449
Views
0
CrossRef citations to date
0
Altmetric
Research Article

Pulling the distribution in supply chains: simulation and analysis of Dynamic Buffer Management approach

ORCID Icon, ORCID Icon, &

References

  • Abdelsalam, H. M., Magdy, M., & AlShaar, A. M. (2013). Optimal location of new distribution center in supply chain network design with varying inventory capacity. In I. Zelinka, V. Snášel, & A. Abraham (Eds.), Handbook of optimization (pp. 553–573). Springer.
  • Banks, J., Carson, J. S. I. I., Nelson, B. L., & Nicol, D. M. (2010). Discrete-event system simulation (5th ed.). Prentice Hall.
  • Barnard, A. (2010). Continuous improvement and auditing. In J. F. Cox III, & J. G. Schleier (Eds.), Theory of Constraints handbook (pp. 403–454). McGraw-Hill.
  • Bashiri, M., & Tabrizi, M. M. (2010). Supply chain design: A holistic approach. Expert Systems with Applications, 37(1), 688–693. https://doi.org/10.1016/j.eswa.2009.06.006
  • Blackstone, J. H. J. (2001). Theory of constraints – A status report. International Journal of Production Research, 39(6), 1053–1080. https://doi.org/10.1080/00207540010028119
  • Chang, K. H., Chang, Y. C., & Chang, Y. S. (2017). Applying theory of constraints-based approach to solve memory allocation of cloud storage. International Journal of Systems Science: Operations and Logistics, 4(4), 311–329. https://doi.org/10.1080/23302674.2015.1106027
  • Chang, Y. C., Chang, K. H., & Huang, C. W. (2014). Integrate market demand forecast and demand-pull replenishment to improve the inventory management effectiveness of wafer fabrication. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 228(4), 617–636. https://doi.org/10.1177/0954405413505556
  • Chang, Y. C., Chang, K. H., Lee, M. C., & Tsao, K. H. (2019). Using exponentially weighted moving average to improve buffer adjustment of demand-driven replenishment strategies. Journal of Testing and Evaluation, 47(1), 602–626. https://doi.org/10.1520/JTE20170346
  • Chang, Y. C., Chang, K. H., & Sun, W. C. (2015). Enhancement of inventory management for the wafer manufacturing industry by combining market demand forecast and demand-pull replenishment. Journal of Testing and Evaluation, 43(4), 948–963. https://doi.org/10.1520/JTE20130216
  • Ciechanska, O., & Szwed, C. (2020). Characteristics and study of make-to-stock and make-to-availability production strategy using simulation modelling. Management and Production Engineering Review, 11(4), 68–80. https://doi.org/10.24425/mper.2020.136121.
  • Cimino, A., Longo, F., & Mirabelli, G. (2010). A general simulation framework for supply chain modeling: State of the art and case study. International Journal of Computer Science Issues, 7(2), 1–9.
  • Cobb, B. R., Rumí, R., & Salmerón, A. (2013). Inventory management with log-normal demand per unit time. Computers and Operations Research, 40(7), 1842–1851. https://doi.org/10.1016/j.cor.2013.01.017
  • Cox, J. F. III, Boyd, L. H., Sullivan, T. T., Reid, R. A., & Cartier, B. (2012). The theory of constraints international certification organization dictionary (2nd ed.). McGraw-Hill.
  • Cox, J. F. III, & Schleier, J. G. (Eds.). (2010). Theory of Constraints handbook. McGraw-Hill.
  • da Silva, C. E. S., Salgado, E. G., Mello, C. H. P., da Silva Oliveira, E., & Leal, F. (2014). Integration of computer simulation in design for manufacturing and assembly. International Journal of Production Research, 52(10), 2851–2866. https://doi.org/10.1080/00207543.2013.853887
  • Davis, J. P., Eisenhardt, K. M., & Bingham, C. B. (2007). Developing theory through simulation methods. Academy of Management Review, 32(2), 480–499. https://doi.org/10.5465/amr.2007.24351453
  • de Freitas, D. C., de Oliveira, L. G., & Alcântara, R. L. C. (2019). A theoretical framework to adopt collaborative initiatives in supply chains. Gestao e Producao, 26(3), 1–15. https://doi.org/10.1590/0104-530X-4194-19.
  • de Souza, F. B., & Pires, S. R. I. (2010). Theory of constraints contributions to outbound logistics. Management Research Review, 33(7), 683–700. https://doi.org/10.1108/01409171011055780
  • de Souza, F. B., & Pires, S. R. I. (2014). Making to availability: An application of the theory of constraints in make-to-stock environments. Gestao e Producao, 21(1), 65–76. https://doi.org/10.1590/S0104-530X2013005000007.
