IDEAS home Printed from https://ideas.repec.org/a/spr/ijsaem/v12y2021i6d10.1007_s13198-021-01163-2.html
   My bibliography  Save this article

Availability and performance optimization of physical processing unit in sewage treatment plant using genetic algorithm and particle swarm optimization

Author

Listed:
  • Deepak Sinwar

    (Manipal University Jaipur)

  • Monika Saini

    (Manipal University Jaipur)

  • Dilbag Singh

    (Manipal University Jaipur)

  • Drishty Goyal

    (Manipal University Jaipur)

  • Ashish Kumar

    (Manipal University Jaipur)

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.

Suggested Citation

  • 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.
    • Handle: RePEc:spr:ijsaem:v:12:y:2021:i:6:d:10.1007_s13198-021-01163-2
    DOI: 10.1007/s13198-021-01163-2
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1007/s13198-021-01163-2
    File Function: Abstract
    Download Restriction: Access to the full text of the articles in this series is restricted.
    File URL: https://libkey.io/10.1007/s13198-021-01163-2?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
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Amit Kumar & Vinod Kumar & Vikas Modgil, 2018. "Performance optimisation for ethanol manufacturing system of distillery plant using particle swarm optimisation algorithm," International Journal of Intelligent Enterprise, Inderscience Enterprises Ltd, vol. 5(4), pages 345-364.
    2. V. N. Aju kumar & Piyush Gupta & O. P. Gandhi, 2019. "Maintenance performance evaluation using an integrated approach of graph theory, ISM and matrix method," 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. 10(1), pages 57-82, February.
    3. Shashank Gupta & Piyush Gupta & Aditya Parida, 2017. "Modeling lean maintenance metric using incidence matrix approach," 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. 8(4), pages 799-816, December.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Mousumi Banerjee & Vanita Garg & Kusum Deep, 2023. "Solving structural and reliability optimization problems using efficient mutation strategies embedded in sine cosine algorithm," 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. 14(1), pages 307-327, March.

    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. M. Suresh & G. Mahadevan & R. Dev Abhishek, 2019. "Modelling the factors influencing the service quality in supermarkets," 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. 10(6), pages 1474-1486, December.
    2. Subhash Malik & P. C. Tewari, 2023. "Performability and maintenance decisions for coal ash handling system of a subcritical thermal power plant," 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. 14(1), pages 45-54, February.
    3. Luo, Xu & Ge, Zhexue & Zhang, ShiGang & Yang, Yongmin, 2021. "A method for the maintainability evaluation at design stage using maintainability design attributes," Reliability Engineering and System Safety, Elsevier, vol. 210(C).

    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:spr:ijsaem:v:12:y:2021:i:6:d:10.1007_s13198-021-01163-2. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: http://www.springer.com .

    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.