IDEAS home Printed from https://ideas.repec.org/a/plo/pone00/0284848.html
   My bibliography  Save this article

Availability optimization of power generating units used in sewage treatment plants using metaheuristic techniques

Author

Listed:
  • Monika Saini
  • Ashish Kumar
  • Dinesh Kumar Saini
  • Punit Gupta

Abstract

Metaheuristic techniques have been utilized extensively to predict industrial systems’ optimum availability. This prediction phenomenon is known as the NP-hard problem. Though, most of the existing methods fail to attain the optimal solution due to several limitations like slow rate of convergence, weak computational speed, stuck in local optima, etc. Consequently, in the present study, an effort has been made to develop a novel mathematical model for power generating units assembled in sewage treatment plants. Markov birth-death process is adopted for model development and generation of Chapman-Kolmogorov differential-difference equations. The global solution is discovered using metaheuristic techniques, namely genetic algorithm and particle swarm optimization. All time-dependent random variables associated with failure rates are considered exponentially distributed, while repair rates follow the arbitrary distribution. The repair and switch devices are perfect and random variables are independent. The numerical results of system availability have been derived for different values of crossover, mutation, several generations, damping ratio, and population size to attain optimum value. The results were also shared with plant personnel. Statistical investigation of availability results justifies that particle swarm optimization outdoes genetic algorithm in predicting the availability of power-generating systems. In present study a Markov model is proposed and optimized for performance evaluation of sewage treatment plant. The developed model is one that can be useful for sewage treatment plant designers in establishing new plants and purposing maintenance policies. The same procedure of performance optimization can be adopted in other process industries too.

Suggested Citation

  • Monika Saini & Ashish Kumar & Dinesh Kumar Saini & Punit Gupta, 2023. "Availability optimization of power generating units used in sewage treatment plants using metaheuristic techniques," PLOS ONE, Public Library of Science, vol. 18(5), pages 1-22, May.
  • Handle: RePEc:plo:pone00:0284848
    DOI: 10.1371/journal.pone.0284848
    as

    Download full text from publisher

    File URL: https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0284848
    Download Restriction: no

    File URL: https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0284848&type=printable
    Download Restriction: no

    File URL: https://libkey.io/10.1371/journal.pone.0284848?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    References listed on IDEAS

