Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets

Jin, Qun; Sugasawa, Yoshio

doi:10.1016/0895-7177(95)00187-7

Cited by 8 publications

(6 citation statements)

References 6 publications

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“…As a bipartite directed graph, Petri nets help to represent the structure of the system precisely. This graphical representation provides an inherently visual model to represent and understand the behavior of complex systems easily (Jin and Sugawa, 1995).…”

Section: Modeling Techniques For Reliability Evaluationmentioning

confidence: 99%

Reliability analysis of pulping system using Petri nets

Sachdeva

Kumar²,

Kumar³

2008

International Journal of Quality &Amp; Reliability Management

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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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Section: Modeling Techniques For Reliability Evaluationmentioning

confidence: 99%

Reliability analysis of pulping system using Petri nets

Sachdeva

Kumar²,

Kumar³

2008

International Journal of Quality &Amp; Reliability Management

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“…} } (19) According to (16) and (19), the fuzzy z L -transform of the discrete-state discrete-time fuzzy stochastic process  ( ) G k can be written as: The dynamic fuzzy availability of the entire DTRMSS for the fuzzy consumer demand ω  at time ( ) 0,1, k k =  is defined as:…”

Section: Fuzzy Dynamic Availability Assessment For Dtrmssmentioning

confidence: 99%

“…Some of them are Monte Carlo simulation [41,42], stochastic Petri nets [19,21], universal generating function [24,32], Markov models [6,37] and the combinations of the above methods [9]. However, conventional availability analysis methods for repairable multi-state systems are based on the continuous time models.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy Availability Assessment for Discrete Time Multi-State System under Minor Failures and Repairs by Using Fuzzy Lz-transform.

Zhang

et al. 2017

EiN

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Article citation info:on a continuous scale. In such situations, the lifetimes and repair times can be expressed in terms of the number of working and repairing periods (cycles), respectively. Thus, it is essential to construct discrete time reliability models for repairable multi-state systems.The discrete time reliability has drawn continuous attention in both model analysis and problem solution. Bracquemond and Gaudoin [5] presented a good overview of discrete probability distributions used in reliability for modeling discrete lifetimes of non-repairable systems. The discrete time reliability modeling for general binary systems can be found in [4,22,34]. Eryilmaz [14], Guerry [16] and Sadek and Limnios [35], presented the discrete time reliability models for Markov multi-state systems. The discrete time reliability models for semi-Markov multi-state systems were investigated in [1,4,10]. However, most of the reported works mainly focus on the issues of IntroductionThe availability, as a performance measure, is one of the most important indicators for characterizing a repairable system and its components. For repairable multi-state systems with various performance levels, the availability is more meaningful than reliability to measure the effectiveness of the system to satisfy consumer demand.In the past few years, a variety of methods are available in the literature for analyzing the availability of repairable multi-state systems. Some of them are Monte Carlo simulation [41,42], stochastic Petri nets [19,21], universal generating function [24,32], Markov models [6,37] and the combinations of the above methods [9]. However, conventional availability analysis methods for repairable multi-state systems are based on the continuous time models. In some engineering circumstances, it is sometimes impossible or inconvenient to measure the lifetimes and repair times length of some systems (components) HU L, SU P, PENG R, ZHANG Z. Fuzzy Availability Assessment for Discrete Time Multi-State System under Minor Failures and Repairs by Using Fuzzy L z -transform. Eksploatacja i Niezawodnosc - Maintenance and Reliability 2017; 19 (2): 179-190 discrete time systems with the exact reliability data. As stated in Garg [15], the complicated system has the massive fuzzy uncertainty due to which it is difficult to get the exact probability of the events. Thus, it is of large practical value to investigate the availability assessment for discrete time repairable system with fuzzy uncertainty. fuzzy discrete time Markov model with fuzzy transition probability matrix is proposed to analyze the fuzzy state probability of each component at any discrete time. The fuzzy L z -transform of the discrete-state discrete-time fuzzy Markov chain is developed to extend the L z -transform of the discrete-state continuous-time Markov model with crisp sets. Based on the α-cut approach and the fuzzy L z -transform, the dynamic fuzzy availability of the system is computed by using parametric programming technique. To illustrate the proposed method,...

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“…FTA and PN methodology are generally used for failure analysis of these systems (Singer, 1990;Soman and Misra, 1993;Jin and Sugawa, 1995;Adamayan and He, 2004). But both of the analyses need precise knowledge of components' functional dependencies of the system and probabilities of occurrence of basic events.…”

Section: Introductionmentioning

confidence: 99%

“…For failure analysis various methods available in literature are Reliability block diagrams (RBD's), Monte Carlo simulation (MCS), Markov modeling (MM), Failure mode effective analysis (FMEA), Root cause analysis (RCA), Fault tree analysis (FTA) and Petri‐nets (PN) etc. FTA and PN methodology are generally used for failure analysis of these systems (Singer, 1990; Soman and Misra, 1993; Jin and Sugawa, 1995; Adamayan and He, 2004). But both of the analyses need precise knowledge of components' functional dependencies of the system and probabilities of occurrence of basic events.…”

Section: Introductionmentioning

confidence: 99%

Stochastic behavior analysis of the forming unit in a paper mill using NGABLT technique

Komal

Sharma

Kumar

2010

Journal of Quality in Maintenance Engineering

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If you would like to write for this, or any other Emerald publication, then please use our Emerald for Authors service information about how to choose which publication to write for and submission guidelines are available for all. Please visit www.emeraldinsight.com/authors for more information. About Emerald www.emeraldinsight.comEmerald is a global publisher linking research and practice to the benefit of society. The company manages a portfolio of more than 290 journals and over 2,350 books and book series volumes, as well as providing an extensive range of online products and additional customer resources and services.Emerald is both COUNTER 4 and TRANSFER compliant. The organization is a partner of the Committee on Publication Ethics (COPE) and also works with Portico and the LOCKSS initiative for digital archive preservation. AbstractPurpose -The puprose of this paper is to analyse the stochastic behavior of an industrial system using a novel hybridized technique NGABLT. The forming unit of a paper mill situated in north India producing approximately 200 tons of paper per day has been considered for analysis. The authors have made efforts to incorporate vague, ambiguous, imprecise and conflicting information quantified by fuzzy numbers. Design/methodology/approach -Field data for repairable industrial systems are in the form of failures and repair rates are vague, ambiguous, qualitative and imprecise in nature. Using the data, system stochastic behavior in terms of six well-known reliability indices is analysed considering some desired degree of accuracy. A practical case of forming unit in a paper mill is considered to compute the reliability indices by using NGABLT technique. Sensitive of system behavior is analysed through surface plots by taking different combinations of reliability indices. The findings have been supplied to the nearby industry for future course of action in maintenance. Findings -The behavior analysis results computed by NGABLT technique have reduced region of prediction in comparison of existing Lambda-Tau technique region i.e. uncertainties involved in the analysis are reduced. It may be a more useful tool to assess the current system condition and to improve the system performance. Originality/value -The authors have suggested a hybridized technique for analyzing the stochastic behavior of the repairable industrial system by computing its reliability indices.

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Representation and analysis of behavior for multiprocess systems by using stochastic Petri nets

Cited by 8 publications

References 6 publications

Reliability analysis of pulping system using Petri nets

Reliability analysis of pulping system using Petri nets

Fuzzy Availability Assessment for Discrete Time Multi-State System under Minor Failures and Repairs by Using Fuzzy Lz-transform.

Stochastic behavior analysis of the forming unit in a paper mill using NGABLT technique

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