IDEAS home Printed from https://ideas.repec.org/a/eee/proeco/v124y2010i1p32-39.html
   My bibliography  Save this article

Managing yield by lot splitting in a serial production line with learning, rework and scrap

Author

Listed:
  • Jaber, Mohamad Y.
  • Khan, Mehmood

Abstract

Wright's (1936) learning curve (WLC) depicts that the time required to accomplish a repetitive operation decreases with each subsequent repetition. The WLC model assumes that the components produced in an operation are all of perfect quality. On the other hand, in many production operations, some of the components require rework. Some components are even scrapped if they cannot be reworked. We employ the WLC model by considering the learning process in the time to produce and the time to rework a given lot. This composite learning curve was developed by Jaber and Guiffrida (2004). The impact of splitting a production lot into batches of equal size is studied through this composite learning curve. The objective of the study is to maximize a combination of performance of average processing time and process yield with respect to the number of batches. The effect of varying the learning curve parameters in production and in rework is studied for the developed model.

Suggested Citation

  • Jaber, Mohamad Y. & Khan, Mehmood, 2010. "Managing yield by lot splitting in a serial production line with learning, rework and scrap," International Journal of Production Economics, Elsevier, vol. 124(1), pages 32-39, March.
    • Handle: RePEc:eee:proeco:v:124:y:2010:i:1:p:32-39
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0925-5273(09)00357-0
    Download Restriction: Full text for ScienceDirect subscribers only
    ---><---

