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Growing Science » International Journal of Industrial Engineering Computations » Aggregate simulation modeling with application to setting the CONWIP limit in a HMLV manufacturing cell

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International Journal of Industrial Engineering Computations
ISSN 1923-2934 (Online) - ISSN 1923-2926 (Print)
Quarterly Publication
Volume 10 Issue 2 pp. 149-160, 2019

Aggregate simulation modeling with application to setting the CONWIP limit in a HMLV manufacturing cell Pages 149-160 PDF Download PDF

Authors: Shahriar Khan, Charles Standridge

📋 Author Affiliations:
Shahriar Khan ORCID 1, Charles Standridge2
1 Grand Rapids Chair Company, 1250 84th St SW, Byron Center, 49315, MI, United States, N/A
2 Grand Valley State University, 301 Fulton Avenue West, Grand Rapids, 49504, MI, United States, N/A
doi 10.5267/j.ijiec.2018.10.002
7 Source: Scopus
Crossref 5 Source: CrossRef

🔑 Keywords: Aggregate simulation modeling, High-Mix, Low-Volume Manufacturing, CONWIP, Production Flow, Discrete-Event Simulation

Abstract: Concepts for aggregate modeling and simulation are presented and applied for the setting of the parameters of a CONWIP flow control system within the steel products cell at Grand Rapids Chair, a high-mix, low-volume manufacturing environment. Aggregation was accomplished by combining the over 100 types of products into one. This resulted in a single arrival process, routing modeled as random movement through workstations, and a single operation time distribution for each production operation. Aggregation reduced the effort required for model development, data analysis, validation, and simulation. The CONWIP control was shown to be effective in managing the work-in-process. A CONWIP parameter of 50 resulted in an equivalent throughput to that achieved with no limit on work-in-process. Lead time can be reduced by approximately 20% by increasing the CONWIP parameter to 58.

How to cite this paper
APA: Khan, S & Standridge, C. (2019). Aggregate simulation modeling with application to setting the CONWIP limit in a HMLV manufacturing cell. International Journal of Industrial Engineering Computations, 10(2), 149-160.
Chicago/Turabian: Khan, S & Standridge, C. 2019. "Aggregate simulation modeling with application to setting the CONWIP limit in a HMLV manufacturing cell." International Journal of Industrial Engineering Computations 10, no. 2 (2019): 149-160.
AMA: Khan, S & Standridge, C. Aggregate simulation modeling with application to setting the CONWIP limit in a HMLV manufacturing cell. International Journal of Industrial Engineering Computations. 2019;10(2):149-160.

References
Banks, J. A., Carson II, J. S., Nelson, B. L. & Nicol, D. M. (2009). Discrete-Event systems simulation, 5th ed. New York : Pearson.
Braglia, M., Frosolini, M., Gabbrielli, R., & Zammori, F. (2011). CONWIP card setting in a flow-shop system with a batch production machine. International Journal of Industrial Engineering Computations, 2(1), 1-18.
Detty, R. B., & Yingling, J. C. (2000). Quantifying benefits of conversion to lean manufacturing with discrete event simulation: a case study. International Journal of Production Research. 38(2), 429-445.
Devore, J. L. (2015). Probability and statistics for engineering and the sciences, 9th . Boston: Cengage Learning.
Etman, L. F. P., Veeger, C. P. L., Lefeber, E., Adan, I. J., & Rooda, J. E. (2011, December). Aggregate modeling of semiconductor equipment using effective process times. In Simulation Conference (WSC), Proceedings of the 2011 Winter (pp. 1790-1802). IEEE.
Hopp, W. J. & Spearman, M. L. (2011). Factory physics: foundations of manufacturing management, 3rd edition. Long Grove, IL : Waveland Press.
Kingman, J. F. C. (1961). The single server queue in heavy traffic. Mathematical Proceedings of the Cambridge Philosophical Society, 57(4), 902
Law, A. M. (2014). Simulation Modeling and Analysis, 5th ed. New York : McGraw-Hill.
Little, J. D. C. (1961). A Proof for the queuing formula: L = λW. Operations Research, 9(3), 383–387.
Maas, M., & Standridge, C. R. (2015). Reducing lead times in a two-process cell using lean and simulation. Research Journal of Applied Sciences, Engineering, and Technology, 10(1), 15-21.
Matt, D. T. (2014). Adaptation of the value stream mapping approach to the design of lean engineer-to-order production systems: a case study. Journal of Manufacturing Technology Management, 25(3), 334-350.
Marvel, J. H. & Standridge, C. R. (2009). A simulation enhanced lean design process. Journal of Industrial Engineering and Management, 2(1), 90-113.
Miller, G., Pawloski, J., & Standridge, C.R. (2010). A case study of lean, sustainable manufacturing. Journal of Industrial Engineering and Management, 3(1), 11-32.
Pergher, I., & Vaccaro, G. L. R. (2014). Work in process level definition: a method based on computer simulation and electre tri. Production, 24(3), 536-547.
Romagnoli, G. (2015). Design and simulation of CONWIP in the complex flexible job shop of a Make-To-Order manufacturing firm. International Journal of Industrial Engineering Computations, 6(1), 117-134.
Sargent, R. G. (2013). Verification and validation of simulation models. Journal of simulation, 7(1), 12-24.
Spearman, M.L., Woodruff, D.L., & Hopp, W.J. (1990). CONWIP: A pull alternative to Kanban. International Journal of Production Research, 28(5), 879-894.
Suri, R. (2010). It’s about time. New York: CRC Press.
Suri, R. (2018). The Practitioner's Guide to POLCA. New York: CRC Press.
Wright, D. & Standridge, C. R. (2016). A case study of lead time reduction by transformation to cellular production. IOSR Journal of Engineering, 6(2), 53-58.
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📚 Journal: International Journal of Industrial Engineering Computations | 📅 Year: 2019 | 📖 Volume: 10 | 📄 Issue: 2 | 👁️ Views: 2468 | 📊 Crossref: 5

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