Article ID: | iaor20141366 |
Volume: | 121 |
Issue: | 3 |
Start Page Number: | 113 |
End Page Number: | 120 |
Publication Date: | Jan 2014 |
Journal: | Reliability Engineering and System Safety |
Authors: | Barber Luis, Crespo Adolfo, Viveros Pablo, Stegmaier Ral |
Keywords: | decision support, mining |
This paper presents a case for practical application of the GAMM method, which has been developed and published by the authors (Barberá L., Crespo A. and Viveros P.) The GAMM method supports decision‐making in the overall maintenance management, through the visualization and graphical analysis of data. In addition, it allows for the identification of anomalous behavior in the equipment analyzed, whether derived from its own operations, maintenance activities, improper use of equipment or even as a result of design errors in the equipment itself. As a basis for analysis, the GAMM method uses a nonparametric estimator of the reliability function using all historical data or, alternatively, part of the history, allowing it to perform an analysis even with limited available data. In the case study developed, GAMM has been used to analyze two slurry pumps in a mining plant located in Chile. Both pumps are part of the same industrial process, which is described in Section 3, and both pumps had a higher failure rate but one more than the other. GAMM identified deficiencies in each of the pumps being studied, thus improving decision‐making and problem solving process related to the maintenance of the pumps. Particularly, this work initially provides a description of the GAMM method (Section 1), and, afterwards, it is depicted with special attention the approach to the problem (Section 2). In Section 3, a background of the industrial context is presented. Then, Section 4 shows step by step the application of GAMM method. Finally, results and conclusions are presented in Section 5 where the main improvements obtained are summarized.