IDEAS home Printed from https://ideas.repec.org/a/gam/jmathe/v7y2018i1p13-d192954.html
   My bibliography  Save this article

Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand

Author

Listed:
  • Muhammad Tayyab

    (Department of Industrial & Management Engineering, Hanyang University, Ansan Gyeonggi-do 155 88, Korea)

  • Biswajit Sarkar

    (Department of Industrial & Management Engineering, Hanyang University, Ansan Gyeonggi-do 155 88, Korea)

  • Bernardo Nugroho Yahya

    (Industrial and Management Engineering Department, Hankuk University of Foreign Studies, 81, Oedae-ro, Mohyeon-myeon, Cheoin-gu, Yongin-si, Gyeonggi-do 17035, Korea)

Abstract

Market conditions fluctuate abruptly in today’s competitive environment and leads to imprecise demand information. In particular, market demand data for freshly launched products is highly uncertain. Further, most of the products are generally manufactured through complex multi-stage production systems that may produce defective items once they enter the out-of-control state. Production management of a multi-stage production system in these circumstances requires robust production model to reduce system costs. In this context, this paper introduces an imperfect multi-stage production model with the consideration of defective proportion in the production process and uncertain product demand. Fuzzy theory is applied to handle the uncertainty in demand information and the center of gravity approach is utilized to defuzzify the objective function. This defuzzified cost objective is solved through the analytical optimization technique and closed form solution of optimal lot size and minimum cost function are obtained. Model analysis verifies that it has successfully achieved global optimal results. Numerical experiment comprising of three examples is conducted and optimal results are analyzed through sensitivity analysis. Results demonstrate that larger lot sizes are profitable as the system moves towards a higher number of stages. Sensitivity analysis indicates that the processing cost is the most influencing factor on the system cost function.

Suggested Citation

  • Muhammad Tayyab & Biswajit Sarkar & Bernardo Nugroho Yahya, 2018. "Imperfect Multi-Stage Lean Manufacturing System with Rework under Fuzzy Demand," Mathematics, MDPI, vol. 7(1), pages 1-18, December.
  • Handle: RePEc:gam:jmathe:v:7:y:2018:i:1:p:13-:d:192954
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2227-7390/7/1/13/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/2227-7390/7/1/13/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2008. "Learning curves for imperfect production processes with reworks and process restoration interruptions," European Journal of Operational Research, Elsevier, vol. 189(1), pages 93-104, August.
    2. Biswajit Sarkar & Kripasindhu Chaudhuri & Shib Sankar Sana, 2010. "A stock-dependent inventory model in an imperfect production process," International Journal of Procurement Management, Inderscience Enterprises Ltd, vol. 3(4), pages 361-378.
    3. Sarkar, Biswajit & Moon, Ilkyeong, 2014. "Improved quality, setup cost reduction, and variable backorder costs in an imperfect production process," International Journal of Production Economics, Elsevier, vol. 155(C), pages 204-213.
    4. Sana, Shib Sankar, 2010. "A production-inventory model in an imperfect production process," European Journal of Operational Research, Elsevier, vol. 200(2), pages 451-464, January.
    5. Chang, Hung-Chi & Yao, Jing-Shing & Ouyang, Liang-Yuh, 2006. "Fuzzy mixture inventory model involving fuzzy random variable lead time demand and fuzzy total demand," European Journal of Operational Research, Elsevier, vol. 169(1), pages 65-80, February.
    6. 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.
    7. Sana, Shib Sankar, 2010. "An economic production lot size model in an imperfect production system," European Journal of Operational Research, Elsevier, vol. 201(1), pages 158-170, February.
    8. Ben-Daya, Mohamed, 2002. "The economic production lot-sizing problem with imperfect production processes and imperfect maintenance," International Journal of Production Economics, Elsevier, vol. 76(3), pages 257-264, April.
    9. Chiu, Singa Wang & Chou, Chung-Li & Wu, Wen-Kuei, 2013. "Optimizing replenishment policy in an EPQ-based inventory model with nonconforming items and breakdown," Economic Modelling, Elsevier, vol. 35(C), pages 330-337.
    10. Khan, M. & Jaber, M.Y. & Guiffrida, A.L. & Zolfaghari, S., 2011. "A review of the extensions of a modified EOQ model for imperfect quality items," International Journal of Production Economics, Elsevier, vol. 132(1), pages 1-12, July.
    11. Yoo, Seung Ho & Kim, DaeSoo & Park, Myung-Sub, 2012. "Lot sizing and quality investment with quality cost analyses for imperfect production and inspection processes with commercial return," International Journal of Production Economics, Elsevier, vol. 140(2), pages 922-933.
    12. Jaber, Mohamad Y. & Zanoni, Simone & Zavanella, Lucio E., 2014. "Economic order quantity models for imperfect items with buy and repair options," International Journal of Production Economics, Elsevier, vol. 155(C), pages 126-131.
    13. Hau L. Lee, 1992. "Lot Sizing to Reduce Capacity Utilization in a Production Process with Defective Items, Process Corrections, and Rework," Management Science, INFORMS, vol. 38(9), pages 1314-1328, September.
    14. 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.
    15. Glock, C. H. & Jaber, M. Y., 2013. "Learning effects and the phenomenon of moving bottlenecks in a two-stage production system," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 62486, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
    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. Falguni Mahato & Chandan Mahato & Gour Chandra Mahata, 2023. "Sustainable optimal production policies for an imperfect production system with trade credit under different carbon emission regulations," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 25(9), pages 10073-10099, September.

