Trend Detection Podcast

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

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

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

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.In this episode we revisit last years SPS to explore the state of readiness in the Danish Market.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

Willkommen zum Trend Detection Podcast, präsentiert von Senseye Predictive Maintenance – der Plattform, die eine skalierbare vorausschauende Instandhaltung für sämtlicheAnlagen ermöglicht.  Beschreibung:  • Die Entwicklung erkunden: Entdecken Sie die aktuellen Fortschritte in der industriellen KI und Automatisierung, während wir uns mit den neusten Tools und Technologien beschäftigen, die die Industrie prägen.  • Die Revolution der Automatisierung: Entdecken Sie mehr über die zukunftsweisenden Projekte von Siemens, darunter das Copilot-System und digitale Geschäftsmodelle im Umfeld der Fabrikautomatisierung.  • Einblicke in KI-Strategien: Erfahren Sie mehr über vorausschauende Instandhaltung, KI-Infrastrukturen und wie generative KI die Industrie verändert.  • Zukünftige Trends: Werfen Sie einen Blick in die Zukunft der industriellen KI, einschließlich aufkommender Technologien und zukünftiger Veränderungen in der Industrie..  Weitere Informationen darüber, wie Senseye Predictive Maintenance ungeplante Ausfälle reduziert und die Nachhaltigkeit Ihrer Produktionsanlagen verbessert, finden Sie unter www.siemens.com/senseye-predictive-maintenance 

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:Overview of the deployment of Senseye Predictive Maintenance deployment at Bluescope SteelDeep dive into a success case that resulted in 24 hours unplanned downtime savingsHow the new copilot functionality in Senseye is transforming the way they workAdvice to other companies looking to implement predictive maintenance solutionsYou 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

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:Optimizing Plant Performance and Reducing DowntimeLearn how predictive maintenance uses data insights to improve efficiency, keep operations smooth, and minimize unplanned downtime.Enhancing Product Quality and Safety Explore how early issue detection helps maintain consistent product quality, safeguards employees, and reduces environmental risks.Scalable Solutions for Proactive Issue DetectionDiscover how our scalable predictive maintenance solutions enable you to detect potential issues before they occur, ensuring safer and more sustainable operations.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

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 with Chris Garrison Covers:The Evolution of Predictive Maintenance and Sensor Technology: How advancements in sensor tools enable proactive fault prediction.Starting Predictive Maintenance with Available Data: Using onboard diagnostics to kickstart predictive maintenance without major investments.Optimizing Sensor Coverage for Different Equipment: Determining the right sensor setup based on equipment complexity and fault characteristics.Adopting a Holistic Approach to Asset Health: Leveraging diverse data types to gain a comprehensive view for proactive maintenance.Unlocking Benefits Beyond Maintenance: How predictive maintenance improves safety, reduces downtime, and enhances efficiency across the organization.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

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.Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!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

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.Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!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

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.Listen to learn how our Senseye Predictive Maintenance improves production and management KPIs by analyzing and predicting machine and maintainer behavior using AI – and you do not have to be data scientist!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

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.In this session, we discussed the following:The role of data analytics in predictive maintenance and how to harness its full potential.How to leverage human expertise alongside advanced algorithms to achieve a more proactive maintenance approach.Using GenAI (Generative Artificial Intelligence) to help prevent equipment failures.Real-world case studies showcasing successful implementations of Senseye Predictive 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

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.For this session, we discussed streamlining Predictive Maintenance with Senseye PdM and Mendix with Johnathan Bonner. This episode covers: Benefits of Predictive Maintenance: Leveraging existing data to reduce downtime, increase maintenance efficiency, and lower operating costs.Role of Low-Code Platforms: Enhancing predictive maintenance with rapid, customizable application development that integrates seamlessly with existing systems.Centralized Maintenance Workflows: Streamlining maintenance processes by combining predictive insights with user-friendly dashboards and mobile accessibility.Scalability and Data Management: Handling large data volumes efficiently and offering flexible, scalable deployment options to support growing operations.Comprehensive Customer Support: Providing ongoing assistance with implementation, customization, and maintenance to ensure successful integration and user adoption.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

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.For this session, we discussed the evolution of maintenance with Richard Jeffers. We cover:Key components of an effective maintenance strategy were highlighted, emphasizing the importance of a proactive and data-driven approach.Challenging technical issues and insights into the innovative solutions used to resolve them.The impact of predictive maintenance on overall efficiency was explored, along with how advancements in IoT and AI are transforming maintenance practices.Current trends and future directions in the maintenance industry, including how the role of maintenance professionals is expected to evolve over the next decade.Follow Richard Jeffers on LinkedInLearn more about RS: Maintenance Solutions | RSYou 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

