If the articles do not appear correctly or the list is incomplete, please contact me at contact@celso-sikora.com.
2023
Lübben, Malte; Pries, Sven; Sikora, Celso Gustavo Stall
Online resequencing of buffers for automotive assembly lines Journal Article
In: Computers & Industrial Engineering, vol. 175, pp. 108857, 2023, (accepted manuscript and data available in Links).
@article{Lübben2023,
title = {Online resequencing of buffers for automotive assembly lines},
author = {Malte Lübben and Sven Pries and Celso Gustavo Stall Sikora},
url = {https://celso-sikora.com/publications/L%C3%BCbben_2023_Online-resequencing-of-buffers-for-automotive-assembly-lines.pdf
https://celso-sikora.com/SupplementaryMaterial/Supplemantary_Material_Online-resequencing-of-buffers.zip},
doi = {10.1016/j.cie.2022.108857},
year = {2023},
date = {2023-01-01},
urldate = {2023-01-01},
journal = {Computers & Industrial Engineering},
volume = {175},
pages = {108857},
abstract = {Mixed-model assembly lines are state of the art in automotive production systems. Because of the high number of customizable options which can be ordered in a vehicle, there is a huge variety of possible products. An important problem in this context is the sequencing of such products. Inevitably, there will be deviations from the intended production sequence in the course of production, as disruptions occur. The products must then be resequenced to ensure an optimal sequence. In this work, we consider the usage of a buffer (in form of an automated storage and retrieval system) between the paint shop and the final assembly to resequence the orders. We consider a high number of variants and, with this, a random input sequence for the buffer. Additionally to the physical resequencing in the buffer, the options get decoupled from the products. That allows virtual resequencing, in which parts and materials are interchanged. The dispatching selection must be made without full information in an online problem. To solve this problem, different heuristics and a lookahead algorithm are applied to minimize the amount of utility work in a paced automotive assembly line.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mixed-model assembly lines are state of the art in automotive production systems. Because of the high number of customizable options which can be ordered in a vehicle, there is a huge variety of possible products. An important problem in this context is the sequencing of such products. Inevitably, there will be deviations from the intended production sequence in the course of production, as disruptions occur. The products must then be resequenced to ensure an optimal sequence. In this work, we consider the usage of a buffer (in form of an automated storage and retrieval system) between the paint shop and the final assembly to resequence the orders. We consider a high number of variants and, with this, a random input sequence for the buffer. Additionally to the physical resequencing in the buffer, the options get decoupled from the products. That allows virtual resequencing, in which parts and materials are interchanged. The dispatching selection must be made without full information in an online problem. To solve this problem, different heuristics and a lookahead algorithm are applied to minimize the amount of utility work in a paced automotive assembly line.
2022
Sikora, Celso Gustavo Stall; Weckenborg, Christian
Balancing of assembly lines with collaborative robots: comparing approaches of the Benders’ decomposition algorithm Journal Article
In: International Journal of Production Research, 2022, (accepted manuscript and data available in Links).
