Down Time Terms and Information Used for Assessment of Equipment Reliability and Maintenance Performance

  • Selvik J
  • Ford E
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Abstract

Reliability and maintenance data is important for predictive analysis related to equipment downtime in the oil and gas industry. For example, downtime data together with equipment reliability data is vital for improving system designs, for optimizing maintenance and in estimating the potential for hazardous events that could harm both people and the environment. The quality is largely influenced by the repair time taxonomy, such as the measures used to define downtime linked to equipment failures. However, although it is important to achieve high quality from maintenance operations as part of this picture, these often seem to receive less focus compared to reliability aspects. Literature and experiences from, e.g., the OREDA project suggest several challenging issues, which we discuss in this chapter, e.g., for the interpretation of "MTTR." Another challenge relates to the duration of maintenance activities. For example, while performing corrective maintenance on an item, one could also be working on several other items while being on site. This provides an opening for different ways of recording the mobilization time and repair time, which may then influence the data used for predictive analysis. Some relevant examples are included to illustrate some of the challenges posed, and some remedial actions are proposed.

Figures

  • Table 1. Maintenance data categories (based on ([14], Table 8)).
  • Table 2. Equipment state categorization.
  • Figure 1. Different measures that could represent the mean time to repair (MTTR).
  • Figure 2. Intrinsic availability distribution for A 1 , (left) using MTTR = MTTRes. Mean = 99.915% and stdev = 1.5 × 10−4. A 2 , (center) using MTTR = MRT. Mean = 99.932% and stdev = 1.4 × 10−4. A 3 , (right) using MTTR = MART. Mean = 99.983% and stdev = 7.0 × 10−5.
  • Figure 3. Expected absolute (left) and expected relative (right) difference between A 1 and A 3 (upper line) and A 2 and A 3 (lower line), as a function of varying MTTF [hours].
  • Figure 4. Intrinsic availability distribution for A 1 , (left) using MTTR = MTTRes. Mean = 99.416 and stdev = 2.3 × 10−3. A 2 , (center) using MTTR = MRT. Mean = 99.990% and stdev = 0.2 × 10−4. A 3 , (right) using MTTR = MART. Mean = 99.997% and stdev = 0.1 × 10−4.
  • Figure 5. Expected absolute (figure to the left) and expected relative (figure to the right) difference between A 1 and A 3 (upper line) and A 2 and A 3 (lower line), as a function of varying MTTF [hours].
  • Figure 6. P-F interval model (equipment degradation model).

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CITATION STYLE

APA

Selvik, J. T., & Ford, E. P. (2017). Down Time Terms and Information Used for Assessment of Equipment Reliability and Maintenance Performance. In System Reliability. InTech. https://doi.org/10.5772/intechopen.71503

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