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.For this session, we discussed the topic of Cautionary tales of predictive maintenance - with Dr Natalie Kurgan. We cover:1. Build the Right FoundationDiscover why setting up the right infrastructure is crucial before implementing any predictive maintenance (PDM) solution. Without it, success is a struggle.2. Clear Goals Drive SuccessLearn how defining clear business objectives and aligning them with your PDM solution can deliver real, measurable value.3. Start Simple, Scale FastGet practical tips on why starting with simpler assets like motors helps you scale effectively to more complex equipment over time.4. Collaboration is KeyUnderstand how involving and educating your team at every stage of implementation is essential for maximizing the benefits of PDM.5. Bust Predictive Maintenance MythsBreak through the marketing hype! Learn what PDM can (and can’t) do— it’s not about predicting failures, but ensuring timely, effective 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

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.In this episode we share a tried and true methodology to implement successful and scalable PdM projects using our industry-leading Senseye Knowledge Platform.  We will cover the five phases crucial to a successful deployment.We cover: Scope: Discovery, putting together a plan, defining success.Design: Creating a detailed project design and machine selection.Deploy: Set up and technical implementation.Operate: Effective usage of Senseye, learning and tracking success.Refine: Gathering and using feedback

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. For this session, we discussed the topic of Bringing the engineering community together - with Thomas Flude. This episode covers: Building an Industrial Manufacturing Community: The episode explores how the guest, Tom and his business partner are creating an industrial manufacturing community through their startup, Engineers Insight. They discuss the unique aspects of this community and its purpose in the industry.Challenges in Engineering Knowledge Retention: The conversation highlights the growing issue of knowledge gaps in engineering, particularly as experienced engineers retire without passing on their expertise to the next generation. The episode discusses the importance of addressing this gap.The Role of Feedback in Product Development: Tom emphasizes the significance of continuous feedback from users, which has shaped Engineers Insight from a simple marketing tool into a comprehensive resource platform. This process of user-driven development is a central theme.Engaging the Next Generation of Engineers: The podcast delves into strategies for connecting with and inspiring the next generation of engineers, including integrating educational institutions into the platform and addressing the generational shift in expectations from young engineers entering the field.The Impact of AI and Technology in Manufacturing: The discussion touches on the role of AI and other technologies in the manufacturing sectorYou 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

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. For this session, we discussed the topic of Readiness for predictive maintenance in Japan - with Taku Shigihara.This episode covers:Trends and Adoption: Growing interest in predictive maintenance in Japan, driven by efficiency needs and supported by AI and IoT investments.Cultural and Regulatory Impact: Japan’s strong quality focus and stringent regulations push adoption, but traditional practices and cautious decision-making can slow progress.Benefits and Innovations: Companies can expect cost savings and efficiency gains, with emerging sector-specific solutions and AI-driven analytics tailored for the Japanese market.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

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. For this session, we discussed the topic of Improving safety with predictive maintenance - with Tom Jacques. This episode covers: How Predictive Maintenance Enhances Safety: Discover how predictive maintenance can prevent equipment failures and reduce incidents, leading to safer industrial and operational environments.The Cost and Industry Impact: Learn about the cost-effectiveness of predictive maintenance and why it’s especially crucial in high-risk industries like manufacturing, aviation, and energy.Workforce and Compliance Considerations: Understand how predictive maintenance affects workforce roles, training, and compliance with safety regulations, contributing to overall job safety.Future Trends and Implementation Strategies: Explore upcoming innovations in predictive maintenance and get practical advice on how to begin implementing these strategies to improve safety in your organization.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

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. For this session, we discussed the topic of Flowing Forward: Digital Transformation in the Water Industry. Key takeaways:Broad Overview: We explore the concept of digital transformation in the water industry, an area often overlooked but crucial for modernizing essential services.Challenges & Scale: Discover the scale of the water industry's operations, including the delivery and treatment of billions of liters of water daily, and the extensive network of infrastructure that supports these processes.The Need for Change: Understand the necessity of digital transformation in an industry faced with aging infrastructure and the demand for increased efficiency and innovation.Learning Across Industries: How lessons from the water sector's digital shift can be applied to other industries and what all sectors can learn from these advancements.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