@article{Sikora2022,
title = {Balancing of assembly lines with collaborative robots: comparing approaches of the Benders’ decomposition algorithm},
author = {Celso Gustavo Stall Sikora and Christian Weckenborg},
url = {https://celso-sikora.com/publications/Sikora_2022_Balancing-of-assembly-lines-with-collaborative-robots.pdf
https://celso-sikora.com/SupplementaryMaterial/SupplementaryMaterial_Cobots_2022.zip},
doi = {10.1080/00207543.2022.2093684},
year = {2022},
date = {2022-07-04},
urldate = {2022-07-04},
journal = {International Journal of Production Research},
abstract = {In recent years, human workers in manual assembly lines are increasingly being supported by the deployment of complementary technology. Collaborative robots (or cobots) represent a low-threshold opportunity for partial automation and are increasingly being utilised by manufacturing corporations. As collaborative robots can be used to either conduct tasks in parallel to the human worker or collaborate with the worker on an identic task, industrial planners experience an increasingly complex environment of assembly line balancing. This contribution proposes three different decomposition approaches for Benders’ decomposition algorithms exploring the multiple possible partitions of the formulation variables. We evaluate the performance of the algorithms by conducting extensive computational experiments using test instances from literature and compare the findings with results generated by a commercial solver and a metaheuristic solution procedure. The results demonstrate the Benders’ decomposition algorithms’ efficiency of finding exact solutions even for large instances, outperforming the benchmark procedures in computational effort and solution quality.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
In recent years, human workers in manual assembly lines are increasingly being supported by the deployment of complementary technology. Collaborative robots (or cobots) represent a low-threshold opportunity for partial automation and are increasingly being utilised by manufacturing corporations. As collaborative robots can be used to either conduct tasks in parallel to the human worker or collaborate with the worker on an identic task, industrial planners experience an increasingly complex environment of assembly line balancing. This contribution proposes three different decomposition approaches for Benders’ decomposition algorithms exploring the multiple possible partitions of the formulation variables. We evaluate the performance of the algorithms by conducting extensive computational experiments using test instances from literature and compare the findings with results generated by a commercial solver and a metaheuristic solution procedure. The results demonstrate the Benders’ decomposition algorithms’ efficiency of finding exact solutions even for large instances, outperforming the benchmark procedures in computational effort and solution quality.
Sikora, Celso Gustavo Stall
Assembly Line Balancing Under Demand Uncertainty PhD Thesis
2022, ISBN: 978-3-658-36281-2.
@phdthesis{Sikora_PhD_2022,
title = {Assembly Line Balancing Under Demand Uncertainty},
author = {Celso Gustavo Stall Sikora},
url = {https://celso-sikora.com/publications/Thesis_2022_Assembly-line-balancing-under-demand-undertainty.pdf
http://celso-sikora.com/SupplementaryMaterial/Data_PhDThesis_Sikora.zip},
doi = {https://doi.org/10.1007/978-3-658-36282-9},
isbn = {978-3-658-36281-2},
year = {2022},
date = {2022-01-03},
urldate = {2021-00-00},
abstract = {Assembly lines are productive systems, which are very efficient for homogeneous products. In the automotive industry, an assembly line is used in the production of several vehicle variants, including numerous configurations, options, and add-ins. As a result, assembly lines must be at the same time specialized to provide high efficiency, but also flexible to allow the mass customization of the vehicles. In this book, the planning of assembly lines for uncertain demand is tackled and optimization algorithms are offered for the balancing of such lines. Building an assembly line is a commitment of several months or even years, it is understandable that the demand will fluctuate during the lifetime of an assembly line. New products are developed, others are removed from the market, and the decision of the final customer plays a role on the immediate demand. Therefore, the variation and uncertainty of the demand must be accounted for in an assembly line. In this book, methods dealing with random demand or random production sequence are presented, so that the practitioners can plan more robust and efficient production systems.},
keywords = {},
pubstate = {published},
tppubtype = {phdthesis}
}
Assembly lines are productive systems, which are very efficient for homogeneous products. In the automotive industry, an assembly line is used in the production of several vehicle variants, including numerous configurations, options, and add-ins. As a result, assembly lines must be at the same time specialized to provide high efficiency, but also flexible to allow the mass customization of the vehicles. In this book, the planning of assembly lines for uncertain demand is tackled and optimization algorithms are offered for the balancing of such lines. Building an assembly line is a commitment of several months or even years, it is understandable that the demand will fluctuate during the lifetime of an assembly line. New products are developed, others are removed from the market, and the decision of the final customer plays a role on the immediate demand. Therefore, the variation and uncertainty of the demand must be accounted for in an assembly line. In this book, methods dealing with random demand or random production sequence are presented, so that the practitioners can plan more robust and efficient production systems.
2021
Lopes, Thiago Cantos; Michels, Adalberto Sato; Sikora, Celso Gustavo Stall; Brauner, Nadia; Magatão, Leandro
Assembly Line Balancing for two Cycle Times: Anticipating Demand Fluctuations Journal Article
In: Computers & Industrial Engineering, vol. 162, pp. 107685, 2021, (accepted manuscript and data available in Links).
