IDEAS home Printed from https://ideas.repec.org/a/gam/jjrfmx/v14y2021i4p173-d533520.html
   My bibliography  Save this article

A Sustainable Economic Recycle Quantity Model for Imperfect Production System with Shortages

Author

Listed:
  • Ali AlArjani

    (Department of Mechanical and Industrial Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 16278, Saudi Arabia)

  • Md. Maniruzzaman Miah

    (Department of Mathematics, Jahangirnagar University, Saver, Dhaka 1342, Bangladesh)

  • Md. Sharif Uddin

    (Department of Mechanical and Industrial Engineering, Prince Sattam Bin Abdulaziz University, Al-Kharj 16278, Saudi Arabia)

  • Abu Hashan Md. Mashud

    (Department of Mathematics, Hajee Mohammad Danesh Science and Technology University, Dinajpur 5200, Bangladesh)

  • Hui-Ming Wee

    (Industrial and Systems Engineering Department, Chung Yuan Christian University, No. 200, Chung Pei Road, Chungli, Taoyuan City 32023, Taiwan)

  • Shib Sankar Sana

    (Kishore Bharati Bhagini Nivedita College, Ramkrishna Sarani, Behala, Kolkata 700060, India)

  • Hari Mohan Srivastava

    (Department of Mathematics and Statistics, University of Victoria, Victoria, BC V8W 3R4, Canada
    Department of Medical Research, China Medical University Hospital, China Medical University, Taichung 40402, Taiwan
    Department of Mathematics and Informatics, Azerbaijan University, 71 Jeyhun Hajibeyli Street, AZ1007 Baku, Azerbaijan
    Section of Mathematics, International Telematic University Uninettuno, I-00186 Rome, Italy)

Abstract

Recycling of products has a great impact on contemporary sustainable business strategies. In this study, a sustainable recycling process in a production-inventory model for an imperfect production system with a fixed ratio of recyclable defective products is introduced. The piecewise constant demand rates of the non-defective items are considered under production run-time, production off-time with positive stock, and production off-time with shortages under varying conditions. Based on the production process, two cases are studied using this model. The first case does not consider recycling processes, while the second case picks up all defective items before sending these items to recycling during the production off-time; the recycled items are added to the main inventory. The aim of this study is to minimize the total cost and identify the optimal order quantity. The manufacturing process with the recycling process provides a better result compared to without recycling in the first case. Some theoretical derivations are developed to enunciate the objective function using the classical optimization technique. To validate the proposed study, sensitivity analysis is performed, and numerical examples are given. Finally, some managerial insights and the scope of future research are provided.

Suggested Citation

  • Ali AlArjani & Md. Maniruzzaman Miah & Md. Sharif Uddin & Abu Hashan Md. Mashud & Hui-Ming Wee & Shib Sankar Sana & Hari Mohan Srivastava, 2021. "A Sustainable Economic Recycle Quantity Model for Imperfect Production System with Shortages," JRFM, MDPI, vol. 14(4), pages 1-21, April.
  • Handle: RePEc:gam:jjrfmx:v:14:y:2021:i:4:p:173-:d:533520
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1911-8074/14/4/173/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1911-8074/14/4/173/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Al-Salamah, Muhammad, 2019. "Economic production quantity in an imperfect manufacturing process with synchronous and asynchronous flexible rework rates," Operations Research Perspectives, Elsevier, vol. 6(C).
    2. Cristina Raluca Gh. Popescu & Gheorghe N. Popescu, 2019. "An Exploratory Study Based on a Questionnaire Concerning Green and Sustainable Finance, Corporate Social Responsibility, and Performance: Evidence from the Romanian Business Environment," JRFM, MDPI, vol. 12(4), pages 1-79, October.
    3. Salameh, M. K. & Jaber, M. Y., 2000. "Economic production quantity model for items with imperfect quality," International Journal of Production Economics, Elsevier, vol. 64(1-3), pages 59-64, March.
    4. Lie-Fern Hsu & Jia-Tzer Hsu, 2016. "Economic production quantity (EPQ) models under an imperfect production process with shortages backordered," International Journal of Systems Science, Taylor & Francis Journals, vol. 47(4), pages 852-867, March.
    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. Pradip Debnath & Hari Mohan Srivastava, 2021. "Optimizing Stock Market Returns during Global Pandemic Using Regression in the Context of Indian Stock Market," JRFM, MDPI, vol. 14(8), pages 1-10, August.
    2. Rubayet Karim & Koichi Nakade, 2022. "A Literature Review on the Sustainable EPQ Model, Focusing on Carbon Emissions and Product Recycling," Logistics, MDPI, vol. 6(3), pages 1-16, August.
    3. Pradip Debnath & Hari Mohan Srivastava, 2021. "Optimal Returns in Indian Stock Market during Global Pandemic: A Comparative Study," JRFM, MDPI, vol. 14(12), pages 1-13, December.