    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. Jaber, Mohamad Y. & Kher, Hemant V. & Davis, Darwin J., 2003. "Countering forgetting through training and deployment," International Journal of Production Economics, Elsevier, vol. 85(1), pages 33-46, July.
    2. Kim, Seung-Lae & Ha, Daesung, 2003. "A JIT lot-splitting model for supply chain management: Enhancing buyer-supplier linkage," International Journal of Production Economics, Elsevier, vol. 86(1), pages 1-10, October.
    3. 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.
    4. Abraham Grosfeld-Nir & Yigal Gerchak, 2004. "Multiple Lotsizing in Production to Order with Random Yields: Review of Recent Advances," Annals of Operations Research, Springer, vol. 126(1), pages 43-69, February.
    5. Chand, Suresh, 1989. "Lot sizes and setup frequency with learning in setups and process quality," European Journal of Operational Research, Elsevier, vol. 42(2), pages 190-202, September.
    6. Keren, Baruch, 2009. "The single-period inventory problem: Extension to random yield from the perspective of the supply chain," Omega, Elsevier, vol. 37(4), pages 801-810, August.
    7. Anne Spence Wein, 1992. "Random Yield, Rework and Scrap in a Multistage Batch Manufacturing Environment," Operations Research, INFORMS, vol. 40(3), pages 551-563, June.
    8. Irwin, Douglas A & Klenow, Peter J, 1994. "Learning-by-Doing Spillovers in the Semiconductor Industry," Journal of Political Economy, University of Chicago Press, vol. 102(6), pages 1200-1227, December.
    9. Andrew Z. Szendrovits, 1975. "Manufacturing Cycle Time Determination for a Multi-Stage Economic Production Quantity Model," Management Science, INFORMS, vol. 22(3), pages 298-308, November.
    10. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2004. "Learning curves for processes generating defects requiring reworks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 663-672, December.
    11. Michael A. Lapré & Amit Shankar Mukherjee & Luk N. Van Wassenhove, 2000. "Behind the Learning Curve: Linking Learning Activities to Waste Reduction," Management Science, INFORMS, vol. 46(5), pages 597-611, May.
    12. Evan L. Porteus, 1986. "Optimal Lot Sizing, Process Quality Improvement and Setup Cost Reduction," Operations Research, INFORMS, vol. 34(1), pages 137-144, February.
    13. Larry R. Dolinsky & Thomas E. Vollmann & Michael J. Maggard, 1990. "Adjusting Replenishment Orders to Reflect Learning in a Material Requirements Planning Environment," Management Science, INFORMS, vol. 36(12), pages 1532-1547, December.
    14. Sarker, Bhaba R. & Jamal, A.M.M. & Mondal, Sanjay, 2008. "Optimal batch sizing in a multi-stage production system with rework consideration," European Journal of Operational Research, Elsevier, vol. 184(3), pages 915-929, February.
    15. Jaber, Mohamad Y. & Bonney, Maurice, 2003. "Lot sizing with learning and forgetting in set-ups and in product quality," International Journal of Production Economics, Elsevier, vol. 83(1), pages 95-111, January.
    16. Sen, Alper & Topaloglu, Engin & Benli, Omer S., 1998. "Optimal streaming of a single job in a two-stage flow shop," European Journal of Operational Research, Elsevier, vol. 110(1), pages 42-62, October.
    17. Grosfeld-Nir, Abraham & Anily, Shoshana & Ben-Zvi, Tal, 2006. "Lot-sizing two-echelon assembly systems with random yields and rigid demand," European Journal of Operational Research, Elsevier, vol. 173(2), pages 600-616, September.
    18. Terwiesch, Christian & E. Bohn, Roger, 2001. "Learning and process improvement during production ramp-up," International Journal of Production Economics, Elsevier, vol. 70(1), pages 1-19, March.
    19. Szendrovits, Andrew Z & Drezner, ZVI, 1980. "Optimizing multi-stage production with constant lot size and varying numbers of batches," Omega, Elsevier, vol. 8(6), pages 623-629.
    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. Muhammad Tayyab & Biswajit Sarkar & Misbah Ullah, 2018. "Sustainable Lot Size in a Multistage Lean-Green Manufacturing Process under Uncertainty," Mathematics, MDPI, vol. 7(1), pages 1-18, December.
    2. Yamane, Yasuo & Takahashi, Katsuhiko & Hamada, Kunihiro & Morikawa, Katsumi & Nur Bahagia, Senator & Diawati, Lucia & Cakravastia, Andi, 2015. "Developing a plant system prediction model for technology transfer," International Journal of Production Economics, Elsevier, vol. 166(C), pages 119-128.
    3. M. Jaber & Z. Givi, 2015. "Imperfect production process with learning and forgetting effects," Computational Management Science, Springer, vol. 12(1), pages 129-152, January.
    4. Tsionas, Mike G., 2023. "Bayesian learning in performance. Is there any?," European Journal of Operational Research, Elsevier, vol. 311(1), pages 263-282.
    5. Anzanello, Michel J. & Fogliatto, Flavio S., 2011. "Selecting the best clustering variables for grouping mass-customized products involving workers' learning," International Journal of Production Economics, Elsevier, vol. 130(2), pages 268-276, April.
    6. Muhammad Babar Ramzan & Shehreyar Mohsin Qureshi & Sonia Irshad Mari & Muhammad Saad Memon & Mandeep Mittal & Muhammad Imran & Muhammad Waqas Iqbal, 2019. "Effect of Time-Varying Factors on Optimal Combination of Quality Inspectors for Offline Inspection Station," Mathematics, MDPI, vol. 7(1), pages 1-18, January.
    7. Jaber, M.Y. & Peltokorpi, J. & Glock, C.H. & Grosse, E.H. & Pusic, M., 2021. "Adjustment for cognitive interference enhances the predictability of the power learning curve," International Journal of Production Economics, Elsevier, vol. 234(C).
    8. Mitali Sarkar & Li Pan & Bikash Koli Dey & Biswajit Sarkar, 2020. "Does the Autonomation Policy Really Help in a Smart Production System for Controlling Defective Production?," Mathematics, MDPI, vol. 8(7), pages 1-21, July.
    9. Mandeep Mittal & Mahesh Kumar Jayaswal & Vijay Kumar, 2022. "Effect of learning on the optimal ordering policy of inventory model for deteriorating items with shortages and trade-credit financing," 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. 13(2), pages 914-924, June.
    10. Sonntag, Danja & Kiesmüller, Gudrun P., 2018. "Disposal versus rework – Inventory control in a production system with random yield," European Journal of Operational Research, Elsevier, vol. 267(1), pages 138-149.
    11. 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.
    12. Anzanello, Michel J. & Fogliatto, Flavio S. & Santos, Luana, 2014. "Learning dependent job scheduling in mass customized scenarios considering ergonomic factors," International Journal of Production Economics, Elsevier, vol. 154(C), pages 136-145.
    13. Zębala, Wojciech & Plaza, Malgorzata, 2014. "Comparative study of 3- and 5-axis CNC centers for free-form machining of difficult-to-cut material," International Journal of Production Economics, Elsevier, vol. 158(C), pages 345-358.

