Design of a Predictive Maintenance Program
A. P. Shrotri1, S. B. Khandagale2
1A.P.Shrotri, Associate Professor, PVPIT, Budhgaon, Dist. Sangli, M.S., India.
2S.B.Khandagale, Assistant Professor, PVPIT, Budhgaon Dist. Sangli, M.S., India.
Manuscript received on March 02, 2012. | Revised Manuscript received on March 31, 2012. | Manuscript published on April 30, 2012. | PP: 242-246| Volume-1 Issue-4, April 2012 | Retrieval Number: D0338041412/2012©BEIESP
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© The Authors. Blue Eyes Intelligence Engineering and Sciences Publication (BEIESP). This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/)
Abstract: The modern manufacturing plants are generally equipped with complex and continuous running machines and equipment. These are characterized with high speeds heavy working loads high temperatures and pressures etc. The shutdown costs are very large in case of such complex plants. Any breakdown or malfunctioning in such cases is not only a costly affair but it also raises the question of safety of plant itself and persons working there in. This initiates the need for prediction of failure of machines as well in advance so as to initiate the corrective action. The condition monitoring and subsequent condition based maintenance is an effective measure in this regard. However in a factory same maintenance practice is neither desirable nor required for all equipment and machines and a routine practice is to use mixed maintenance scheme. As the predictive maintenance efforts are very expensive hence the design of predictive maintenance scheme itself becomes a task of utmost care. This paper suggests a stepwise procedure for design of predictive maintenance program and also discusses the justification factors, choice of monitoring techniques and various related facts regarding predictive maintenance. The paper also includes a case study of condition monitoring and thereby arranging a predictive maintenance for sugar industry.
Keywords: condition monitoring, Predictive maintainance, VEIN analysis, vibration analysis.