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Failure Mode Structured Preventive Maintenance Scheduling With Changing Failure Rates in Industry 4.0 Environment

journal contribution
posted on 2024-11-03, 09:42 authored by Theyab Alamri, John MoJohn Mo
Critical manufacturing systems consist of many different components working together. Each component is important to the operation and performance of the whole system. It is crucial to have a sound maintenance plan to ensure continuous production output. The strategy of current research is to focus on the failure mode modelling of the manufacturing system and divide it according to failure mode in production blocks. The preventive replacement intervals are determined using mean time to failure values of components, with group replacements of components within the production blocks to prevent unexpected functional breakdown failures. With the implementation of Industry 4.0 infrastructure, the mean time to failure values of components are constantly updated. The multi-mode mathematical model developed in this paper is able to adjust the preventive replacement schedule dynamically to suit changing system conditions. The results indicate that preventive replacement of components can achieve consistent minimum system reliability of 90% while minimizing system costs due to maintenance and downtime. Novelty of the approach lies in developing a holistic preventive maintenance schedule using failure mode and effects analysis for a complete system. The approach not only improves maintainability and reliability, lowers the cost of maintenance, but also keeps continuity of production.

History

Related Materials

  1. 1.
    DOI - Is published in 10.3389/fmtec.2022.828986
  2. 2.
    ISSN - Is published in 28130359

Journal

Frontiers in Manufacturing Technology

Volume

2

Number

828986

Start page

1

End page

17

Total pages

17

Publisher

Frontiers Research Foundation

Place published

Switzerland

Language

English

Copyright

© 2022 Alamri and Mo. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY).

Former Identifier

2006124847

Esploro creation date

2023-09-07

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