Trend Detection Podcast Podcast Por Siemens arte de portada

Trend Detection Podcast

Trend Detection Podcast

De: 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.Siemens AG
Episodios
  • The Evolution of Industrial Data: From Sensors to Strategy - with Vlad Romanov

    The Evolution of Industrial Data: From Sensors to Strategy - with Vlad Romanov
    Apr 1 2026
    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 Vlad Romanov, an industrial automation and data integration specialist with experience spanning plant‑floor engineering, systems integration, and enterprise strategy, who shares a practical view on how industrial data moves from machines to board‑level decisions:What industrial data really is, starting at sensors and control systems on the plant floor and evolving into decision‑ready information used across SCADA, MES, and enterprise systems.How data flows from machines to strategy, explaining the progression from standalone equipment, to production lines, to site‑wide and multi‑site performance insights.Why digitalisation has accelerated in recent years, particularly post‑COVID, as manufacturers needed remote visibility, faster decision‑making, and more resilient operations.The reality of IT/OT integration, including cultural differences, conflicting priorities, and why alignment and over‑communication matter more than technology alone.Where AI and machine learning add value today—and where they don’t yet, highlighting realistic use cases such as analysis support, infrastructure modernisation, and decision assistance rather than full autonomy.What separates successful data initiatives from failed ones, including mindset, patience, iterative improvement, and the willingness to modernise legacy infrastructure step by step.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 Vlad on LinkedIn:https://www.linkedin.com/in/vladromanov/
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    42 m
  • Reliability in Regulated Plants: 5 Rules That Actually Scale - with Steve Lomax

    Reliability in Regulated Plants: 5 Rules That Actually Scale - with Steve Lomax
    Mar 24 2026
    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 Steve Lomax, an independent reliability and maintenance consultant with decades of experience in highly regulated pharmaceutical environments, who shares a practitioner’s perspective on predictive maintenance, reliability, and digital transformation.What predictive maintenance really means in regulated industries, focusing less on “magic AI” and more on reducing uncertainty, managing risk, and stabilising critical processes.Why reliability must be framed in business language, connecting maintenance decisions to availability, risk, patient impact, and CFO‑level financial outcomes.How global standards and local realities must coexist, with predictive maintenance deployed through a common framework but adapted site‑by‑site based on maturity, assets, and regulation.Why data quality, simplicity, and cultural readiness matter more than more sensors, starting with existing data and building trust in digital records and AI‑supported insights.How to introduce predictive maintenance without overwhelming teams, by focusing on asset criticality, bad actors, cross‑functional ownership, and a clear reliability roadmap.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 Steve on LinkedIn:https://www.linkedin.com/in/steve-lomax-56730912/Learn more about Rheon Insights:https://www.rheoninsight.co.uk/
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    35 m
  • From Student to Senseye Educator: Predictive Maintenance in the Classroom with Jasleen Kaur

    From Student to Senseye Educator: Predictive Maintenance in the Classroom with Jasleen Kaur
    Mar 18 2026
    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 Jasleen Kaur, a graduate electrical and electronics engineer at Siemens Digital Industries, who shares her firsthand experience delivering industry‑led education through the Connected Curriculum initiative.How industry and academia can work together effectively through initiatives like Connected Curriculum to close the skills gap between university education and real-world engineering roles.The practical difference between condition monitoring and predictive maintenance, and why predictive maintenance adds real value by anticipating failures and reducing unplanned downtime.How AI-powered tools like Senseye (and its Copilot) help beginners and professionals alike interpret machine data, troubleshoot issues, and make informed maintenance decisions using natural language.What a real-world, hands-on predictive maintenance course looks like, including the use of synthetic data, staged learning over several weeks, and practical platform experience rather than theory alone.Why human judgment still matters in an AI-driven workplace, and how students are taught to combine critical thinking with AI insights rather than relying blindly on automated recommendations.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 Jasleen on LinkedIn:https://www.linkedin.com/in/jasleen-kaur-907391268/Previous episodes about Connected Curriculumhttps://podcasts.apple.com/ca/podcast/hands-on-with-ai-bringing-senseye-to-the-classroom/id1589803102?i=1000724963690
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    29 m
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