Deeper Plant Insights With AI/ ML Based IOT Analytics
Data collection and analysis of this data acquired from different sensors, equipment or systems needs to be accurate and precise for effective predictions. With IOT Analytics, the data is first acquired using the suitable protocols in standard format and multiple frequencies. This huge data can be analyzed in multiple ways such as Machine learning analytics, standard SQL queries or with the custom analysis system. Rubus IoT analyzes the historical and the real time data to create the wider deeper insights to compare the equipment and plant performance. Rubus has powerful digital insights which is a rich guided analytics application that has custom dashboards with hierarchical view to monitor and analyze operational metrics and KPIs in different formats.
The visualization dashboard showcases patterns, relationships and trends through interactive charting, correlation graphics and well-organized user interface. Its strong analytics capability offers data driven actionable insights that has business impact. The dashboards are dynamic and gets updated with the real time data and also has full access to the underlying data with flexibility to add or remove devices at any point in time. Rubus IOT also consist of features like built-in device protocol drivers and powerful dynamic dashboards for visualization and analysis that helps in rapidly establishing data acquisition backed by an analysis engine. Rubus capitalizes on advanced analytics capability coupled with the latest data technologies like Orcentration and blending of Centralized & decentralized data to aggregate, sort, and analyze the high velocity, high volume, complex machine data to generate actionable Insights. Also, Rubus has ready to deploy insightful dashboards for some specific industries like Food and beverage, Cement, steel, Power generation, metro and seaports to name a few.Learn more
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the company has implemented automated solutions for condition monitoring of their production plants. This improves maintenance planning, saves energy and increases production efficiency.
Implementing Industry 4.0 creates a digital silhouette of a plant to optimize processes. Essential information is provided by many sensors that are already installed for machine control.
Implementing IO-Link has given them real-time access to machine health and has allowed them to implement remote maintenance monitoring.