S3Food hands out 14 grants to projects for digital innovation in food manufacturing

DSP Valley is glad to announce that 28 SMEs will receive funding from S3FOOD, the pan European project for digital Industry 4.0 transition in which we take part as one of the 13 international consortium partners. 14 projects have been selected with themes like ‘data-driven fermentation management’, ‘egg processing with enhanced data integration’ or  ‘smart systems for real-time monitoring of evaporation in wine aging’.

14 cross-sectoral collaboration projects

This has already been the second S3FOOD voucher call within the project. 14 innovative SME driven projects have been selected all across Europe. The winning projects will receive funding to develop and adopt innovative digital solutions to concrete challenges food processing companies are facing to modernize and improve food production.

Alltogether, the 14 cross–sectoral collaboration projects will receive different types of vouchers for an amount close to 1.3 million Euros. The types of vouchers vary depending on the development stage of the project, called the TRL, or Technology Readiness Level. The earliest stage projects receive up to 15,000 Euro while the larger scale collaboration projects  receive up to 180,000 Euro.

Industry 4.0 transition

S3FOOD wants to establish an innovation-friendly, cross-border and cross-sectoral ecosystem to help SMEs start their Industry 4.0 transition.

Veerle De Graef, Innovation Manager, Flanders’ FOOD– coordinator of the S3FOOD project: “Companies that still rely on a few in-house specialists to register and interpret processing data are at risk of losing important knowledge and expertise. Using for instance smart sensors, makes it possible to secure everything in automated systems and to bring sustainable benefits to their business, improving efficiency and quality of the production methods.”

Besides the funding, being a part of S3FOOD also grants the 14 projects access to industry experts, knowledge sharing, a solid network of like-minded SMEs and much more.

A revolution in progress

Many larger companies have already responded to the fourth industrial revolution – the digital revolution -, by automating and digitalizing their process. This includes benefiting from the related data generation, which opens the door to identify processing issues quicker. This also gives opportunities for continuous improvement.

S3FOOD targets the many SMEs in the agri-food industry in Europe, that have still not found the partners and funds to start the same journey towards digitalization.

The consortium has already supported 44 projects with 51 unique SMEs across Europe and now adds 14 new projects to the portfolio.

“While we are still in the middle of the S3FOOD project, we can already begin to see the results of the first projects that received the funding vouchers. It’s fascinating to see how SMEs can truly benefit from the latest technology, and we are happy to be able to welcome another 14 projects to S3FOOD, and to the future of food production,” says project leader Veerle De Graef.

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S3FOOD is a 5 million Euro Innosup – 01 project under H2020 that aims to stimulate the uptake of smart sensor solutions by the small and medium sized enterprises in the agri-food sector with the purpose of improving efficiency, sustainability and safety. S3FOOD started in May 2019 and has launched two voucher calls where SMEs could apply for funding for the implementation of innovative digital solutions to concrete challenges of the food processing industry.

The S3FOOD consortium consists of 13 partners from across Europe:
Flanders’ FOOD, Belgium; DSP Valley, Belgium; Wagralim, Belgium; INNOSKART, Hungary; AgriFood Capital BV, The Netherlands; AIN, Spain; ASINCAR, Spain; Bretagne Développement Innovation, France; CLUSAGA, Spain; CORALLIA , Greece; Food & Bio Cluster Denmark, Denmark; Food-Processing Initiative, Germany and CIMES, France.

Read more about S3FOOD on www.s3food.eu  or follow the project on LinkedIn and twitter: @s3food_eu

S3FOOD has received funding from the European Union’s Horizon 2020 research and innovation program under grant agreement No. 824769-S3FOOD.

Sfella, the Smart Flush solution, is ready to enter the Legionella prevention market

In the Netherlands, 300 to 400 people are infected per year with the legionella bacteria (Legionnaires’ disease or Pontiac fever), a number that is rising each year. Victims of the bacteria suffer for a long period, from several months up to more than a year. Between 5 and 10% of cases are lethal.

Legionella infections mostly occur through people breathing in legionella-contaminated aerosols. Aerosols are small droplets of water that are generated, for example, when showering. For this reason, public showers like the ones in sports centres, swimming halls, and saunas, as well as truck stops and camp sites, need to be flushed regularly to prevent legionella growing in the water pipes. The required flushing is often done manually or semi-automated, which is very time consuming, prone to human errors, and labor intensive. Especially when one takes into account the legal obligations to report data like date, time, water temperature, and flush duration per shower.

