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Ing. Madeleine Mickeleit에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Ing. Madeleine Mickeleit 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.
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#177 | (EN) Lifetime Monitoring: KNF & b.telligent digitize testing | b.telligent & KNF

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Manage episode 494783552 series 2705853
Ing. Madeleine Mickeleit에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Ing. Madeleine Mickeleit 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

www.iotusecase.com
#PredictiveMaintenance #EdgeComputing #CloudTransformation

In Episode 177 of the IoT Use Case Podcast, host Ing. Madeleine Mickeleit speaks with Soroush Khandouzi, Cloud Solution Engineer at KNF, and Florian Stein, Domain Lead for Cloud Transformation and Data Infrastructure at b.telligent.

The focus is on a joint IIoT project for pump lifetime monitoring, showing how traditional mechanical engineering companies are using intelligent data to future-proof their products – from edge integration to a scalable cloud setup.

Podcast Summary

Lifetime monitoring, predictive maintenance, and edge integration – how KNF is driving digitalization in mechanical engineering

This episode explores a real-world digitalization project by pump manufacturer KNF, developed together with IoT partner b.telligent. The goal: replace manual testing and documentation with an automated system for long-term pump monitoring – powered by an edge-to-cloud architecture based on Azure IoT and custom-built Data Acquisition Controllers (DAC).

The challenge:
Until now, key parameters like pressure, temperature, and current were recorded manually – sometimes daily, and over several years. With four production sites worldwide, fragmented systems made consistent evaluation nearly impossible.

The solution:
A scalable IoT infrastructure built on Azure IoT Edge, near-real-time data transmission, a burst mode for high-frequency measurements (up to 10 kHz), and visualization in Grafana. In addition to automating centralized testing for more than 1,500 pumps, the system enables cross-site monitoring, AI-driven analysis, and predictive maintenance.

The key insight:
Data is not just collected – it’s made actionable in real time, enabling faster development cycles, higher product quality, and entirely new service offerings.

This episode is a must-listen for anyone looking to scale IIoT projects – from R&D to testing and production.

👉 Tune in and discover practical best practices.

-----
Relevante Folgenlinks:
Madeleine (https://www.linkedin.com/in/madeleine-mickeleit/)
Florian (https://www.linkedin.com/in/florian-stein-33692617b/)
Soroush (https://www.linkedin.com/in/soroush-khandouzi/)

Jetzt IoT Use Case auf LinkedIn folgen

1x monatlich IoT Use Case Update erhalten

  continue reading

191 에피소드

Artwork
icon공유
 
Manage episode 494783552 series 2705853
Ing. Madeleine Mickeleit에서 제공하는 콘텐츠입니다. 에피소드, 그래픽, 팟캐스트 설명을 포함한 모든 팟캐스트 콘텐츠는 Ing. Madeleine Mickeleit 또는 해당 팟캐스트 플랫폼 파트너가 직접 업로드하고 제공합니다. 누군가가 귀하의 허락 없이 귀하의 저작물을 사용하고 있다고 생각되는 경우 여기에 설명된 절차를 따르실 수 있습니다 https://ko.player.fm/legal.

www.iotusecase.com
#PredictiveMaintenance #EdgeComputing #CloudTransformation

In Episode 177 of the IoT Use Case Podcast, host Ing. Madeleine Mickeleit speaks with Soroush Khandouzi, Cloud Solution Engineer at KNF, and Florian Stein, Domain Lead for Cloud Transformation and Data Infrastructure at b.telligent.

The focus is on a joint IIoT project for pump lifetime monitoring, showing how traditional mechanical engineering companies are using intelligent data to future-proof their products – from edge integration to a scalable cloud setup.

Podcast Summary

Lifetime monitoring, predictive maintenance, and edge integration – how KNF is driving digitalization in mechanical engineering

This episode explores a real-world digitalization project by pump manufacturer KNF, developed together with IoT partner b.telligent. The goal: replace manual testing and documentation with an automated system for long-term pump monitoring – powered by an edge-to-cloud architecture based on Azure IoT and custom-built Data Acquisition Controllers (DAC).

The challenge:
Until now, key parameters like pressure, temperature, and current were recorded manually – sometimes daily, and over several years. With four production sites worldwide, fragmented systems made consistent evaluation nearly impossible.

The solution:
A scalable IoT infrastructure built on Azure IoT Edge, near-real-time data transmission, a burst mode for high-frequency measurements (up to 10 kHz), and visualization in Grafana. In addition to automating centralized testing for more than 1,500 pumps, the system enables cross-site monitoring, AI-driven analysis, and predictive maintenance.

The key insight:
Data is not just collected – it’s made actionable in real time, enabling faster development cycles, higher product quality, and entirely new service offerings.

This episode is a must-listen for anyone looking to scale IIoT projects – from R&D to testing and production.

👉 Tune in and discover practical best practices.

-----
Relevante Folgenlinks:
Madeleine (https://www.linkedin.com/in/madeleine-mickeleit/)
Florian (https://www.linkedin.com/in/florian-stein-33692617b/)
Soroush (https://www.linkedin.com/in/soroush-khandouzi/)

Jetzt IoT Use Case auf LinkedIn folgen

1x monatlich IoT Use Case Update erhalten

  continue reading

191 에피소드

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