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

    Trend Detection Revisited - Bluescope Steel Success Case - with Chris Wonson
    2026/09/09
    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.
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    47 分
  • From Planned Shutdowns to Predictive Maintenance: Highland Pellets' AI Journey - with Andrew Rehm

    From Planned Shutdowns to Predictive Maintenance: Highland Pellets' AI Journey - with Andrew Rehm
    2026/09/01
    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
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    31 分
  • The Two Sides of Digitalization: Technology and Skills - A Special Episode

    The Two Sides of Digitalization: Technology and Skills - A Special Episode
    2026/08/25
    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
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    25 分
  • Industrial AI Beyond the Hype: Context, Reasoning and Autonomous Action - with James Loach

    Industrial AI Beyond the Hype: Context, Reasoning and Autonomous Action - with James Loach
    2026/08/20
    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
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    32 分
  • From Insight to Action: Connecting Predictive Maintenance and CMMS - with Chris Smith

    From Insight to Action: Connecting Predictive Maintenance and CMMS - with Chris Smith
    2026/08/13
    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, Niall Sullivan is joined by Chris Smith, Head of Operations for Senseye Predictive Maintenance, to explore the relationship between predictive maintenance and computerized maintenance management systems, or CMMS.Chris explains why organizations should consider establishing value and learning how predictive maintenance fits within their operations before fully integrating it into existing workflows. He also discusses how CMMS data can provide valuable context, reduce manual investigation and help maintenance teams focus their attention on the issues that require action.In this episode, you’ll learn:When to integrate predictive maintenance with your CMMSHow CMMS data adds context and accelerates decision-makingWhy trust and ownership matter more than technology aloneHow to turn predictive insights into maintenance actionWhy standardised integrations still require local flexibilityYou 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
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    32 分
  • Managed Services: When Customers Can't Do PdM Alone - with Todd Martin

    Managed Services: When Customers Can't Do PdM Alone - with Todd Martin
    2026/08/05
    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 speak with Todd Martin from Siemens.Drawing on experience as both a long-term Senseye user and managed services specialist, Todd explains how expert support can help maintenance teams turn predictive insights into action, reduce administration and build trust in the approach.Listen to discover:What predictive maintenance managed services look like in practiceHow expert analysis and customer maintenance teams work togetherWhy technology alone is not enough to deliver resultsThe role of trust, feedback and internal championsWhy an open mind remains one of the most valuable maintenance skillsYou 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
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    26 分
  • Meet Eigen: The AI Agent Transforming Automation Engineering - with Michael Schrapp

    Meet Eigen: The AI Agent Transforming Automation Engineering - with Michael Schrapp
    2026/07/30
    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 the latest episode of the Trend Detection Podcast, we speak with Michael Schrapp, Director, Global Go-to-Market for Data & AI at Siemens, about the Eigen Engineering Agent and the connection between automation engineering, reliability and maintenance.In the episode, we explore:🔹 Why industrial AI needs domain and project context🔹 How integration with TIA Portal reduces manual translation and context loss🔹 How validated engineering can support reliability and maintainability🔹 The changing roles of skills, governance and accountability🔹 Why the engineer remains central to review and approvalYou 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
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    27 分
  • The Connectivity Reality Behind Predictive Maintenance - with Johnathan Bonner

    The Connectivity Reality Behind Predictive Maintenance - with Johnathan Bonner
    2026/07/22
    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 the latest episode of the Trend Detection podcast, we're joined by Johnathan Bonner, Head of Solutions Engineering for Senseye, to explore why connectivity is often the most underestimated part of a predictive maintenance deployment.In this episode We discuss:Why industrial connectivity is rarely as simple as “plug and play”How different machines, systems and communication protocols create complexityWhy IT, OT and cybersecurity teams need to be involved from the outsetHow connectivity and integration can account for much of the implementation effortWhy trying to reduce upfront costs can ultimately delay time to valueHow mapping your infrastructure and data sources can support predictive maintenance and future digitalization projectsYou 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
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    30 分