Document Type : Research Paper

Authors

1 Bu-Ali Sina University

2 Department of Industrial Engineering, Faculty of Engineering, Bu-Ali Sina University, Hamedan, Iran

Abstract

In the recent years, robots have been widely used in assembly systems as called robotic assembly lines where a set of tasks have to be assigned to stations and each station needs to select one of the different robots to process the assigned tasks. Our focus is on u-type layouts because they are widely employed in many industries due to their efficiency and flexibility . In these lines, a worker can be assigned to multiple stations located at entrance and exit sides. However, in many realistic situations, robots may be unavailable during the scheduling horizon for different reasons, such as breakdowns. This research deals with line balancing under uncertainty The Objective in this research is minimizing the cycle time for a given number of workstations and minimizing robot cost.This research deals with line balancing under uncertainty and presents one robust optimization model for balancing and sequencing of u-shaped robotic assembly line with considering set up times between task, failure robot times and preventive maintenance times for every robot. Since the NP-hard nature of the problem, multi-objective harmony search is developed to solve it. Numerical experiments also demonstrated that by increasing uncertainty level, the objective function values, cost and cycle times (minimum, maximum and average) increased. performance of the robust approach by the results, shows that in real conditions, considering the probability of event failure, values of cycle time and cost change significantly, which indicates the need to consider uncertainty, especially failure in robotic assembly lines.

