A new assistant for the coatings industry

Paints, lacquers, and other coatings basically consist of four components: solvents, binders, pigments, and additives (see graphic p. 36). A solvent keeps a wall paint in a liquid state, for example. The solvent evaporates after the paint is applied, causing it to dry. Pigments give the paint the desired color. Binders are used to ensure the paint remains attached to the wall and is effective. This component is colorless and bonds the paint with the substrate. Additives make up the smallest percentage of a formulation. Although their share is less than five percent, they nevertheless play a key role. Additives eliminate foam when paint is applied. They also prevent the paint’s pigments from agglutinating. They make coatings thixotropic, i. e. they make them easy to apply, but prevent them from forming runs when they dry on vertical surfaces. Other additives make coatings more scratch-resistant, for example.

The various components influence each other’s effects, depending on the mixture. The number of possible combinations is immense. Even if only ten curing agents, ten binders, ten pigments, and ten additives are considered during the development of a coating recipe, these numbers translate into 10,000 possible combinations. And this doesn’t even take into account variations in the ratios of the components used. “Customers have very precise ideas about the capabilities that a product should have once it’s finished,” says Blanda. In order to develop a functional voice-controlled assistant for the coatings industry, the researchers at first began to structure all of the available information and feed it into a huge database. In the next step, they made it possible to call up this information using a voice-control function.

For example, if you ask the assistant, “Which additive is suited for printing ink?,” the system obviously has to be able to understand each word. Among other things, COATINO™ had to learn that “additive” designates a certain category of coating components. In the next step, the assistant has to access its data, search through it, create suitable links, and assign the data to a possibly relevant result. To do so, it first breaks down the sequence of sounds into their smallest components and conducts a data search on the basis of characteristic properties. A special challenge for the assistant is that COATINO™ has to be able to understand not only German nouns in the nominative case but also in other cases. The researchers also want to make sure that the speaker’s dialect or accent won’t hamper the result. The ultimate aim is to enable COATINO™ to understand customers’ pronunciations worldwide. Added to these challenges are the speakers’ different talking speeds and pitches as well as the specific context of a discussion. “The training process is very nerve-wracking,” says Kröhl. “And after the trial run with our colleague in Shanghai was finally successful, it went wrong with our colleagues in Essen.” For almost two years now, COATINO™ has been jointly developed and trained by the business line and an external development company from Berlin. The assistant passed its first important development test when the prototype was demonstrated at the ECS.

COATINO™ has a lot of things it can say. When asked about suitable additives, it not only presents a list of products but also prioritizes them. “COATINO™ can tell me which additive would be best suited for my formulation and my requirements. It can thus give me well-founded recommendations,” says Blanda. Once a user has found the desired product, he can issue a voice command to tell COATINO™ to order a sample, directly call up the pertinent technical data sheet by e-mail or have a conversation with an expert arranged. “For us, customer-oriented digital solutions enable people to talk with one another more efficiently about innovative solutions,” says Kröhl.

The COATINO™ prototype was ready just in time for the start of the European Coating Show. “We immediately presented it to a select group of our customers,” says Blanda. Instead of a can, the users imparted their wishes to a tablet via a microphone. “The feedback was even better than we’d hoped. We were able to gain some of the customers as first users who will test the assistant.” They will pass on their experiences to Blanda and his team. “We wanted to get the customers involved at an early stage,” says Blanda. “Such a project can only work if customers also think it benefits them.” In 2020 the researchers plan to make COATINO™ available for the entire coatings industry.

However, there is no end in sight for the system’s further development. “When you use digital assistants, you continually come up with ideas for new features,” says Kröhl. For example, COATINO™ could conceivably not only supply existing formulations but also suggest its own new mixtures. The scientists could directly test these mixtures in the lab and enhance them for their own use. “Our COATINO™ might one day really become an artificially intelligent entity,” says Blanda. “But we still have a long, long way to go until then.”

Photos: Getty Images (2),Studio Firma/stocksy.com, Bonninstudio/stocksy.com, Guille Faingold/stocksy.com, Cactus Creative Studio/stocksy.com, Illustration: KNSKB+