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Asset Performance Management (APM) Software

Panel Discussion: Making Predictive Analytics Actionable

Introduction

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Asset Performance Management (APM) Software

Video

The industry is buzzing with terms like artificial intelligence, machine learning and industrial internet of things.  At GE Digital, we leverage these new technologies within asset performance management via predictive analytics to drive best practices, optimize proactive work, and achieve top quartile economic results.  This advanced predictive maintenance technique is a key enabler behind a complete asset management strategy which targets identifying and eliminating defects that can become failures by providing timely and actionable insights with an end-to-end decision-making process.

 

As part of this discussion GE Digital’s subject matter experts will discuss the importance of revisiting and optimizing asset strategies when plant operators experience reoccurring failures or diminished strategy effectiveness KPIs. Combined, these actions contribute to reducing both the impact of failures and the cost of preventing them.

 

Key takeaways:

  • How predictive analytics fit into a holistic APM approach
  • How this solution fits in with existing CBM approaches and techniques.
  • How to identify the right starting point for predictive analytics

The industry is buzzing with terms like artificial intelligence, machine learning and industrial internet of things.  At GE Digital, we leverage these new technologies within asset performance management via predictive analytics to drive best practices, optimize proactive work, and achieve top quartile economic results.  This advanced predictive maintenance technique is a key enabler behind a complete asset management strategy which targets identifying and eliminating defects that can become failures by providing timely and actionable insights with an end-to-end decision-making process.

 

As part of this discussion GE Digital’s subject matter experts will discuss the importance of revisiting and optimizing asset strategies when plant operators experience reoccurring failures or diminished strategy effectiveness KPIs. Combined, these actions contribute to reducing both the impact of failures and the cost of preventing them.

 

Key takeaways:

  • How predictive analytics fit into a holistic APM approach
  • How this solution fits in with existing CBM approaches and techniques.
  • How to identify the right starting point for predictive analytics

 

Panelists:

Moderator: Abdullah Wahbeh, Senior Solutions Architect, GE Digital

Sultan A. Al Hazmi, Superintendent Reliability, TASNEE

Jeremi J. Arena Smith , Senior Reliability Engineer – imoms, Saudi Aramco

Fernando Merino Blanco, Manager, Phygital Division, Minsait Indra