Community > News > Detail RETURN

Optimization of filter nonwoven fabric


The Fraunhoff Institute of Industrial Mathematics (ITWM) has developed a toolbox for simulating and optimizing filter nonwoven quality.Jessica Owen reports.

Due to Covid-19, mask production has increased dramatically over the past few years.

According to EDANA, the EU alone (which is not known for making masks) has increased its production 20-fold in 2020 compared to pre-pandemic levels — which equates to 1.5 billion three-ply masks per month.

But while mask makers should be applauded for their quick response to the pandemic, quality is likely to suffer as a result. After all, the severe lack of supply means that is is the first time many companies are producing the commodity.

That's why, in May 2020, an interdepartmental team at ITWM in Germany decided to launch the ProQuIV (Production and Quality Optimization of Nonwoven Infection Protective Clothing) project - to improve meltblown nonwovens The quality of woven fabrics and help producers optimize processes.

Quantitative Homogeneity

The first step in the project was to simulate the meltblown nonwoven manufacturing process to quantitatively measure the homogeneity of the final fabric—a factor that greatly affects fabric quality and filtration efficiency.

Dr. Ralf Kirsch, head of the Fraunhofer ITWM filtration and separation team, said: " It is fair to say that the 'beauty' of a homogeneous non-woven fabric is inseparable from the protection it provides.”

Simulating this process is challenging because of the complexity of the meltblowing process: molten polymer is forced through a nozzle into a forward-flowing high-velocity stream, then stretched and cooled in a highly turbulent airflow before being laid out into a web. All fibers have non-uniform diameters and are laid in a random fashion, so there are always fluctuations in the basis weight of the material, Steiner said.

That is, these parameters are ultimately integrated into the simulation as a digital twin. To do this, images of the real process were taken to determine factors such as fiber distribution, and previously validated models were used to determine airflow and other parameters.

"The entire chain can be simulated in a computer. So in the end you have a model that can control the process like a machine," Steiner said.

Next, the researchers took images of the formed nonwoven fabric and used image analysis techniques to quantify the uniformity, also known as "turbidity." The turbidity index (CLI) describes the homogeneity complementary to the local basis weight and its variance, and the frequency that goes into the calculation can be chosen so that the CLI is meaningful for a specific application area.

Kirsch explains: “After calibration for a given nonwoven, the image data is correlated with the grammage distribution of the nonwoven. For example, a certain gray level of a pixel represents a certain value of grams per square inch. "

He added: "Once you have the grammage distribution information, you can specify properties such as local flow resistance and efficiency. From this you can infer the overall filtration efficiency in relation to the uniformity of the material."

The team used image analysis techniques to quantify homogeneity


The digital twin and calculations developed also helped the team understand which production parameters in the meltblowing process were related to uniformity. This means they can adjust different factors and see how they affect the final nonwoven produced. It's almost like a cheat sheet for producing quality materials.

"Prior to the pandemic, many companies had no experience producing masks, and they couldn't meet the breathability and protection level requirements," Kirsch said. "Our development can now help these people control the process to achieve different materials and different levels of protection. ."

ProQuIV tools not only improve quality, but also help save waste, time and money. For example, the process can be reconfigured once the simulation predicts a failure in the level of filtration efficiency.

Additionally, since all of this can be done virtually, time is saved that might otherwise be spent in the upgrade process in a test facility. Scaling up to a real machine is a time-consuming and often problematic step in the development process, because real machines operate slightly differently than test factories. But this way, companies can fast-track testing and production capacity while maintaining or even improving quality.

"You can simulate tests to see what affects the process," Steiner said. "For example, you might need to increase airflow or change heating. All of these can be precomputed and optimized ahead of time to be implemented on a real machine."

Parameters are integrated into the simulation as a digital twin

Get the toolbox

The toolbox developed by Fraunhofer ITWM is just such a toolbox. It is not suitable for any machinery or application (for example, it can also be used for hygiene or liquid filtration). Instead, simulations and models that need to be tweaked and calibrated procedures to optimize specific company processes.

“You have to adjust the factors for every machine, every process, every material and every function you want,” says Steiner. So we do consulting projects and studies to adjust these tools to specific needs. Interested in this technology and really want to use it for success. We are working with several nonwovens producers and are in contact with a machine manufacturer.”

Kirsch added: "Yes, it's a very interesting tool for producers of meltblown machines because it helps customers trust that the final product has the desired quality."

Alternatively, the toolbox can be licensed to a company. Although Steiner and Kirsch suggest different, as companies may first need the experimental investigations, product quality assurance and scientific expertise provided by Fraunhofer ITWM.

Future capabilities

Going forward, Kirsch and Steiner hope to include the charging process itself in the digital twin in order to optimize and control this important part of production.

"I think there will be a real increase in interest in understanding electrostatic charging in the future," Kirsch said. "One of the main failures of newcomers to the personal protection business is that they don't charge their respirator properly. So we see room to improve and optimize this process. ."

The project presented several challenges, so it could take a year or more to quantify this capability, Kirsch said. For example, one needs to figure out how to measure the charge of the fibers on such a small scale, how to validate the experiments and how to develop a method to measure these factors without destroying the charge.

The team hopes to include the charging process in the digital twin in the future

Kirsch added: "This is truly multiphysics because you have a lot to think about. It will take some time, but now is the right time to start because electrostatic charge and its impact on protection levels are critical."

Thanks to the increased protection level of the charged fibers, you can design nonwovens to be lighter and more breathable—an improvement that could encourage more people to wear masks.

"Breathability is one of the most well-known arguments for not wearing a mask, especially for those who must wear a mask throughout their shift," Kirsch added.

In fact, Steiner said the team is about to start a project that will use ProQuIV technology to design and manufacture a new generation of improved masks.

In addition to ProQuIV, Steiner and Kirsch say they hope to explore many other areas related to the mechanical properties of nonwovens in the future. Measuring softness is one way, another is how friction between fibers affects the adhesive. If they could model and simulate all of these factors using just a few parameters, "it would be a dream come true," Kirsch said.

Elsewhere, sustainability is an increasingly problematic issue for teams. They are involved in simulating new fibers, such as bio-based, recycled and carbon-neutral alternatives to synthetic fibers, to understand how to optimize the manufacture of these nonwovens.

Kirsch concludes:”Innovations in nonwovens design for filtration and other applications will certainly benefit from suitable digital technologies. In some application areas, competition comes from stainless steel woven filter materials or membranes, which may affect nonwovens and their an industry that has dominated for decades.”


You can comment after