Flows and Analytics Explained
Flows and Analytics are important Litmus Edge (LE) features, offering robust data manipulation and analysis tools in industrial settings. You can enhance your data-driven decision-making and operational efficiency with these tools. See Flows Manager and Analytics to learn more about each feature. Review the following information to compare both features and help you determine when you should use each.
Flows refer to a series of processes designed to handle data in a way that can be customized to meet various operational requirements. They are particularly important for complex operational tasks, permitting detailed data processing and tailored workflows. The Flows Manager is a central feature that enables users to create and manage individual flows.
Litmus Edge provides a user-friendly interface that allows users to easily create, edit, and manage workflows by dragging and dropping nodes onto the flow canvas. Even those with limited programming experience can design workflows using this interface. However, you need to have a good understanding of JSON and Node-RED to effectively customize these flows.
The ability to visually customize flows with low-code development and in a web-browser-based flow editor is a key feature of Litmus Edge. This tool is ideal for complex industrial applications, allowing users to tailor the flows to their specific requirements. You can integrate various data sources, apply diverse processing rules, and execute sophisticated logic.
Litmus Edge Flows offers many filter nodes, including:
- DataHub Subscribe and Publish
- Inject
- Debug
- Trigger
- Execute
- JSON Parser
- Read File
- Automate your manufacturing workflows with Flows: Flows automate complex manufacturing workflows, controlling the sequence of operations and adjusting settings, routing materials, and changing schedules dynamically based on real-time data inputs.
- Customized Data Processing for Equipment Optimization: Flows can create customized data processing algorithms in specialized manufacturing settings. For example, in facilities that use high-precision tools, Flows can analyze sensor data to optimize tool usage, predict maintenance needs, and prevent equipment failure.
Review the following limitations for Flows to help you determine if the Analytics feature is a more appropriate tool for your specific requirements.
- Technical Complexity for Non-Experts: Correctly configuring your JSON and Flows canvas without syntax errors and bugs is crucial in Litmus Edge. Mistakes in JSON code can cause malfunctions in flow processes, affecting the efficiency and reliability of manufacturing operations.
- Scalability Concerns in Large-Scale Operations: As the number and complexity of flows increase, managing and maintaining these flows can be difficult. This is especially true in large manufacturing settings where data from thousands of sensors and devices need to be processed and analyzed continuously.
Analytics is a powerful tool for simplifying industrial data interpretation and visualization. It is designed to provide users of varying technical expertise levels with a straightforward and accessible method of processing, calculating, and computing analytical functions. The analytics feature in Litmus Edge offers a full set of readily deployable processors, allowing users to quickly and efficiently add different mathematical functions to make informed decision-making in industrial environments. The Analytics feature is user-friendly and does not require extensive programming knowledge, making it an ideal tool for users who need to analyze industrial data but need more specialized data science or programming skills.
Litmus Edge Analytics offers many processor functions, including:
- Anomaly Detection
- ARIMA Filter
- Feature Extraction
- Linear Prediction
- Normalization
- Statistical Prediction
- XMR Chart
- Routine Performance Monitoring: Analytics is an ideal tool for regularly monitoring manufacturing processes. It can track critical performance indicators (KPIs), such as production output, operational efficiency, and machine uptime. The data can be presented in an easily understandable format, and various customization options are available for each function.
- Predictive Maintenance: Analytics can predict machine or component failures based on historical and real-time data. This enables proactive maintenance scheduling, which minimizes downtime and saves money in the long term.
Review the following limitations for Analytics to help you determine if the Flows feature is a more appropriate tool for your specific requirements.
- Limited Customizability: The Analytics feature has limitations in terms of customization and works best with predefined processes and functions that can be configured for different parameters. It may be useful only for certain specialized industrial requirements.
- Surface-Level Insights for Complex Data: Advanced data sets require more sophisticated analytical tools to provide in-depth insights beyond surface-level analysis. In such cases, more sophisticated, customized analysis (such as that offered by Flows) might be necessary to uncover deeper patterns and correlations.
Review the following capabilities of both features.
Capability/Requirement | Flows | Comment | Analytics | Comment |
|---|---|---|---|---|
Knowledge of JSON required | Yes | Required for customizing certain nodes and functions | No | Pre-defined functions are ready to use and only require limited configurations |
Ability to view output of data on canvas | Yes | Use the debug node to view output | Yes | Click the View icon on a processor to view data output |
Ability to publish output to defined topic | Yes | DataHub Publish node available | Yes | DataHub Publish output function available |
Out-of-the-box functions available | No | Functions and data processing need to be manually configured | Yes | A number of pre-defined functions and KPIs are available to use |
Easy-to-use workflow for setting up data processing and publishing | No | Flows need to be manually set up and configured | Yes | You can easily set up a flow by selecting the input, processor, and output |
Ability to fully customize functions and processes | Yes | You can fully customize flows to your specific requirements | No | Pre-defined functions have limited customization options |
Ability to parse data into different formats | Yes | Parser nodes are available for formats such as CSV, XML, and YAML | No | This option is not available |
Ability to create a dashboard to view data | Yes | You can create and customize Flow dashboards | No | This option is not available |
Ability to send alerts through email and text message | Yes | The email and Twilio out nodes are available | No | This option is not available |