Abstract: Systems and methods are disclosed herein for contextual data analysis and proactive intervention in industrial plant processes. Each of multiple data streams in an industrial plant are mapped to a common hierarchical data structure, wherein the data streams correspond to respective values or states associated with unit operations, assets, and process streams in the plant. The mapped data streams define hierarchical process relationships between subsets of the unit operations, assets, and process streams. Real-time data is collected to populate at least one level of the hierarchical data structure for certain data streams, wherein future outcomes are predicted for downstream operations based on the collected real-time data for at least one data stream, and at least one other data stream having a defined hierarchical process relationship therewith.

Abstract: Systems and methods are disclosed herein for contextual data analysis and proactive intervention in industrial plant processes. Each of multiple data streams in an industrial plant are mapped to a common hierarchical data structure, wherein the data streams correspond to respective values or states associated with unit operations, assets, and process streams in the plant. The mapped data streams define hierarchical process relationships between subsets of the unit operations, assets, and process streams. Real-time data is collected to populate at least one level of the hierarchical data structure for certain data streams, wherein future outcomes are predicted for downstream operations based on the collected real-time data for at least one data stream, and at least one other data stream having a defined hierarchical process relationship therewith.

Abstract: Systems and methods are disclosed herein for optimizing the supply of products to industrial plants. Each of multiple data streams in a plant are mapped to a common hierarchical data structure, wherein the data streams correspond to respective values or states associated with process elements. The mapped data streams define hierarchical process relationships between subsets of the respective process elements. One or more of the process elements are determined as correlating to consumption for each of the supplied products. Real-time data are collected to populate at least one level of the hierarchical data structure for one or more of the data streams, and data is inferred to virtually populate the at least one level of the hierarchical data structure for at least one other data stream, based on the collected real-time data for data streams having defined derivative relationships therewith. An output corresponding to a replenishment schedule is dynamically produced for each supplied product.