The risk of legionella contamination has increased in the current Covid-19 crisis with the (temporary) closure of facilities. Showers are not used by clients and facility engineers who have to stay home and are not allowed to come to their facilities for the requisite flushing.

Sfella is the Smart Flush solution by Mioto* that addresses all of the above issues. Sfella is a user-friendly, reliable and easy-to-install solution for legionella prevention. The system is modular, for use within environments with multiple showers. It assures flushing the shower(s) happens after an operator-defined time period. The system reports the important flush data like date, time, duration, and water temperature. This reporting and control of the showers happens locally or remote via a dedicated gateway.

Sfella is powered by the mesh network MyriaNed. It is an infrastructure of nodes that connect directly, dynamically, and non-hierarchically. This allows easy configuration and scalability. Data transfer to and from the shower units (represented by a node) is wireless and bi-directional. Therefore, settings can be changed remotely, while the report with flush-related data can be received remotely in your email inbox. MyriaNed can be configured to use either 868MHz or 2.4GHz. This allows for the optimal fit in each local environment in terms of coverage and energy usage.

In February 2020, just before the first Covid-19 wave struck the Netherlands, van Mierlo Ingenieursbureau B.V. started a pilot program with Sfella on 15 showers in a care institute. The unforeseen Covid-19 crisis forced the care institute to close its sports facilities for several months, a perfect period to test the installed Sfella system. It appears the automatic flushing happened every 72 hours as programmed. Once the facilities opened again in early summer, final confirmation arrived: examinations of the water samples taken showed no legionella contamination in the related water pipes. This offered the most convincing evidence that Sfella delivered.

van Mierlo Ingenieursbureau is now to actively approaching the Dutch market and discussing with sales and distribution partners, as well as technology partners, to broaden the Sfella roadmap. If you are interested in partnering for sales and distribution, including outside the Netherlands, please contact us.

A video about Sfella is available at our website.

For further information, please reach out to info@vanmierlo.com

* Mioto is a brand of van Mierlo Ingenieursbureau B.V. in Eindhoven the Netherlands

Fulco Verheul

Responsible for marketing, sales, business development, product management and product development activities at van Mierlo Ingenieursbureau B.V.

Smart Sensors 4 Agri-Food Kicks Off

On February 21, the members of the Thematic Smart Specialization Partnership Smart Sensors 4 Agri-Food met at CTIC in the Gijón Technology Park in Spain. The main topic on the agenda was agreement on the partnership’s governance structure and its working plan for the near future. Additionally, the members elected the partnership’s chairs.

Connecting competences, facilitating digital transformation

18 clusters and research partners from 14 European regions set themselves the twin goals of boosting the digital transformation of the agri-food sector and facilitating access to applicable solutions for industry. By connecting competences across Europe, the partners as well as their members and stakeholders will gain a better understanding of agri-food´s opportunities, challenges, and requirements with relation to digital technologies.

The partnership has identified four core challenges that it will address initially:

  • Match the needs of agri-food companies with the solutions and capabilities of the technology and digital solution providers, building a “trust zone” between the involved sectors.
  • Roll out a step-by-step approach to digital transformation by creating cross-border innovation communities and providing funding opportunities.
  • Develop and demonstrate the integration of digital technologies in production lines with specific requirements for robust solutions.
  • Adopt and establish vocational and professional training programs for companies and their employees.

Two European projects up and running

The meeting was held adjacent to a program of study visits and matchmaking events, organized within the two European projects originating from the partnership: “Smart Sensor Systems for Food Safety, Quality Control and Resource Efficiency in the Food Processing Industry‘ (S3FOOD) and “Connecting smart sensor systems for the food industry‘ (Connsensys). S3FOOD provides support to SMEs and a dedicated funding scheme for developing and implementing technologies and digital solutions in the food processing industry. Connsensys focuses on the role and potential of living labs in the innovation ecosystem for the sector’s digital transformation. As such, the Connsensys project is paving the way for a network of living labs that will form a cornerstone in the SS4AF strategy.

