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 engineers 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 operational situations.
But new technology approaches and technology convergence are changing this. Convergence is the gateway to optimizing plant performance through cloud-based solutions, in-memory computing, and powerful analytics, as well as the source of massive amounts of training data for machine learning and predictive maintenance solutions.
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 scattered through the enterprise.