System and method for foundation model functionalities for time series data of operational processes with industrial context information for industrial applications

A computer program product comprising instructions which, when executed by a computing system, enable and/or cause the computing system to perform a computer-implemented method for obtaining, for industrial applications, foundation model functionalities for time series data of operational processes with industrial context information, the computer program product comprising:

• instructions for transforming the time series data of operational processes associated with at least a first industrial plant into a sequence of time units associated with respective pieces of the operational processes;
• instructions for attaching time units of the sequence of time units with the industrial context information, wherein pieces of the industrial context information are associated with the pieces of the operational processes and wherein the time units are attached with concurrent pieces of the industrial context information;
• instructions for using a tokenization method to obtain a sequence of context tokens from the attaching, wherein one context token represents one time unit to which concurrent pieces of the industrial context information are attached;
• instructions for training a generative artificial intelligence (AI) model on the sequence of context tokens using a loss function;
• and
• instructions for using the trained generative AI model having the foundation model functionalities for at least one of:
• i) finetuning the trained generative AI model for a second industrial plant different from the first industrial plant, and
• ii) forecasting a further progression of an operational process for the second industrial plant.