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Optimizing Complex Items: Analytics and Decision Models for Equipment Reliability

This guide outlines the approach to optimizing complex items in equipment maintenance using EXAKT’s data models. Complex items, defined as equipment with multiple significant failure modes, can be effectively monitored and analyzed through comprehensive data mapping tables. The analysis leverages conditional distribution functions and hazard models to establish a reliability framework that is age-independent. Additionally, it emphasizes the creation of a DMDR database for better decision-making and risk management. This framework enhances the ability to predict and mitigate failure risks for complex equipment.

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Optimizing Complex Items: Analytics and Decision Models for Equipment Reliability

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Presentation Transcript

  1. CBM Optimization – Complex items • An item is a group of components that is convenient to monitor and analyze together • Equipment units, as defined in the CMMS asset register are, in general, well defined items. • A complex item is an item with more than one significant failure mode.

  2. EXAKT data model These are data mapping tables. They enable the analysis of complex items and are automatically populated by EXAKT in the mapping procedure to be discussed in Slide 5

  3. Attach external database(s) to the analysis

  4. General project data

  5. Data mapping of the first failure mode on Gearbox A

  6. Build the proportional hazard model Age not significant. So fix shape parameter to one.

  7. Final model – reliability is age independent

  8. Transition and Decision models

  9. Cost function

  10. Decisions

  11. Creating the DMDR database

  12. Attach the DMDR database tables

  13. Store decision model

  14. EXAKT for decisions

  15. Attach DMDR tables

  16. Create a report list and run the models

  17. Graphics Conditional Distribution Function Conditional Density Function Replacement Decision Failure Risk

  18. All Units report

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