Abstract
Two mathematical models are proposed in order to obtain assembly line configurations that guarantee a maximum productivity while the ergonomic risk of workstations is controlled and the available space for the line is respected. Both models, with different optimization approaches, are assessed through a daily demand plan linked with the Nissan powertrain plant in Barcelona. Results show the influence of limitations on the efficient assignment of operations to workstations of the line. The effectiveness of models for establishing the number of workstations and the cycle time of the assembly line that maximizes productivity is demonstrated given a demand plan.
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Notes
- 1.
The ideal cycle time is equal to the average of processing times of operations in regard with the number of workstations of the assembly line.
References
Baybars I (1986) A survey of exact algorithms for the simple assembly line balancing problem. Manag Sci 32(8):909–93. https://doi.org/10.1287/mnsc.32.8.909
Battaïa O, Dolgui A (2012) Reduction approaches for a generalized line balancing problem. Comput Oper Res 39(10):2337–2345. https://doi.org/10.1016/j.cor.2011.11.022
Bautista J, Alfaro-Pozo R (2017) Minimizing the ergonomic risk dispersion between the workstations of an assembly line. In: Proceedings of the 11th International Conference on Industrial Engineering and Industrial Management. XXI Congreso de Ingeniería de Organización, Valencia. https://www.researchgate.net/publication/318362597
Bautista J, Alfaro-Pozo R, Batalla-García C (2016a) Maximizing comfort in assembly lines with temporal, spatial and ergonomic attributes. Int J Comput Intell Syst 9(4):788–799. http://doi.org/10.1080/18756891.2016.1204125
Bautista J, Batalla-García C, Alfaro-Pozo R (2016b) Models for assembly line balancing by temporal, spatial and ergonomic risk attributes. Eur. J. Oper. Res. 251:814–829. https://doi.org/10.1016/j.ejor.2015.12.042
Bautista J, Pereira J (2007) Ant algorithms for a time and space constrained assembly line balancing problem. Eur J Oper Res 177(3):2016–2032. https://doi.org/10.1016/j.ejor.2005.12.017
Esmaeilbeigi R, Naderi B, Charkhgard P (2015) The type E simple assembly line balancing problem: a mixed integer linear programming formulation. Comput Oper Res 64:168–177. https://doi.org/10.1016/j.cor.2015.05.017
Otto A, Battaïa O (2017) Reducing physical ergonomic risks at assembly lines by line balancing and job rotation: a survey. Comput Ind Eng 111:467–480. https://doi.org/10.1016/j.cie.2017.04.011
Scholl A, Becker C (2006) State-of-the-art exact and heuristic solution procedures for simple assembly line balancing. Eur J Oper Res 168(3):666–693. https://doi.org/10.1016/j.ejor.2004.07.022
Th Zacharia P, Nearchou AC (2013) A meta-heuristic algorithm for the fuzzy assembly line balancing type-E problem. Comput Oper Res 40(12):3033–3040. https://doi.org/10.1016/j.cor.2013.07.012
Acknowledgements
This research was subsidized by the Ministry of Economy and Competitiveness of the Government of Spain through project OPTHEUS (ref. PGC2018-095080-B-I00), including European Regional Development Funds (ERDF).
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Bautista, J., Alfaro-Pozo, R. (2020). A MILP Approach to Maximize Productivity in Mixed-Model Assembly Lines. In: de Castro, R., Giménez, G. (eds) Advances in Engineering Networks. ICIEOM 2018. Lecture Notes in Management and Industrial Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-44530-0_18
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