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Dynamic residual life estimation of industrial equipment based on failure intensity proportions
Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006.
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University of Pretoria
2013
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| _version_ | 1867613523637436416 |
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| access_status_str | Open Access |
| author2 | Claasen, S.J. (Schalk Johannes) |
| author_browse | Claasen, S.J. (Schalk Johannes) |
| author_facet | Claasen, S.J. (Schalk Johannes) |
| collection | Thesis |
| dc_rights_str_mv | © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. |
| description | Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006. |
| format | Thesis |
| id | oai:repository.up.ac.za:2263/30180 |
| institution | University of Pretoria (South Africa) |
| last_indexed | 2026-06-10T12:37:30.383Z |
| license_str | Other — see source repository |
| provenance_str_mv | Harvested via OAI-PMH from UPSpace — University of Pretoria Institutional Repository |
| publishDate | 2013 |
| publishDateRange | 2013 |
| publishDateSort | 2013 |
| publisher | University of Pretoria |
| publisherStr | University of Pretoria |
| record_format | dspace |
| source_str | UPSpace — University of Pretoria Institutional Repository |
| spelling | oai:repository.up.ac.za:2263/30180 Dynamic residual life estimation of industrial equipment based on failure intensity proportions Claasen, S.J. (Schalk Johannes) upetd@ais.up.ac.za Vlok, Pieter-Jan Industrial equipment maintenance Production engineering System failures engineering monitoring Industrial equipment performance UCTD Thesis (PhD (Industrial Engineering))--University of Pretoria, 2006. There is a world-wide drive to optimize maintenance decisions in an increasingly competitive manufacturing industry. Preventive maintenance if often the most organized and cost efficient strategy to follow, but a decision still has to be made on the optimal instant to perform preventive maintenance. Use based preventive maintenance decisions have been optimized through statistical analysis of failure date while predictive preventive maintenance (condition monitoring) has been optimized by utilizing more sophisticated technology. Very little work has however been done to combine the advantages of the two schools of thought. This thesis originated from a realization of the potential improvement in maintenance practice by combining use based preventive maintenance optimization techniques with high technology condition monitoring. In this thesis an approach is developed to estimate residual life of industrial equipment dynamically by combining statistical failure analysis and sophisticated condition monitoring technology. The approach is based on failure intensity proportions determined from historic survival time information and corresponding diagnostic information such as condition monitoring. Combined Proportional Intensity Models (PIMs) for non-repairable and repairable systems, containing the majority of conventional PIM enhancements as special cases, with numerical optimization techniques to solve for the regression coefficients, are derived. In addition to the residual life estimation approach, a user-friendly graphical method with which residual life estimates can be presented was also developed. This method is natural and easy to comprehend, even by inexperienced data analysts. The residual life estimation approach is applied to a typical data set from a South African industry and results are compared to those obtained from a similar, established maintenance decision support tool. This comparison showed that the approach developed in this thesis is relevant, practical and marginally better than the established decision support tool for certain criteria. Industrial and Systems Engineering unrestricted 2013-09-07T18:13:05Z 2005-12-08 2013-09-07T18:13:05Z 2002-04-01 2006-12-08 2005-12-07 Thesis Vlok, P 2002, Dynamic residual life estimation of industrial equipment based on failure intensity proportions, PhD thesis, University of Pretoria, Pretoria, viewed yymmdd < http://hdl.handle.net/2263/30180 > http://hdl.handle.net/2263/30180 http://upetd.up.ac.za/thesis/available/etd-12072005-150219/ © 2002, University of Pretoria. All rights reserved. The copyright in this work vests in the University of Pretoria. No part of this work may be reproduced or transmitted in any form or by any means, without the prior written permission of the University of Pretoria. application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf application/pdf University of Pretoria |
| spellingShingle | Industrial equipment maintenance Production engineering System failures engineering monitoring Industrial equipment performance UCTD Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title | Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title_full | Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title_fullStr | Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title_full_unstemmed | Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title_short | Dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| title_sort | dynamic residual life estimation of industrial equipment based on failure intensity proportions |
| topic | Industrial equipment maintenance Production engineering System failures engineering monitoring Industrial equipment performance UCTD |
| url | http://hdl.handle.net/2263/30180 http://upetd.up.ac.za/thesis/available/etd-12072005-150219/ |