IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v12y2024i18p2836-d1477023.html
   My bibliography  Save this article

A Sustainable Supply Chain Model with Variable Production Rate and Remanufacturing for Imperfect Production Inventory System under Learning in Fuzzy Environment

Author

Listed:
  • Basim S. O. Alsaedi

    (Department of Statistics, University of Tabuk, Tabuk 71491, Saudi Arabia)

Abstract

In the present paper, a sustainable supply chain model is investigated with a variable production rate and remanufacturing for the production of defective items under the effect of learning fuzzy theory, where the lower and upper variations in fuzzy demand rate are affected by learning parameters and backorders are also allowed. Our proposed model reveals a springy manufacturing inventory organization that makes various types of items, and imperfect items can be created through the method of manufacturing things in a fuzzy environment. When the screening process is completed, defective items are remanufactured immediately, and a limited financial plan and space limitations are assumed concerning the product assembly. We minimized the total fuzzy inventory cost with different distributions (beta, triangular, double triangular, uniform, and χ 2 (chi−square)) concerning the production rate, lot size, and backorder under learning in a fuzzy environment where the costs of screening, manufacturing, carrying, carbon emissions, backorders, and remanufacturing are included. The Kuhn–Tucker optimization technique is applied to solve non-linear equations that are based on some distributions. Numerical examples, sensitivity analysis, managerial insights and observations, limitations, future work, and applications are provided for the validation of our proposed model, and the industrial scope of this proposed work is included.

