Abstract
Predicting the optimum availability of the physical processing unit of sewage treatment plant is defined as a Nondeterministic Polynomial time-hard problem. Recently many researchers have utilized soft computing techniques to handle this issue. However, the existing techniques are far from the optimal solutions as soft computing techniques suffer from various issues such as, poor computational speed, getting stuck in local optima, pre-mature convergence, etc. Therefore, in this work a novel mathematical model is designed and implemented using Markov process and Chapman-Kolmogorov equations derived by assuming arbitrary repair rates and exponentially distributed failure rates. Thereafter, Genetic Algorithm and Particle Swarm Optimization techniques are utilized to optimize the availability and performance of physical processing unit. The needed data has been collected with the help of plant personnel and results are also shared with them. Experimental results reveal that the Particle Swarm Optimization based proposed model outperforms the competitive techniques.
Similar content being viewed by others
Abbreviations
- \(X,Y,Z,Z_{1} ,W,U\) :
-
All subsystems are working with full capacity
- \(W_{1}\) :
-
\(W_{1}\) Is working as cold standby
- \(\overline{Z}\) :
-
One main unit failed, and standby unit becomes operative
- G:
-
Good state
- \(x,y,z,w,w_{1} ,u\) :
-
Represent the failed state of the subsystems
- \(k_{i\,} \left( {1 \le i \le 6} \right)\) :
-
Respectively failure rates in subsystems \(X,Y,Z,Z_{1} ,W,U,W_{1}\)
- \(\upsilon_{i\,} (x)\left( {1 \le i \le 6} \right)\) :
-
Respectively repair rate in subsystems \(X,Y,Z,Z_{1} ,W,U,W_{1}\)
- \(\prod_{0} (t)\) :
-
Probability that system is working with full capacity
- \(\prod_{i} (x,t),(i = 1, \ldots ,19)\) :
-
Probability of subsystem on ith state at time t with repair time x
- \(S_{i} ,(i = 1,2, \ldots ,19)\) :
-
State of the subsystem
References
Abualigah L, & Diabat A (2021) Advances in sine cosine algorithm: a comprehensive survey. Artif Intell Rev, 1–42
Abualigah, L., & Dulaimi, A. J. (2021), A novel feature selection method for data mining tasks using hybrid sine cosine algorithm and genetic algorithm. Cluster Comput 1–16
Abualigah L, Diabat A, Mirjalili S, Abd Elaziz M, Gandomi AH (2021a) The arithmetic optimization algorithm. Comput Methods Appl Mech Eng 376:113609
Abualigah L, Yousri D, Abd Elaziz M, Ewees AA, Al-qaness MA, Gandomi AH (2021b) Aquila optimizer: a novel meta-heuristic optimization algorithm. Comput Ind Eng. https://doi.org/10.1016/j.cie.2021.107250
Aggarwal AK, Singh V, Kumar S (2014) Availability analysis and performance optimization of a butter oil production system: a case study. Int J Syst Assur Eng Manag 8:538–554
Aju Kumar VN, Gupta P, Gandhi OP (2019) Maintenance performance evaluation using an integrated approach of graph theory, ISM and matrix method. Int J Syst Assur Eng Manag 10(1):57–82
Bugajski P, Almeid MAA, Kurek K (2016) Reliability of sewage treatment plants processing sewage from school buildings located in non-urban areas. Infrastruktura i Ekologia Terenów Wiejskich
Choudhary D, Tripathi M, Shankar R (2019) Reliability, availability and maintainability analysis of a cement plant: a case study. Int J Qualit Reliab Manag. https://doi.org/10.1108/IJQRM-10-2017-0215
Engelbrecht AP (2007) Computational intelligence an introduction, second. Wiley
Garg H (2013) Performance analysis of complex repairable industrial systems using PSO and fuzzy confidence interval-based methodology. ISA Trans 52(2):171–183
Garg H, Rani M (2013) An approach for reliability analysis of industrial systems using PSO and IFS technique. ISA Trans 52(6):701–710
Goyal D, Kumar A, Saini M, Joshi H (2019) Reliability, maintainability and sensitivity analysis of physical processing unit of sewage treatment plant. SN Appl Sci 1:1507. https://doi.org/10.1007/s42452-019-1544-7
Gupta P, Gandhi OP (2014) Equipment redesign feasibility through maintenance-work-order records using fuzzy cognitive maps. Int J Syst Assur Eng Manag 5(1):21–31
Gupta S, Gupta P, Parida A (2017) Modeling lean maintenance metric using incidence matrix approach. Int J Syst Assur Eng Manag 8(4):799–816
John H (1992) Adaptation in natural and artificial systems. MIT Press, Cambridge, MA
KennedyJ and EberhartR (1995) Particle Swarm Optimization. In International Conference on Neural Networks, pp. 1942–1948
Khanduja R, Tewari PC, Chauhan RS (2011) Performance modeling and optimization for the stock preparation unit of a paper plant using genetic algorithm. Int J Qualit Reliab Manag 28(6):688–703
Kumar P, Tewari PC (2017) Performance analysis and optimization for CSDGB filling system of a beverage plant using particle swarm optimization. Int J Ind Eng Comput 8:303–314
