Performance optimisation for ethanol manufacturing system of distillery plant using particle swarm optimisation algorithm

Kumar, Amit; Kumar, Vinod; Modgil, Vikas

doi:10.1504/ijie.2018.095723

Cited by 7 publications

(4 citation statements)

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“…It has applications in analyzing time-based reliability and availability analysis. Okafor et al [3], Gupta and Tewari [4], Kumar and Modgil [5], Tomasz et al [6], Dahiya et al [7] and recently Gupta et al [2] have used Markov birth-death process technique to formulate the mathematical performance model of the system and evaluate its availability measures. However, a major limitation of this modeling tool is its state`s explosion even though it is applied to relatively small systems.…”

Section: Modeling Toolsmentioning

confidence: 99%

“…availability of such systems using non-traditional optimization techniques such as Teacher Learning Based Optimization (TLBO), Genetic Algorithm (GA), Particle Swarm Optimization (PSO), Ant Colony Algorithm, Immune Algorithm, Bumble Bees Mating Optimization algorithm and Biogeography Based Optimization (BBO) algorithm, etc. [5], [23] and [24]. These are robust and may give the best solution for complex systems.…”

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confidence: 99%

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Petri Nets Modelling and Analysis of the Veneer Layup System of Plywood Manufacturing Plant

Kumar

Tewari

Sachdeva

2020

IJEM

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In this paper performance behaviour is analysed in respect of the availability of the Veneer layup system of a plywood manufacturing plant. Generalized Stochastic Petri Nets (GSPN) technique is applied for modelling interactions among various components as well as the subsystems. The effects of the failure and repair rates, as well as availability of repair facilities on the behaviour of the system is investigated using a licensed software package. The outcomes will provide guidelines for the effective maintenance priorities to the practitioners and help in selecting appropriate maintenance strategies.

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Section: Modeling Toolsmentioning

confidence: 99%

mentioning

confidence: 99%

Petri Nets Modelling and Analysis of the Veneer Layup System of Plywood Manufacturing Plant

Kumar

Tewari

Sachdeva

2020

IJEM

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“…It can not only be used in cases where the components are independent but also for systems involving dependent failure and repair modes. Gupta and Tewari [3], Okafor et al [4], Kumar et al [5], Dahiya et al [6] and recently Gupta et al [7] used a Markov birth-death process technique to formulate the mathematical performance model and evaluate system availability measures. However, Markov models are too complex and challenging to analyze for systems with a more significant number of states and subsystems.…”

Section: Modeling Toolsmentioning

confidence: 99%

Performance assessment of milk processing system using Petri nets

2020

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The study presents the quantitative effect of the recorded failure and repair data on the performance of a liquid milk processing plant in terms of its availability and reduced capacity. Process modeling and behavioral analysis of the system has been carried out by dividing the system into four subsystems placed in series using Petri Nets approach. A licensed software package (named Petri module of GRIF) has been used for model formalism and its simulation. The results of this study are expected to be useful to the proprietors of the milk processing plant as well as for practitioners from other fields such as multiprocessor electronic systems, telecommunication systems and production systems among others who want to analyze, understand and predict the behavior of various types of equipments. Reliability, Availability, and Maintainability modeling tools described here can be of helpful to them in planning selective maintenance strategies for their systems.

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“…Kumar and Ram (2013) investigated the reliability and sensitivity analysis of a coal handling system of thermal power plant. Kumar et al (2018) selected the ethanol manufacturing plant to demonstrate the application of PSO algorithm for performance optimization whereas Kumar and Tewari (2017) used the PSO technique to optimize the availability of various sub-systems in a beverage plant. Raju et al (2018) used a hybrid PSO-BFO algorithm for the optimization of FDM process parameters in order to improve the mechanical and surface quality of complex objects manufactured through the 3D printer.…”

Section: Bfo-pso Algorithmmentioning

confidence: 99%

Performance modeling and optimization for complex repairable system of paint manufacturing unit using a hybrid BFO-PSO algorithm

Kumar¹,

Kumar

Modgil

2019

IJQRM

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Purpose The purpose of this paper is to optimize the performance for complex repairable system of paint manufacturing unit using a new hybrid bacterial foraging and particle swarm optimization (BFO-PSO) evolutionary algorithm. For this, a performance model is developed with an objective to analyze the system availability. Design/methodology/approach In this paper, a Markov process-based performance model is put forward for system availability estimation. The differential equations associated with the performance model are developed assuming that the failure and repair rate parameters of each sub-system are constant and follow the exponential distribution. The long-run availability expression for the system has been derived using normalizing condition. This mathematical framework is utilized for developing an optimization model in MATLAB 15 and solved through BFO-PSO and basic particle swarm optimization (PSO) evolutionary algorithms coded in the light of applicability. In this analysis, the optimal input parameters are determined for better system performance. Findings In the present study, the sensitivity analysis for various sub-systems is carried out in a more consistent manner in terms of the effect on system availability. The optimal failure and repair rate parameters are obtained by solving the performance optimization model through the proposed hybrid BFO-PSO algorithm and hence improved system availability. Further, the results obtained through the proposed evolutionary algorithm are compared with the PSO findings in order to verify the solution. It can be clearly observed from the obtained results that the hybrid BFO-PSO algorithm modifies the solution more precisely and consistently. Research limitations/implications There is no limitation for implementation of proposed methodology in complex systems, and it can, therefore, be used to analyze the behavior of the other repairable systems in higher sensitivity zone. Originality/value The performance model of the paint manufacturing system is formulated by utilizing the available uncertain data of the used manufacturing unit. Using these data information, which affects the performance of the system are parameterized in the input failure and repair rate parameters for each sub-system. Further, these parameters are varied to find the sensitivity of a sub-system for system availability among the various sub-systems in order to predict the repair priorities for different sub-systems. The findings of the present study show their correspondence with the system experience and highlight the various availability measures for the system analyst in maintenance planning.

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Performance optimisation for ethanol manufacturing system of distillery plant using particle swarm optimisation algorithm

Cited by 7 publications

References 0 publications

Petri Nets Modelling and Analysis of the Veneer Layup System of Plywood Manufacturing Plant

Petri Nets Modelling and Analysis of the Veneer Layup System of Plywood Manufacturing Plant

Performance assessment of milk processing system using Petri nets

Performance modeling and optimization for complex repairable system of paint manufacturing unit using a hybrid BFO-PSO algorithm

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