RELIABILITY ANALYSIS OF A MAINTENANCE FLOAT MODEL.

Item

Title
RELIABILITY ANALYSIS OF A MAINTENANCE FLOAT MODEL.
Identifier
AAI8601673
identifier
8601673
Creator
MADU, CHRISTIAN NDUBISI.
Contributor
Michael N. Chanin
Date
1985
Language
English
Publisher
City University of New York.
Subject
Business Administration, Management
Abstract
The objective of this paper is to extend the concept of maintenance float modeling to include failure distributions such as: gamma, erlang-2, exponential, uniform, normal and lognormal distributions. From the maintenance float factors (MFF) derived for gamma failure distribution, the special cases of gamma such as exponential (p = 1), erlang-2 (p = 2), and constant or degenerate (p = (INFIN)) were obtained. The MFF obtained for the exponential distribution using the gamma case is the same as that obtained directly from the exponential distribution. The MFF for gamma is obtained through Taylor series approximation. Using the limit theorem, it was also shown that when the number of phases p (--->) (INFIN), the float factor for the gamma distribution approaches 0. This implies that when failure distribution is constant, there is no need to maintain standby units. We therefore state that if the failure distribution is from a constant distribution, then the total float (F) is approaching 0. It is further shown that when P (GREATERTHEQ) 10, it is safe to approximate a constant or degenerate distribution.;This paper was further extended to utilize the asymptotic property of the MFF. It was shown that as the number (N) initially in operation increases, the maintenance float factor derived for each of the distributions will approach an asymptotic value. This we refer to as the asymptotic maintenance float factor (AMFF). The AMFF shows that for N (GREATERTHEQ) 100, the calculation of the MFF depends only on the mean time to repair (MTTR) and the mean time between failure (MTBF) and is independent of N.
Type
dissertation
Source
PQT Legacy CUNY.xlsx
degree
Ph.D.
Program
Business
Item sets
CUNY Legacy ETDs