  • Erraoui, Y., Charkaoui, A., & Echchatbi, A. (2019). Demand driven DRP: Assessment of a new approach to distribution. International Journal of Supply and Operations Management, 6(1), 1–10. https://doi.org/10.22034/2019.1.1.
  • Gholami, A., Mirzazadeh, A., & Liu, S. (2018). An inventory model with controllable lead time and ordering cost, log-normal-distributed demand, and gamma-distributed available capacity. Cogent Business and Management, 5(1), 1–17. https://doi.org/10.1080/23311975.2018.1469182
  • Goldratt, E. M. (1988). Computerized shop floor scheduling. International Journal of Production Research, 26(3), 443–455. https://doi.org/10.1080/00207548808947875
  • Goldratt, E. M. (1990). What is this thing called theory of constraints and how should it be implemented? North River Press.
  • Goldratt, E. M. (1994). It’s not luck. North River Press.
  • Goldratt, E. M., Eshkoli, I., & Brownleer, J. (2009). Isn’t it obvious? North River Press.
  • Goldratt, E. M., & Goldratt, A. (2003). TOC insights into distribution and supply chain. Goldratt's Marketing Group.
  • Goldratt, E. M., Schragenheim, E., & Ptak, C. A. (2000). Necessary but not sufficient. North River Press.
  • Gupta, M. C., & Andersen, S. (2018). Throughput/inventory dollar-days: TOC-based measures for supply chain collaboration. International Journal of Production Research, 56(13), 4659–4675. https://doi.org/10.1080/00207543.2018.1444805
  • Hill, C. A., Zhang, G. P., & Miller, K. E. (2018). Collaborative planning, forecasting, and replenishment & firm performance: An empirical evaluation. International Journal of Production Economics, 196, 12–23. https://doi.org/10.1016/j.ijpe.2017.11.012
  • Hopp, W. J., & Spearman, M. L. (2011). Factory physics. Waveland Press.
  • Huang, C. L., Li, R. K., Tsai, C. H., Chung, Y. C., & Shih, C. H. (2014). A comparative study of pull and push production methods for supply chain resilience. International Journal of Operations and Logistics Management, 3(1), 1–15.
  • Huang, M. G. (2013). Economic ordering model for deteriorating items with random demand and deterioration. International Journal of Production Research, 51(18), 5612–5624. https://doi.org/10.1080/00207543.2013.791753
  • Ikeziri, L. M., de Souza, F. B., Gupta, M. C., & de Camargo Fiorini, P. (2019). Theory of constraints: Review and bibliometric analysis. International Journal of Production Research, 57(15-16), 5068–5102. https://doi.org/10.1080/00207543.2018.1518602
  • Jacobs, F. R. (1984). OPT uncovered: Many production planning and scheduling concepts can be applied with or without the software. Industrial Engineering, 16(10), 32–41.
  • Jammernegg, W., & Reiner, G. (2007). Performance improvement of supply chain processes by coordinated inventory and capacity management. International Journal of Production Economics, 108(1-2), 183–190. https://doi.org/10.1016/j.ijpe.2006.12.047
  • Janssens, G. K., & Ramaekers, K. M. (2011). A linear programming formulation for an inventory management decision problem with a service constraint. Expert Systems with Applications, 38(7), 7929–7934. https://doi.org/10.1016/j.eswa.2010.12.009
  • Karabağ, O., & Tan, B. (2019). An empirical analysis of the main drivers affecting the buyer surplus in E-auctions. International Journal of Production Research, 57(11), 3435–3465. https://doi.org/10.1080/00207543.2018.1536835
  • Keyvani, P., & Lotfi, M. M. (2019). Dynamic TOC-based approach to planning and controlling accessories in MTO environments. Scientia Iranica, 26(5), 2885–2903. https://doi.org/10.24200/SCI.2018.20610.
  • Lee, C. J., & Rim, S. C. (2019). A mathematical safety stock model for DDMRP inventory replenishment. Mathematical Problems in Engineering, 2019, 1–10. https://doi.org/10.1155/2019/6496309.
  • Limpert, E., Stahel, W. A., & Abbt, M. (2001). Log-normal distributions across the sciences: Keys and clues. Bioscience, 51(5), 341–352. https://doi.org/10.1641/0006-3568(2001)051[0341:LNDATS]2.0.CO;2
  • Lowalekar, H., & Basu, S. (2020). Theory of constraints based mafia offer for supply chains of deteriorating products. International Journal of Production Research, 58(14), 4421–4449. https://doi.org/10.1080/00207543.2019.1654629
