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Production Line Layout Planning Based on Complexity Measurement

Authors: Guoliang Fan, Aiping Li, Nan Xie, Liyun Xu, Xuemei Liu


Mass customization production increases the difficulty of the production line layout planning. The material distribution process for variety of parts is very complex, which greatly increases the cost of material handling and logistics. In response to this problem, this paper presents an approach of production line layout planning based on complexity measurement. Firstly, by analyzing the influencing factors of equipment layout, the complexity model of production line is established by using information entropy theory. Then, the cost of the part logistics is derived considering different variety of parts. Furthermore, the function of optimization including two objectives of the lowest cost, and the least configuration complexity is built. Finally, the validity of the function is verified in a case study. The results show that the proposed approach may find the layout scheme with the lowest logistics cost and the least complexity. Optimized production line layout planning can effectively improve production efficiency and equipment utilization with lowest cost and complexity.

Keywords: Production line, layout planning, complexity measurement, optimization, mass customization.

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[1] S. A. A. Naqvi, M. Fahad, M. Atir, M. Zubair, and M. M. Shehzad. “Productivity improvement of a manufacturing facility using systematic layout planning.” Cogent Engineering, vol.3, no.1, pp.1-13, Jul. 2016.
[2] K. Efthymiou, A. Pagoropoulos, N. Papakostas, D. Mourtzis, and G. Chryssolouris. “Manufacturing systems complexity review: challenges and outlook.” Procedia CIRP, vol. 3, no.1, pp.644-649, 2012.
[3] C. C. Gao, Z. L. Wang, and W. C. Tang. “Complex systems' facility layout optimization method based on dynamic demand.” Computer Integrated Manufacturing Systems, vol.16, no.9, pp.1921-1927, 2010.
[4] J. Z. Huang, A. P. Li, X. M. Liu, and N. Xie. “Optimal design of production line layout considering buffer allocation.” Journal of Tongji University, vol.43, no.7, pp.1075-1081, 2015.
[5] Z. Taha, F. Tahriri, and A. Zuhdi. “Job sequencing and layout optimization in virtual production line.” Journal of Quality, vol.18, no.4, pp.351-374, 2011.
[6] I. Suemitsu, K. Izui, T. Yamada, S. Nishiwaki, A. Noda, and T. Nagatani. “Simultaneous optimization of layout and task schedule for robotic cellular manufacturing systems.” Computers & Industrial Engineering. vol.102, no.1, pp.396-407, 2016.
[7] T. Berlec, P. Potočnik, E. Govekar, and M. Starbek. “A method of production fine layout planning based on self-organising neural network clustering.” International Journal of Production Research, vol.52, no.24, pp.7209-7222, 2014.
[8] R. D. Prasad, K. V. Kumar, and P. A. Jeeva. “Systematic Layout Planning and Balancing of Engine Production Processes for After Test and After Paint Assembly Lines.” International Journal of Vehicle Structures & Systems, vol.8, no.1, pp.41-44, 2016.
[9] I. N. Papadaki, and A. P. Chassiakos. “Multi-objective Construction Site Layout Planning Using Genetic Algorithms.” Procedia Engineering, vol.164, pp.20-27, 2016.
[10] H. Wang, X. Zhu, H. Wang, S. J. Hu, Z. Lin, and G. Chen. “Multi-objective optimization of product variety and manufacturing complexity in mixed-model assembly systems”. Journal of Manufacturing Systems, vol.30, no.1, pp.16-27, 2011.
[11] H. A. ElMaraghy, O. Kuzgunkaya, and R. J. Urbanic. “Manufacturing systems configuration complexity.” CIRP Annals - Manufacturing Technology, vol.54, no.1, pp.445-450, 2005.