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DTSTAMP:20240117T183637Z
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DTSTART;TZID=America/New_York:20240117T110000
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DESCRIPTION:Artificial Intelligence (AI) is upending businesses by unlockin
 g value & drastically changing operating models. Will Reliability Engineer
 ing be transformed? The data-intensive exercises of reliability testing\, 
 verification & validation\, and fleet monitoring can be improved vastly by
  deploying AI tools. How should the AI implementation be done to get the m
 aximum benefits?\n\nThe presentation explores answers to these questions i
 n the context of implementing a Predictive Maintenance (PdM) program where
  repair work is always planned & executed at optimal times. A strategic fr
 amework is needed to plan\, execute\, and sustain an AI program. Utilizing
  algorithms to predict machine failures empowers Reliability Engineers wit
 h information that they use to manage design iterations\, repair work\, sp
 are parts\, and production. No more reacting to failures after a breakdown
  resulting in huge losses\; project teams will be proactive & efficient. W
 hether you're an Executive\, an Engineer\, or a Student\, the talk will ha
 ve key takeaways to set you up on the reliability transformation journey.\
 n\nSpeaker(s): Arun Gowtham\, \n\nAgenda: \n11:00 AM Technical Presentatio
 n\n\n11:45 AM Questions and Answers\n\n12:00 PM Adjournment\n\nVirtual: ht
 tps://events.vtools.ieee.org/m/390437
LOCATION:Virtual: https://events.vtools.ieee.org/m/390437
ORGANIZER:james.yakura@ieee.org 
SEQUENCE:24
SUMMARY:Webinar - Transforming Reliability with AI 
URL;VALUE=URI:https://events.vtools.ieee.org/m/390437
X-ALT-DESC:Description: <br /><div>Artificial Intelligence (AI) is upending
  businesses by unlocking value &amp\; drastically changing operating model
 s. Will Reliability Engineering be transformed?&nbsp\; The&nbsp\;data-inte
 nsive exercises of reliability&nbsp\;testing\, verification &amp\; validat
 ion\, and fleet monitoring can be improved&nbsp\;vastly by deploying AI to
 ols. How should the AI implementation be done to get the maximum benefits?
 &nbsp\;</div>\n<div>&nbsp\;</div>\n<div>The presentation explores answers 
 to these questions in the context of implementing a Predictive Maintenance
  (PdM) program where repair work is always planned &amp\; executed at opti
 mal times. A strategic framework is needed to plan\, execute\, and sustain
  an AI program. Utilizing algorithms to predict machine failures empowers 
 Reliability Engineers with information that they use to manage design iter
 ations\, repair work\, spare parts\, and production. No more reacting to f
 ailures after a breakdown resulting in huge losses\; project teams will be
  proactive &amp\; efficient. Whether you're an Executive\, an Engineer\, o
 r a Student\, the talk will have key takeaways to set you up on the reliab
 ility transformation journey.&nbsp\;&nbsp\;</div><br /><br />Agenda: <br /
 ><p><strong>11:00 AM</strong>&nbsp\;&nbsp\;&nbsp\;Technical Presentation</
 p>\n<p><strong>11:45 AM</strong>&nbsp\;&nbsp\; Questions and Answers</p>\n
 <p><strong>12:00 PM</strong>&nbsp\;&nbsp\;&nbsp\;Adjournment</p>
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