Trend Detection Podcast

Siemens
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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.

  1. AI-based Predictive Maintenance from the factory floor to the cloud - live from SPS

    VOR 2 TAGEN

    AI-based Predictive Maintenance from the factory floor to the cloud - live from SPS

    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, the host is joined by Tobias, Head of Maintenance and Improvement at Siemens, alongside Pablo and Anya, to share a real‑world predictive maintenance journey from Siemens’ highly automated Cham factory in Bavaria.They explore how unplanned downtime drives lost output, rising costs, and customer impact—and why predictive maintenance starts with shop‑floor visibility, not just software.The conversation walks through how Siemens combined smart hardware, OT modernisation, and AI‑driven analytics to predict failures before they happen, even in a brownfield environment with live production.Using Senseye Predictive Maintenance, maintenance teams gain clear insights, explanations, and recommended actions—helping them focus on critical assets and avoid firefighting.With early results already preventing multiple breakdowns, the episode also looks at how Siemens plans to scale the approach across factories and embed predictive maintenance earlier in the machine lifecycle.A practical, experience‑led look at how predictive maintenance delivers value on the factory floor.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-maintenanceRead the reference in full below:Siemens Cham, Germany - Reduced unplanned downtime with Senseye Predictive Maintenance

    23 Min.
  2. Finding the Right Predictive Maintenance Partner - with Kelli Case

    3. MÄRZ

    Finding the Right Predictive Maintenance Partner - with Kelli Case

    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, Liz McGinn is joined by Kelli Case, a Business Development Director for Senseye at Siemens, who shares practical guidance drawn from her experience working with organizations adopting predictive maintenance.Why choosing a predictive maintenance partner is a strategic, long‑term decision, not just a software purchase—covering culture change, transformation, and sustained value.How to assess your organization’s readiness for predictive maintenance, including maintenance maturity, data access, internal capabilities, and willingness to change.What separates a strong PDM partner from a weak one, such as listening skills, adaptability, domain experience, global support, and the ability to scale with your business.Key technology and architecture considerations to look for, including openness and vendor agnosticism, data ownership, security, configurability vs. customization, and integration across systems.How to avoid common pitfalls and measure success, from unrealistic promises and long time‑to‑value to proving ROI quickly, enabling user adoption, and planning for future evolution toward prescriptive maintenance.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-maintenance

    52 Min.
  3. From Copilots to Agentic AI in Manufacturing — with Lina Huertas

    25. FEB.

    From Copilots to Agentic AI in Manufacturing — with Lina Huertas

    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 Lina Huertas, Industry Executive for Manufacturing at Microsoft UK, to explore how generative AI, copilots, and agentic AI are reshaping digital manufacturing — not just speeding up tasks, but changing how work is designed, delivered, and governed.We unpack the difference between copilots (which assist and enhance human work) and AI agents (which can complete tasks end‑to‑end within defined boundaries), and what this shift could mean across the shop floor, engineering, and back office.You’ll learn:How copilots and agentic AI differ — and why that matters for manufacturing workflows and roles.How organisations are thinking about moving from assistance to more end‑to‑end task execution (with human oversight and clear boundaries). Why human–AI collaboration is becoming a core capability, with work shifting toward supervision, decision‑making, leadership, and critical thinking.The key barriers to scaling AI in manufacturing: data silos, fragmented systems, shadow IT, and organisational structure.The skills manufacturers (and individuals) need next: hands‑on AI literacy, “learning how to learn,” and leading in a workforce that increasingly includes AI systems.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-maintenanceConnect with Lina on LinkedIn:https://www.linkedin.com/in/linaahuertas/

    35 Min.
  4. Beyond the AI Hype: What Actually Works in Manufacturing - with Nick Leeder

    18. FEB.

    Beyond the AI Hype: What Actually Works in Manufacturing - with Nick Leeder

    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.What you will learn in this episode:Why many industrial AI initiatives fail to move beyond pilots, despite heavy investment and executive attention.How AI hype and “fear of missing out” often lead companies to start with the technology rather than the business or process problem.Why process maturity, data relevance, and context are essential prerequisites before applying AI at scale.How to identify repeatable, scalable AI use cases—with predictive maintenance highlighted as a strong example.What to measure to prove success, including operational impact, financial value, and real improvements to frontline workers’ day‑to‑day work.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-maintenanceConnect with Nick on LinkedIn:https://www.linkedin.com/in/redeel/

