C-FER works with operators to improve their understanding of how equipment is performing by collecting and organizing data, while applying advanced statistical analyses techniques. This process is often hampered by data that is incomplete, incorrect and inconsistent.
The challenge of incomplete data can be overcome by coordinated data collection programs that focus on the key information required for the performance analysis. This can include data mining existing data sets or pursuing additional field measurements.
In many cases, individual operators do not have sufficient equipment installations or a broad enough range of applications to make the data set suitable for detailed analysis. Sharing data among multiple operators in a Joint Industry Project (JIP) can help to assemble a data set large enough to yield meaningful and reliable results.
Ensuring that the data is correct is largely the responsibility of the operator or vendor; however, the data collection process can incorporate various checks that flag data that might be incorrect.
This can be done by applying simple engineering calculations or dimensional checks such as determining if the reported operating conditions are within the normal operating range for the reported equipment or that all of the reported equipment components are compatible with each other.
Data consistency can be improved by developing standardized reporting templates and nomenclatures that all parties can use to collect and assemble their data.
These tools are most effective when they are implemented as software products that employ standardized menus and selection lists as well as automated data checking routines.
A critical component of the analysis is the operational expertise and field experience of the operators and equipment vendors. This knowledge directs the use of advanced reliability analysis methods and helps to explain the meaning and implications of the results.