Panel manufacturers have a new ally in their quest to achieve a specified board quality. It’s called EVORIS, and the digital and intuitive platform from Dieffenbacher is helping manufacturers produce smarter and more sustainably.
EVORIS apps that predict quality and detect anomalies use artificial intelligence (AI) to help manufacturers optimize board quality while simultaneously lowering production costs, avoiding rejects and reducing the use of wood, glue and other expensive raw materials.
In the traditional approach for optimizing board quality, usually once per shift, a sample board is cut and sent to a laboratory for analysis. Measuring quality parameters this way can take from several hours to days, sometimes forcing long delays in the control and production circuit.
The EVORIS Quality Prediction app uses artificial intelligence to provide a continuous, real-time prediction of board quality parameters during production. Manufacturers view quality parameters and laboratory measurements on the EVORIS Dashboard. All relevant quality parameters are displayed live and up to one month retrospectively. Quality deviations prompt warnings, which allow operators and technologists to identify their causes and make corrections faster. The AI-supported system learns and improves itself independently as more lab data flows automatically into the app. The result is increasingly accurate quality predictions.
In the near future, a simulation of changed production parameters will be able to produce quality predictions without the need to change production. Trained models will automatically adapt to changing production conditions and products. Manufacturers will be able to speed up production and work with lower tolerances by moving closer to quality limits.
In combination with the new AI-based anomaly detection, deviations in the production process can be detected even faster. This avoids downtime and helps to achieve consistent quality. Meanwhile, the anomaly detection can be used for different processes at the same time, which enables diagnoses that are more accurate.
More EVORIS enhancements are on the way. The Quality Prediction app will deploy AI algorithm ensembles to analyze quality parameters in parallel, improving prediction accuracy. Operators will also be able to view the accuracy of each potential production model.
Another app being developed will track particle size. Particle size has an enormous impact on board quality and can indicate machinery defects or wear. The Particle Size app will allow manufacturers to measure and analyze particle size and distribution online. This information will enhance the quality prediction AI algorithm. Together, these innovations put the possibility of a self-regulating plant closer to reality than ever.
In the meantime, plant managers who take full advantage of EVORIS today can be confident they’re on a trustworthy path to save resources, reduce downtime, produce specified board qualities and increase output rates.