“It will be a long way, but based on the established relations to our companies and the focus on applicable solutions, we will generate real added-value for our companies and regions with our partnership,” stated Simon Maas, AgriFood Capital BV (The Netherlands) after he was elected to be the first chair of Smart Sensors 4 Agri-food. Cécile Guyon from Bretagne Dévelopement Innovation (France), and newly-elected vice-chair added, “Connecting competences across European regions is an important key to successfully support SMEs and to facilitate their digital transformation processes. This is why I am happy to be part of this unique partnership.” DSP Valley’s own Bjorn van de Vondel is the newly-chosen chair of the Technology Intelligence working group. Flanders’ FOOD (Belgium) will host the Brussels-based head office of the partnership.

Stay connected

If you want to stay updated about SS4AF, send an e-mail to Veerle Rijkaert (Flanders Food) to receive all the latest news on the partnership and its projects.

Deltaray Launches Disruptive Tech

Less than a year ago, Deltaray officially came on the scene as a new company. They’re already turning heads and disrupting conversations with their unique technology: 3D Xray equipment for 100% inspection of mission-critical mechanical parts.

Quality control woes

Industry needs quality control. It ensures customers receive defect-free products that meet their needs. This we all know. We also know that the current system isn’t perfect. Incomplete or incorrect inspections put users at risk and lead to recalls, which are, of course, are a nightmare for companies. The damage to the company’s reputation, the hassle, the expense.

Inspecting products thoroughly reduces the chances of recalls and also ensures that a company’s products function as they should every time, all the time. Current inspection technology, using CT scanning, cannot yet scan thoroughly and fast enough to do more than random sample checks. Employees can only visually check a product, and often can only do so for a few seconds before needing to move on to the next specimen.

A scanned image demonstrating how Deltaray’s technology works

A unique solution

This is where Deltaray comes in. In cooperation with the University of Antwerp, they’ve developed accelerated 3D x-ray technology that can inspect every individual unit both inside and out, comparing each component to engineering files using AI.

How do they do it? Image-based 3D x-ray scanning enables real time inspection in-line or near-line. at 50 to 100 µm resolution. Form-fit inspections use the CAD file as quality master, making use of AI-enabled inspection to perform fully automated defect detection. The data-driven analysis and resulting reporting is Quality 4.0 compliant.

The exciting technology behind Deltaray’s turnkey inspection solutions offers plenty of possibilities for critical part manufacturers in the automotive, additive manufacturing, critical assemblies, and medical devices industries.

Find out more

Deltaray’s official launch takes place in two weeks. You can meet them and find out more for yourself at the free entry Virtual Industry Fair on June 10. They’ll be one of the keynote speakers at the event.

Interested companies can attend a private open house on 16 and 17 June, where they’ll get a glimpse of the first demo system and be able to interact with the Deltaray team. You can visit their website to get your personal invitation.

Flexlines presents progress at Flexible Electronics and Smart Textiles Seminar

flexible electronics
By Shirine Irani, DSP Valley

Our Flexlines consortium was present at the DSP Valley seminar Flexible Electronics and Smart Textiles on 15 November 2019. The workshop focused on Flexible Electronics in general and Smart Textiles more specifically. DSP Valley has been key in        bringing together companies (SMEs) and research actors necessary to advance this exciting domain.

Continue reading “Flexlines presents progress at Flexible Electronics and Smart Textiles Seminar”

Looking back at the China-EU Semiconductor Summit

DSP Valley, together with BCSemi NL, CyNergy-Consulting and Xiamen Semiconductor Investment Group (XMSIG), co-organized the China-EU Semiconductor Summit on 10 September in Eindhoven. The event focused on further collaboration between the China and European semiconductor industry to develop solutions for 5G, faster wireless internet, self-driving cars and for more innovative health solutions. We reported on its success in October.

Continue reading “Looking back at the China-EU Semiconductor Summit”

Research Project Delivers New UQ Software

The numerical analysis and applied mathematics research group NUMA at KU Leuven has successfully developed a new Uncertainty Quantification (UQ) software package allowing for an efficient treatment of problems that depend on many uncertain parameters.

The research group had been part of the EUFORIA research project, an SBO project (Strategisch BasisOnderzoek or Strategic Basic Research) that ran from February 2015 through April 2019. Funded by IWT (now VLAIO), SBO projects support “high-quality level basic research with a pronounced focus on high-risk, inventive and original research and with a high and strategic valorization potential of the results in Flanders.” In this case, the project brought together academics from five institutions and worked with a “Users Committee” of Flanders-based companies to assess the project’s outcomes. The Users Committee members’ activities include domains as diverse as heat exchangers, computational physics (CFD), and software and energy engineering, ensuring that the project output would be widely applicable. One of the more extreme uses for the software, and one that eloquently illustrates how it works, involves designing earthquake-resistant structures. While certainly not the only application, it is an exciting advancement in civil engineering.

