Verify upfront the resulting deposit layer thickness
Achieve 100% coverage
Electrocoating or e-coating uses an electrical charge to deposit organic paint on structures. Widely used in the automotive industry to protect the Body-in-White (BIW) structure against corrosion, Elsyca's solution supports automotive OEMs in their process optimization to:
ensure the right amount of paint thickness at each location including inner structures and internal cavities;
analyze sheet metal perforation on final paint deposition quality;
consider infrastructure, flow conditions, and electrochemical paint characteristics' impacts on the e-coating process.
Predict paint thickness at each location of your designs and achieve 100% coverage the first time!
Leveraging the digital twin of your electrocoating line
Changes in vehicles designs impact the final deposit layer thickness. Quantifying this impact is a very expensive and time-consuming effort as only a limited number of trials are possible before the design of the car is frozen and taken into production.
Elsyca's solution provides OEMs a digital twin of their electrocoating lines that:
contains all the line characteristics and operating conditions information including voltage program, flow conditions, and electrochemical paint characteristics;
quickly and accurately predicts the final deposit layer thickness whatever the complexity of the vehicle geometries within 2-micron margin;
is a comprehensive modeling solution tackling all industrial challenges such as the impact of gas trap and liquid drag over.
The final quality of the coating highly depends on its electrochemical characteristics. To retrieve these parameters, specific post-processing of the lab measurements is required to not only understand the paint properties but also feed any electrocoating simulation solution.
Elsyca's solution delivers end users a fast and efficient solution to:
capture electromechanical properties of paints based on lab measurements;
create an in-house proprietary database of paints to run multiple e-coating analyses;
automatically fit lab data with simulated ones to ensure accurate numerical prediction.