Fuzzy availability modeling and analysis of biscuit manufacturing plant: a case study

Abstract

Conventional reliability analysis relies on the probability model, which is often inappropriate for handling complex systems due to the lack of sufficient probabilistic information. For large complex systems made up of many components, the uncertainty of each individual parameter amplifies the uncertainty of the total system reliability. To overcome this problem, the concept of fuzzy approach has been used in the evaluation of the reliability of a system. In this article, we use a biscuit manufacturing plant consisting of six sub-systems to capture the effect of coverage factor, failure and repair on its fuzzy availability. Mathematical formulation of the problem is carried out using mnemonic rule and the governing differential equations are solved using Matlab 7.4 by Runge-Kutta method of order four (Ode 45 function).

Application of fuzzy theory for identifying the required availability of an autonomous localization unit in European Train Control System

“…Among numerous uncertainty theories, the fuzzy set theory provides robust methodology to analyze the reliability and availability in the case of lacking or of inaccurate data (e.g. failure or repair rate of components; Kumar & Kumar, 2011). In fact, the fuzzy theory is recommended as a tool to model reality better than traditional probabilistic approaches because of improved results of empirical validation (Zimmermann, 2010).…”

Mathematical modeling and fuzzy availability analysis for serial processes in the crystallization system of a sugar plant

“…Kumar and Kumar (2011) stated that the probability of successful reconfiguration operation of a fault-tolerant system is defined as a coverage factor. It is denoted by 'c'…”

The Mathematical Modelling and Performance Evaluation of Paint Manufacturing System using Fuzzy Reliability Approach

“…Coverage factor Kumar and Kumar (2011) stated that the probability of successful reconfiguration operation of a fault-tolerant system is defined as a coverage factor. It is denoted by 'c' and if its value is less than 1, then it is known as imperfect coverage.…”