Method and System for Predicting Operation of a Technical Installation

Method and system for predicting the operation of a technical installation in which a process-engineering process having a process step runs, wherein datasets are acquired and stored in a memory and, during a learning phase, a self-organizing map is learned, symptom threshold values and associated tolerances are ascertained and stored for each neuron per SOM and all permissible temporal profiles of victor neurons are ascertained and stored per process step or batch for all timestamps, where a time starting from which operation of the technical installation should be predicted is determined during an evaluation phase, a victor neuron profile for the overall process step or batch is ascertained using current datasets of a process step via learned victor neuron profiles, and values, stored in neurons of this victor neuron profile, of the process variables are displayed after the previously determined time as a predicted profile.