Abstract
In smart manufacturing practices, finding a balance between the size of cyber-physical system (CPS) deployment and the performance of production systems is the preliminary goal pursued by some small or medium-sized one-of-a-kind production enterprises with limited resources in implementing the transformation of smart production systems. To achieve this goal, we first address the pull control strategies in lean production systems as a principle to guide the CPS deployment for shop floors. Specifically, we use the Path-based bottleneck (PBB), Constant work-in-process (CONWIP), and Capacity-slack CONWIP (CSC) as pull CPS deployment schemes, in which the CSC is a modified CONWIP strategy that integrates the order review function of the PBB. We summarize the characteristics of these pull control strategies and analyze important roles in guiding the CPS deployment. Then, we compare the performance of the three pull control strategies by simulation. Our findings show that it is feasible to get the balance between the size of CPS deployment and the system performance through a suitable pull control strategy to guide CPS deployment. Finally, we introduce a case of a strander manufacturer and use the case data to estimate the performance and implementation costs of the CPS deployment schemes which are guided by pull control strategies.
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References
Ajorlou, S., & Shams, I. (2013). Artificial bee colony algorithm for CONWIP production control system in a multi-product multi-machine manufacturing environment. Journal of Intelligent Manufacturing, 24, 1145–1156. https://doi.org/10.1007/s10845-012-0646-5.
Alfnes, E., & Skjelstad, L. (2009). How to implement a mass customization strategy: Guidelines for manufacturing companies. In F. T. Piller & M. M. Tseng (Eds.), Handbook of research in mass customization and personalization (pp. 44–64). World Scientific Publishing Company.
Cheng, Y., Zhang, Y., Ji, P., Xu, W., Zhou, Z., & Tao, F. (2018). Cyber-physical integration for moving digital factories forward towards smart manufacturing: A survey. The International Journal of Advanced Manufacturing Technology, 97, 1209–1221. https://doi.org/10.1007/s00170-018-2001-2.
Fredendall, L. D., Ojha, D., & Wayne Patterson, J. (2010). Concerning the theory of workload control. European Journal of Operational Research, 201, 99–111. https://doi.org/10.1016/j.ejor.2009.02.003.
Germs, R., & Riezebos, J. (2010). Workload balancing capability of pull systems in MTO production. International Journal of Production Research, 48, 2345–2360. https://doi.org/10.1080/00207540902814314.
Gill, H. (2006). NSF perspective and status on cyber-physical systems. Austin, TX: National Workshop on Cyber-Physical Systems.
González-R, P. L., Framinan, J. M., & Pierreval, H. (2012). Token-based pull production control systems: An introductory overview. Journal of Intelligent Manufacturing, 23, 5–22. https://doi.org/10.1007/s10845-011-0534-4.
Harrod, S., & Kanet, J. J. (2013). Applying work flow control in make-to-order job shops. International Journal of Production Economics, 143, 620–626. https://doi.org/10.1016/j.ijpe.2012.02.017.
Hopp, W. J., Iravani, S. M. R., Shou, B., & Lien, R. (2009). Design and control of agile automated CONWIP production lines. Naval Research Logistics, 56, 42–56. https://doi.org/10.1002/nav.20325.
Huang, G., & Chen, J. (2017). Making CONWIP scheme in one-of-a-kind production: A case study. In Y. Khojasteh (Ed.), Production management: Advanced tools, models, and applications for pull systems (pp. 143–160). Boca Raton, FL: CRC Press.
Huang, G., Chen, J., Wang, X., Shi, Y., & Tian, H. (2017). From loop structure to policy-making: A CONWIP design framework for hybrid flow shop control in one-of-a-kind production environment. International Journal of Production Research, 55, 3374–3391. https://doi.org/10.1080/00207543.2016.1234723.
Ip, W. H., Yung, K. L., Huang, M., & Wang, D. (2002). A CONWIP model for FMS control. Journal of Intelligent Manufacturing, 13, 109–117. https://doi.org/10.1023/a:1014532129642.
Kagermann, H., Wahlster, W., & Helbig, J. (2013). Recommendations for implementing the strategic initiative INDUSTRIE 4.0. Frankfurt.
Kolberg, D., Knobloch, J., & Zühlke, D. (2016). Towards a lean automation interface for workstations. International Journal of Production Research, 55, 2845–2856. https://doi.org/10.1080/00207543.2016.1223384.
Land, M. J. (2009). Cobacabana (control of balance by card-based navigation): A card-based system for job shop control. International Journal of Production Economics, 117, 97–103. https://doi.org/10.1016/j.ijpe.2008.08.057.
Li, B. M., Xie, S. Q., & Xu, X. (2011). Recent development of knowledge-based systems, methods and tools for One-of-a-Kind Production. Knowledge-Based Systems, 24, 1108–1119. https://doi.org/10.1016/j.knosys.2011.05.005.
Liu, X., & Tu, Y. L. (2008). Capacitated production planning with outsourcing in an OKP company. International Journal of Production Research, 46, 5781–5795. https://doi.org/10.1080/00207540701348779.
Luo, X., Li, W., Tu, Y., Xue, D., & Tang, J. (2010). Optimal resource allocation for hybrid flow shop in one-of-a-kind production. International Journal of Computer Integrated Manufacturing, 23, 146–154. https://doi.org/10.1080/09511920903440339.
Ma, J., Wang, Q., & Zhao, Z. (2017). SLAE-CPS: Smart lean automation engine enabled by cyber-physical systems technologies. Sensors (Basel, Switzerland). https://doi.org/10.3390/s17071500.
