Logix AI Module

The FactoryTalk® Analytics™ LogixAI® module transforms operations by applying analytics directly within the controller application to drive process improvements. This plug-in module, used with ControlLogix® controllers, is installed directly into the control chassis and streams controller data through the backplane to build predictive models. It continuously monitors manufacturing operations, detects anomalies based on its derived understanding, and enables operators and technicians to easily apply machine learning concepts to address product quality issues. It also helps safeguard process integrity without the need to develop, validate, or maintain custom machine learning algorithms.

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Product introduction

Powerful Modeling Engine

The strength of FactoryTalk Analytics LogixAI lies in its modeling engine, which is specifically designed for industrial manufacturing use cases. It allows control engineers to deploy machine learning with ControlLogix® as the execution engine and ControlLogix tags as the primary data source. It streams controller data and converts it into high-speed calculations required for process-critical control. The predictive operational values can be used to replace manual readings or deployed in areas where traditional sensors or instruments cannot be used. The operations team can leverage these predictions to improve quality, increase yield, enhance asset utilization, and gain tangible insights along their journey toward operational excellence.

Driving Production Closer to Perfection with Process Optimization Use Cases

Perfect Fill
For fluid products, the filling or dispensing stage is one of the most critical and expensive steps in the process. However, many manufacturers struggle to achieve accurate and consistent filling, leading to overfilling or underfilling. Overfilling results in unnecessary product giveaways, higher costs, and revenue loss, while underfilling increases product and packaging scrap, rework, and regulatory or consumer risks. FactoryTalk Analytics LogixAI analyzes available production data and builds models to predict the product weight filled in each package. By deploying models at the edge, it allows for real-time predictions based on current operating conditions. These predictions help the operations team control the filling process by providing the information needed to adjust fill setpoints when predicted weight is too low and reduce fill setpoints when predicted weight is too high.

Perfect Fit
The term “splice” refers to the length of the overlapping material at the bond point. For industrial processes involving rolled products with splicing, the splice length is a critical process variable. Short splices can reduce product quality, while long splices waste raw materials. Typically, operators must manually adjust the process to achieve consistent splice lengths within tolerances. With FactoryTalk Analytics LogixAI, you can use real-time or historical data to build and train machine learning models to predict whether the splice is within tolerance or out of tolerance, reducing manual intervention. The predictions can be integrated with ControlLogix, enabling continuous process adjustments that actively correct splices that are out of tolerance, thereby increasing productivity and profitability.

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