Maintenance Model Implementation on Manufacturing Systems

Authors(2) :-Nwadinobi, Chibundo Princewill

In this research, a mathematical model was deployed that improves the effectiveness of maintenance planning for manufacturing systems. It utilizes operational data as obtained from industrial equipment to monitor the reliability and availability of the test equipment. A parametric test was conducted on the model by varying the input parameters to ascertain their effects on the overall system. For each case, varied values of failure rates and repair rates at given states are used to calculate the state probabilies considering the discrete states of the equipment under study. Continuing, this evaluation, gives an insight to the most appropriate maintenance action to undertake at any given time so as to improve on the reliability and availability of the equipment. The prescribed procedure, assists in planning preventive maintenance, which stands preferred to having a corrective maintenance action on manufacturing systems as it makes for increased operational life cycle, cost effectiveness, improving availability and reliability of such systems.

Authors and Affiliations

Department of Mechanical Engineering, Abia State University, Uturu, Abia State
Chibundo Princewill
Department of Mechanical Engineering, Abia State University, Uturu, Abia State

Mathematical Model, Manufacturing Systems, Maintenance, Availability, Reliability

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Publication Details

Published in : Volume 4 | Issue 9 | July-August 2018
Date of Publication : 2018-07-30
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 314-321
Manuscript Number : IJSRSET184963
Publisher : Technoscience Academy

Print ISSN : 2395-1990, Online ISSN : 2394-4099

Cite This Article :

Nwadinobi, Chibundo Princewill, " Maintenance Model Implementation on Manufacturing Systems, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 9, pp.314-321, July-August-2018.
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