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  • AI Is Ready. Are We? - with Richard Jeffers | The Adoption Gap - Part 1

    AI Is Ready. Are We? - with Richard Jeffers | The Adoption Gap - Part 1
    2026/06/17
    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 opening episode of The Adoption Gap, we're joined by independent asset management consultant Richard Jeffers to explore a simple but uncomfortable question:If predictive maintenance technology has been around for decades, why are so many organisations still struggling to make it work? Richard argues that the gap isn't in the algorithms, it's in the culture, data maturity, and leadership required to turn capability into results.What you'll learn in this episode:Why predictive maintenance is a way of life, not a technology deployment and what that distinction means in practiceWhere the real gap sits between what AI can do today and what most organisations are actually ready to do with itWhy being "data-led" requires far more than having data and what data maturity really looks like on the shop floorWhat separates the manufacturers who scale predictive maintenance from those who never get past the pilotHow leadership commitment and clear ownership determine whether PdM becomes embedded or abandonedYou 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-maintenanceConnect with Richard on LinkedIn:https://www.linkedin.com/in/richard-jeffers-2860a08/
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    29 分
  • The Adoption Gap: A 4-Part Special Series — Trailer

    The Adoption Gap: A 4-Part Special Series — Trailer
    2026/06/16
    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 special four-part series, we tackle the uncomfortable truth behind most predictive maintenance programmes: the technology works, it's the adoption that doesn't. Across four episodes, we hear from four experts, each with a different perspective on why industrial AI projects stall after the pilot, and what the organisations that succeed actually do differently.What you'll learn in this series:Why organisational readiness (not algorithm accuracy) is the real bottleneck for predictive maintenance, and what "being ready" actually looks like in practiceHow change management should be designed into a project from day one, not bolted on when adoption starts to stallThe most common patterns behind failed industrial AI projects, from pilot traps and misaligned KPIs to trust gaps that never get closedWhy asset selection and internal champions make or break the first 90 days after go-live, and what happens when either one is wrongHow to build momentum from early wins, turning resistors into advocates and scaling from one line to an entire plantThe real KPIs that drive renewal and expansion and why downtime avoided is only part of the pictureYou 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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    1 分
  • Sustainability Actions for Mid-Size Manufacturers: Practical Starting Points - with Nick Leeder

    Sustainability Actions for Mid-Size Manufacturers: Practical Starting Points - with Nick Leeder
    2026/06/11
    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 Nick Leeder to explore what sustainability really means for mid-sized manufacturers — and how moving beyond strategy into practical, measurable action can unlock both operational efficiency and improved profitability.What you’ll learn in this episode:Why sustainability must be treated as a core business initiative — with clear ownership, budget, and measurable outcomes, not just a strategy documentHow external pressures (regulation, supply chain requirements) and internal drivers (cost, competitiveness) are accelerating adoption for mid-sized manufacturersPractical starting points — using existing data like energy bills and focusing on simple, high-impact improvements such as reducing idle energy consumptionHow to build a business case by directly linking sustainability initiatives to financial outcomes, from cost savings to risk reductionThe biggest pitfalls to avoid — lack of governance, too many initiatives, and failure to embed sustainability into daily operations and decision-makingYou 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
  • AIoT Time - with Peter Schopf

    AIoT Time - with Peter Schopf
    2026/06/02
    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 Peter Schopf to unpack the latest industrial and AI trends coming out of Hannover Messe 26 — from the rise of humanoid robotics to the growing divide between operational and strategic AI, and why many organizations are still missing where the real value lies.What you’ll learn in this episode:What stood out at Hannover Messe — including the rise of humanoid (embodied) AI and the shift from hype to more tangible industrial use casesWhy IT/OT integration and industrial data access remain persistent challenges, despite years of investment and innovationPractical generative AI use cases on the shop floor — from documentation and troubleshooting to AI-powered assistants for operatorsWhy most organizations focus too heavily on operational AI — and are missing the much bigger opportunity at the strategic decision-making levelHow “strategic prompting” and better AI interaction can dramatically accelerate complex business decisions, and why context and experience matter more than technical skillYou 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
  • When a Small Vibration Signal Prevents a Major Failure - with Emily Trott

