Table of Contents
International Journal of Quality, Statistics, and Reliability
Volume 2012, Article ID 203842, 14 pages
Research Article

Fuzzy RAM Analysis of the Screening Unit in a Paper Industry by Utilizing Uncertain Data

Department of Mathematics, Indian Institute of Technology, Roorkee 247667, Uttarakhand, India

Received 18 July 2012; Accepted 6 October 2012

Academic Editor: Tadashi Dohi

Copyright © 2012 Harish Garg et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Reliability, availability, and maintainability (RAM) analysis has helped to identify the critical and sensitive subsystems in the production systems that have a major effect on system performance. But the collected or available data, reflecting the system failure and repair patterns, are vague, uncertain, and imprecise due to various practical constraints. Under these circumstances it is difficult, if not possible, to analyze the system performance up to desired degree of accuracy. For this, Artificial Bee Colony based Lambda-Tau (ABCBLT) technique has been used for computing the RAM parameters by utilizing uncertain data up to a desired degree of accuracy. Results obtained are compared with the existing Fuzzy Lambda-Tau results and we conclude that proposed results have a less range of uncertainties. Also ranking the subcomponents for improving the performance of the system has been done using RAM-Index. The approach has been illustrated through analyzing the performance of the screening unit of a paper industry.