Mazlite has manufactured a class 1 div 1 sensor that can be installed inside a paint booth and developed a platform that facilitates real-time monitoring of coating sprays. Spray analytics are then correlated based on scientific principles to optimize process parameters such as colour, coating film thickness, and transfer efficiency. Preliminary results show 80% accuracy in detecting defects of an ML model applied to images captured using the sensor. The goal now is to make data collection faster by reducing-edge computing and by capturing less data to minimize the amount of coatings used when making a measurement. This will demonstrate the platform’s savings and quantify the reduction in the environmental impact.
The automotive paint shop is the biggest source of regulated chemicals including GHG/VOC emissions; over 80% of all environmental concerns in automobile assembly are related to painting processes. Mazlite offers an industrial spray digitization platform. Mazlite’s platform combines a unique Industrial IoT sensor for direct measurement, software analytics, physics-based AI, and an end-to-end cloud data management system. Mazlite provides a complete solution to improve spray processes to enable manufacturers to to solve product quality issues, improve sustainability, minimize material and energy waste, reduce re-works and boost profitability.
We are seeking manufacturers interested in optimizing their complex spraying processes in industrial applications (The ideal market would be coatings such as automotive paint or industrial coatings sectors). They may be facing issues in nozzle selection, determining the optimal spray operating settings, or maintaining consistency in their spraying process in order to reduce waste and increase the quality of work.
If you are interested please complete the following form.