Monostori, L., Kádár, B., Bauernhansl, T., Kondoh, S., Kumara, S., Reinhart, G., et al. (2016). Cyber-physical systems in manufacturing. CIRP Annals, 65, 621–641. https://doi.org/10.1016/j.cirp.2016.06.005.
Morgan, J., & O’Donnell, G. E. (2018). Cyber physical process monitoring systems. Journal of Intelligent Manufacturing, 29, 1317–1328. https://doi.org/10.1007/s10845-015-1180-z.
Philipoom, P. R., Malhotra, M. K., & Jensen, J. B. (1993). An evaluation of capacity sensitive order review and release procedures in job shops. Decision Sciences, 24, 1109–1134. https://doi.org/10.1111/j.1540-5915.1993.tb00506.x.
Piplani, R., & Ang, A. W. H. (2018). Performance comparison of multiple product kanban control systems. International Journal of Production Research, 56, 1299–1312. https://doi.org/10.1080/00207543.2017.1332436.
Prakash, J., & Chin, J. F. (2015). Modified CONWIP systems: A review and classification. Production Planning & Control, 14, 1–12. https://doi.org/10.1080/09537287.2014.898345.
Rajkumar, R., Lee, I., Sha, L., & Stankovic, J. (2010). Cyber-physical systems. In S. Sapatnekar (Ed.), The 47th design automation conference, Anaheim, California, 2010-6-13-2010-6-18 (p. 731). New York, NY: ACM Press. https://doi.org/10.1145/1837274.1837461.
Ribeiro, L., & Bjorkman, M. (2018). Transitioning from standard automation solutions to cyber-physical production systems: An assessment of critical conceptual and technical challenges. IEEE Systems Journal, 12, 3816–3827. https://doi.org/10.1109/JSYST.2017.2771139.
Sabuncuoglu, I., & Karapinar, H. Y. (2000). A load-based and due-date-oriented approach to order review/release in job shops. Decision Sciences, 31, 413–447. https://doi.org/10.1111/j.1540-5915.2000.tb01629.x.
Spearman, M., Woodruff, D., & Hopp, W. (1990). CONWIP: A pull alternative to kanban. International Journal of Production Research, 28, 879–894. https://doi.org/10.1080/00207549008942761.
Stump, B., & Badurdeen, F. (2012). Integrating lean and other strategies for mass customization manufacturing: A case study. Journal of Intelligent Manufacturing, 23, 109–124. https://doi.org/10.1007/s10845-009-0289-3.
Suri, R. (1998). Quick response manufacturing: A companywide approach to reducing lead times/Rajan Suri. Portland, OR: Productivity Press.
Thürer, M., Fernandes, N. O., Stevenson, M., & Qu, T. (2017). On the backlog-sequencing decision for extending the applicability of ConWIP to high-variety contexts: an assessment by simulation. International Journal of Production Research, 55, 4695–4711. https://doi.org/10.1080/00207543.2017.1281462.
Thürer, M., Land, M. J., Stevenson, M., Fredendall, L. D., & Godinho Filho, M. (2015). Concerning workload control and order release: The pre-shop pool sequencing decision. Production and Operations Management, 24, 1179–1192. https://doi.org/10.1111/poms.12304.
Thürer, M., Stevenson, M., & Protzman, C. W. (2016). Card-based production control: A review of the control mechanisms underpinning Kanban, ConWIP, POLCA and COBACABANA systems. Production Planning & Control, 27(14), 1143–1157.
Tortorella, G. L., & Fettermann, D. (2018). Implementation of Industry 4.0 and lean production in Brazilian manufacturing companies. International Journal of Production Research, 56, 2975–2987. https://doi.org/10.1080/00207543.2017.1391420.
Tu, Y., & Dean, P. (2011). One-of-a-kind production. London: Springer.
Urbina Coronado, P. D., Lynn, R., Louhichi, W., Parto, M., Wescoat, E., & Kurfess, T. (2018). Part data integration in the Shop Floor Digital Twin: Mobile and cloud technologies to enable a manufacturing execution system. Journal of Manufacturing Systems, 48, 25–33. https://doi.org/10.1016/j.jmsy.2018.02.002.
Wang, L., Törngren, M., & Onori, M. (2015). Current status and advancement of cyber-physical systems in manufacturing. Journal of Manufacturing Systems, 37, 517–527. https://doi.org/10.1016/j.jmsy.2015.04.008.
Yao, X., Zhou, J., Lin, Y., Li, Y., Yu, H., & Liu, Y. (2017). Smart manufacturing based on cyber-physical systems and beyond. Journal of Intelligent Manufacturing, 10, 175. https://doi.org/10.1007/s10845-017-1384-5.
Zhang, K., Qu, T., Zhou, D., Thürer, M., Liu, Y., Nie, D., et al. (2019). IoT-enabled dynamic lean control mechanism for typical production systems. Journal of Ambient Intelligence and Humanized Computing, 10, 1009–1023. https://doi.org/10.1007/s12652-018-1012-z.
Acknowledgements
This work was supported by the Scientific Research Foundation of Xihua university under grant number w202254. We thank the editors and anonymous referees for their helpful comments on earlier versions of our paper.
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Huang, G., Chen, J. & Khojasteh, Y. A cyber-physical system deployment based on pull strategies for one-of-a-kind production with limited resources. J Intell Manuf 32, 579–596 (2021). https://doi.org/10.1007/s10845-020-01589-8
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DOI: https://doi.org/10.1007/s10845-020-01589-8