Dynamic Root Cause Analysis Tool IIOT
Automate and Control have partnered with the Big Data Analysis company Trendminer, giving our customers visual indexing of their process data for rapid historical and dynamic RCA analysis of their process ensuring consistency of their process.
TrendMiner software is based on a high-performance analytics engine for data captured in time series. With TrendMiner, process engineers and operators can easily search for trends and question their process data directly – without help from a data scientist.
TrendMiner delivers all you need to analyze, monitor and predict the performance of batch, grade and continuous plants.
Analyze
When there’s a process problem, you need fast answers. That’s exactly what TrendMiner is designed to deliver. With a high speed search engine, advanced filter options and patented pattern recognition technology, you get data-based insights that are actionable. Our self-service analytics platform speeds up your root cause analysis and help you identify new areas for process and asset optimization…
Monitor
Your data never sleeps – and neither does our software. With TrendMiner you can monitor live processes 24/7 and receive automatic notifications for events of interests. Automatically capture knowledge to speed up response times and improve collaboration between teams. Avoid abnormal situations and automate routine data inspection tasks with the click of a button…
Predict
Why react when you can predict the future instead? Our interactive and model-free predictive mode is based on patent-pending technology and works in a fundamentally different way than model-based predictive technologies. Based on all available historical data, TrendMiner users can predict future evolutions of batch runs, transitions or equipment startups in minutes
Contextualize
Make better decisions, faster with contextualization of time-series data. Context can be captured automatically via monitors, manually added or disclosed from other business applications. With TrendMiner you can illuminate your time-series data with context, to get a clear view on operational behaviour and improve operational excellence faster.
