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     Research Journal of Applied Sciences, Engineering and Technology

    Abstract
2014(Vol.8, Issue:12)
Article Information:

Increasing the Probability of Fault Detection in Non Perfect Inspection Model of Delay Time Analysis with Compromise on Inspection Time

Babu Chellappachetty and R. Raju
Corresponding Author:  Babu Chellppachetty 
Submitted: ‎June ‎17, ‎2014
Accepted: ‎July ‎19, ‎2014
Published: September 25, 2014
Abstract:
This study separates the real inspection content (soft portion) within the total maintenance inspection activity and attempts to repeat the same some additional number of times during actual inspection. Effect of repetition of soft portion on inspection related time, fault detection probability and the consequence variable of down time per unit time is analyzed. Statistical test proves that both the inspection time and probability of fault detection has nearly same rate of influence on the consequence variable though in opposite direction. A factor ω is introduced to account for the proportion of soft portion over the maintenance inspection time. As the number of repetitions of soft portion is increased for a given value of ω, it is found from analysis that the new set of inspection time and probability of fault detection improves downtime per unit time until an optimum number of repetitions is reached. Improvement is better as the value of ω is on the lower side. The practitioner is to take this possibility of soft repeatable portion of maintenance inspection time into account while estimating these two input parameters when employing delay time methodology as a preventive maintenance strategy.

Key words:  Delay time analysis, down time, maintenance inspection, non perfect inspection, optimizing down time, preventive maintenance,
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Cite this Reference:
Babu Chellappachetty and R. Raju, . Increasing the Probability of Fault Detection in Non Perfect Inspection Model of Delay Time Analysis with Compromise on Inspection Time. Research Journal of Applied Sciences, Engineering and Technology, (12): 1442-1449.
ISSN (Online):  2040-7467
ISSN (Print):   2040-7459
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