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InStep Software is a leading provider of real-time performance management software and solutions for the utility, process, and manufacturing industries. InStep's software products extend the investment in modern control, monitoring and smart devices by collecting, storing, displaying, analyzing and reporting the information provided by these systems. These software products are used by many of the world's leading companies on a plant and enterprise wide basis to actively manage and analyze the ever growing amount of real-time operational and asset health related information.
Customer Reference Examples: Exelon, Southern Company, Minnesota Power, Tyco, Southern California Edison, General Electric, Progress Energy, Eskom, Pacific Gas
& Electric, EDF Group, LukOil, GDF Suez, Tokyo Electric Power Company, Korean Electric Power Company, China Power International, China Datang Corporation, East China Power Grid Dispatch Center.
Company Founded: 1995
eDNA (enterprise Distributed Network Architecture) is an advanced software suite of products for collecting, archiving, displaying and reporting of a company's real-time operational and asset health related information. The product suite includes a highly scalable enterprise data historian for efficiently archiving and providing rapid retrieval of high fidelity time series data. A highly advanced lossless compression technology is used to minimize the required storage capacity while maintaining the original collected resolution of the data. InStep supports the ability to easily integrate with hundreds of control, monitoring and other enterprise business systems that companies rely on for day to day operations. An RDBMS database is incorporated into the software suite and integrated with the eDNA time series database to provide for organization and access of the data through the use of an object or meta data model. InStep's advanced eDNA Client applications, eDNA programming interfaces and eDNA Web technology provide for real-time company wide access to this information.
PRiSM is a self-learning analytical software application for monitoring the real-time
health of critical assets in support of Condition Based Maintenance (CBM). PRiSM uses
artificial intelligence, pattern recognition and sophisticated data mining techniques to
determine when a piece of equipment is performing poorly or is likely to fail. The early
identification of equipment problems leads to reduced maintenance costs and increased availability, reliability, production quality and capacity.
PRiSM learns from an asset's individual operating history and develops a series of normal operational profiles for each specific piece of equipment. PRiSM then compares the known operational profiles with real-time operating data to detect the subtle changes in system behavior that are often the early warning signs of pending equipment failure. An advanced alarm manager and email notification provide near real-time updates of how well a plant or system is functioning. PRiSM includes an advanced analysis application for identifying why an asset is not performing as expected. The software is not specific to certain types of equipment or processes and has been used in a wide variety of equipment health and performance monitoring applications.
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