Abstract: An apparatus and method for receiving operational data and displaying summaries of processes for an industrial system includes a block object to define blocks for defining aspects of variables related to the operational data as well as a display client for using the blocks to provide useful and concise summaries of the processes.

Abstract: A method and system for performing model-based multi-objective asset optimization and decision-making is provided. The method includes building at least two predictive models for an asset. The building includes categorizing operational historical data via at least one of: controllable variables, uncontrollable variables, output objectives, and constraints. The building also includes selecting at least two output objectives or constraints, and identifying at least one controllable or uncontrollable variable suitable for achieving the at least two output objectives or constraints. The method also includes validating each predictive model and performing multi-objective optimization using the predictive models. The multi-objective optimization includes specifying search constraints and applying a multi-objective optimization algorithm. The method further includes generating a Pareto Frontier, and selecting a Pareto optimal input-output vector.

Abstract: A method and system for performing multi-objective predictive modeling, monitoring, and update for an asset is provided. The method includes determining a status of each of at least two predictive models for an asset as a result of monitoring predicted performance values. The status of each predictive model includes at least one of: acceptable performance values, validating model, and unacceptable performance values. Based upon the status of each predictive model, the method includes performing at least one of: terminating use of the at least two predictive models for the asset, generating an alert for the asset of the status of the at least two predictive models, and updating the at least two predictive models based upon the status of the at least two predictive models.

Abstract: A method of managing a machinery monitoring system is provided. The machinery monitoring system includes a database of at least one rule set, the rule set including at least one rule expressed as a relational expression of a real-time data output relative to a real-time data input, the relational expression being specific to a plant asset. The method includes importing data representative of a rule set into the machinery monitoring system, applying the at least one rule set to a specific plant asset wherein the at least one rule set is configured to locate the data input using at least a portion of the relative path information, determining a data output of the at least one rule set using the at least one relational expression and the data input, and transmitting the data output to at least one of the machinery monitoring system and the plant monitoring and control system.

Abstract: A computer-implemented method of managing a machinery monitoring system is provided. The method includes relating an asset output to at least one asset input, generating at least one rule based on the relation, selecting at least one of live asset data, historical asset data, user-supplied asset data, and third party supplied asset data to test the at least one rule, testing the at least one rule incrementally using the selected asset data, and monitoring the output of the at least one rule at each increment.