  • Lowalekar, H., & Ravi, R. R. (2017). Revolutionizing blood bank inventory management using the TOC thinking process: An Indian case study. International Journal of Production Economics, 186, 89–122. https://doi.org/10.1016/j.ijpe.2017.02.003
  • Mateen, A., & More, D. (2013). Applying TOC thinking process tools in managing challenges of supply chain finance: A case study. International Journal of Services and Operations Management, 15(4), 389–410. https://doi.org/10.1504/IJSOM.2013.054882
  • Modi, K., Lowalekar, H., & Bhatta, N. M. K. (2019). Revolutionizing supply chain management the theory of constraints way: A case study. International Journal of Production Research, 57(11), 3335–3361. https://doi.org/10.1080/00207543.2018.1523579
  • Munir, M., Jajja, M. S. S., Chatha, K. A., & Farooq, S. (2020). Supply chain risk management and operational performance: The enabling role of supply chain integration. International Journal of Production Economics, 227, 1–14. https://doi.org/10.1016/j.ijpe.2020.107667
  • Narita, V. T., Ikeziri, L. M., & de Souza, F. B. (2021). Evaluation of dynamic buffer management for adjusting stock level: A simulation-based approach. Journal of Industrial and Production Engineering, 38(6), 452–465. https://doi.org/10.1080/21681015.2021.1931493
  • Nguyen, D. T., Adulyasak, Y., & Landry, S. (2021). Research manuscript: The bullwhip effect in rule-based supply chain planning systems–A case-based simulation at a hard goods retailer. Omega, 98, 1–16. https://doi.org/10.1016/j.omega.2019.102121
  • Nimmy, J. S., Chilkapure, A., & Pillai, V. M. (2019). Literature review on supply chain collaboration: Comparison of various collaborative techniques. Journal of Advances in Management Research, 16(4), 537–562. https://doi.org/10.1108/JAMR-10-2018-0087
  • Pacheco, D. A. J., Antunes Junior, J. A. V., & de Matos, C. A. (2021). The constraints of theory: What is the impact of the theory of constraints on operations strategy? International Journal of Production Economics, 235, 1–16. https://doi.org/10.1016/j.ijpe.2020.107955.
  • Park, C. L., & Paiva, E. L. (2018). How do national cultures impact the operations strategy process? International Journal of Operations and Production Management, 38(10), 1937–1963. https://doi.org/10.1108/IJOPM-03-2017-0145
  • Pérez, J. L. (1997). TOC for world class global supply chain management. Computers and Industrial Engineering, 33(1-2), 289–293. https://doi.org/10.1016/S0360-8352(97)00095-8
  • Ponte, B., Costas, J., Puche, J., De La Fuente, D., & Pino, R. (2016). Holism versus reductionism in supply chain management: An economic analysis. Decision Support Systems, 86, 83–94. https://doi.org/10.1016/j.dss.2016.03.010
  • Promodel Corporation. (2015). ProModel 2014 user guide.
  • Rahman, S. U. (2002). The theory of constraints’ thinking process approach to developing strategies in supply chains. International Journal of Physical Distribution & Logistics Management, 32(10), 809–828. https://doi.org/10.1108/09600030210455429
  • Robinson, S. (2014). Simulation: The practice of model development and use (2nd ed.). Palgrave Macmillan.
  • Roh, J. J., & Hong, P. (2015). Taxonomy of ERP integrations and performance outcomes: An exploratory study of manufacturing firms. Production Planning and Control, 26(8), 617–636. https://doi.org/10.1080/09537287.2014.950624
  • Rossi Filho, T. A., Pacheco, D. A. J., Pergher, I., Antunes, J. A. V. Jr., Vaccaro, G. L. R., & da Luz, D. F. (2013). A reference approach to deploy the solution of logistics theory of constraints. Espacios, 34(7).
  • Rossi Filho, T. A., Pacheco, D. A. J., Pergher, I., Vaccaro, G. L. R., & & Antunes, J. A. V. Jr. (2016). A new approach for decision making in distribution supply chains: A theory of constraints perspective. International Journal of Logistics Systems and Management, 25(2), 266–282. https://doi.org/10.1504/IJLSM.2016.078916
  • Schragenheim, A. (2010). Supply chain management. In J. F. Cox III, & J. G. Schleier (Eds.), Theory of Constraints handbook (pp. 265–302). McGraw-Hill.
  • Schragenheim, E. (2010). Managing make-to-stock and the concept of make-to-availability. In J. F. Cox III, & J. G. Schleier (Eds.), Theory of Constraints handbook (pp. 239–264). McGraw-Hill.
