podcast.de
Anmeldung
Anmeldung Registrierung
Auto Hell Dunkel
Erweiterte Suche
  1. Startseite
  2. Podcasts
  3. Trend Detection Podcast Podcast
Trend Detection Podcast

Trend Detection Podcast

Siemens.FM team 266 Episoden Neueste vor 4 Tagen

Trend Detection Podcast is a Siemens Technology podcast

Technologie
Zu Sammlung hinzufügen

Du hast noch keine Sammlungen.
Teilen Kommentare Alle Episoden anzeigen

Episoden

Trend Detection Revisited: AI-based Predictive Maintenance from Factory Floor to Cloud

23 Minuten
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.From the Trend Detection archive - a factory-floor perspective on AI-based predictive maintenance.Tobias, Head of Maintenance and Improvement at Siemens, shares the predictive maintenance journey of Siemens’ highly automated factory in Bavaria.The discussion explores how smart hardware, OT modernisation and AI-driven analytics were brought together in a live brownfield production environment. It also examines how Senseye Predictive Maintenance helped maintenance teams focus on critical assets, act on emerging equipment issues and reduce reactive firefighting.This episode was recorded previously, so references to the project and product reflect the position at the time of recording.

Trend Detection Revisited - Bluescope Steel Success Case - with Chris Wonson

47 Minuten
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – the platform which enables predictive maintenance at scale across all of your assets, across all of your plants.This week, Trend Detection revisits a standout episode from the archive.In this conversation, Chris Wonson shares the story behind the deployment of Senseye Predictive Maintenance at BlueScope Steel and explores how predictive maintenance was being applied across its operations.The episode covers:How Senseye Predictive Maintenance was deployed at BlueScope SteelA success case that helped avoid 24 hours of unplanned downtimeHow Senseye Copilot was supporting the way teams worked at the time of recordingPractical advice for manufacturers implementing predictive maintenanceThis archive episode provides a valuable customer perspective on scaling predictive maintenance and turning asset data into practical maintenance action.Find out more about how Senseye Predictive Maintenance can help manufacturers reduce unplanned downtime and improve maintenance efficiency across their plants by visiting: www.siemens.com/senseye-predictive-maintenancePlease note that this conversation was originally recorded and published previously. Some product details may have evolved since the original recording.

From Planned Shutdowns to Predictive Maintenance: Highland Pellets' AI Journey - with Andrew Rehm

31 Minuten
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.In this episode we're joined by Andrew Rehm, Director of Reliability and Planning at Highland Pellets, to explore how predictive maintenance is transforming industrial operations.Andrew shares Highland Pellets' journey from traditional inspection-based maintenance to a more proactive, data-driven approach powered by AI. We discuss how the company increased plant uptime from 60% to 89%, uncovered critical issues before they became failures, and built trust in predictive maintenance across operations, maintenance, and reliability teams.The conversation goes beyond technology, covering change management, workforce adoption, maintenance planning, and why predictive maintenance is becoming a core part of Highland Pellets' long-term strategy.In this episode you will learn:Why predictive maintenance looks very different today than it did ten years agoHow Highland Pellets identified the right assets to monitor firstThe story behind a critical failure that was detected before it shut down productionMoving from scheduled inspections to condition-based maintenanceBuilding trust in AI-driven insights among maintenance teamsConnecting predictive maintenance with CMMS workflows and planning processesLessons learned from the first deployment and plans to scale furtherWhy the future of maintenance is data-driven, proactive, and predictiveYou can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenance

The Two Sides of Digitalization: Technology and Skills - A Special Episode

25 Minuten
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.In this episode of the Trend Detection podcast, guest host Nienke Vergeer is joined by Vera Kaupmann, Global Marketing Manager for SITRAIN, to explore how industrial companies can keep workforce skills aligned with the accelerating pace of technological change.They discuss the growing skills and knowledge gap created as experienced employees retire, why traditional classroom training must be complemented by more flexible digital learning, and how continuous learning can become part of an organization’s culture rather than an occasional activity.The conversation also explores how digital learning can help organizations:Capture and transfer expertise before it is lostAccelerate onboarding for new employeesProvide consistent training across teamsFit learning into the working day through short, self-paced sessionsPrepare employees for emerging areas such as industrial AI, data and cybersecurity The episode also introduces SITRAIN access, Siemens’ digital learning platform for industrial training, including its subscription-based learning membership and free introductory learning content.Digital learning is not only your next competitive advantage, but it’s always at your fingertips – anytime, anywhere.Try it out for free with Freemium | SITRAIN access:https://sitrain.siemens.com/web/page/lex_auth_01452623641047040012

