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Predictive Maintenance for digitally experienced operators

By Laboratory for Manufacturing Systems and Automation of Patras - BIBA

Type of course:

Digital learning, Path

Language:

EN

Duration:

6 hours

Workload:

12 hours

Proficiency:

Intermediate

Target:

Manager, Professionals, Students, Workers

The “Predictive Maintenance for digitally experienced operators” learning path discusses useful technological aspects that will facilitate industrial upgrade of a factory’s maintenance approach. The whole learning path serves as an all-around educational package that will accomplish a first introduction and apprehension of the Predictive Maintenance (PdM) concept. For such a novel and promising concept like PdM, that  has only recently found its first industrial applications, both low and high-level employees and computer science experts cannot directly involve with approach implementation due to a vast amount of new knowledge. This learning path aims to smoothen this procedure and accelerate PdM culture approval. Focus of this path will be directed to digitally experienced operators and providing them with essential information on their way to their first involvement with Predictive Maintenance. Most important topics discussed:

•Predictive Maintenance basics and advanced knowledge

•Introduction to Artificial Intelligence and Data Analytics

•Introduction to Maintenance software 

•Maintenance Task management  and Material Mechanics


Learning outcomes

  1. Describe Predictive Maintenance basics and implementation guidelines
  2. Recognize possible failures of mechanical components
  3. Interpret Materials Mechanics and their effects on everyday operations

Topics

Advanced Manufacturing, Digital Transformation, CNC Machining, Mechanics, Internet of Things (IoT), Artificial Intelligence (AI), Data Analytics

Provided by

Content created in 2023
+223 enrolled
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Course Includes

  • 2 Quizzes
  • 1 Certificate of achievement

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