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Aase, G.R., Olson, J.R., Schniederjans M.J (2004), “U-shaped assembly line layouts and their impact on labor productivity: an experimental study”, European Journal of Operational Research, 156(3), 698–711.
Akpinar, S., Baykasoglu, A (2014), “Modeling and solving mixed-model assembly line balancing problem with setups. Part I: a mixed integer linear programming model”, Journal of Manufacturing Systems, 33 (1), 177–187.
Ben-Tal, A., Ghaoui, L.E., Nemirovski, A (2009), “Robust optimization”, Princeton series in applied mathematics, Princeton University press.
Hazir, Ö., Dolgui, A (2013), “Assembly line balancing under uncertainty: Robust optimization models and exact solution method”, Computers & Industrial Engineering, 65, 261–267.
Hazir, Ö., Dolgui, A (2015), “A decomposition-based solution algorithm for utype assembly line balancing with interval data”, Computers & Operations Research, 59, 126–131.
Hwang, R.K., Katayama, H., Gen, M (2008), “U-shaped assembly line balancing problem with genetic algorithm”, International Journal of Production Research, 46(16), 4637-4649.
Jin, W.He, Z.Wu, Q. (2021), “Robust optimization of resource-constrained assembly line balancing problems with uncertain operation times”, Engineering Computations, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/EC-01-2021-0061.
Li, Z., Ding, R., Floudas, C.A. (2011), “A Comparative Theoretical and Computational Study on Robust Counterpart Optimization: I. Robust Linear Optimization and Robust Mixed Integer Linear Optimization”, Industrial & Engineering Chemistry Research, 50(18), 10567–10603.
Liu, X., Yang, X., Lei, M. (2021). “Optimisation of mixed-model assembly line balancing problem under uncertain demand”. Journal of Manufacturing Systems, 59, 214-227.
Lu, Z., Cui, W., Han, X (2015), “production and preventive maintenance scheduling for a single machine with failure uncertainty”, Computers & Industrial Engineering, 80, 236–244.
Miltenburg, J (2001), “U-shaped production lines: a review of theory and practice”, International Journal of Production Economics, 70(3), 201–214.
Nilakantan, J.M., Nielsen, I., Ponnambalam, S.G., Venkataramanaiah, S (2016), “Differential evolution algorithm for solving RALB problem using cost and time-based models”, International Journal of Advanced Manufacturing Technology, 89, 311–332.
Nilakantan, J.M., Ponnambalam, S.G. (2015), “Robotic U-shaped assembly line balancing using particle swarm optimization”, Engineering Optimization, 48(2), 231-252.
Nilakantan, J.M., Ponnambalam, S.G., Jawahar, N (2016), “Design of energy efficient RAL system using evolutionary algorithms”, Engineering Computations, 33(2), 580-602.
Nourmohammadi, A., Zandieh, M., Tavakkoli-Moghaddam, R. (2013), “An imperialist competitive algorithm for multi-objective U-type assembly line design”, Journal of Computational Science.
Oksuz, M.K., Buyukozkan, K., Satoglu, S.I. (2017), “U-shaped Assembly Line Worker Assignment and Balancing Problem: A Mathematical Model and Two Meta-heuristics”, Computers & Industrial Engineering, 112, 246-263.
Özcan, U. (2019). “Balancing and scheduling tasks in parallel assembly lines with sequence-dependent setup times”, International Journal of Production Economics, International Journal of Production Economics, 213, 81-96.
Pereira, J. (2018), “The Robust (minmax regret) assembly line worker assignment and balancing problem”, Computers and Operations Research, 93, 27-40.
Pereira, J., Miranda, E.A. (2017), “An exact approach for the robust assembly line balancing problem”, Omega, 78, 85-98.
Pereira, J., Ritt, M., Vasquez, O.C. (2018), “A memetic algorithm for the Cost-oriented Robotic Assembly Line Balancing Problem”, Computers and Operations Research, 99, 249-261.
Purnomo, H.D., Wee, H.M. (2014), “Maximizing production rate and workload balancing in a two-sided assembly line using Harmony Search”, Computers & Industrial Engineering, 76, 222–230.
Rabbani, M., Moghaddam, M., Manavizadeh, N (2012), “Balancing of mixed model two-sided assembly lines with multiple u-shaped layout”, The International Journal of Advanced Manufacturing Technology, 59, 1191–1210.
 Rabbani, M., Mousavi, Z. Farrokhi-Asl, H (2016), “Multi-objective metaheuristics for solving a type II robotic mixed-model assembly line balancing problem”, Journal of Industrial and Production Engineering, 33(7), 472–484.
Rubinovitz, J., Bukchin, J. (1991). “Design and balancing of robotic assembly lines”. In: Proceedings of the fourth world conference on robotics research, Pittsburgh, PA.
Samouei, P. & Ashayeri, J (2019), “Developing Optimization & Robust Models for a Mixed-Model Assembly Line Balancing Problem with Semi-Automated Operations”, Applied Mathematical Modelling, 72, 259-275.
Sirovetnukul, R. & Chutima, P (2010), “The impact of walking time on U-shaped assembly line worker allocation problems”, Engineering Journal, 14(2), 53-78.
Sivasubramani, S. & Swarup, K.S. (2011), “Multi-objective harmony search algorithm for optimal power flow problem”, Electrical Power and Energy Systems 33(3), 745–752.
Sobaszek Ł., Gola A., Świć A. (2022), “The Algorithms for Robust Scheduling of Production Jobs Under Machine Failure and Variable Technological Operation Times”, In: Machado J., Soares F., Trojanowska J., Ivanov V. (eds) Innovations in Industrial Engineering. icieng 2021. Lecture Notes in Mechanical Engineering. Springer, Cham. https://doi.org/10.1007/978-3-030-78170-5_6.
Thomopoulos, N.T. (2014) “Assembly line planning and control”, Stuart School of Business Illinois Institute of Technology, Chicago, IL, USA
Toksarı, M.D., İşleyen, S.K., Güner, E. & Baykoç, Ö.F. (2008), “Simple and U-type assembly line balancing problems with a learning effect”, Applied Mathematical Modelling, 32(12), 2954-2961.
Yılmaz, Ö. F. (2020). “Robust optimization for U-shaped assembly line worker assignment and balancing problem with uncertain task times”. Croatian Operational Research Review, 229-239.
Zhang, Z., Tang, Q. & Zhang, L (2019), “Mathematical model and grey wolf optimization for low-carbon and low-noise U-shaped robotic assembly line balancing problem”, Journal of Cleaner Production, 215, 744-756.
Zhang, Z., Tang, Q., Chica, M. (2021). “A robust MILP and gene expression programming based on heuristic rules for mixed-model multi-manned assembly line balancing”. Applied Soft Computing, 107513.
Zhou, B., Wu, Q. (2020). “Decomposition-based bi-objective optimization for sustainable robotic assembly line balancing problems”. Journal of Manufacturing Systems, 55, 30-43.