Suggested Citation

  • Basim S. O. Alsaedi, 2024. "A Sustainable Supply Chain Model with Variable Production Rate and Remanufacturing for Imperfect Production Inventory System under Learning in Fuzzy Environment," Mathematics, MDPI, vol. 12(18), pages 1-49, September.
    • Handle: RePEc:gam:jmathe:v:12:y:2024:i:18:p:2836-:d:1477023
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/12/18/2836/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2227-7390/12/18/2836/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ashraf, Muhammad Hasan & Chen, Yuwen & Yalcin, Mehmet G., 2022. "Minding Braess Paradox amid third-party logistics hub capacity expansion triggered by demand surge," International Journal of Production Economics, Elsevier, vol. 248(C).
    2. Kilic, Onur A. & Tunc, Huseyin, 2019. "Heuristics for the stochastic economic lot sizing problem with remanufacturing under backordering costs," European Journal of Operational Research, Elsevier, vol. 276(3), pages 880-892.
    3. Basim S. O. Alsaedi & Osama Abdulaziz Alamri & Mahesh Kumar Jayaswal & Mandeep Mittal, 2023. "A Sustainable Green Supply Chain Model with Carbon Emissions for Defective Items under Learning in a Fuzzy Environment," Mathematics, MDPI, vol. 11(2), pages 1-36, January.
    4. Heydari, Jafar & Govindan, Kannan & Sadeghi, Razieh, 2018. "Reverse supply chain coordination under stochastic remanufacturing capacity," International Journal of Production Economics, Elsevier, vol. 202(C), pages 1-11.
    5. Charpin, Remi & Lee, Min Kyung & Wu, Ting, 2021. "Mobile procurement platforms: Bridging the online and offline worlds in China's restaurant industry," International Journal of Production Economics, Elsevier, vol. 241(C).
    6. Buisman, Marjolein E. & Rohmer, Sonja U.K., 2022. "Inventory decisions for ameliorating products under consideration of stochastic demand," International Journal of Production Economics, Elsevier, vol. 252(C).
    7. Md Shajalal & Petr Hajek & Mohammad Zoynul Abedin, 2023. "Product backorder prediction using deep neural network on imbalanced data," International Journal of Production Research, Taylor & Francis Journals, vol. 61(1), pages 302-319, January.
    8. Balter, Anne G. & Huisman, Kuno J.M. & Kort, Peter M., 2022. "Effects of creative destruction on the size and timing of an investment," International Journal of Production Economics, Elsevier, vol. 252(C).
    9. Bhatia, Purvee & Diaz-Elsayed, Nancy, 2023. "Facilitating decision-making for the adoption of smart manufacturing technologies by SMEs via fuzzy TOPSIS," International Journal of Production Economics, Elsevier, vol. 257(C).
    10. Hariga, Moncer & As’ad, Rami & Khan, Zeinab, 2017. "Manufacturing-remanufacturing policies for a centralized two stage supply chain under consignment stock partnership," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 362-374.
    11. Chen, Tsung-Hui, 2017. "Optimizing pricing, replenishment and rework decision for imperfect and deteriorating items in a manufacturer-retailer channel," International Journal of Production Economics, Elsevier, vol. 183(PB), pages 539-550.
    12. Kosmas Alexopoulos & Ioannis Anagiannis & Nikolaos Nikolakis & George Chryssolouris, 2022. "A quantitative approach to resilience in manufacturing systems," International Journal of Production Research, Taylor & Francis Journals, vol. 60(24), pages 7178-7193, December.
    13. M. Sanjai & S. Periyasamy, 2018. "Production inventory model with reworking of imperfect items and integrates cost reduction delivery policy," International Journal of Operational Research, Inderscience Enterprises Ltd, vol. 32(3), pages 329-349.
    14. Subhendu Ruidas & Mijanur Rahaman Seikh & Prasun Kumar Nayak, 2022. "A production-repairing inventory model considering demand and the proportion of defective items as rough intervals," Operational Research, Springer, vol. 22(3), pages 2803-2829, July.
    15. Gouiaa-Mtibaa, A. & Dellagi, S. & Achour, Z. & Erray, W., 2018. "Integrated Maintenance-Quality policy with rework process under improved imperfect preventive maintenance," Reliability Engineering and System Safety, Elsevier, vol. 173(C), pages 1-11.
    16. Polotski, V. & Kenne, J.-P. & Gharbi, A., 2019. "Joint production and maintenance optimization in flexible hybrid Manufacturing–Remanufacturing systems under age-dependent deterioration," International Journal of Production Economics, Elsevier, vol. 216(C), pages 239-254.
    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. Baishakhi Ganguly & Bikash Koli Dey & Sarla Pareek & Biswajit Sarkar, 2023. "Cost-Effective Imperfect Production-Inventory System under Variable Production Rate and Remanufacturing," Mathematics, MDPI, vol. 11(15), pages 1-24, August.
    2. Mangla, Sachin Kumar & Srivastava, Praveen Ranjan & Eachempati, Prajwal & Tiwari, Aviral Kumar, 2024. "Exploring the impact of key performance factors on energy markets: From energy risk management perspectives," Energy Economics, Elsevier, vol. 131(C).
    3. Visentin, Andrea & Prestwich, Steven & Rossi, Roberto & Tarim, S. Armagan, 2021. "Computing optimal (R,s,S) policy parameters by a hybrid of branch-and-bound and stochastic dynamic programming," European Journal of Operational Research, Elsevier, vol. 294(1), pages 91-99.
    4. Gunasekara, Lahiru & Robb, David J. & Zhang, Abraham, 2023. "Used product acquisition, sorting and disposition for circular supply chains: Literature review and research directions," International Journal of Production Economics, Elsevier, vol. 260(C).
    5. Feng Tao & Tijun Fan & Xuefeng Jia & Kin Keung Lai, 2021. "Optimal production strategy for a manufacturing and remanufacturing system with return policy," Operational Research, Springer, vol. 21(1), pages 251-271, March.
    6. Suzanne, Elodie & Absi, Nabil & Borodin, Valeria, 2020. "Towards circular economy in production planning: Challenges and opportunities," European Journal of Operational Research, Elsevier, vol. 287(1), pages 168-190.
    7. Deqing Ma & Pengcheng Ma & Jinsong Hu, 2024. "The Impact of Blockchain Technology Adoption on an E-Commerce Closed-Loop Supply Chain Considering Consumer Trust," Sustainability, MDPI, vol. 16(4), pages 1-41, February.
    8. Taleizadeh, Ata Allah & Sadeghi, Razieh, 2019. "Pricing strategies in the competitive reverse supply chains with traditional and e-channels: A game theoretic approach," International Journal of Production Economics, Elsevier, vol. 215(C), pages 48-60.
    9. Ye, Fanglin & Paulson, Nicholas & Khanna, Madhu, 2024. "Strategic innovation and technology adoption under technological uncertainty," Journal of Economic Dynamics and Control, Elsevier, vol. 165(C).
    10. Chan, Chi Kin & Fang, Fei & Langevin, André, 2018. "Single-vendor multi-buyer supply chain coordination with stochastic demand," International Journal of Production Economics, Elsevier, vol. 206(C), pages 110-133.
    11. Duong, Quang Huy & Zhou, Li & Meng, Meng & Nguyen, Truong Van & Ieromonachou, Petros & Nguyen, Duy Tiep, 2022. "Understanding product returns: A systematic literature review using machine learning and bibliometric analysis," International Journal of Production Economics, Elsevier, vol. 243(C).
    12. Basim S. O. Alsaedi, 2024. "A Sustainable Supply Chain Model with a Setup Cost Reduction Policy for Imperfect Items under Learning in a Cloudy Fuzzy Environment," Mathematics, MDPI, vol. 12(10), pages 1-33, May.
    13. Subrata Panja & Shyamal Kumar Mondal, 2023. "Sustainable production inventory management through bi-level greening performance in a three-echelon supply chain," Operational Research, Springer, vol. 23(1), pages 1-55, March.
    14. Santos, Augusto César de Jesus & Cavalcante, Cristiano Alexandre Virgínio & Wu, Shaomin, 2023. "Maintenance policies and models: A bibliometric and literature review of strategies for reuse and remanufacturing," Reliability Engineering and System Safety, Elsevier, vol. 231(C).
    15. Kuen-Suan Chen & Tsun-Hung Huang & Chun-Min Yu & Hui-E Lee, 2024. "Fuzzy Evaluation Model for Operational Performance of Air Cleaning Equipment," Mathematics, MDPI, vol. 12(17), pages 1-12, August.
    16. Giovanni Zenezini & Anna Corinna Cagliano & Giulio Mangano & Carlo Rafele, 2023. "Impacts of COVID-19 on Logistics Service Providers’ Operations: An Italian Empirical Study," Sustainability, MDPI, vol. 16(1), pages 1-13, December.
    17. Love, Peter E.D. & Matthews, Jane, 2020. "Quality, requisite imagination and resilience: Managing risk and uncertainty in construction," Reliability Engineering and System Safety, Elsevier, vol. 204(C).
    18. Boumallessa, Zeineb & Chouikhi, Houssam & Elleuch, Mounir & Bentaher, Hatem, 2023. "Modeling and optimizing the maintenance schedule using dynamic quality and machine condition monitors in an unreliable single production system," Reliability Engineering and System Safety, Elsevier, vol. 235(C).
    19. Saâdaoui, Foued & Rabbouch, Hana, 2024. "Financial forecasting improvement with LSTM-ARFIMA hybrid models and non-Gaussian distributions," Technological Forecasting and Social Change, Elsevier, vol. 206(C).
    20. Wakiru, James & Pintelon, Liliane & Muchiri, Peter N. & Chemweno, Peter K., 2021. "Integrated remanufacturing, maintenance and spares policies towards life extension of a multi-component system," Reliability Engineering and System Safety, Elsevier, vol. 215(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:gam:jmathe:v:12:y:2024:i:18:p:2836-:d:1477023. 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.