AI Tool Optimizes, Automates Powder Coating

Maximum efficiency on a powder coating line is a difficult goal for many finishers to achieve. Relying on trial and error, tribal knowledge and manual adjustments does not usually produce the most efficacious results. But there is hope: One company has developed an artificial intelligence (AI) platform that optimizes and automates coating lines, while simultaneously reducing costs and powder waste and improving quality.

The company, coatingAI (Winterthur, Switzerland), has created a system called Blueprint OS that offers precision-adjusted process settings that generate uniform coatings and eliminate rejects of the coated product, the company says. The system presents powder coaters that have automated lines with tools that improve efficiency. These modules include: health check, powder equalization, spray calibration, closed-loop optimization, fine-tuning and predictive maintenance (PM).

“We are bridging the gap between the powder manufacturer and the booth manufacturer and that tribal knowledge of the client,” says Link Brown, chief revenue officer at coatingAI. “We are striving to eliminate the art and turn it into science, so it’s a predictable method for clients to for clients run under optimal conditions.”

Maximized uptime with minimal powder use, rejects and rework is coatingAI’s ultimate goal. To accomplish this, the company developed a complete system so the powder coater has no concerns, Brown says. With that mindset, PM is an obvious focus and thus has been worked into Blueprint OS.

The platform is also designed to work with a company’s pre-existing automatic booth no matter the brand and powder type. An automatic booth can be old or new, with fixed or reciprocating guns. Its customers are job coaters, OEMs, manufacturers and coating product buyers.

“Every powder will behave differently in every system,” says Marlon Boldrini, CEO. “But we can bring that all together. We integrate the machine and powder for best coating results.”

Although the company guarantees a minimum of 10% savings, users are seeing anything between 16% and 30% savings in powder, according to Brown.

The role of AI

The company’s large-format tool, called coatingAI Co-Pilot, is described as physics-informed AI that understands the science happening within the powder booth. This technology, mostly designed for advanced manufacturing businesses, provides full automation of a coating line. Still in the pilot stage, the tool uses a combination of humidity and temperature sensors, thickness measurements and 3D parts scanning to read the powder functionality, booth equipment environment and other factors to control the powder coating process. Boldrini says this provides optimal coating.

While Co-Pilot is still in development, the company’s Blueprint technology, a simplified version of coatingAI that is deployed faster than the larger platform, is currently in use across the U.S. and abroad. Within Blueprint, the AI is learning the intrinsic behavior of the application in combination with the powders in use. With every iteration of calibrating powder outputs of the guns and the resulting measured thickness distributions, the system learns to better predict this non-linear correlation.

Six tools in one system

When running automated powder coating processes, integrating a system that deciphers just the right recipes is beneficial when the goal is optimal efficiency and predictability. Blueprint OS provides the following six functions for automated powder coating booths:

1. HealthCheck: Produces a benchmark to understand performance and current state of wear and tear on booth components. It can help companies gain clarity to adjust process parameters and to identify out-of-range parts.
2. Powder Equalization: Equalizes powder output to ensure all guns are spraying at the same level, offering uniform powder distribution. With each equalization, the AI learns the correlation between powder output and corresponding thickness, and adapts over time. This tool optimizes powder use to minimize waste and manual adjustment.
3. Spray Calibration System: Optimizes reciprocator settings and nozzle angles based on the spray pattern of the powders used most often. This system eliminates inconsistent spray patterns and manual adjustments.
4. Closed-Loop Optimization System: Measures and adjusts process outputs based on thickness measurements taken across the part, in real time. It automatically fine-tunes each gun’s output without manual intervention. The closed-loop optimization gives significant improvements to the powder laydown right out of the box, though the real impact happens after continuous use of the system. 
5. Fine-Tuning Module: Consistently monitors and adjusts to keep the system performing at its best. Instead of frequent downtime, quick (less than 15-minute) weekly checks help provide optimal performance.
6. PM: Tracks wear and tear across components and provides early warnings of parts likely to fail. The system uses AI to track changes made to spray gun settings and process settings, and then over a couple of months it begins to suggest adjustments to PM schedules. 

Demo and onboarding

Once a powder coater expresses interest in exploring the benefits of Blueprint OS for its automatic powder coating booths, the process for

onboarding is designed to be straightforward. It starts with an introductory video call with coatingAI with no strings attached. Then, if the potential customer decides to move forward, the call is followed by an on-site demo and quick onboarding. The process, laid out in more detail, is as follows:

• Prior to arriving on-site, Brown and his team hold a video call with the interested company to discuss the powder coater’s current challenges and goals. The coatingAI team reveals pricing information. Next, the powder coater commits to a hands-on demonstration with no obligation to purchase if results are not proven.
• For the on-site demo, the downtime required is 15-30 minutes; however, the entire process takes about two hours. Exact timing depends on the complexity of the coating line and potential underlying problems. CoatingAI dives deep into the customer’s operations, running a benchmark to understand current performance metrics.
• By the end of the demo, measurable savings and performance improvements are shared with the customer. If the customer approves, the coatingAI team can proceed with full onboarding immediately.
• All major powders and secondary powders are optimized. Production continues during this optimization process.

Equipment and support

Blueprint OS is designed to integrate seamlessly without significant disruption or additional equipment investment. A calibration tool and software are the only items necessary.

Coatmaster Flex calibration tool from Nordson helps optimize recipricator settings based on each powder’s spray pattern. It helps benchmark current powder distribution and optimize powder thickness. Blueprint OS software operates independently, without requiring direct integration with PLCs or booth controls. The software’s operator function can be used weekly when pumps or guns must be switched out.

After initial setup, the coatingAI service providers conduct monthly service visits to ensure all functions maintain optimization.

“These visits are streamlined to minimize downtime — typically requiring only 15 minutes of line time per booth for updates and preventive maintenance alignment,” Brown explains. “Visits are during regular breaks, so there is no production impact.”

Keeping in contact with its customers has been a priority for the coatingAI team since stepping into the commercial market about a year-and-a-half ago. Brown explains that it is important to hear feedback from the customer to help him and the team continue to cater to customer needs. Therefore, they have created a customer success team which ensures that clients are receiving premium service during the monthly visits from a service provider but also they review monthly powder spend and provide online trainings to ensure customer satisfaction. 

Environmental impact

With the tools that Blueprint OS offers, coatingAI can track how its efficiency not only saves powder use but also reduces emissions. This data is especially useful for its large, corporate customers, according to Brown.

The ability to track powder use comprising of waste and rework can also be correlated to emissions reductions during the powder coating process inside customers’ booths. Environmental costs and savings are transparent to the customer as well.

No competition

According to Boldrini, coatingAI technology is not competing with an already existing technology or company.
“We want to build an ecosystem where we connect all silos that currently exist,” he explains. “Right now, there’s a powder manufacturer and a booth equipment manufacturer. CoatingAI brings in an intelligent system to combine those things.”
CoatingAI technology is currently being developed for optimizing oven use as well. “We are integrating AI to reduce energy use. We are leveraging feedback from customers to figure out what more we can do to help them,” Brown concludes.