Home GMV PitIA Early detection of anomalies Print Artificial intelligence in industry General information Operational and predictive maintenance A solution focused on high-performance predictive maintenance for industrial plants, where we automate the process for detecting anomalies during operation by managing variables in real time. Technological summary A scalable and modular system Easy to manage for operators Simple development and maintenance of models Characteristics GMV PitIA Use cases ▪ A modular monitoring and early warning system for anomalies, during production processes and for critical equipment ▪ A flexible solution that can be adapted to the user’s specific needs, and that can be integrated with platforms used to record operating data ▪ A tool for operational assistance and optimization of continuous and batch processes Who is it suitable for? Applicable to any industry performing continuous, discontinuous, or lot-based processes, where there is an interest in improving operations while enhancing safety for workers and equipment, increasing the quality of products obtained, and reducing costs by avoiding unexpected shutdowns. It can also be used for designing new processes and products, and even as a predictive maintenance technique. Data acquisition ▪ Uses connectors to capture historical data for operation, maintenance, and planning ▪ Prepares data using transformation (ETL process: Extract, Transform, Load) ▪ Produces predictions in real time Processing ▪ Modeling using multivariate statistical techniques ▪ PCA and PLS models based on latent variables ▪ An interactive tool for constructing models ▪ Also applicable at multi-product plants ▪ Has its own metrics for early detection of anomalies, during operation and in the model itself
