• Start Time:
    01:00PM
  • End Time:
    01:40PM
  • Day:
    Day 1

Talk:

  • Exploring the technology available for condition monitoring and predictive maintenance across industry, from maintaining wind turbines to services elevators.
  • Are we moving from reactive to predictive maintenance, and what role can ML play here? What about fixing problems remotely?
  • The potential benefits for business innovation and strategy of implementing IoT for maintenance, and what is holding industries back here?
  • Discussing the impact that data models used for predictive maintenance have on field services, and the need for feedback loops to continually refine them.

Associated Speakers:

Anita Rajasekaran

EMEA Marketing Lead for Anomaly Detection and Prediction solution

Progress DataRPM

Associated Talks:

01:00PM - Day 1

View Panel: Predictive Maintenance – How to unlock true ‘actionable insight’

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Sidney Stokkers

Aircraft Engineer Big Data

Air France Industries KLM Engineering & Maintenance

Associated Talks:

01:00PM - Day 1

View Panel: Predictive Maintenance – How to unlock true ‘actionable insight’

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Domenico Tucci

IoT Client Solution Architect

Trelleborg Sealing Solutions

Associated Talks:

01:00PM - Day 1

View Panel: Predictive Maintenance – How to unlock true ‘actionable insight’

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Don Gerretsen

Product Owner IoT/Predictive Maintenance

Schiphol Group

Associated Talks:

01:00PM - Day 1

View Panel: Predictive Maintenance – How to unlock true ‘actionable insight’

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