Streamline Data & Empower Operations: Flows & Analytics in Litmus Edge

This article dives into the heart of two Litmus Edge features – Flows and Analytics, showcasing how they simplify data management and empower businesses.

Industry 4.0
Edge
Analytics
Streamline Data & Empower Operations: Flows & Analytics in Litmus Edge
Streamline Data & Empower Operations: Flows & Analytics in Litmus Edge

In the era of Industry 4.0, data reigns supreme. Industrial environments are generating more information than ever, but unlocking its true potential requires sophisticated tools. That’s where Litmus Edge provides a simplified Industrial DataOps journey – delivering faster time-to-value.

This article dives into the heart of two features – Flows and Analytics, showcasing how they simplify data management and empower businesses.

Mastering the Data Flow with Litmus Edge Flows

Litmus Edge Flows acts as the orchestrator for your industrial data symphony. Built on the intuitive Node-RED framework, it allows users of all programming levels to:

  • Visually design workflows:

    Drag and drop nodes to create complex data pipelines with ease.

  • Process and analyze data:

    Transform raw inputs into actionable insights for optimized operations.

  • Boost efficiency:

    Automate repetitive tasks, freeing up resources for strategic initiatives.

  • Predict maintenance:

    Implement proactive measures to avoid downtime and ensure smooth production.

  • Optimize processes:

    Fine-tune operations for maximum efficiency and productivity.

Unlocking Intelligence with Litmus Edge Analytics

The Analytics suite adds a layer of intelligence to your data, offering:

  • Pre-defined functions: Leverage ready-made tools for real-time monitoring, predictive maintenance, and more.

  • Simplified setup: Get started quickly with minimal coding expertise.

  • Diverse analytical methods: Explore options like ARIMA Filter, Feature Extraction, Normalization Processors, Linear Prediction, Statistical Prediction, and Machine Learning (ML) Models for predictive, classification, or anomaly detection tasks.

  • Tailored solutions: Find industry-specific functions for targeted insights.

Litmus Edge has various types of Analytics functions that are tailored for specific industrial scenarios. By implementing these functions, organizations can experience a significant reduction in downtime, an increase in productivity, and foster innovation in their operations. This marks a significant leap forward towards realizing the goals of Industry 4.0.

Choosing the Right Tool for the Job

Both Flows and Analytics feature in Litmus Edge offers distinct capabilities for data management.

Flows

Flows require JSON knowledge for full customization, allowing for complex data routing and format parsing, with options for creating specialized dashboards and sending alerts.

Flows automate and refine manufacturing sequences, adjusting operations in response to live data. They excel in precision-dependent facilities, where they fine-tune tool performance and predict maintenance, safeguarding against equipment failure.

  • Automate Manufacturing Workflows

    : Use Flows to control manufacturing operations dynamically, responding in real-time to data inputs.

  • Customized Data Processing

    : Tailor Flows to optimize equipment performance in precision-dependent settings, ensuring tool longevity and preempting failures.

Analytics

Analytics simplifies the process with pre-set functions and an easier setup, ideal for those with less coding experience, but offers limited customization. It can output topics and visualize data, fitting different user needs in industrial data processes.

Analytics stands out in predictive maintenance, utilizing data trends to forecast equipment malfunctions. This foresight enables timely interventions, saving costs and maintaining uninterrupted production.

  • Routine Performance Monitoring

    : Ideal for tracking KPIs in manufacturing, providing clarity on performance metrics, and facilitating informed decision-making.

  • Predictive Maintenance

    : Harness historical and real-time data to anticipate machine failures scheduling maintenance to prevent downtime.

Summary

By streamlining data processing, gaining actionable insights, and optimizing operations, you can achieve:

  • Increased efficiency and productivity

  • Reduced downtime and maintenance costs

  • Improved decision-making

  • Enhanced innovation and competitive advantage

Ready to unlock the power of your industrial data? Explore Litmus Edge today and discover how Flows and Analytics can revolutionize your operations.

Explore Litmus Edge today!

Mrinal Walia

Machine Learning: The Key to Smarter Industrial Decisions

Mrinal Walia is a Technical Writer at Litmus.

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