Industrial AI Beyond the Hype: Context, Reasoning and Autonomous Action - with James Loach

32 Minuten
Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – which gives you visibility and insights into all your assets, from single machines to full plants to help you reduce downtime, increase knowledge sharing and accelerate digital transformation across your organization.In this episode of the Trend Detection Podcast, we're joined by James Loach, Head of Research for Senseye Predictive Maintenance at Siemens, to explore what industrial AI means in practice and how it is changing the future of maintenance. James explains how statistical systems, machine learning and generative AI can work together to monitor assets at scale, investigate potential problems and provide more prescriptive guidance to maintenance teams. He also discusses why machine context, maintenance history and human expertise will become increasingly important as AI models grow more capable.In this episode, you’ll learn:What industrial AI means beyond the marketing terminologyHow machine learning and generative AI work together at scaleWhy context is critical for improving AI-generated insightsHow agentic AI could support more prescriptive maintenance decisionsWhy the future of maintenance could become increasingly autonomousYou can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenance
Alle Folgen ansehen (266)
In Podcasts werben
Schalte jetzt Werbung in Podcasts.

Über diesen Podcast

Welcome to the Trend Detection podcast, brought to you by Senseye Predictive Maintenance – the platform, powered by Siemens, which enables predictive maintenance at scale across all of your assets, across all of your plants.Listen to gain insights from our bi-weekly live events and interviews with industry experts about all things predictive maintenance, IoT and digital transformation.Please subscribe via your selected podcast provider to be notified about future episodes.You can find out more about how Senseye Predictive Maintenance can reduce unplanned downtime and contribute towards improved sustainability within your manufacturing plants, by visiting: www.siemens.com/senseye-predictive-maintenanceDISCLAIMER: Unnecessary maintenance," "wasteful activities," or "over-maintenance" only exist when they are unrelated to safety and safety of personnel. Always verify if the maintenance intervals are safety-related; if so, please contact your manufacturer or consult your operating manual.
Webseite
Trend Detection Podcast | Siemens.FM
Urheberangabe
Siemens AG
Durchschnittliche Länge
Ø 32 Min.
Erscheinungsweise
Wöchentlich
Letzter Check
vor 5 Std.
Zuerst veröffentlicht
vor 2 J.
Podcast melden

„Trend Detection Podcast“

Worum geht es? Danach fragen wir noch nach dem Grund.

Abonnenten

Teilen

Mein Archiv

Deine Privatkopie der Folgen, die du nicht verlieren willst.

Podcast-Folgen verschwinden. Feeds werden auf die letzten Episoden gekürzt, Hoster räumen alte Dateien ab, Formate wechseln den Anbieter und lassen ihr Archiv zurück. Mit „Mein Archiv“ sichert podcast.de die Folgen deiner Podcasts für dich — angefangen bei den ältesten, denn die sind zuerst weg.

  • Deine gesicherten Folgen bleiben hörbar, auch wenn das Original offline geht.
  • Auch Folgen, die im heutigen Feed gar nicht mehr stehen — podcast.de kennt sie noch.
  • Herunterladen bleibt möglich, solange die Folge beim Podcaster liegt. Der zählt seine Abrufe wie bisher.
Startet bald

Sei beim Start von Mein Archiv dabei

Mein Archiv ist fast fertig. Trag dich ein, dann bekommst du eine E-Mail, sobald es losgeht – und bist von Anfang an dabei. Wir schreiben dir nur zum Start, keine Werbung, keine Weitergabe deiner Daten.

Du bekommst zuerst eine Bestätigungsmail. Abmelden geht jederzeit. Datenschutz