    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. Soosan Moradi & Mohammad Reza Gholamian & Arash Sepehri, 2023. "An inventory model for imperfect quality items considering learning effects and partial trade credit policy," OPSEARCH, Springer;Operational Research Society of India, vol. 60(1), pages 276-325, March.
    2. David Almorza-Gomar & Rafael Ravina-Ripoll & Cristina Raluca Gh. Popescu & Araceli Galiano-Coronil, 2022. "Evaluation of an Experience of Academic Happiness through Football at University," IJERPH, MDPI, vol. 19(11), pages 1-13, May.
    3. Manoranjan De & Barun Das & Manoranjan Maiti, 2016. "EPL models for complementary and substitute items under imperfect production process with promotional cost and selling price dependent demands," OPSEARCH, Springer;Operational Research Society of India, vol. 53(2), pages 259-277, June.
    4. Alamri, Adel A. & Syntetos, Aris A., 2018. "Beyond LIFO and FIFO: Exploring an Allocation-In-Fraction-Out (AIFO) policy in a two-warehouse inventory model," International Journal of Production Economics, Elsevier, vol. 206(C), pages 33-45.
    5. Bikash Koli Dey & Hyesung Seok, 2024. "Intelligent inventory management with autonomation and service strategy," Journal of Intelligent Manufacturing, Springer, vol. 35(1), pages 307-330, January.
    6. Mahesh Kumar Jayaswal & Mandeep Mittal, 2022. "Impact of Inflation and Credit Financing Policy on the Supply Chain With Learning," International Journal of Information Systems and Supply Chain Management (IJISSCM), IGI Global, vol. 15(1), pages 1-25, January.
    7. Dharmendra Yadav & Umesh Chand & Ruchi Goel & Biswajit Sarkar, 2023. "Smart Production System with Random Imperfect Process, Partial Backordering, and Deterioration in an Inflationary Environment," Mathematics, MDPI, vol. 11(2), pages 1-20, January.
    8. Jana Kozáková & Mária Urbánová & Radovan Savov, 2021. "Factors Influencing the Extent of the Ethical Codes: Evidence from Slovakia," JRFM, MDPI, vol. 14(1), pages 1-18, January.
    9. Wang, Chih-Hsiung, 2005. "Integrated production and product inspection policy for a deteriorating production system," International Journal of Production Economics, Elsevier, vol. 95(1), pages 123-134, January.
    10. Maria Luisa Scalvedi & Laura Rossi, 2021. "Comprehensive Measurement of Italian Domestic Food Waste in a European Framework," Sustainability, MDPI, vol. 13(3), pages 1-17, February.
    11. Al-Salamah, Muhammad, 2019. "Economic production quantity in an imperfect manufacturing process with synchronous and asynchronous flexible rework rates," Operations Research Perspectives, Elsevier, vol. 6(C).
    12. Mahesh Kumar Jayaswal & Mandeep Mittal & Isha Sangal, 2021. "Ordering policies for deteriorating imperfect quality items with trade-credit financing under learning effect," 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(1), pages 112-125, February.
    13. Bimal Kumar Sett & Bikash Koli Dey & Biswajit Sarkar, 2020. "Autonomated Inspection Policy for Smart Factory—An Improved Approach," Mathematics, MDPI, vol. 8(10), pages 1-19, October.
    14. Tapan Kumar Datta, 2017. "Inventory system with defective products and investment opportunity for reducing defective proportion," Operational Research, Springer, vol. 17(1), pages 297-312, April.
    15. Tseng-Fung Ho & Chi-Chung Lin & Chih-Ling Lin, 2020. "Determining the Optimal Inventory and Number of Shipments for a Two-Resource Supply Chain with Correlated Demands and Remanufacturing Products Allowing Backorder," Mathematics, MDPI, vol. 8(4), pages 1-16, April.
    16. Ashoke Kumar Bera & Dipak Kumar Jana, 2017. "Multi-item imperfect production inventory model in Bi-fuzzy environments," OPSEARCH, Springer;Operational Research Society of India, vol. 54(2), pages 260-282, June.
    17. Ivan Darma Wangsa & Hui Ming Wee & Shih-Hsien Tseng, 2019. "A coordinated vendor–buyer system considering loss and damage claims, insurance cost and stochastic lead time," 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(3), pages 384-398, June.
    18. József Vörös, 2013. "Economic order and production quantity models without constraint on the percentage of defective items," Central European Journal of Operations Research, Springer;Slovak Society for Operations Research;Hungarian Operational Research Society;Czech Society for Operations Research;Österr. Gesellschaft für Operations Research (ÖGOR);Slovenian Society Informatika - Section for Operational Research;Croatian Operational Research Society, vol. 21(4), pages 867-885, December.
    19. Chen, Tsung-Hui & Tsao, Yu-Chung, 2014. "Optimal lot-sizing integration policy under learning and rework effects in a manufacturer–retailer chain," International Journal of Production Economics, Elsevier, vol. 155(C), pages 239-248.
    20. Eroglu, Abdullah & Ozdemir, Gultekin, 2007. "An economic order quantity model with defective items and shortages," International Journal of Production Economics, Elsevier, vol. 106(2), pages 544-549, April.

    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:gam:jjrfmx:v:14:y:2021:i:4:p:173-:d:533520. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.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.