Artificial intelligence and automation are increasingly shaping industrial coating processes. PaintExpo 2026 is picking up on this development and showcasing solutions for process monitoring, quality assurance, material efficiency, and plant control.
The focus is on applications that are already being used in production environments. Suppliers such as AOM-Systems will demonstrate systems for real-time monitoring of spraying processes, which can be used to control layer thicknesses and immediately identify deviations. The aim is to achieve more stable process control and reduce material and energy consumption.
Convergent Information Technologies presents software solutions for robot-assisted paint repair. The use of machine learning allows complex repair processes to be planned automatically and new component variants to be integrated more quickly.
Automated paint application and material supply
Among other things, Dürr Systems AG will be showcasing overspray-free paint application with the EcoPaintJet and further developments in the field of modular paint supply systems. Material losses can be reduced through precise application and almost complete recovery of unused paint.
Digital control and analysis systems are also used in powder coating. Gema Switzerland will present networked control software for the continuous recording and visualization of production data. The aim is to optimize powder quantities, reduce overspray, and improve process control.
Simulation, conveyor technology, and surface treatment
ESS Engineering Software Steyr presents automated workflows for simulation and virtual process development. Digital models can shorten development times and reduce prototyping costs.
FerRobotics is showcasing robot-assisted systems for grinding, polishing, and masking. Active force control and automatic tolerance compensation enable reproducible results on sensitive surfaces.
M&N Fördersysteme demonstrates advanced rotary transfer systems with optimized control and guidance systems. A continuous material flow contributes to the stabilization of the entire process chain.
In paint and coating development, companies such as Pi Probaligence rely on machine learning for data-based test planning and simulation. Digital models can analyze formulations faster and systematically optimize process parameters.
PaintExpo 2026 thus reflects the current state of networked coating processes, in which process data, quality parameters, and plant control are increasingly evaluated in an integrated manner.