Incorporates: International Journal of Quality Science
Online from: 1984
Subject Area: Managing Quality
|Title:||Reliability analysis of pulping system using Petri nets|
|Author(s):||Anish Sachdeva, (Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India), Dinesh Kumar, (Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India), Pradeep Kumar, (Department of Mechanical and Industrial Engineering, Indian Institute of Technology, Roorkee, India)|
|Citation:||Anish Sachdeva, Dinesh Kumar, Pradeep Kumar, (2008) "Reliability analysis of pulping system using Petri nets", International Journal of Quality & Reliability Management, Vol. 25 Iss: 8, pp.860 - 877|
|Keywords:||Maintenance, Performance management, Reliability management|
|Article type:||Research paper|
|DOI:||10.1108/02656710810898667 (Permanent URL)|
|Publisher:||Emerald Group Publishing Limited|
Purpose – This paper aims to propose a methodology based on Petri nets to evaluate the reliability characteristics of the pulping system of a paper industry in a realistic working environment. The effects of occurrence of failure/course of actions and availability of repair facilities on system performance have been investigated.
Design/methodology/approach – Stochastic Reward Nets (SRN), an extension of Petri nets, are applied to model the interactions among the active/standby units of the system and reliability parameters have been evaluated using Monte Carlo simulation.
Findings – The methodology adopted in this paper provides a better understanding of the behavior of the system under varying operating conditions. Reliability analysis of a pulping system of a paper industry presented in this paper will help the management in deciding upon the maintenance strategy to be adopted to improve the performance of the system and consequently reduce the operation and maintenance cost.
Originality/value – The application of the proposed technique will not only help the reliability engineers/managers/system engineers to understand the dynamic behavior of complex systems but also helps to plan/adapt suitable maintenance policies to improve system reliability/availability.
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