovation alliance
The Alliance’s commitment is manifold. The network is not only committed to professional exchange, but also wants to contribute to social challenges.
Society is changing, and in recent years the labor market has been shaken up considerably. The need for new work models, more home office and a generally improved work-life balance are sprouting up.
After an introduction of Priska Burkard from techface about facts and figures to the actual situation of women in tech force we discussed the challenges and first ideas about possible solutions.
A workshop dedicated to these topics led to surprising results!
Employers have adapted to the new circumstances and offer (from their point of view) flexible working conditions.
However, many of them fail to make the working conditions visible to the outside.
In daily business, the working conditions are not lived, promises are too often broken.
The needs of the employees often do not coincide with the offers of the employers.
In a typical organization, people with different needs work together. This also means (from the employees’ point of view) that they do not all need the same working conditions.
We consider it important to further deepen these discussions. The next step is to find the right form of discussions and then produce a tangible output.
By Focus Topic Leads Industry 4.0: Patricia Deflorin, FHGR, Philipp Schmid, CSEM and Philipp Hauri, Industrie 2025
Research meets Industry – from ideas to business cases.
In the knowledge that networking and cooperation with universities is an important success factor for the innovation activities of companies, Industrie 2025 initialized the “R&D Conferences on Industry 4.0”.
In these conferences, you will get an overview of the topics of the near future in an efficient way and get insights what is being researched and developed at universities and universities of applied sciences in the field of Industry 4.0.On the 24th of January, they invited for the 8th R&D Conference on Industry 4.0, which was hosted by HSLU (Lucerne University of Applied Sciences and Arts) in the city of Rotkreuz.
After the welcome by Philip Hauri (Industrie 2025) and an inspiring keynote from Stephan Keller (V-Zug, HSLU), 23 university projects linked to emerging topics in the fields of Artificial Intelligence, Smart Factory, or Digital Twin were presented.
In this context, Sybille Aeschbacher from Innosuisse presented, how knowledge transfer from universities to industry can be promoted and what tools are available in Switzerland for this purpose – where of course the Innobooster Databooster is part of it. Next to the talks, a poster exhibition gave the participants the opportunity to get in direct contact with the speakers and learn more about the projects presented.
The conference convinced with the knowledge and innovative spirit among the speakers and participants and how the intensive exchange between research and industry was noticeable during the whole time. And in the end, it has once again become clear that rapid technological developments only develop their full potential when the corresponding business cases are in place.
By Markus Christen, UZH, Christoph Heitz, ZHAW and Karin Lange, La Mobilière
On December 15, eight members of the Data Ethics Expert Group met to look back to this year’s achievements and to determine the theme of 2023. The group decided to focus its activities on “Responsible AI”.
In the year 2022, the main activities of the Data Ethics Expert Group focused on three events, one internal event for discussing recent research projects on data and AI, one public event presenting the Digital Trust Label (see https://data-innovation.org/what-are-the-benefits-of-the-digital-trust-label/) and one public event organized together with Economiesuisse and the UZH Digital Society Initiative (see https://ethics.dsi.uzh.ch/news/ethics-and-the-data-economy/), where more than 30 industry representatives exchanged on practices to improve data ethics.
Furthermore, expert group member Christian Hauser reported on a funding success that emerged out of expert group activities: Innosuisse will fund the project “Entwicklung eines digitalen Dialogsystems für die heuristikbasierte Integration von ELSI in datenbezogene Entscheidungen bei Schweizer Unternehmen”. This project is partly based on the Data Ethics Code created by the Expert Group and published in 2020.
For 2023, the activities of the expert group will be centered around the topic of “responsible AI”. Due to the recent attempts of the European union to put forward AI regulation, many companies are starting to question the practical implications. Thus, the expert group aims to support the clarification process by focusing on the potential compliance challenges and related consultation needs companies may have. The expert group thus aims to organize a series of events and other activities (e.g., member survey) to first assess the compliance challenges associated with the current draft of the EU AI regulation and then to discuss the concrete needs that follow from those challenges. A detailed program will be worked out in Q1 2023 by the expert group leaders.
