The truth about predictive maintenance – with Nat Ford [Video]

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 (http://www.siemens.com/senseye-predictive-maintenance)