Abstract
Mass customization production is the next stage in the development of production systems that combines an individual approach to the client needs and benefits of mass production. This approach forces manufacturers to seek new, more effective methods of production flow planning, in particular methods for solving the assembly line balancing problem. The traditional approaches and methods proposed for solving balancing problems require adaptation to new constraints associated with the increasingly widespread introduction of multi-manned and spatially divided assembly workstations. This requires considering additional location restrictions and a more complex allocation of tasks in contrast to restricted only by technological precedencies and time constraints for Simple Assembly Line Balancing Problem. The paper presents a proposal for solving the problem of line balancing with location constraints using new hybrid heuristic algorithm, which is a combination of a modified RPW algorithm and a local search of task sequence on assembly stations zones. Moreover, the concepts of smoothness and efficiency is referred to two separate areas: stations and employees. Experimental results for the literature case of a 30 tasks problem indicate the effectiveness of the proposed approach in practice.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Pape, T.: Heuristics and lower bounds for the simple assembly line balancing problem type 1: Overview, computational tests and improvements. Eur. J. Oper. Res. 240(1), 32–42 (2015). https://doi.org/10.1016/j.ejor.2014.06.023
Gansterer, M., Hartl, R.F.: One- and two-sided assembly line balancing problems with real-world constraints. Int. J. Prod. Res. 56(8), 3025–3042 (2018). https://doi.org/10.1080/00207543.2017.1394599
Make, M.R.A., Rashid, M.F.F.A., Razali, M.M.: A review of two-sided assembly line balancing problem. Int. J. Adv. Manuf. Technol. 89, 1743 (2017). https://doi.org/10.1007/s00170-016-9158-3
Zemczak, M., Skolud, B., Krenczyk, D.: Two-stage orders sequencing system for mixed-model assembly. In: IOP Conference Series: Materials Science and Engineering, vol. 95, p. 012130 (2015). https://doi.org/10.1088/1757-899x/95/1/012130
Rashid, M.F.F., Hutabarat, W., Tiwari, A.: A review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches. Int. J. Adv. Manuf. Technol. 59, 335 (2012). https://doi.org/10.1007/s00170-011-3499-8
Fathi, M., Ghobakhloo, M.: A technical comment on “a review on assembly sequence planning and assembly line balancing optimisation using soft computing approaches”. Int. J. Adv. Manuf. Technol. 71, 2033–2042 (2014). https://doi.org/10.1007/s00170-014-5613-1
Tuncel, G., Topaloglu, S.: Assembly line balancing with positional constraints, task assignment restrictions and station paralleling: a case in an electronics company. Comput. Ind. Eng. 64(2), 602–609 (2012). https://doi.org/10.1016/j.cie.2012.11.006
Cheng, Y., Sun, F., Zhang, Y., Tao, F.: Task allocation in manufacturing: a review. J. Ind. Inf. Integr. (2018, in press). https://doi.org/10.1016/j.jii.2018.08.001
Krenczyk, D., Skolud, B., Herok, A.: A heuristic and simulation hybrid approach for mixed and multi model assembly line balancing. Adv. Intell. Syst. Comput. 637, 99–108 (2018). https://doi.org/10.1007/978-3-319-64465-3_10
Hamid, Y., Mustafa, Y.: Multi-manned assembly line balancing problem with balanced load density. Assem. Autom. 35(1), 137–142 (2015). https://doi.org/10.1108/AA-05-2014-041
Dimitriadis, S.G.: Assembly line balancing and group working: a heuristic procedure for workers’ groups operating on the same product and workstation. Comput. Oper. Res. 33(9), 2757–2774 (2006). https://doi.org/10.1016/j.cor.2005.02.027
Roshani, A., Roshani, A., Roshani, A., Salehi, M., Esfandyari, A.: A simulated annealing algorithm for multi-manned assembly line balancing problem. J. Manuf. Syst. 32(1), 238–247 (2013). https://doi.org/10.1016/j.jmsy.2012.11.003
Prasad, M.M., Ganesan, K., Suresh, R.K.: An optimal balancing of multiple assembly line for a batch production unit. Int. J. Lean Think. 4(2), 22–32 (2013)
Krenczyk, D., Dziki, K.: A multi-manned assembly line balancing in spatial restrictions. In: Knosala, R. (ed.) Management Engineering. Digitalization of Production. Research news, PWE Warszawa (2019, in press). (in polish)
Grzechca, W.: Estimation of time and cost oriented assembly line balancing problem. In: 19th International Conference on Systems Engineering, Las Vegas, NV, pp. 248–253 (2008). https://doi.org/10.1109/icseng.2008.48
Assembly Line Balancing Data sets & Research topics (2019). https://assembly-line-balancing.de/. Accessed 01 Feb 2019
Scholl, A.: Data of assembly line balancing problem. Darmstadt Technical University (1993)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Switzerland AG
About this paper
Cite this paper
Krenczyk, D., Dziki, K. (2020). A Hybrid Heuristic Algorithm for Multi-manned Assembly Line Balancing Problem with Location Constraints. In: Martínez Álvarez, F., Troncoso Lora, A., Sáez Muñoz, J., Quintián, H., Corchado, E. (eds) 14th International Conference on Soft Computing Models in Industrial and Environmental Applications (SOCO 2019). SOCO 2019. Advances in Intelligent Systems and Computing, vol 950. Springer, Cham. https://doi.org/10.1007/978-3-030-20055-8_32
Download citation
DOI: https://doi.org/10.1007/978-3-030-20055-8_32
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-030-20054-1
Online ISBN: 978-3-030-20055-8
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)