Author(s)

Necip Akar ¹, Safiye Turgay ¹

Affiliation(s)

¹ Department of Industrial Engineering, Sakarya University, Sakarya, Turkey

Corresponding Author

Necip Akar

ABSTRACT

Cellular manufacturing is a lean manufacturing approach that involves grouping machines, processes, and workstations into self-contained cells to reduce material handling, waiting times, and inventory. The layout design of cellular manufacturing facilities has a significant impact on their efficiency, productivity, and throughput. However, traditional trial-and-error methods for facility layout design can be time-consuming, costly, and risky. Digital twin simulation offers a powerful alternative by allowing designers to create virtual models of the facility and test different layout configurations before physically implementing them. Our study shows that digital twin simulation can help identify the optimal layout design that maximizes productivity, minimizes waste, and ensures the smooth flow of materials and products. Additionally, it enables us to evaluate the impact of changes in the production system on the facility's performance, helping decision-makers make informed decisions. Overall, this paper highlights the potential of digital twin simulations as a powerful tool for optimizing cellular manufacturing facility layout design and improving operational performance.

KEYWORDS

Digital Twin, Cellular Manufacturing, Simulation, Mathematical Modelling

CITE THIS PAPER

Necip Akar, Safiye Turgay, Optimizing Cellular Manufacturing Facility Layout Design through Digital Twin Simulation: A Case Study. Industrial Engineering and Innovation Management (2023) Vol. 6: 1-12. DOI: http://dx.doi.org/10.23977/ieim.2023.060601.

REFERENCES

[1] Liu D., Wang X., & Wu X. (2021). A digital twin-based optimization method for the layout design of cellular manufacturing systems. International Journal of Production Research, 1-21
[2] J. Ren et al. (2020). A digital twin-driven approach to optimizing the layout of a manufacturing workshop. Robotics and Computer-Integrated Manufacturing, 63, 101942
[3] Jiang P., Wang W., Zhang C., & Li H. (2019). A digital twin based approach for the layout optimization of cellular manufacturing systems. Journal of Cleaner Production, 232, 1178-1189
[4] Lee J., Lee S., & Kim Y. (2019). Digital twin-based design of a cellular manufacturing system for improved production efficiency. Journal of Manufacturing Systems, 50, 8-21
[5] Chen W., Gao L., & Li Y. (2021). Cellular manufacturing system layout optimization based on a digital twin simulation. Journal of Cleaner Production, 311, 127704
[6] Zhang Y., Liu Y., Cheng Y., Li J., & Li Y. (2021). Digital twin-based intelligent manufacturing: A review. Journal of Manufacturing Systems, 61, 1-13
[7] Khan S., Farnsworth M., McWilliam R., Erkoyuncu J., On the requirements of digital twin-driven autonomous maintenance, Annual Reviews in Control, Volume 50, 2020, Pages 13-28, ISSN 1367-5788, https: // doi. org/ 10. 1016/ j. arcontrol. 2020.08.003.
[8] T. Li et al. (2020). A digital twin-based simulation method for layout optimization of a flexible manufacturing system. Journal of Manufacturing Systems, 55, 273-286
[9] Wang F., Lv J., & Guo Q. (2019). Digital twin-driven optimization for smart manufacturing. Robotics and Computer-Integrated Manufacturing, 58, 165-175
[10] Jiangfeng Cheng, He Zhang, Fei Tao, Chiafeng Juang, DT-II:Digital twin enhanced Industrial Internet reference framework towards smart manufacturing,Robotics and Computer-Integrated Manufacturing,Volume 62, 2020, 101881, ISSN 0736-5845, https://doi.org/10.1016/j.rcim.2019.101881
[11] Zhang X, Shen J, Saini PK, Lovati M, Han M, Huang P and Huang Z (2021) Digital Twin for Accelerating Sustainability in Positive Energy District: A Review of Simulation Tools and Applications. Front. Sustain. Cities 3:663269. doi: 10.3389/frsc.2021.663269
[12] Vahidnia M. H., & Alesheikh A. A. (2014). Ontological exploration of geospatial objects in context. Geo-spatial Information Science, 17(2), 129-138.
[13] Wang C., Wang X., & Zheng L. (2020). A review of digital twin technology: from concept to application. Journal of Cleaner Production, 271, 122754
[14] Wang Z., Huang G. Q., & Hu H. (2021). Digital twin-based production system design and optimization. Journal of Manufacturing Systems, 60, 166-183
[15] Turgay S., Bilgin Ö., Akar N., Digital Twin Based Flexible Manufacturing System Modelling with Fuzzy Approach. Advances in Computer, Signals and Systems (2022) Vol. 6: 10-17. DOI: http://dx.doi.org/10.23977/acss.2022.060702
[16] Xu X. W., & Chen L. (2018). Digital twin and its industrial prospects. Journal of Manufacturing Systems, 48, 157-165
[17] Lu J., Wang Z., & Chen Y. (2021). Digital twin modeling and simulation of a cellular manufacturing system: A case study. Journal of Manufacturing Systems, 59, 82-92
[18] Ma Y., Wang F., Li Y., & Zhao Y. (2021). A simulation-based optimization approach for cellular manufacturing system layout design. Journal of Intelligent Manufacturing, 32(2), 471-482
[19] Min S., Ko H., & Lee S. (2016). Cellular manufacturing systems: literature review, analysis, and future research directions. International Journal of Precision Engineering and Manufacturing-Green Technology, 3(2), 209-227
[20] Ng A. H., Tan R. R., & Chiu Y. P. (2019). Digital twin: The paradigm shift towards customer-centric design in manufacturing. Journal of Manufacturing Systems, 52, 146-156
[21] Alves M., Barbosa J., & Carvalho H. (2019). A digital twin approach for factory layout optimization. Procedia CIRP, 84, 485-490
[22] Xue Y., Liu Y., Guo Q., & Wang H. (2020). Simulation optimization of cellular manufacturing system layout based on digital twin. Journal of Intelligent Manufacturing, 31(4), 793-806
[23] Saha S., Saha S., & Mondal S. (2021). Digital twin-based optimization of cellular manufacturing system layout considering multiple objectives. International Journal of Production Research, 59(13), 3867-3885 

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