In the past, operating companies in the process industries viewed the separation of enterprise and plant floor systems as a challenging hurdle. Integrating ERP and real-time plant data has been expensive and difficult to maintain at best. Often somewhat less-than-elegant middle-ware, ETL (extract, transform, and load) and other batch load mechanisms for data and data warehouse architectures have long been staples in the IT domain. This is changing rapidly with the emergence of IT Platforms consisting of distributed computing, in-memory technology, and closer technology partnerships.
Although operations and maintenance groups generate vast quantities of data – both structured and unstructured – they can only leverage a small percentage of data to make better decisions. For decades, much of the process data collected from real-time operational systems were “locked up” in process historians. The majority of these data was seldom used, except by engi-neers and maintenance and operations staffs that tend to use either basic visualization tools or somewhat more sophisticated, but usually difficult-to-use, historian tools to investigate opera-tional situations. While some software vendors have made efforts to improve these tools, most are still very laborious to use and lack context with transactional and unconventional data scat-tered through the enterprise.
“Liberating” process data to enable enterprises to efficiently capitalize on the plant or shop floor information requires an overhaul of the data integration strategies.
Process historian infrastructures are designed to collect, store, normalize, and cleanse time-series sensor data from industrial equipment and processes. When made available to the appro-priate O&M personnel, this information can empower the real-time analysis of asset perfor-mance, troubleshoot problems so industrial businesses can improve operations and maintenance efficiency. In the process industries, most process information is stored in the historian.
High-performing industrial organizations are becoming increasingly data-driven and companies in every industry and every geography rely on the process historian infrastructure as their pri-mary operational data store to support real-time analysis and troubleshooting, enable historical and complex analytics, and reduce data management costs. Historians can help connect islands of production and maintenance information and remove barriers to decision-making by provid-ing a single version of the truth with a common data foundation and consistent data cleansing.
However, in the past, plant data often did not move beyond the historian infrastructure. But new technology approaches and technology convergence are changing this. Convergence is the gateway to optimizing plant performance through cloud-based solutions, in-memory compu-ting, and powerful analytics, as well as the source of massive amounts of training data for ma-chine learning and predictive maintenance solutions. This changes the way businesses and op-erations perform and compete by making data accessible and actionable. The ability of an in-dustrial process manufacturer to leverage OT or operational data will hinge on the use and de-ployment of the process historian and the manner in which this data is consumed by the busi-ness and enterprise systems.
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