Article

# Availability Analysis of A Cattle Feed Plant Using Matrix Method

International Journal of Engineering 01/2009;

Source: DOAJ

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**ABSTRACT:**This paper discusses a decision support system for a Tab manufacturing plant. Tab manufacturing mainly consists of six subsystems working in series .Two subsystems namely Grinding machine, Electroplating machine are supported by stand-by units with perfect switch over devices and the remaining four subsystem are prone to failure. The mathematical model of Tab manufacturing plant has been developed using Markov birth – death Process. The differential equations has been developed on the basis of probabilistic approach using transition diagram which are further solved for steady state availability in order to develop the decision matrices which provide the various availability levels for different combinations of failure and repair rates of each subsystem.. INTRODUCTION Majority of the systems in the industries are repairable systems. The performance of these systems can influence the quality of product, the cost of business, the service to the customers, and thereby the profit of enterprises directly. Modern repairable systems tend to highly complex due to increase in complexity and automation of civil and military systems So far as the production operations are concerned, steady state availability analysis is essential, again on account of increased complexity and cost of present day equipment. Also the markets are getting globalize and more competitive. Penalties for delayed deliveries have increased. Sometimes the orders are cancelled and defaulting units are not favored with orders. To overcome these types of problems, steady state availability analysis is necessary for performance studies in the area of discrete manufacturing systems. Many researcher discussed steady state analysis of manufacturing plant by using different approaches. Law 23 used simulation modeling ,Dallery and Gershwin 24 discussed Markov chain models, Buzacott and Yao 25 , Buzacott and Yao 26 , Kouvelis and Tirupati 27 used queues and queuing network models , Viswanadham and Narahari 28 ,Al-Jaar and Desrochers 29 used stochastic Petri net models, Tewari,Kumar ,Kajal and Khanduja 16 used markov models for steady state analysis of manufacturing plant. Steady-state analysis deals mainly with customer average measures or time average measures. Performance measures such as steady-state waiting time belong to the first category whereas measures such as steady-state number of jobs in system are time average measures. Major results in queueing theory, such as Burke's result 30 , Little's law 31 , Jackson's theorem 35 , product form of closed queueing networks 32 , the BCMP formulation 33 , and the arrival theorem 34 are all concerned with steady-state analysis. This paper also deals with the steady state analysis of manufacturing plant namely Tab manufacturing. Which mainly consists of six subsystems working in series .Two subsystems namely Grinding machine, Electroplating machine are supported by stand-by units with perfect switch over devices and the remaining four subsystem are prone to failure. The mathematical modeling is done by using Markov birth – death Process and differential equations has been developed on the basis of probabilistic approach using transition diagram and solved for steady state. In this paper a decision support system is also developed which helps in determining the optimal maintenance strategy, which will ensure the maximum availability of the Tab manufacturing plant.Journal of Mechanical Engineering. 01/2010; 41(1). - [Show abstract] [Hide abstract]

**ABSTRACT:**Purpose: The purpose of paper is to compute reliability of a Pharmaceutical plant .A Pharmaceutical plant consists of nine sub-systems working in series. One subsystem namely Rotary Compression Machine is supported by stand-by units having perfect switch over devices and remaining eight subsystems are subjected to major failure only. Methodology/approach-The mathematical model of Pharmaceutical plant has been developed using Markov birth – death Process. Equations are solved with the help of matlab-program. Findings-The study of analysis of reliability can help in increasing the quality and production of Pharmaceutical plant. To ensure the system performance throughout its service life, it is necessary to set up proper maintenance planning and control which can be done after studying the variation of reliability with respect to time. Originality/value-Industrial implications of the results have been discussed.International Journal of Electronic Engineering Research. 01/2009;

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