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Computipg Reliability Data

Data is not information, Information is not knowledge, Knowledge is not understanding, Understanding is not wisdom.

Gary Schubert, Professor of Art & Computer Science, Alderson-Broaddus College, West Virginia.

Author: V. Narayan

Location: 2.3.2 Large Oil & Gas Production Company

Background

We need good reliability data to take decisions that will help improve safety, environmental, and cost performance. Such data is not readily available, so we tend to use generic data sources. Some of these data sources have well-defined taxonomies and good control of data quality. Even in these cases, there can be a large spread between the maximum and minimum values. While the operating context and maintenance effectiveness of the items in the data sets will be broadly similar, there will be differences that cause this large spread. In most cases, we end up using mean values, which may be significantly different from those applicable in our own operating context. The solution is to use our own data to develop a reliability database.

We had well-defined maintenance strategies and procedures in the company. With the help of a Computerized Maintenance Management System (CMMS), we issued Preventive maintenance (PM), testing, calibration and condition monitoring (CM) work orders, along with relevant procedures. Technicians recorded repair history in the CMMS and test results in calibration sheets.

We removed Pressure Relief Valves (PRVs) periodically for re-certification, and tested them before and after repairs or adjustments. The pre-overhaul data was recorded in relief valve data sheets. Wellhead valve and sub-surface safety valve test records were kept separately. Similarly, rotating machinery trip and bump-test results were kept in the equipment files. Test records from emergency shut-down (ESD) valves; fire, gas, and smoke detectors; deluge valves; and sprinkler-head tests were kept in calibration sheets. All this amounted to a veritable data mountain, available for inspection by any interested party, including the Regulator.

These records provided an audit trail and helped prove that the company was behaving responsibly and openly. The records were proof of its diligence. Nobody had considered the possibility of milking this data to improve safety and cost performance.

 
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