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Rethinking Maintenance Terminology for an Industry 4.0 Future.

Melinda Hodkiewicz1, Sarah Lukens2, Michael P Brundage3

  • 1Faculty of Engineering and Mathematical Sciences, University of Western Australia, Perth, 6009, Australia.

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Summary
This summary is machine-generated.

New maintenance strategies leverage prognostic health management (PHM) and Industry 4.0 advancements. This research redefines maintenance terminology to better evaluate work management performance and detect PHM-driven activities.

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Area of Science:

  • Engineering
  • Computer Science
  • Data Science

Background:

  • Sensors and mathematical models have been utilized since the 1990s for system health assessment and anomaly detection.
  • The Internet of Things (IoT) and cloud computing are enabling cost-effective data collection and democratizing prognostic health management (PHM) technologies.
  • Industry 4.0 developments are transforming maintenance planning and execution towards predictive approaches.

Purpose of the Study:

  • To demonstrate the need for revised maintenance terminology in the context of Industry 4.0.
  • To propose new definitions for consistent evaluation of work management performance.
  • To offer recommendations for improved detection of work related to PHM activities.

Main Methods:

  • Case studies were employed to illustrate the limitations of current maintenance terminology.
  • Analysis of maintenance work management metrics in the context of predictive and condition-based maintenance.

Main Results:

  • Current metrics often fail to capture the value of proactive maintenance driven by PHM.
  • A shift in maintenance is occurring, where work is initiated based on detected potential failures rather than after functional failure.
  • Existing definitions of corrective work do not adequately encompass PHM-driven interventions.

Conclusions:

  • Rethinking maintenance terminology is crucial for accurately measuring performance in an Industry 4.0 environment.
  • Consistent definitions are needed to evaluate work management effectiveness for PHM-driven maintenance.
  • Improved methods for identifying and tracking PHM-related maintenance tasks are recommended.