Uncertainty Quantification in earthquake-resistant structures

Inside Taiwan’s Taipei 101 building, one of the world’s tallest skyscrapers, is a large metal sphere weighing 660 tons, mounted between the 88th and 92nd floor. This sphere is not an architectural frivolity but is one of the buildings’ key features. As earthquakes are common in east Taiwan, tall earthbound structures must be designed so that they can withstand the additional stresses produced inside their structural components. If those stresses become too large, the building might experience permanent damage or even collapse. The large sphere on top of the Taipei 101 is designed precisely to prevent such catastrophic events from happening. To that end, structural engineers who design such buildings must take into account the inherently uncertain nature of earthquakes, since no two earthquakes are ever identical and all differ in strength, vibration pattern and duration. To do so, engineers can resort to UQ, the study of the impact of imperfect information on the design of products or processes.

Earthquake modeling

To perform uncertainty quantification, one must have a mathematical model describing the impact of an earthquake on the horizontal motion of the building. In civil engineering, this motion is typically simulated using rigid body models for the building. Seismologists then describe the ground acceleration caused by earthquakes as a combination of many high-frequency components. Subsequently, the ground acceleration is used as input to the rigid body model. Together, the ground acceleration and building model form a mathematical model for the effect that an earthquake has on the building’s motion. In this mathematical model, the high-frequency components form the set of input parameters, whereas the model output – also termed the quantity of interest – is given by the maximum stress inside the building.

However, as every earthquake is unique, the maximum stress should be computed for a wide variety of possible model inputs. Consequently, these inputs now become uncertain parameters, and, as a result, the predicted output quantity (the maximum stress) also becomes uncertain. Instead of a single output value, the result is now specified as a distribution of potential output values. Determining the effect the uncertain parameters have on the distribution of the output quantity of interest is the main task of UQ.

It is an exciting advancement in civil engineering.

UQ – Monte Carlo methods to the rescue

Once the mathematical model is set up, the uncertainty quantification task can start. A very popular UQ technique is the brute-force Monte Carlo method, which repeatedly chooses a random value for each of the uncertain parameters. For each set of random input parameters, one computes the quantity of interest using the mathematical model. The obtained set of output values – sometimes called the ensemble – is then used to approximate the distribution of the quantity of interest. Unfortunately, it is well known that the Monte Carlo method suffers from a low efficiency: to get an additional digit of accuracy, the number of model evaluations must increase a hundredfold!

To remedy the inefficiency of the Monte Carlo method, about 10 years ago, multilevel methods were invented. Instead of only computing with the high accuracy model as in Monte Carlo, multilevel methods use many cheap-to-compute model evaluations with low accuracy, and subsequently add corrections from a hierarchy of models with increasing levels of accuracy – but also increasing computational cost. Each model in the hierarchy is referred to as a level, and, when combined with Monte Carlo, the method is called Multilevel Monte Carlo. In the context of earthquake-resistant buildings, a hierarchy of cheaper models can be obtained by varying, for example, the time increment used in the simulation of the earthquake-building model. Simulations with finer time steps yield more accurate results, but are also more expensive to compute.

It is important to stress that a multilevel method yields the same accuracy as the Monte Carlo method, but its computational cost is heavily reduced. For a simple one-story building model, for example, the distribution of the maximum stress inside the building subject to an earthquake-input with 1000 high-frequency components is computed almost 10 times faster with a 6-level method than with the original Monte Carlo method.

Open-source UQ software – MultilevelEstimators.jl

The multilevel Monte Carlo methodology for uncertainty quantification is implemented in an all-purpose Julia software library MultilevelEstimators.jl, created by NUMA. This freely available generic library focuses on the efficient computation of the distribution of a quantity of interest using multilevel methods.

Rightly so, the research group is proud of their achievement. They hope more applications for it will come to light as more audiences begin to use it. The software is both lightweight and flexible, with the major advantage that it wraps around an existing user code that is considered as a black box; no modifications to the user code are required! The software has proven to be significantly more efficient in several industrial cases and is now ready to be used in your application! If you want to try out the software in your own domain, have questions, or just want more information, feel free to get in touch with Ward.Melis@kuleuven.be.