#153 | (EN) Smart Manufacturing: IoT for Leak Detection at ALPS | EXOR & ALPS Inspection

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Previously titled “#153 | (EN) Smart Manufacturing: How ALPS Inspection Uses IoT for Leak Detection | EXOR & ALPS Inspection” — renamed by the publisher on Sep 1, 2026

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Recorded22 Jan 2025

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#EdgeComputing #HMI #DataDrivenwww.iotusecase.comIn episode 153 of the IoT Use Case Podcast, we dive into the world of IoT-driven quality inspection for plastic containers. Ken Kamlowsky, Managing Director of EXOR America, and Adam Thibert, Senior Controls Engineer at ALPS Inspections, talk about their successful partnership and how they leverage IoT data to overcome challenges in industrial quality assurance.Podcast episode summaryDigitalization in mechanical engineering is opening up new opportunities to increase efficiency and better meet customer needs. ALPS Inspections, a medium-sized company specializing in non-destructive leak testing of plastic containers, was looking for a modern solution to make machines more efficient, utilize data more effectively, and provide flexible remote support for customers. With the support of EXOR, a system was developed that combines hardware, software, and IoT integration. At the core of this solution are JSmart HMIs, which capture data directly at the machine, the versatile JMobile software for analysis and reporting, and the IoT platform CORVINA Cloud for remote access.The implementation of this IoT solution has successfully enabled several key use cases:Data-driven optimization of test processes: With new tools, customers receive a graphical representation of machine processes in real time, allowing them to optimize test and production settings precisely. Read moreGeneration of automated reports: Diagnostic data is compiled directly on the HMI into a 12-page PDF report, which can be sent via email or accessed remotely via the CORVINA Cloud. Read moreImproved response times and service efficiency: Instead of waiting for an on-site service technician, maintenance personnel can now gain immediate remote access to machines via a hotspot. Read moreIntegration of real-time data for predictive maintenance: A predictive maintenance model is currently in development to help customers identify and prevent potential issues early on.Data analysis for efficiency improvement: ALPS now has the capability to store data directly on the HMI, visualize it graphically, and use it for improved troubleshooting.The implementation has led to significant improvements: service costs have been greatly reduced through remote diagnostics, production processes run more efficiently, and customers benefit from real-time insights and automated reports. A key highlight is the close collaboration between ALPS and customers to tailor the system to their specific needs.Looking ahead, both companies aim to leverage AI and machine learning based on IoT data to further optimize machines. EXOR is focusing on its “Micro Edge” solutions, which aim to bring data processing even closer to the machines. This project demonstrates the importance of a clear strategy, open platforms, and collaborative partnerships for the successful implementation of IoT projects.-----Relevant links from this episode:Madeleine (https://www.linkedin.com/in/madeleine-mickeleit/)Ken (https://www.linkedin.com/in/ken-kamlowsky-3a297869/)Adam (Jetzt IoT Use Case auf LinkedIn folgen1x monatlich IoT Use Case Update erhalten

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