Flows and Analytics Explained

flows and analytics offer 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 docid bvxnzlgo8fsoglib4o l and analytics docid\ zaowl1npjlkefhjbxhgvu to learn more about each feature this topic compares the features and helps you determine when you should use them flows flows are a series of processes that handle data in a way that can be customized to meet various operational requirements flows are particularly useful for tackling complex operational tasks as they permit detailed data processing and tailored workflows the flows manager is a central feature that enables you to create and manage individual flows litmus edge provides a user friendly interface that allows you to easily create, edit, and manage workflows by dragging and dropping nodes onto the flow canvas you can design workflows with this interface if you have limited programming experience 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 you 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 user scenarios 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 use flows to create customized data processing algorithms for 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 for additional detailed guides and user scenarios for leveraging flows, see flows guides docid 6vrru18gsnyam7hcfe9m7 limitations review the following limitations for flows to 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 also be complex this is especially true in large manufacturing settings where data from thousands of sensors and devices must be processed and analyzed continuously analytics 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 you 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 user scenarios routine performance monitoring analytics is an ideal tool for regularly monitoring manufacturing processes it can track key 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 for additional detailed guides and user scenarios for leveraging analytics, see analytics guides docid\ g xbmnakgtz4wzqhdhgug limitations 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 flows and analytics compared 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 viewing data output on canvas yes use the debug node to view output yes click the view icon on a processor to view data output p ublishing 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 customizing functions and processes yes you can fully customize flows to your specific requirements no pre defined functions have limited customization options parsing data into different formats yes parser nodes are available for formats such as csv, xml, and yaml no this option is not available creating a dashboard to view data yes you can create and customize flow dashboards no this option is not available sending alerts through email and text message yes the email and twilio out nodes are available no this option is not available