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

M. Saini, Drishty Goyal, Ashish Kumar, R. Patil
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引用次数: 7

Abstract

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.
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基于遗传算法和粒子群优化的生化处理单元可用性优化
目的对污水处理厂的需求与日俱增,尤其是在印度等国家。此类污水处理厂的生物和化学装置至关重要,需要进行设计和开发,以达到所需的可靠性、可维护性和可用性水平。设计/方法/途径本文调查并优化了污水处理厂生物和化学装置的可用性。利用马尔可夫出生-死亡过程建立了该单元的新数学模型。推导了该模型的一组Chapman–Kolmogorov微分方程,并使用软计算技术,即遗传算法(GA)和粒子群优化(PSO),发现了广义解。利用Nature启发的优化技术,可用性函数的结果表明,PSO优于GA。生物和化学处理单元的可用性的最佳值为0.9324,对应于使用GA实现的种群大小100、进化次数300、突变0.6和交叉0.85,而PSO结果反映了45次迭代后实现的最佳可用性为0.936240。最后,PSO优于GA。研究局限性/含义本文调查并优化了污水处理厂生物和化学单元的可用性。利用马尔可夫出生-死亡过程建立了该单元的新数学模型。独创性/价值利用现场故障数据和从专家那里收集的判断,开发了污水处理的生物和化学单元的可用性模型。此外,系统的可用性已得到优化,以达到所需的可靠性和可维护性水平。
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来源期刊
CiteScore
5.60
自引率
12.00%
发文量
53
期刊介绍: In today''s competitive business and industrial environment, it is essential to have an academic journal offering the most current theoretical knowledge on quality and reliability to ensure that top management is fully conversant with new thinking, techniques and developments in the field. The International Journal of Quality & Reliability Management (IJQRM) deals with all aspects of business improvements and with all aspects of manufacturing and services, from the training of (senior) managers, to innovations in organising and processing to raise standards of product and service quality. It is this unique blend of theoretical knowledge and managerial relevance that makes IJQRM a valuable resource for managers striving for higher standards.Coverage includes: -Reliability, availability & maintenance -Gauging, calibration & measurement -Life cycle costing & sustainability -Reliability Management of Systems -Service Quality -Green Marketing -Product liability -Product testing techniques & systems -Quality function deployment -Reliability & quality education & training -Productivity improvement -Performance improvement -(Regulatory) standards for quality & Quality Awards -Statistical process control -System modelling -Teamwork -Quality data & datamining
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