Availability and performance optimization of urea decomposition system using genetic algorithm and particle swarm optimization

Saini, Monika; Raghav, Yashpal Singh; Kumar, Ashish; Chandnani, Divya

doi:10.1007/s41872-021-00167-y

Cited by 8 publications

(6 citation statements)

References 23 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…(2020), Sinwar et al. (2021) and Saini et al. (2021) provided guidelines to clearly define a certain set of assumptions that were made to develop the proposed model.…”

Section: Methodsmentioning

confidence: 99%

“…Nevertheless, literature studies (Sinwar et al. , 2021; Saini et al. , 2021) reveal that very little attention is given to PSO in sewage treatment plants and their subsystems availability analysis.…”

Section: Optimization Of Availability Of Biological and Chemical Proc...mentioning

confidence: 99%

“…The suitable assumptions are made based on the availability of information, data collected from the field (time between failure and time to repair) and discussion with the experts. The studies presented in the literature review, especially Jagtap et al (2020), Sinwar et al (2021) and Saini et al (2021) provided guidelines to clearly define a certain set of assumptions that were made to develop the proposed model. The assumptions are also justified that the proposed assumptions are relevant to present real-world process industries.…”

Section: System Descriptionmentioning

confidence: 99%

“…It gives an advantage to PSO over other metaheuristic approaches. Nevertheless, literature studies (Sinwar et al, 2021;Saini et al, 2021) reveal that very little attention is given to PSO in sewage treatment plants and their subsystems availability analysis. Hence, the present study strives to accomplish the recognized research gap and the PSO method is applied to biological and chemical processing units.…”

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

See 3 more Smart Citations

Availability optimization of biological and chemical processing unit using genetic algorithm and particle swarm optimization

Saini

Goyal

Kumar

et al. 2022

IJQRM

Self Cite

View full text Add to dashboard Cite

PurposeThe demand of sewage treatment plants is increasing day by day, especially in the countries like India. Biological and chemical unit of such sewage treatment plants are critical and needs to be designed and developed to achieve desired level of reliability, maintainability and availability.Design/methodology/approachThis paper investigates and optimizes the availability of biological and chemical unit of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process. A set of Chapman–Kolmogorov differential equations are derived for the model and a generalized solution is discovered using soft computing techniques namely genetic algorithm (GA) and particle swarm optimization (PSO).FindingsNature-inspired optimization techniques results of availability function depicted that PSO outperforms GA. The optimum value of the availability of biological and chemical processing unit is 0.9324 corresponding to population size 100, the number of evolutions 300, mutation 0.6 and crossover 0.85 achieved using GA while PSO results reflect that optimum achieved availability is 0.936240 after 45 iterations. Finally, it is revealed that PSO outperforms than GA.Research limitations/implicationsThis paper investigates and optimizes the availability of biological and chemical units of a sewage treatment plant. A novel mathematical model for this unit is developed using the Markovian birth-death process.Originality/valueAvailability model of biological and chemical units of a sewage treatment is developed using field failure data and judgments collected from the experts. Furthermore, availability of the system has been optimized to achieve desired level of reliability and maintainability.

show abstract

“…(2020), Sinwar et al. (2021) and Saini et al. (2021) provided guidelines to clearly define a certain set of assumptions that were made to develop the proposed model.…”

Section: Methodsmentioning

confidence: 99%

Section: Optimization Of Availability Of Biological and Chemical Proc...mentioning

confidence: 99%

Section: System Descriptionmentioning

confidence: 99%

Section: Particle Swarm Optimization (Pso)mentioning

confidence: 99%

See 2 more Smart Citations

Availability optimization of biological and chemical processing unit using genetic algorithm and particle swarm optimization

Saini

Goyal

Kumar

et al. 2022

IJQRM

Self Cite

View full text Add to dashboard Cite

show abstract

“…A stochastic model is developed by using the concept of redundancy. Saini et al (2021Saini et al ( , 2022 applied genetic algorithm and particle swarm Optimization of load haul dump machines optimization for performance optimization of urea manufacturing and biological and chemical processing units of sewage treatment plants. Gupta et al (2021) investigated reliability measures like reliability and maintainability of generators in steam turbine power plant through simple probabilistic concepts.…”

Section: Introductionmentioning

confidence: 99%

Reliability and maintainability optimization of load haul dump machines using genetic algorithm and particle swarm optimization

Saini

Sinwar

Swarith

et al. 2022

JQME

Self Cite

View full text Add to dashboard Cite

PurposeReliability and maintainability estimation of any system depends on the identification of the best-fitted probability distribution of failure and repair rates. The parameters of the best-fitted probability distribution are also contributing significantly to reliability estimation. In this work, a case study of load haul dump (LHD) machines is illustrated that consider the optimization of failure and repair rate parameters using two well established metaheuristic approaches, namely, genetic algorithm (GA) and particle swarm optimization (PSO). This paper aims to analyze the aforementioned points.Design/methodology/approachThe data on time between failures (TBF) and time to repairs (TTR) are collected for a LHD machine. The descriptive statistical analysis of TBF & TTR data is performed, trend and serial correlation tested and using Anderson–Darling (AD) value best-fitted distributions are identified for repair and failure times of various subsystems. The traditional methods of estimation like maximum likelihood estimation, method of moments, least-square estimation method help only in finding the local solution. Here, for finding the global solution two well-known metaheuristic approaches are applied.FindingsThe reliability of the LHD machine after 60 days on the real data set is 28.55%, using GA on 250 generations is 17.64%, and using PSO on 100 generations and 100 iterations is 30.25%. The PSO technique gives the global best value of reliability.Practical implicationsThe present work will be very convenient for reliability engineers, researchers and maintenance managers to understand the failure and repair pattern of LHD machines. The same methodology can be applied in other process industries also.Originality/valueIn this case study, initially likelihood function of the best-fitted distribution is optimized by GA and PSO. Reliability and maintainability of LHD machines evaluated by the traditional approach, GA and PSO are compared. These results will be very helpful for maintenance engineers to plan new maintenance strategies for better functioning of LHD machines.

show abstract

Contribution of Refreshment Provided to the Server During His Job in the Repairable Cold Standby System

Barak¹,

Kumar²,

Garg³

2023

Computational Intelligence in Sustainable Reliability Engineering

View full text Add to dashboard Cite

Availability and performance optimization of urea decomposition system using genetic algorithm and particle swarm optimization

Cited by 8 publications

References 23 publications

Availability optimization of biological and chemical processing unit using genetic algorithm and particle swarm optimization

Availability optimization of biological and chemical processing unit using genetic algorithm and particle swarm optimization

Reliability and maintainability optimization of load haul dump machines using genetic algorithm and particle swarm optimization

Contribution of Refreshment Provided to the Server During His Job in the Repairable Cold Standby System

Contact Info

Product

Resources

About