TY  - JOUR
AB  - Purpose Centrifugal compressors are integral components in oil industry, thus effective maintenance is required. Condition-based maintenance and prognostics and health management (CBM/PHM) have been gaining popularity. CBM/PHM can also be performed remotely leading to e-maintenance. Its success depends on the quality of the data used for analysis and decision making. A major issue associated with it is the missing data. Their presence may compromise the information within a set, causing bias or misleading results. Addressing this matter is crucial. The purpose of this paper is to review and compare the most widely used imputation techniques in a case study using condition monitoring measurements from an operational industrial centrifugal compressor.Design/methodology/approach Brief overview and comparison of most widely used imputation techniques using a complete set with artificial missing values. They were tested regarding the effects of the amount, the location within the set and the variable containing the missing values.Findings Univariate and multivariate imputation techniques were compared, with the latter offering the smallest error levels. They seemed unaffected by the amount or location of the missing data although they were affected by the variable containing them.Research limitations/implications During the analysis, it was assumed that at any time only one variable contained missing data. Further research is still required to address this point.Originality/value This study can serve as a guide for selecting the appropriate imputation method for missing values in centrifugal compressor condition monitoring data.
VL  - 23
IS  - 3
SN  - 1355-2511
DO  - 10.1108/JQME-08-2016-0032
UR  - https://doi.org/10.1108/JQME-08-2016-0032
AU  - Loukopoulos Panagiotis
AU  - Zolkiewski George
AU  - Bennett Ian
AU  - Pilidis Pericles
AU  - Duan Fang
AU  - Mba David
PY  - 2017
Y1  - 2017/01/01
TI  - Dealing with missing data as it pertains of e-maintenance
T2  - Journal of Quality in Maintenance Engineering
PB  - Emerald Publishing Limited
SP  - 260
EP  - 278
Y2  - 2024/04/26
ER  -