    as
    1. Triet Pham & Hoang Pham, 2019. "A generalized software reliability model with stochastic fault-detection rate," Annals of Operations Research, Springer, vol. 277(1), pages 83-93, June.
    2. Nebojsa Bacanin & Catalin Stoean & Miodrag Zivkovic & Miomir Rakic & Roma Strulak-Wójcikiewicz & Ruxandra Stoean, 2023. "On the Benefits of Using Metaheuristics in the Hyperparameter Tuning of Deep Learning Models for Energy Load Forecasting," Energies, MDPI, vol. 16(3), pages 1-21, February.
    3. H. Wang & H. Pham, 1999. "Some maintenance models and availability withimperfect maintenance in production systems," Annals of Operations Research, Springer, vol. 91(0), pages 305-318, January.
    4. Bakhtiar Ostadi & Ramtin Hamedankhah, 2021. "A two-stage reliability optimization approach for solving series–parallel redundancy allocation problem considering the sale of worn-out parts," Annals of Operations Research, Springer, vol. 304(1), pages 381-396, September.
    5. Hoang Pham, 2016. "Reliability management and computing," Annals of Operations Research, Springer, vol. 244(1), pages 1-2, September.
    6. Deepak Sinwar & Monika Saini & Dilbag Singh & Drishty Goyal & Ashish Kumar, 2021. "Availability and performance optimization of physical processing unit in sewage treatment plant using genetic algorithm and particle swarm optimization," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 12(6), pages 1235-1246, December.
    7. Hoang Pham, 2006. "System Software Reliability," Springer Series in Reliability Engineering, Springer, number 978-1-84628-295-9, July.
    8. Da Hye Lee & In Hong Chang & Hoang Pham, 2020. "Software Reliability Model with Dependent Failures and SPRT," Mathematics, MDPI, vol. 8(8), pages 1-14, August.
    9. Ping-Chen Chang, 2019. "Reliability estimation for a stochastic production system with finite buffer storage by a simulation approach," Annals of Operations Research, Springer, vol. 277(1), pages 119-133, June.
    10. Yi-Kuei Lin & Thi-Phuong Nguyen & Louis Cheng-Lu Yeng, 2019. "Reliability evaluation of a multi-state air transportation network meeting multiple travel demands," Annals of Operations Research, Springer, vol. 277(1), pages 63-82, June.
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Da Hye Lee & In Hong Chang & Hoang Pham, 2020. "Software Reliability Model with Dependent Failures and SPRT," Mathematics, MDPI, vol. 8(8), pages 1-14, August.
    2. Dahye Lee & Inhong Chang & Hoang Pham, 2023. "Study of a New Software Reliability Growth Model under Uncertain Operating Environments and Dependent Failures," Mathematics, MDPI, vol. 11(18), pages 1-17, September.
    3. Hoang Pham, 2020. "On Estimating the Number of Deaths Related to Covid-19," Mathematics, MDPI, vol. 8(5), pages 1-9, April.
    4. Ping-Chen Chang, 2022. "Reliability evaluation and big data analytics architecture for a stochastic flow network with time attribute," Annals of Operations Research, Springer, vol. 311(1), pages 3-18, April.
    5. Qing Tian & Chun-Wu Yeh & Chih-Chiang Fang, 2022. "Bayesian Decision Making of an Imperfect Debugging Software Reliability Growth Model with Consideration of Debuggers’ Learning and Negligence Factors," Mathematics, MDPI, vol. 10(10), pages 1-21, May.
    6. Thi-Phuong Nguyen, 2021. "Assess the Impacts of Discount Policies on the Reliability of a Stochastic Air Transport Network," Mathematics, MDPI, vol. 9(9), pages 1-13, April.
    7. Liviu Adrian COTFAS & Andreea DIOSTEANU, 2010. "Software Reliability in Semantic Web Service Composition Applications," Informatica Economica, Academy of Economic Studies - Bucharest, Romania, vol. 14(4), pages 48-56.
    8. Aleksandr Kulikov & Pavel Ilyushin & Anton Loskutov & Konstantin Suslov & Sergey Filippov, 2022. "WSPRT Methods for Improving Power System Automation Devices in the Conditions of Distributed Generation Sources Operation," Energies, MDPI, vol. 15(22), pages 1-20, November.
    9. Kwang Yoon Song & In Hong Chang & Hoang Pham, 2019. "A Testing Coverage Model Based on NHPP Software Reliability Considering the Software Operating Environment and the Sensitivity Analysis," Mathematics, MDPI, vol. 7(5), pages 1-21, May.
    10. Levitin, Gregory & Finkelstein, Maxim & Dai, Yuanshun, 2018. "Optimizing availability of heterogeneous standby systems exposed to shocks," Reliability Engineering and System Safety, Elsevier, vol. 170(C), pages 137-145.
    11. Thi-Phuong Nguyen, 2022. "Evaluation of network reliability for stochastic-flow air transportation network considering discounted fares from airlines," Annals of Operations Research, Springer, vol. 311(1), pages 335-355, April.
    12. Cheng-Fu Huang & Ding-Hsiang Huang & Yi-Kuei Lin, 2022. "System reliability analysis for a cloud-based network under edge server capacity and budget constraints," Annals of Operations Research, Springer, vol. 312(1), pages 217-234, May.
    13. Lin, Zu-Liang & Huang, Yeu-Shiang & Fang, Chih-Chiang, 2015. "Non-periodic preventive maintenance with reliability thresholds for complex repairable systems," Reliability Engineering and System Safety, Elsevier, vol. 136(C), pages 145-156.
    14. Faraz Qasim & Doug Hyung Lee & Jongkuk Won & Jin-Kuk Ha & Sang Jin Park, 2021. "Development of Advanced Advisory System for Anomalies (AAA) to Predict and Detect the Abnormal Operation in Fired Heaters for Real Time Process Safety and Optimization," Energies, MDPI, vol. 14(21), pages 1-24, November.
    15. Ahmadi, Reza & Newby, Martin, 2011. "Maintenance scheduling of a manufacturing system subject to deterioration," Reliability Engineering and System Safety, Elsevier, vol. 96(10), pages 1411-1420.
    16. Yi-Kuei Lin & Lance Fiondella & Ping-Chen Chang, 2022. "Reliability of time-constrained multi-state network susceptible to correlated component faults," Annals of Operations Research, Springer, vol. 311(1), pages 239-254, April.
    17. Subhashis Chatterjee & Shobhit Nigam & Jeetendra Bahadur Singh & Lakshmi Narayan Upadhyaya, 2012. "Effect of change point and imperfect debugging in software reliability and its optimal release policy," Mathematical and Computer Modelling of Dynamical Systems, Taylor & Francis Journals, vol. 18(5), pages 539-551, March.
    18. Yunpeng Bai & Xiangke Zhang & Yajing Wang & Lei Wang & Qinqin Wei & Wenlei Zhao, 2024. "Residual current detection method based on improved VMD-BPNN," PLOS ONE, Public Library of Science, vol. 19(2), pages 1-22, February.
    19. Sangeeta & Kapil Sharma & Manju Bala, 2020. "An ecological space based hybrid swarm-evolutionary algorithm for software reliability model parameter estimation," International Journal of System Assurance Engineering and Management, Springer;The Society for Reliability, Engineering Quality and Operations Management (SREQOM),India, and Division of Operation and Maintenance, Lulea University of Technology, Sweden, vol. 11(1), pages 77-92, February.
    20. Wang, Jinyong & Wu, Zhibo, 2016. "Study of the nonlinear imperfect software debugging model," Reliability Engineering and System Safety, Elsevier, vol. 153(C), pages 180-192.

    More about this item

    Statistics

    Access and download statistics

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:plo:pone00:0284848. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: plosone (email available below). General contact details of provider: https://journals.plos.org/plosone/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.