Course detail: Predictive Maintenance Strategy

Description

Condition-based maintenance uses equipment operating condition to make data-driven decisions. In practice, this philosophy can improve your facility and equipment's quality, productivity, and profitability. Unlike industry courses that focus on applying specific predictive technologies, like vibration monitoring or oil analysis, this course focuses on establishing, managing, and sustaining results from a comprehensive condition-based program.

This course considers predictive maintenance as a component of a larger asset maintenance strategy to diagnose, prevent, and postpone failures. You will learn the theory and application of multiple PdM technologies and review critical success factors of results-producing programs. Through group activities and case studies, you will determine which technologies to use and how to set goals and track progress for your program. Then, you will practice how to communicate results to different stakeholders. By the end of the session, you will have outlined what a successful condition-based program can look like at your organization.


Learning Objectives

  • Define the purpose and benefits of condition-based maintenance.
  • Describe how predictive maintenance enables proactive maintenance planning and scheduling.
  • Explain how to use risk mitigation to establish a condition-based maintenance program: Criticality, FMEA, and Failure Modes
  • Make a business case to justify CbM program investment.
  • Summarize benchmarks and trends in the predictive and condition-based maintenance disciplines.
  • Summarize prevalent condition-based technologies in use today
  • Describe the role of Precision Maintenance in a Condition-based Maintenance program
  • Report program results: reliability improvements and financial value.
  • Draft program action plan that incorporates critical success factors in the following areas:
    • Program objectives
    • Application: technology, techniques and equipment
    • Measures
    • Infrastructure and resources
    • Organizational support
  • Explain how applying a combination of maintenance strategies mitigates risk and optimizes your asset maintenance plan

Who Should Attend?

This course is designed for maintenance managers, PdM managers, maintenance professionals, continuing education students, and any person responsible for justifying or managing duties related to a condition-based monitoring program.


Live Online Training

Virtual, Instructor-Led Training (VILT) combines the benefits of traditional classroom training and online learning. It allows participants to have the experience of live instructor-led training without having to go to a classroom or have the instructor present in person.

Using Zoom's technology, this video-based training allows learners to ask questions, participate in discussions, and get trained together irrespective of their location. Participants in the Institute's virtual classes will learn the same content from the Institute's in-person classes while participating in professionally facilitated sessions with activities that stimulate participation and learning:

  • Online breakout sessions with facilitator support
  • Individual and group assignments and discussions
  • Polls, Q&A, and online whiteboard activities that keep learners engaged

Life Cycle Institute's virtual classes were developed by industry-leading subject matter experts and certified professional instructional designers with experience converting live, instructor-led classes into engaging and effective online learning experiences using learning best practices.


Certificate Track

Part of the Life Cycle Institute Reliability Engineering Certification
and the LCI Maintenance Management Certification Program.

 


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Course Resources
Reliability Engineering Certification Information (PDF Document)
Predictive Maintenance Strategy Course Description (PDF Document)
Maintenance Management Certification Information (PDF Document)
KU Life Cycle Institute Catalog 2020-2021

Available sessions

November 3-5, 2020, Daily Live Online Training (Online, OTHER)

(This session is full; you may join the waitlist)