Beyond the AI Hype: What Actually Works in Manufacturing - with Nick Leeder
vor 2 Monaten
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 ac ...
Podcast
Podcaster
Beschreibung
vor 2 Monaten
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/
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/
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