    When a Small Vibration Signal Prevents a Major Failure - with Emily Trott
    2026/05/26
    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 Emily Trott from BlueScope Steel to unpack a real-world predictive maintenance success case, where a single vibration sensor helped prevent a critical failure before it happened.It’s a practical, end-to-end story of how AI, engineering expertise, and process come together to move from early signal to real intervention — and how that translates into avoided downtime and operational impact.What you’ll learn in this episode:How a small vibration signal led to the discovery of a hidden failure on a connected assetWhy predictive maintenance is not one alert → one fix, but a multi-step investigation involving both AI and human expertiseThe gap between traditional monitoring and predictive maintenance and why most failures are only detected when it’s already too lateHow combining Senseye insights with on-site expertise changes the outcome from reactive to controlled interventionWhy sharing success cases internally is key to driving adoption, scaling, and new use cases across sitesYou 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-maintenanceTo find out more about Bluescope Steel's approach to asset intelligence, please watch the video below:https://www.youtube.com/watch?v=0dnDST5B1V4
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    26 分
  • What Actually Works in Senseye Deployments - A Panel Discussion

    What Actually Works in Senseye Deployments - A Panel Discussion
    2026/05/18
    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 three Senseye deliver experts to share real-world lessons from Senseye deployments.They will discuss what actually works, what doesn’t, and what separates successful projects from the rest.What you’ll learn in this episode:Why choosing the right assets early is critical to proving value and building momentumHow data quality and context (not volume) determine success in predictive maintenanceWhy early wins are essential to drive trust, adoption, and scaling across teamsThe common pitfalls in implementations, from wrong failure assumptions to poor asset selectionHow successful deployments depend on combining AI with real-world expertise and customer ownershipYou 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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    41 分
  • Data-driven manufacturing at Arca Continental: With Insights Hub and Senseye Predictive Maintenance

    Data-driven manufacturing at Arca Continental: With Insights Hub and Senseye Predictive Maintenance
    2026/05/12
    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 experts from Siemens live from Hannover Messe 26 to explore how Arca Continental, one of the world’s largest Coca-Cola bottlers, is driving a data-led manufacturing transformation across its global operations, and how combining transparency, predictive maintenance, and a strong digital foundation is unlocking measurable operational impact at scale.What you’ll learn in this episode:How Arca Continental is scaling digital transformation across 45 sites by starting with transparency (OEE, cost, loss drivers) before moving to advanced use casesWhy predictive maintenance success depends on strong cultural alignment and early digital maturity — not just technologyA real-world example delivering impact in days — saving 13 hours of downtime on a critical production assetHow Insights Hub provides a unified data foundation to connect use cases, systems, and workflows at scaleWhat’s next: expanding with AI, contextualized data, and prescriptive insights to drive continuous operational improvementYou 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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    13 分
  • Digital Drivetrains & Predictive Maintenance: Turning Motion Data into Action - with Louis Mahlau

    Digital Drivetrains & Predictive Maintenance: Turning Motion Data into Action - with Louis Mahlau
    2026/05/06
    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 Louis Mahlau, Product & Portfolio Manager - IoT & Analytics at Siemens, who explores how digital drivetrains are transforming the way industrial assets are monitored and maintained and how combining IoT, AI, and domain expertise is unlocking a new generation of predictive maintenance.What a digital drivetrain is and why it underpins so much of modern industrial operationsHow predictive maintenance shifts organizations from reactive and preventive approaches to truly predictive insights How sensors, connectivity, cloud computing, and digital twins come together to turn raw machine data into actionable intelligence A real-world example of how connecting a single motor enabled early detection of issues before production downtime occurred Where the true value lies beyond technology — including data quality, scalability, and change management Why many pilots fail to scale, and what successful organizations do differently from the start How industrial AI and copilots are making complex machine data easier to understand and act on What the future looks like — from prescriptive maintenance to autonomous, self-optimizing systemsYou 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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    33 分