    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. Biswajit Sarkar & Mehran Ullah & Seok-Beom Choi, 2019. "Joint Inventory and Pricing Policy for an Online to Offline Closed-Loop Supply Chain Model with Random Defective Rate and Returnable Transport Items," Mathematics, MDPI, vol. 7(6), pages 1-20, June.
    2. 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.
    3. Chang Wook Kang & Misbah Ullah & Mitali Sarkar & Muhammad Omair & Biswajit Sarkar, 2019. "A Single-Stage Manufacturing Model with Imperfect Items, Inspections, Rework, and Planned Backorders," Mathematics, MDPI, vol. 7(5), pages 1-18, May.
    4. Hsu, Jia-Tzer & Hsu, Lie-Fern, 2013. "An EOQ model with imperfect quality items, inspection errors, shortage backordering, and sales returns," International Journal of Production Economics, Elsevier, vol. 143(1), pages 162-170.
    5. Bouslah, Bassem & Gharbi, Ali & Pellerin, Robert, 2013. "Joint optimal lot sizing and production control policy in an unreliable and imperfect manufacturing system," International Journal of Production Economics, Elsevier, vol. 144(1), pages 143-156.
    6. Naoufel Cheikhrouhou & Biswajit Sarkar & Baishakhi Ganguly & Asif Iqbal Malik & Rafael Batista & Young Hae Lee, 2018. "Optimization of sample size and order size in an inventory model with quality inspection and return of defective items," Annals of Operations Research, Springer, vol. 271(2), pages 445-467, December.
    7. Taleizadeh, Ata Allah & Khanbaglo, Mahboobeh Perak Sari & Cárdenas-Barrón, Leopoldo Eduardo, 2016. "An EOQ inventory model with partial backordering and reparation of imperfect products," International Journal of Production Economics, Elsevier, vol. 182(C), pages 418-434.
    8. Sarkar, Biswajit & Sarkar, Mitali & Ganguly, Baishakhi & Cárdenas-Barrón, Leopoldo Eduardo, 2021. "Combined effects of carbon emission and production quality improvement for fixed lifetime products in a sustainable supply chain management," International Journal of Production Economics, Elsevier, vol. 231(C).
    9. Hauck, Zsuzsanna & Vörös, József, 2015. "Lot sizing in case of defective items with investments to increase the speed of quality control," Omega, Elsevier, vol. 52(C), pages 180-189.
    10. Ouyang, Liang-Yuh & Chang, Chun-Tao, 2013. "Optimal production lot with imperfect production process under permissible delay in payments and complete backlogging," International Journal of Production Economics, Elsevier, vol. 144(2), pages 610-617.
    11. Lee, Sunghee & Kim, Daeki, 2014. "An optimal policy for a single-vendor single-buyer integrated production–distribution model with both deteriorating and defective items," International Journal of Production Economics, Elsevier, vol. 147(PA), pages 161-170.
    12. Shaktipada Bhuniya & Biswajit Sarkar & Sarla Pareek, 2019. "Multi-Product Production System with the Reduced Failure Rate and the Optimum Energy Consumption under Variable Demand," Mathematics, MDPI, vol. 7(5), pages 1-20, May.
    13. 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.
    14. 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.
    15. Pal, Brojeswar & Sana, Shib Sankar & Chaudhuri, Kripasindhu, 2014. "Joint pricing and ordering policy for two echelon imperfect production inventory model with two cycles," International Journal of Production Economics, Elsevier, vol. 155(C), pages 229-238.
    16. Kazaz, Burak & Sloan, Thomas W., 2013. "The impact of process deterioration on production and maintenance policies," European Journal of Operational Research, Elsevier, vol. 227(1), pages 88-100.
    17. 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.
    18. Chiu, Yuan-Shyi Peter & Chen, Yung-Chung & Lin, Hong-Dar & Chang, Huei-Hsin, 2014. "Combining an improved multi-delivery policy into a single-producer multi-retailer integrated inventory system with scrap in production," Economic Modelling, Elsevier, vol. 39(C), pages 163-167.
    19. Harun Öztürk, 2019. "Modeling an inventory problem with random supply, inspection and machine breakdown," OPSEARCH, Springer;Operational Research Society of India, vol. 56(2), pages 497-527, June.
    20. Sarkar, Mitali & Sarkar, Biswajit, 2013. "An economic manufacturing quantity model with probabilistic deterioration in a production system," Economic Modelling, Elsevier, vol. 31(C), pages 245-252.

    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:7:y:2018:i:1:p:13-:d:192954. 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.