Kumar A, Kumar V, Modgil V (2018) Performance optimisation for ethanol manufacturing system of distillery plant using particle swarm optimisation algorithm. Int J Int Enterprise 5(4):345–364
Kuma A, Kumar V, and Modgil V (2019) Behavioral analysis and availability optimization of complex repairable industrial system using particle swarm optimization. IOP Conf. Series: J Phys Conf. Series 1240, 012158, https://doi.org/10.1088/1742-6596/1240/1/012158
Lu J-Y, Wang X-M, Liu H-Q, Han-Qing Yu, Li W-W (2019) Optimizing operation of municipal wastewater treatment plants in China: the remaining barriers and future implications. Environ Int 129:273–278. https://doi.org/10.1016/j.envint.2019.05.057
Malik S and Tewari PC (2017) Performance modeling and maintenance priorities decision for water flow system of a coal based thermal power plant. IntJ Qualit Reliab Manag
Mishra S, Bhardwaj P, Bhadauria N (2016) Optimal availability analysis of brake drum manufacturing system by using Markov approach. Int J Eng Technol Manag Appl Sci 4:147–154
Niwas R, Garg H (2018) An approach for analyzing the reliability and profit of an industrial system based on the cost-free warranty policy. J Braz Soc Mech Sci Eng. https://doi.org/10.1007/s4043
Pandey P, Mukhopadhyay AK, Chattopadhyaya S (2018) Reliability analysis and failure rate evaluation for critical subsystems of the dragline. J Braz Soc Mech Sci Eng. https://doi.org/10.1007/s4043
Pant S, Anand D, Kishor A, Singh SB (2015) A particle swarm algorithm for optimization of complex system reliability. Int J Perform Eng 11(1):33–42
Pawar A, Chikalthankar SB (2017) Failure mode effect analysis of rollers in mill stand. J Innov Res Sci Eng Technol 6(1):457–463
Piri J, Pirzadeh B, Keshtegar B, Givehchi M (2021) Reliability analysis of pumping station for sewage network using hybrid neural networks-genetic algorithm and method of moment. Process Saf Environ Protect 145:39–51
Rabbani M, Mohammadi S, Mobini M (2018) Optimum design of a CCHP system based on economical, energy and environmental considerations using GA and PSO. Int J Ind Eng Comput 9(1):99–122
Ram M, Kumar A (2015) Performability analysis of a system under 1-out-of-2: G scheme with perfect reworking. J Braz Soc Mech Sci Eng 37:1029. https://doi.org/10.1007/s40430-014-0227-y
Rezaee MJ, Yousefi S, Babaei M (2017) Multi-stage cognitive map for failures assessment of production processes: an extension in structure and algorithm. Euro Comput 232:69–82
Rezaee JM, Yousefi S, Valipour M, Dehdar MM (2018) Risk analysis of sequential processes in food industry integrating multi-stage fuzzy cognitive map and process failure mode and effects analysis. Comput Ind Eng 123:325–337
Richter B, Bokelmann W (2016) Approaches to the German food industry for addressing the issue of food losses. Waste Manag 48:423–429
Saini M, Kumar A (2019) Performance analysis of evaporation system in sugar industry using RAMD analysis. J Braz Soc Mech Sci Eng 41:4
Selim H, Yunusoglu MG, Yılmaz Balaman Ş (2015) A Dynamic maintenance planning framework based on fuzzy TOPSIS and FMEA: application in an international food company. Qualit Reliab Eng Int 32(3):795–804
Sinha RS, Mukhopadhyay AK (2016) Failure analysis of jaw crusher and its components using ANOVA. J Braz Soc Mech Sci Eng 38(2):665–678
Sun J, Dai X, Wang Q, van Loosdrecht MC, Ni BJ (2019) Microplastics in wastewater treatment plants: detection, occurrence and removal. Water Res 152:21–37
Veldkamp T, Wada Y, Aerts J et al (2017) Water scarcity hotspots travel downstream due to human interventions in the 20th and 21st century. Nat Commun 8:15697. https://doi.org/10.1038/ncomms15697
Zhang QH, Yang WN, Ngo HH, Guo WS, Jin PK, Dzakpasu M, Yang SJ, Wang Q, Wang XC, Ao D (2016) Current status of urban wastewater treatment plants in China. Environ Int 92–93:11–22. https://doi.org/10.1016/j.envint.2016.03.024
Zhang J, Li N, Dai X, Tao W, Jenkinson IR, Li Z (2018) Enhanced dewaterability ofsludge during anaerobic digestion with thermal hydrolysis pretreatment: new insights through structure evolution. Water Res 131:177–185. https://doi.org/10.1016/j.watres.2017.12.042
Author information
Authors and Affiliations
Corresponding author
Additional information
Publisher's Note
Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Rights and permissions
About this article
Cite this article
Sinwar, D., Saini, M., Singh, D. et al. Availability and performance optimization of physical processing unit in sewage treatment plant using genetic algorithm and particle swarm optimization. Int J Syst Assur Eng Manag 12, 1235–1246 (2021). https://doi.org/10.1007/s13198-021-01163-2
Received:
Revised:
Accepted:
Published:
Issue Date:
DOI: https://doi.org/10.1007/s13198-021-01163-2