This new analytics solution provides one answer at the device level. Delivered on a plug-in appliance, the solution crawls the industrial network and discovers assets – like AC drives and condition sensors. It provides analytics by transforming the data generated into preconfigured health and diagnostic dashboards.
As the appliance uncovers information about how the devices are related to each other, such as fault causality, it starts to understand the system on which it is deployed – and can make prescriptive recommendations. For example, it can send an “action card” to a user’s smartphone or tablet if a drive needs to be reconfigured to maintain optimal performance.
Ultimately, this prescriptive approach enables maintenance teams to be more proactive – and helps minimize potential downtime.
Changing the Game for Automotive Manufacturing
Scalable analytics is a game changer for discrete automotive applications. In addition, this transformational approach promises to be vital in complex continuous processes where machine learning can have a significant impact on product quality and manufacturing velocity.
One example? Prismatic pouch cell battery production. Prismatic pouch cells deliver more energy per volume than their cylindrical counterparts and are gaining traction in the electric vehicle market.
However, prismatic pouch cell production involves a high degree of motion, precision and continuous processing. Optimizing a process in this type of dynamic, multivariable environment is a challenge. But it’s a challenge made for scalable analytics – and machine learning.
Using dynamic mathematical models, the system learns to recognize the impact one variable has on another and automatically adjusts subsequent actions for optimal results. At the same time, the system can deliver critical analytics to operators – such as SPC charts – which enable continual quality monitoring and proactive adjustments.
Keep in mind a scalable approach can extend beyond devices and be applied at the machine and process levels. The platform also can be integrated with MES, OEE and other manufacturing operations and analytics systems to help drive optimization across the enterprise in areas as diverse as production scheduling and energy management.
Learn more about scalable analytics – and how you can start making better decisions at the source of your data.
Co-authored by Todd Montpas, Product Manager, Information Software, Rockwell Automation