    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. Jaber & Z. Givi, 2015. "Imperfect production process with learning and forgetting effects," Computational Management Science, Springer, vol. 12(1), pages 129-152, January.
    2. Nadeau, Marie-Claude & Kar, Ashish & Roth, Richard & Kirchain, Randolph, 2010. "A dynamic process-based cost modeling approach to understand learning effects in manufacturing," International Journal of Production Economics, Elsevier, vol. 128(1), pages 223-234, November.
    3. 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.
    4. Yamane, Yasuo & Takahashi, Katsuhiko & Hamada, Kunihiro & Morikawa, Katsumi & Nur Bahagia, Senator & Diawati, Lucia & Cakravastia, Andi, 2015. "Developing a plant system prediction model for technology transfer," International Journal of Production Economics, Elsevier, vol. 166(C), pages 119-128.
    5. Patricia Heuser & Peter Letmathe & Matthias Schinner, 2022. "Workforce planning in production with flexible or budgeted employee training and volatile demand," Journal of Business Economics, Springer, vol. 92(7), pages 1093-1124, September.
    6. Chen, Cheng-Kang & Lo, Chih-Chung & Liao, Yi-Xiang, 2008. "Optimal lot size with learning consideration on an imperfect production system with allowable shortages," International Journal of Production Economics, Elsevier, vol. 113(1), pages 459-469, May.
    7. M-C Wu & L-C Huang & H-M Hsu & T-S Su, 2011. "Multiple lot-sizing decisions in a two-stage production with an interrupted geometric yield and non-rigid demand," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(6), pages 1075-1084, June.
    8. Jaber, M.Y. & Goyal, S.K. & Imran, M., 2008. "Economic production quantity model for items with imperfect quality subject to learning effects," International Journal of Production Economics, Elsevier, vol. 115(1), pages 143-150, September.
    9. Jaber, Mohamad Y. & Guiffrida, Alfred L., 2004. "Learning curves for processes generating defects requiring reworks," European Journal of Operational Research, Elsevier, vol. 159(3), pages 663-672, December.
    10. Jaber, Mohamad Y. & Bonney, Maurice & Guiffrida, Alfred L., 2010. "Coordinating a three-level supply chain with learning-based continuous improvement," International Journal of Production Economics, Elsevier, vol. 127(1), pages 27-38, September.
    11. Khan, M. & Jaber, M.Y. & Wahab, M.I.M., 2010. "Economic order quantity model for items with imperfect quality with learning in inspection," International Journal of Production Economics, Elsevier, vol. 124(1), pages 87-96, March.
    12. Xiang Li, 2017. "Optimal procurement strategies from suppliers with random yield and all-or-nothing risks," Annals of Operations Research, Springer, vol. 257(1), pages 167-181, October.
    13. Bogaschewsky, Ronald W. & Buscher, Udo D. & Lindner, Gerd, 2001. "Optimizing multi-stage production with constant lot size and varying number of unequal sized batches," Omega, Elsevier, vol. 29(2), pages 183-191, April.
    14. 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.
    15. 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.
    16. Metzker Soares, Paula & Thevenin, Simon & Adulyasak, Yossiri & Dolgui, Alexandre, 2024. "Adaptive robust optimization for lot-sizing under yield uncertainty," European Journal of Operational Research, Elsevier, vol. 313(2), pages 513-526.
    17. Hsiao, Yu-Cheng & Lin, Yi & Huang, Yun-Kuei, 2010. "Optimal multi-stage logistic and inventory policies with production bottleneck in a serial supply chain," International Journal of Production Economics, Elsevier, vol. 124(2), pages 408-413, April.
    18. Carolyn D. Egelman & Dennis Epple & Linda Argote & Erica R.H. Fuchs, 2013. "Learning by Doing in a Multi-Product Manufacturing Environment: Product Variety, Customizations, and Overlapping Product Generations," NBER Working Papers 19674, National Bureau of Economic Research, Inc.
    19. Linda Argote & Sunkee Lee & Jisoo Park, 2021. "Organizational Learning Processes and Outcomes: Major Findings and Future Research Directions," Management Science, INFORMS, vol. 67(9), pages 5399-5429, September.
    20. Gel, Esma S. & Salman, F. Sibel, 2022. "Dynamic ordering decisions with approximate learning of supply yield uncertainty," International Journal of Production Economics, Elsevier, vol. 243(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:eee:proeco:v:124:y:2010:i:1:p:32-39. 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: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/locate/ijpe .

    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.