Numerical analysis of reliability and availability of the serial processes in butter‐oil processing plant

Gupta, Pawan; Lal, A. K.; Sharma, Rajendra K.; Singh, Jagdev

doi:10.1108/02656710510582507

Cited by 71 publications

(34 citation statements)

References 10 publications

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“…The transition t 7 corresponds to the repair complet ion of the partial failed subsystem 0, whereas t 8 corresponds to the complete failu re of co mponent 0. If the transition t 7 fires then it removes a token each fro m the places P 6 and P 17 and deposits a token each in the places P 0 and P 19 . This means that the component 0 is repaired and the system starts working normally.…”

Section: Gspn Specificationmentioning

confidence: 99%

“…Tokens in the places P 0 and P 19 may enable the transition t 0 , which corresponds to the partial failure of the subsystem 0. If the transition t 0 is fired, then it removes a token each fro m p laces P 0 and P 19 and deposits a token each in the p laces P 6 and P 17 . The token in the place P 6 indicates the component 0 is in the partial failure mode and the one in the place P 17 indicates the system is in partial failed state.…”

Section: Gspn Specificationmentioning

confidence: 99%

“…The availability analysis of the core veneer manufacturing system in a plywood manufacturing system was performed by [16]. Reference [17] evaluated reliab ility parameters of a butter manufacturing system in a diary p lant considering constant failure rates of various components. Semi-Markov processes and regenerative point technique are used to analyze three-unit standby system of water pu mps in which two units are operative simu ltaneously and the third one is cold standby for an ash handling plant.…”

Section: Literature Reviewmentioning

confidence: 99%

See 2 more Smart Citations

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

Thangamani¹

2012

AJCAM

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A very high level of availab ility is crucial to the economic operation of modern power plants, in view of the huge expenditure associated with their failures. Th is paper deals with the availab ility analysis of a Lube oil system used in a combined cycle power plant. The system is modeled as a Generalized Stochastic Petri Net (GSPN) taking into consideration of partial failures of their subsystems and common-cause failures; analyzed using Monte Carlo Simu lation approach. The major benefit of GSPN approach is hardware, software and human behavior can be modeled using the same language and hence more suitable to model co mplex system like power p lants. The superiority of this approach over others such as network, fault tree and Markov analysis are outlined. The numerical estimates of availability, failure criticality index o f various subsystems, co mponents causing unavailability of lube oil system are brought out. The proposed GSPN is a pro mising tool that can be conveniently used to model and analyze any co mple x systems.

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Section: Gspn Specificationmentioning

confidence: 99%

Section: Gspn Specificationmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

See 1 more Smart Citation

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

Thangamani¹

2012

AJCAM

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“…They also discussed the behavioral analysis of refining system using GA. Coit et al (2004) proposed a multiple objective formulation for maximizing the system availability. Gupta et al (2005) discussed the reliability parameters of butter making system of dairy plant taking exponentially distributer failure and repair rates of various subsystems. Kumar et al (2007) evaluated the availability of CO2 cooling system of a fertilizer plant using markovian approach.…”

Section: Introductionmentioning

confidence: 99%

Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization

Kumar¹,

Tewari²

2017

10.5267/j.ijiec

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The paper deals with the performance analysis and optimization for Carbonated Soft Drink Glass Bottle (CSDGB) filling system of a beverage plant using Particle Swarm Optimization (PSO) approach. The CSDGB system consists of seven main subsystems arranged in series namely Uncaser, Bottle Washer, Electronic Inspection Station, Filling Machine, Crowner, Coding Machine and Case Packer. Considering exponential distribution for probable failures and repairs, mathematical modeling is performed using Markov Approach (MA). The differential equations have been derived on the basis of probabilistic approach using transition diagram. These equations are solved using normalizing condition and recursive method to drive out the steady state availability expression of the system i.e. system's performance criterion. The performance optimization of system has been carried out by varying the number of particles and number of generations. It has been observed that the maximum availability of 90.27% is achieved at flock size of 55 and 90.84% at 300 th generation. Thus, findings of the paper will be useful to the plant management for execution of proper maintenance decisions.

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“…Kumar and Tewari [15] have modelled the CO 2 cooling system of a fertilizer plant by Markov birth-death process and then optimized the system performance by genetic algorithm. Gupta et al [16] have dealt with the system reliability and availability in butter oil processing plant by using Markov process and Runge-kutta method. Kumar et al [17] have proposed a method based on Markov approach to evaluate an availability simulation model in a thermal power plant.…”

Section: Introductionmentioning

confidence: 99%

Application of Markov Process in Performance Analysis of Feeding System of Sugar Industry

Sharma

Vishwakarma

2014

Journal of Industrial Mathematics

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To analyse the performance measures of complex repairable systems having more than two states, that is, working, reduced and failed, it is essential to model suitably their states so that the system governs a stochastic process. In this paper, the application of time-homogeneous Markov process is used to express reliability and availability of feeding system of sugar industry involving reduced states and it is found to be a powerful method that is totally based on modelling and numerical analysis. The selection of appropriate units/components in designing a system with different characteristics is necessary for the system analyst to maintain the failure-free operation. Keeping this concept in this study, the steady state availability of concern system is analysed and optimized by using a popular search technique, genetic algorithm. The objective of this paper is to consider the system operative process as Markov process and find its reliability function and steady state availability in a very effective manner and also to obtain an optimal system designing constituents which will allow a failure-free operation for long time period as required for maximum system productivity. The system performance measures and optimized design parameters are described and obtained here by considering an illustrative example.

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Numerical analysis of reliability and availability of the serial processes in butter‐oil processing plant

Cited by 71 publications

References 10 publications

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

Generalized Stochastic Petri Nets for Reliability Analysis of Lube Oil System with Common-Cause Failures

Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization

Application of Markov Process in Performance Analysis of Feeding System of Sugar Industry

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