{"id":18179,"date":"2026-08-17T14:13:26","date_gmt":"2026-08-17T12:13:26","guid":{"rendered":"https:\/\/www.delphin.de\/?p=18179"},"modified":"2026-08-17T14:13:30","modified_gmt":"2026-08-17T12:13:30","slug":"furnace-monitoring","status":"publish","type":"post","link":"https:\/\/www.delphin.de\/en\/ofenmonitoring\/","title":{"rendered":"Furnace Monitoring in Aluminum Production"},"content":{"rendered":"

Reliably Collect, Visualize, and Analyze Process Data<\/h2>\n\n\n\n

A real-world example from the industrial sector demonstrates how furnace data, fan readings, and operating parameters are integrated into a comprehensive monitoring system.<\/p>\n\n\n\n

At an aluminum smelter, relevant measurement data from several electrolytic cells is collected, visualized, and made available for analysis and process control. The solution combines standalone data loggers, centralized data storage, visualization, and the integration of external operational data via an additional driver.<\/p>\n\n\n\n

In the application described, a total of 270 electrolytic cells are in operation at an aluminum production facility. To control heat loss, a specially developed heat exchanger is installed on ten of these furnaces. A dedicated monitoring system was implemented for these furnaces to transparently monitor heat loss, operating conditions, and relevant parameters.<\/p>\n\n\n\n

The solution combines measurement data collected locally at the furnaces with additional operational data from a higher-level data source. Some of this information is also transmitted via PROFIBUS<\/a> transferred to a PLC, which controls and regulates the heat exchanger.<\/p>\n\n\n\n

System Architecture<\/strong><\/p>\n\n\n\n

The Software solution<\/a> It is based on ProfiSignal as well as the DataService and DataService Configurator components. The system is supplemented by a DLL driver that reads in additional furnace process data and makes it available to the monitoring software.<\/p>\n\n\n\n

On the hardware side, only DAQ systems of the type ProfiMessage<\/a> are used. These devices capture the analog sensor signals, convert them into physical quantities with units, and also store the data locally within the device.<\/p>\n\n\n\n

Practical example<\/strong><\/p>\n\n\n\n

The overview screen allows the user to immediately see which oven is active, what the current temperature is, and what the voltage is. In addition, the temperature and speed values of the fans are displayed, providing a quick overview of the system's status.<\/p>\n\n\n\n

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The furnace detail view allows you to examine the data for a single furnace in greater detail. It displays local measurement values and additional operating parameters side by side, while trend charts facilitate historical analysis and comparisons of different data types.<\/p>\n\n\n\n

Technical Value-Added<\/strong><\/p>\n\n\n\n

Would you like to monitor thermal processes, furnace systems, or heat exchangers in a structured manner and centrally visualize relevant operating data? If so, you\u2019ll benefit from an approach that combines measurement hardware, analysis software, alarm systems, and external data interfaces into a single solution.<\/p>\n\n\n\n

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Would you like to find out more?<\/strong><\/h2>\n\n\n\n
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Get in touch with us<\/strong><\/a><\/div>\n<\/div>\n<\/div><\/div>\n\n\n
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Frequently Asked Questions About Furnace Monitoring in Practice<\/h2>\n\n\n
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1. What measurement data is typically recorded during furnace monitoring?<\/strong> Data collected includes, among other things, temperatures, voltages, and fan parameters such as temperature and speed, measured directly at the furnaces. These local measurements are combined with additional operating parameters to provide a complete picture of the system's condition.<\/p>\n\n\n\n

2. How does the visualization of furnace data work during operation?<\/strong> An overview diagram shows at a glance which furnaces are active and what the current temperature and voltage values are. In a detailed view, individual furnaces can be examined more closely, with trend charts allowing users to view historical trends and compare measurement values.<\/p>\n\n\n\n

3. Why is local, self-contained data storage important for furnace monitoring?<\/strong> Data loggers with local ring memory store measurement data even when there is no constant connection to the server. This ensures that safety-critical process data is not lost, even in the event of network outages.<\/p>\n\n\n\n

4. How can warning and alarm thresholds be set up effectively in furnace monitoring?<\/strong> Individual warning and alarm limits, including delay times and status alarm detection, can be configured via virtual channels. This enables early detection of deviations before they lead to critical process disruptions.<\/p>\n\n\n\n

5. How are additional operational data from other systems integrated into the monitoring system?<\/strong> A driver can be used to import external process data from higher-level data sources and merge it directly with the locally recorded measurement values in the monitoring software. This provides a comprehensive view of all relevant furnace parameters, regardless of their source.<\/p>\n\n\n\n

6. What practical benefits does visualization offer in everyday life?<\/strong> In the overview screen, users can immediately see which furnace is active, the current temperature and voltage, and the fan readings\u2014providing a quick overview of the entire system. In the furnace details view, trend charts also allow for historical analysis and comparison of individual parameters.<\/p>\n\n<\/div>\n<\/div>","protected":false},"excerpt":{"rendered":"

An industrial case study demonstrates how furnace and fan data can be monitored transparently<\/p>","protected":false},"author":6,"featured_media":18211,"comment_status":"closed","ping_status":"closed","sticky":false,"template":"","format":"standard","meta":{"_acf_changed":false,"footnotes":""},"categories":[18,107,114],"tags":[172,80],"blog-kategorie":[125],"intern":[],"class_list":["post-18179","post","type-post","status-publish","format-standard","has-post-thumbnail","hentry","category-software","category-analyse-ueberwachung","category-prozessmonitoring","tag-monitoring","tag-prozessanalyse","blog-kategorie-wissenswertes"],"acf":[],"_links":{"self":[{"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/posts\/18179","targetHints":{"allow":["GET"]}}],"collection":[{"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/posts"}],"about":[{"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/types\/post"}],"author":[{"embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/users\/6"}],"replies":[{"embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/comments?post=18179"}],"version-history":[{"count":17,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/posts\/18179\/revisions"}],"predecessor-version":[{"id":18210,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/posts\/18179\/revisions\/18210"}],"wp:featuredmedia":[{"embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/media\/18211"}],"wp:attachment":[{"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/media?parent=18179"}],"wp:term":[{"taxonomy":"category","embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/categories?post=18179"},{"taxonomy":"post_tag","embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/tags?post=18179"},{"taxonomy":"blog-kategorie","embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/blog-kategorie?post=18179"},{"taxonomy":"intern","embeddable":true,"href":"https:\/\/www.delphin.de\/en\/wp-json\/wp\/v2\/intern?post=18179"}],"curies":[{"name":"wp","href":"https:\/\/api.w.org\/{rel}","templated":true}]}}