@article{Lopes2021,
title = {Assembly Line Balancing for two Cycle Times: Anticipating Demand Fluctuations},
author = {Thiago Cantos Lopes and Adalberto Sato Michels and Celso Gustavo Stall Sikora and Nadia Brauner and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2021_Assembly-Line-Balancing-for-two-Cycle-Times-Anticipating-Demand-Fluctuations.pdf
https://celso-sikora.com/SupplementaryMaterial/Supporting-Information_Lopes_2021_Assembly-Line-Balancing-for-two-Cycle-Times-Anticipating-Demand-Fluctuations.zip},
doi = {https://doi.org/10.1016/j.cie.2021.107685},
year = {2021},
date = {2021-12-01},
urldate = {2021-12-01},
journal = {Computers & Industrial Engineering},
volume = {162},
pages = {107685},
abstract = {Unpredictable crises such as pandemics, as well as predictable oscillations such as seasonality, can produce significant demand fluctuations. Although it is possible to adapt the manufacturing system to these perturbations, there are significant opportunities in anticipating them in the design stage. This paper proposes the Economically Robust Assembly Line Balancing Problem (ERALBP), which addresses the issue by designing assembly lines to allow flexible alternation between two or more cycle times. A Mixed-Integer Linear Programming (MILP) model is introduced to describe the problem. Moreover, a heuristic procedure is implemented in order to quickly produce high-quality solutions. While the model failed to find solutions for most medium and large instances, the heuristic quickly produced high-quality solutions, reaching low solution gaps even for large instances. Finally, a case study with industrial data further highlights the advantages of the proposed strategy: by anticipating demand fluctuations, the proposed heuristic's solution facilitates alternation between two demand scenarios, both with the optimal number of stations. This approach is less costly than the re-balancing alternative, which requires re-assigning and re-positioning tasks. By enabling companies to perform this fast switching between output rates, we allow them to benefit from economic opportunities tied to increased seasonal effects or unexpected demand spikes.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Unpredictable crises such as pandemics, as well as predictable oscillations such as seasonality, can produce significant demand fluctuations. Although it is possible to adapt the manufacturing system to these perturbations, there are significant opportunities in anticipating them in the design stage. This paper proposes the Economically Robust Assembly Line Balancing Problem (ERALBP), which addresses the issue by designing assembly lines to allow flexible alternation between two or more cycle times. A Mixed-Integer Linear Programming (MILP) model is introduced to describe the problem. Moreover, a heuristic procedure is implemented in order to quickly produce high-quality solutions. While the model failed to find solutions for most medium and large instances, the heuristic quickly produced high-quality solutions, reaching low solution gaps even for large instances. Finally, a case study with industrial data further highlights the advantages of the proposed strategy: by anticipating demand fluctuations, the proposed heuristic's solution facilitates alternation between two demand scenarios, both with the optimal number of stations. This approach is less costly than the re-balancing alternative, which requires re-assigning and re-positioning tasks. By enabling companies to perform this fast switching between output rates, we allow them to benefit from economic opportunities tied to increased seasonal effects or unexpected demand spikes.
Sikora, Celso Gustavo Stall
Benders’ decomposition for the balancing of assembly lines with stochastic demand Journal Article
In: European Journal of Operational Research, vol. 292, pp. 108-124, 2021, (accepted manuscript and data available in Links).
