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FactoryTalk Analytics Edge ML

Empower OT Personnel to Leverage Machine Learning in Low-latency Edge Environments
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As manufacturers generate huge volumes of high-speed industrial data at the edge, the challenge of quickly discovering insights—using low-footprint hardware—and applying them to the control systems at low latency response times has gained importance. At the same time, relying on a centralized data science or IT analysis function can take days or months before a turnaround can happen at the plant floor.

To break this deadlock, OT professionals need the ability to easily navigate data challenges and deploy machine learning applications for applying streaming data directly from the control application—the source of high-speed and voluminous industrial data. They should be able to apply the model outputs to both the Rockwell Automation control system layer and other off-the-shelf hardware. With these powerful capabilities, OT professionals can improve manufacturing yield, improve overall equipment effectiveness, and other KPIs that matter to their key business outcomes.


Bringing Machine Learning to the Edge

FactoryTalk® Analytics™ Edge ML empowers OT professional on the plant floor to leverage the power of machine learning and visual data pipelines, while fully applying their deep discrete or process manufacturing expertise to their advantage. FactoryTalk Analytics Edge ML provides ease of use in connecting data sources, data pipelines, and the flexibility to bring your own model—right on the industrial edge. As a result, OT professionals can continuously improve operations by deploying models that help detect defects before packaging and optimize process or production parameters on the factory floor via event-based controller feedback at low latencies. All this is achieved by using low-footprint hardware such as compute modules, gateways, and headless industrial PCs.

Ecolab Transforms to a Connected Enterprise
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Case Study
Ecolab Transforms to a Connected Enterprise

Leader in water, hygiene and infection-prevention solutions is improving consistency and connectivity across 130 plants.

Read Now

Product Features

Controller

Closed-loop Feedback on Low-footprint Hardware

Now you can run machine learning models at the plant floor on low-footprint hardware—such as compute modules, information gateways, headless industrial PCs—and immediately apply insights to your control layer in real time.

Linear system plan workflow

Robust Visual Model Building and Reuse

OT personnel can visually build complex data pipelines in a collaborative manner or bring in pre-built machine learning models from IT for scoring. These can be reused and deployed on-premise in the plant across lines, leading to reduction in time and cost to deploy.

Network

Out-of-the-box Connectivity and Data Preprocessing

FactoryTalk Analytics Edge ML offers built-in adapters for data ingestion from Rockwell Automation controllers, so that you can quickly assemble and organize your plant-floor data for analysis. The data can be preprocessed at the edge to create efficient data flow, which not only reduces load on controllers but also enables rapid decisions close to the consumer. Lastly, data analyzed at the edge can be egressed to persistent data-stores (on-prem or cloud), message queues or data visualization tools.

Compute digital chip

Bring-your-own-Model or Use Pre-existing Open-source ML Libraries

Bring in your own pre-built machine learning or analytical models and call upon pre-built open-source ML libraries compatible with Python or PMML to scale building analytics applications and increase the pace of innovation.

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