  • Schragenheim, E., Dettmer, H. W., & Patterson, J. W. (2009). Supply chain management at warp speed: Integrating the system from end to end. CRC Press.
  • Sharma, D., Taggar, R., Bindra, S., & Dhir, S. (2020). A systematic review of responsiveness to develop future research agenda: A TCCM and bibliometric analysis. Benchmarking, 27(9), 2649–2677. https://doi.org/10.1108/BIJ-12-2019-0539
  • Shen, L., Ren, Y., Xiong, N., Li, H., & Chen, Y. (2018). Why small towns can not share the benefits of urbanization in China? Journal of Cleaner Production, 174, 728–738. https://doi.org/10.1016/j.jclepro.2017.10.150
  • Simatupang, T. M., Wright, A. C., & Sridharan, R. (2004). Applying the theory of constraints to supply chain collaboration. Supply Chain Management, 9(1), 57–70. https://doi.org/10.1108/13598540410517584
  • Singhry, H. B., & Rahman, A. A. (2019). Enhancing supply chain performance through collaborative planning, forecasting, and replenishment. Business Process Management Journal, 25(4), 625–646. https://doi.org/10.1108/BPMJ-03-2017-0052
  • Trapero, J. R., Cardós, M., & Kourentzes, N. (2019). Empirical safety stock estimation based on kernel and GARCH models. Omega, 84, 199–211. https://doi.org/10.1016/j.omega.2018.05.004
  • van Steenbergen, R. M., & Mes, M. R. K. (2020). Forecasting demand profiles of new products. Decision Support Systems, 139, 1–15. https://doi.org/10.1016/j.dss.2020.113401
  • Walker, W. T. (2002). Practical application of drum-buffer-rope to synchronize a two-stage supply chain. Production and Inventory Management Journal, 43(3-4), 13–23.
  • Wan, X., & Evers, P. T. (2011). Supply chain networks with multiple retailers: A test of the emerging theory on inventories, stockouts, and bullwhips. Journal of Business Logistics, 32(1), 27–39. https://doi.org/10.1111/j.2158-1592.2011.01003.x
  • Wang, L. C., Cheng, C. Y., Tseng, Y. T., & Liu, Y. F. (2015). Demand-pull replenishment model for hospital inventory management: A dynamic buffer-adjustment approach. International Journal of Production Research, 53(24), 7533–7546. https://doi.org/10.1080/00207543.2015.1102353
  • Watson, K., & Polito, T. (2003). Comparison of DRP and TOC financial performance within a multi-product, multi-echelon physical distribution environment. International Journal of Production Research, 41(4), 741–765. https://doi.org/10.1080/0020754031000065511
  • Wu, H. H., Chen, C. P., Tsai, C. H., & Tsai, T. P. (2010). A study of an enhanced simulation model for TOC supply chain replenishment system under capacity constraint. Expert Systems with Applications, 37(9), 6435–6440. https://doi.org/10.1016/j.eswa.2010.02.074
  • Wu, H. H., Huang, H. H., & Jen, W. T. (2012). A Study of the elongated replenishment frequency of TOC Supply Chain replenishment systems in plants. International Journal of Production Research, 50(19), 5567–5581. https://doi.org/10.1080/00207543.2011.649803
  • Wu, H. H., Liao, M. Y., Tsai, C. H., Tsai, S. C., Lu, M. J., & Tsai, T. P. (2013). A study of theory of constraints supply chain replenishment system. International Journal of Academic Research in Accounting, Finance and Management Sciences, 3(3), 78–88. https://doi.org/10.6007/IJARAFMS/v3-i3/38.
  • Yuan, K. J., Chang, S. H., & Li, R. K. (2003). Enhancement of theory of constraints replenishment using a novel generic buffer management procedure. International Journal of Production Research, 41(4), 725–740. https://doi.org/10.1080/0020754031000065502
  • Zemzam, A., El Maataoui, M., Hlyal, M., El Alami, J., & El Alami, N. (2017). Inventory management of supply chain with robust control theory: literature review. International Journal of Logistics Systems and Management, 27(4), 438–465. https://doi.org/10.1504/IJLSM.2017.085223

Reprints and Corporate Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

To request a reprint or corporate permissions for this article, please click on the relevant link below:

Academic Permissions

Please note: Selecting permissions does not provide access to the full text of the article, please see our help page How do I view content?

Obtain permissions instantly via Rightslink by clicking on the button below:

If you are unable to obtain permissions via Rightslink, please complete and submit this Permissions form. For more information, please visit our Permissions help page.