Representative End User Clients
Representative Automation Clients
Representative Software Clients
Although plant operations and maintenance typically generate vast quantities of data – both structured and unstructured – operations and maintenance can only leverage a small percentage of data to make better decisions. Most process data from plant systems is stored process historians archives and represent a challenge predicting process conditions or the assets that may perform poorly and impact the process bottom line.
To improve process performance, a level of operational intelligence and understanding of data is required. Engineers and other stakeholders must be able to search time series data over a specific timeline and visualize all related plant events quickly and efficiently. This includes the time series data generated by the process control systems, maintenance and lab systems, and observations made by operators and engineers.
Emerging predictive and more rare prescriptive process analytics solutions can leverage your current data and nicely sit on top of process historian infrastructure and to provide a mechanism for search and the ability to detect patterns effectively. Users can predict more precisely what is occurring or what will happen in the future with continuous and batch industrial processes.
ARC remains steadfast in the belief that analytics technologies are at the core of ARC's IIoT Technology definition. ARC's David White wrote about the emergence of analytics within the framework of IIoT - Prescriptive analytics and Industrial IoT: Growing up together. I have also written about the emergence of database structures and database sets that provide a greater ability to predict and prescribe process and asset related events in the article Does Predictive Analytics Need More Than A Historian. While on-prem best-of-breed or cloud-enabled Hadoop-style enterprise solutions exist, fundamentally these solutions will re-index historian archives and change the presentation layer from process historian desktop tools significantly.
AT the ARC Advisory Group 20th Annual Industry Forum in Orlando I will be hosting a session about industrial process analytics and predicting process and asset events. The session will bring together industry thought leaders from CSX, Mtell, Seeq, TrendMiner and explore the benefits and achievements of emerging technologies and the changing needs of industrial process stakeholders.
To improve process performance, a level of operational intelligence and understanding of data is required. Engineers and other stakeholders must be able to search time series data over a specific timeline and visualize all related plant events quickly and efficiently. This includes the time series data generated by the process control systems, maintenance and lab systems, and observations made by operators and engineers.
Emerging predictive and more rare prescriptive process analytics solutions can leverage your current data and nicely sit on top of process historian infrastructure and to provide a mechanism for search and the ability to detect patterns effectively. Users can predict more precisely what is occurring or what will happen in the future with continuous and batch industrial processes.
ARC remains steadfast in the belief that analytics technologies are at the core of ARC's IIoT Technology definition. ARC's David White wrote about the emergence of analytics within the framework of IIoT - Prescriptive analytics and Industrial IoT: Growing up together. I have also written about the emergence of database structures and database sets that provide a greater ability to predict and prescribe process and asset related events in the article Does Predictive Analytics Need More Than A Historian. While on-prem best-of-breed or cloud-enabled Hadoop-style enterprise solutions exist, fundamentally these solutions will re-index historian archives and change the presentation layer from process historian desktop tools significantly.
AT the ARC Advisory Group 20th Annual Industry Forum in Orlando I will be hosting a session about industrial process analytics and predicting process and asset events. The session will bring together industry thought leaders from CSX, Mtell, Seeq, TrendMiner and explore the benefits and achievements of emerging technologies and the changing needs of industrial process stakeholders.