    38 Min.
  5. Applying AI to Predictive Maintenance at Scale: A Senseye Perspective

    11. FEB.

    Applying AI to Predictive Maintenance at Scale: A Senseye Perspective

    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 episode with David Humphrey, Director of Research, ARC Europe, we discuss:How predictive maintenance has evolved from scheduled inspections to data‑driven decision‑making using connected machine data.What Senseye Predictive Maintenance is, how it works as a cloud‑based analytics application, and where it fits within Siemens’ broader asset and maintenance portfolio.How machine learning and generative AI are used to detect abnormal asset behavior and translate complex analytics into actionable maintenance guidance.How historical machine data, maintenance records, and technical documentation are leveraged to speed diagnosis and reduce dependency on individual expert knowledge.Why scalability, usability, and organizational adoption are critical success factors for predictive maintenance programs operating at hundreds or thousands of assets.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-maintenance

    23 Min.
  6. Wireless Multisensors Meet Predictive Maintenance - with Niklas Frey

    4. FEB.

    Wireless Multisensors Meet Predictive Maintenance - with Niklas Frey

    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.This episode covers:How the SITRANS MS200 wireless multisensor measures vibration, temperature, and magnetic fields to enable condition monitoring on rotating and vibrating assets.Why retrofittable, battery-powered sensors are key to bringing predictive maintenance to assets that previously had no condition data.How the CC220 gateway integrates seamlessly with Senseye Predictive Maintenance, supporting both stand‑alone deployments and existing IT infrastructures via MQTT.What makes the solution highly flexible and scalable, from single gateways to plant‑wide sensor networks without complex IT overhead.Where the MS200 roadmap is heading, including configurable measurement cycles, on‑sensor KPI calculation, improved battery life, and expanded frequency ranges for future applications.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-maintenance

    26 Min.
  7. Creative Thinking in Predictive Maintenance: A Conversation with Jordan Walters

    28. JAN.

    Creative Thinking in Predictive Maintenance: A Conversation with Jordan Walters

    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.This episode covers:The Essence of Creativity in Engineering: How creative thinking is crucial for innovating solutions to complex problems in predictive maintenance (PM), moving beyond established methods to develop bespoke approaches for each customer.Unconventional Problem-Solving with Existing Tools: Discover how seemingly limited data, like temperature readings from electric car charger pins, can be creatively manipulated using features like "derived measures" to detect degradation, even when traditional sensor deployment isn't feasible.Bridging the Gap: From Industrial Practice to Education: Learn about the "Connected Curriculum" initiative, which brings Senseye to university students, and the creative adaptations needed to teach real-world data challenges (like noisy or incomplete data) and PM principles in an academic setting.Debunking Misconceptions about AI and Data: Understand that perfect data is a myth and that effective AI in PM, like Senseye, thrives on curated, clean data focused on specific condition indicators, rather than a "big data" dump, to provide nuanced and accurate insights.AI as an Enabler for Human Creativity: Explore how AI serves as a powerful tool to support and amplify human ingenuity in engineering, emphasizing the importance of asking questions, providing context, and fostering a collaborative environment to drive innovation and personal growth in the field.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-maintenance

    31 Min.
  8. Vibration Analysis 101: Unlocking the Power of Predictive Maintenance - with Chris Garrison

    20. JAN.

    Vibration Analysis 101: Unlocking the Power of Predictive Maintenance - with Chris Garrison

    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.This episode covers:The Evolution of Vibration Analysis: Discover how this crucial predictive maintenance technique has evolved from manual listening with a screwdriver to sophisticated instrumentation, enabling early detection of equipment issues weeks in advance.Best Practices for Implementation: Understand the importance of careful planning, selecting the right sensors for specific assets, and conducting criticality assessments to avoid common pitfalls like "whack-a-mole" problems and ensure a strong return on investment.Why Vibration Analysis is a Foundational PDM Technology: Explore its broad applicability across various industrial equipment and environments, making it one of the most comprehensive methods for identifying a wide range of fault modes compared to more niche predictive maintenance technologies.The Game-Changing Impact of AI and Cloud: Learn how these advanced technologies have revolutionized vibration analysis by enabling rapid data interpretation, providing remote access to expert insights, offering scalable monitoring solutions for any facility size, and ensuring continuous software updates.Achieving Actionable, Contextualized Insights: Find out why cross-departmental cooperation is vital for successful implementation and how AI-driven platforms like Senseye provide tailored recommendations by understanding a facility's unique operational context, maintenance history, and risk tolerance.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-maintenance

    33 Min.
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Info

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.

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