A digital assistant for a multi-stage processing facility, comprising: a communication interface circuitry for receiving real-time data from the multi-stage processing facility; a database for storing historical data of the multi-stage processing facility; a model repository for storing at least one model training code; a configuration memory for storing a first group of configuration commands; a processing circuitry in communication with the database, the model repository, and the configuration memory, the processing circuitry configured to: generate a set of executable digital representations each corresponding to one of multiple physical stages of the multi-stage processing facility by interpreting a first set of commands of the first group of configuration commands, wherein at least one of the set of executable digital representations comprises a model trained using a model training code from the model repository and the historical data; retrieve a second set of commands from the first group of configuration commands specifying a connection topology of the set of executable digital representations that digitally replicates the multi-stage processing facility; retrieving a third set of commands from the first group of configuration commands that further specify a flow of batches of materials through the set of executable digital representations; retrieve a fourth set of commands from the first group of configuration commands in the configuration memory that specify triggering or linking signals for the digital representations; load and execute the set of executable digital representations in a time sequence according to the flow of batches of materials through the connection topology of the set of executable digital representations and according to the triggering or linking signals for the digital representations; and generate a graphic display of a predicted key performance indicator output from the execution of the set of executable digital representations. a communication interface circuitry for receiving real-time data from the multi-stage processing facility; a database for storing historical data of the multi-stage processing facility; a model repository for storing at least one model training code; a configuration memory for storing a first group of configuration commands; a processing circuitry in communication with the database, the model repository, and the configuration memory, the processing circuitry configured to: generate a set of executable digital representations each corresponding to one of multiple physical stages of the multi-stage processing facility by interpreting a first set of commands of the first group of configuration commands, wherein at least one of the set of executable digital representations comprises a model trained using a model training code from the model repository and the historical data; retrieve a second set of commands from the first group of configuration commands specifying a connection topology of the set of executable digital representations that digitally replicates the multi-stage processing facility; retrieving a third set of commands from the first group of configuration commands that further specify a flow of batches of materials through the set of executable digital representations; retrieve a fourth set of commands from the first group of configuration commands in the configuration memory that specify triggering or linking signals for the digital representations; load and execute the set of executable digital representations in a time sequence according to the flow of batches of materials through the connection topology of the set of executable digital representations and according to the triggering or linking signals for the digital representations; and generate a graphic display of a predicted key performance indicator output from the execution of the set of executable digital representations. generate a set of executable digital representations each corresponding to one of multiple physical stages of the multi-stage processing facility by interpreting a first set of commands of the first group of configuration commands, wherein at least one of the set of executable digital representations comprises a model trained using a model training code from the model repository and the historical data; retrieve a second set of commands from the first group of configuration commands specifying a connection topology of the set of executable digital representations that digitally replicates the multi-stage processing facility; retrieving a third set of commands from the first group of configuration commands that further specify a flow of batches of materials through the set of executable digital representations; retrieve a fourth set of commands from the first group of configuration commands in the configuration memory that specify triggering or linking signals for the digital representations; load and execute the set of executable digital representations in a time sequence according to the flow of batches of materials through the connection topology of the set of executable digital representations and according to the triggering or linking signals for the digital representations; and generate a graphic display of a predicted key performance indicator output from the execution of the set of executable digital representations.