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| Content Provider | Springer Nature Link |
|---|---|
| Author | James, Ajith Tom Gandhi, O. P. Deshmukh, S. G. |
| Copyright Year | 2017 |
| Abstract | Maintenance errors in automobiles can lead to premature failures or even accidents. This is attributed to system design, contextual factors prevailing at the garages and human elements performing the maintenance tasks. Use of two well known diagrammatic procedures; event tree diagram and Fishbone diagram, are applied to understand failure initiation of maintenance errors and its effects, and identifying causes and sub-causes attributed to these respectively. This is followed by use of soft computing technique of fuzzy cognitive map to model the interrelationship among maintenance error causes and asses the failure due to these. This is demonstrated through a case study. The proposed methodology helps in better understanding of maintenance errors and the failures attributed to these. Moreover, it is capable of handling high degree of uncertainty and variability associated with the maintenance errors. It provides a ranking of maintenance errors, which can guide automobile service organizations in providing quality and reliability of service, including feedback to designers and practicing engineers in minimizing maintenance errors. |
| Starting Page | 719 |
| Ending Page | 739 |
| Page Count | 21 |
| File Format | |
| ISSN | 09756809 |
| Journal | International Journal of System Assurance Engineering and Management |
| Volume Number | 8 |
| Issue Number | 4 |
| e-ISSN | 09764348 |
| Language | English |
| Publisher | Springer India |
| Publisher Date | 2017-02-16 |
| Publisher Place | New Delhi |
| Access Restriction | One Nation One Subscription (ONOS) |
| Subject Keyword | Automobiles Maintenance induced failures Fishbone diagram Event tree diagram Fuzzy cognitive map Quality Control, Reliability, Safety and Risk Engineering Economics, Organization, Logistics, Marketing |
| Content Type | Text |
| Resource Type | Article |
| Subject | Strategy and Management Safety, Risk, Reliability and Quality |
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