• Trend Detection Podcast

  • 著者: Siemens
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Trend Detection Podcast

著者: Siemens
  • サマリー

  • 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-maintenance
    Siemens AG
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あらすじ・解説

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-maintenance
Siemens AG
エピソード
  • The truth about predictive maintenance - with Nat Ford
    2024/11/21
    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.Episode Summary:Predictive Maintenance Evolution: Understanding the progression from condition monitoring to predictive maintenance, emphasizing the benefits of reducing unplanned downtime and improving maintenance efficiency.Conversational Predictive Maintenance: Introduction of conversational predictive maintenance powered by AI, which makes interacting with maintenance data more user-friendly through chat functions and copilots.Data Utilization: Discussion on how even small amounts of data can effectively inform maintenance decisions, challenging the misconception that large datasets are necessary for predictive maintenance.AI's Role in Maintenance: Exploration of generative AI's role in making maintenance tasks more accessible and scalable, allowing users to ask natural language questions about machine conditions and get informed, contextual responses.Human and Machine Collaboration: Insights into how the integration of AI is transforming predictive maintenance into a more interactive process, supporting users in real-time decision-making and troubleshooting.Ongoing Innovation: Speculation on the future of predictive maintenance, particularly how AI-driven insights will continue to evolve and improve maintenance strategies.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
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    33 分
  • Digital Transformation and AI in Mining - a discussion with Joseph Starwood from Microsoft
    2024/11/19
    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.Episode Summary:Exploring AI's Role in Mining: Learn how AI and digital transformation are reshaping the mining industry, from improving operational efficiency to offering predictive insights.Fostering a Data-Driven Workforce: We’ll discuss the importance of a people-centric approach, where a data-driven culture enhances safety, productivity, and decision-making.Simple Wins in Digitization: Expect insights on how mining companies can easily start their digital journey by automating manual processes for faster, safer operations.Addressing Workforce Gaps with AI: Hear how AI and automation can fill critical skill gaps as the mining workforce ages, making the industry safer and less dependent on physical labor.Building Strategic Partnerships: We’ll talk about the value of collaborating with tech providers to build a secure, open ecosystem that accelerates digital transformation in mining.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
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    42 分
  • Understanding predictive maintenance buzzwords - with Maria Thoms
    2024/11/14
    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 episode covers:The Basics of Predictive Maintenance: Understand how predictive maintenance uses data to forecast machine failures and optimize maintenance schedules, saving time and resources.AI and Machine Learning in Maintenance: Learn how AI and machine learning algorithms analyze data to detect anomalies and predict equipment breakdowns.Condition Monitoring as a Foundation: Discover how condition monitoring collects real-time data to enable predictive maintenance, providing insights into equipment performance.Digital Twins Explained: Explore the concept of digital twins—virtual models of physical assets—and how they help simulate, test, and optimize machinery before real-world deployment.Cloud vs. On-Premise Data Solutions: Understand the differences between cloud and on-premise storage, focusing on security, accessibility, and scalability for industrial 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
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    40 分

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