@article{Sikora2021,
title = {Benders’ decomposition for the balancing of assembly lines with stochastic demand},
author = {Celso Gustavo Stall Sikora},
url = {https://celso-sikora.com/publications/Sikora_2021_Benders-decomposition-for-the-balancing-of-assembly-lines-with-stochastic-demand.pdf
https://celso-sikora.com/SupplementaryMaterial/Supporting%20Information_Sikora_2021_Benders-decomposition-for-the-balancing-of-assembly-lines-with-stochastic-demand.7z},
doi = {10.1016/j.ejor.2020.10.019},
year = {2021},
date = {2021-07-01},
journal = {European Journal of Operational Research},
volume = {292},
pages = {108-124},
abstract = {The quality of the balancing of mixed-model assembly lines is intimately related to the defined production sequence. The two problems are, however, incompatible in time, as balancing takes place when planning the line, while sequencing is an operational problem closely related to market demand fluctuations. In this paper, an exact procedure to solve the integrated balancing and sequencing problem with stochastic demand is presented. The searched balancing solution must be flexible enough to cope with different demand scenarios. A paced assembly line is considered and utility work is used as a recourse for station border violations. A Benders’ decomposition algorithm is developed along with valid inequalities and preprocessing as a solution procedure. Three datasets are proposed and used to test algorithm performance and the value of treating uncertainty in mixed-model assembly lines. The integration of the strategic balancing problem with the operational sequencing problem results in more robust assembly lines.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The quality of the balancing of mixed-model assembly lines is intimately related to the defined production sequence. The two problems are, however, incompatible in time, as balancing takes place when planning the line, while sequencing is an operational problem closely related to market demand fluctuations. In this paper, an exact procedure to solve the integrated balancing and sequencing problem with stochastic demand is presented. The searched balancing solution must be flexible enough to cope with different demand scenarios. A paced assembly line is considered and utility work is used as a recourse for station border violations. A Benders’ decomposition algorithm is developed along with valid inequalities and preprocessing as a solution procedure. Three datasets are proposed and used to test algorithm performance and the value of treating uncertainty in mixed-model assembly lines. The integration of the strategic balancing problem with the operational sequencing problem results in more robust assembly lines.
2020
Lopes, Thiago Cantos; Sikora, Celso Gustavo Stall; Michels, Adalberto Sato; Magatão, Leandro
An iterative decomposition for asynchronous mixed-model assembly lines: combining balancing, sequencing, and buffer allocation Journal Article
In: International Journal of Production Research, vol. 58, no. 2, pp. 615–630, 2020, ISSN: 1366588X, (accepted manuscript and data available in Links).
@article{Lopes2020,
title = {An iterative decomposition for asynchronous mixed-model assembly lines: combining balancing, sequencing, and buffer allocation},
author = {Thiago Cantos Lopes and Celso Gustavo Stall Sikora and Adalberto Sato Michels and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2019_An-iterative-decomposition-for-asynchronous-mixed-model-assembly-lines-combining-balancing-sequencing-and-buffer-allocation.pdf
https://celso-sikora.com/SupplementaryMaterial/Instances_Lopes_2019_Iterative_decomposition.7z},
doi = {10.1080/00207543.2019.1598597},
issn = {1366588X},
year = {2020},
date = {2020-01-17},
urldate = {2020-01-17},
journal = {International Journal of Production Research},
volume = {58},
number = {2},
pages = {615--630},
abstract = {Asynchronous Mixed-Model Assembly lines are common production layouts dedicated to large-scale manufacturing of similar products. Cyclically scheduling such products is an interesting strategy to obtain high and stable throughput. In order to best optimise these lines, it is necessary to combine line balancing, model sequencing, and buffer allocation. However, few works integrate these three degrees of freedom, and evaluating steady-state performance as a consequence of these decisions is challenging. This paper presents a mathematical model that allows an exact steady-state performance evaluation of these lines, and hence their optimisation. While the combination of degrees of freedom is advantageous, it is also computational costly. An iterative decomposition procedure based on alternation between two mathematical models and on optimality cuts is also presented. The decomposition is tested against the proposed mathematical model in a 700-instance dataset. The developed methods obtained 142 optimal answers. Results show that the decomposition outperforms the monolithic mathematical model, in particular for larger and harder instances in terms of solution quality. The optimality cuts are also shown to help the decomposition steps in terms of solution quality and time. Comparisons to a sequential procedure further demonstrate the importance of simultaneously optimising the three degrees of freedom, as both the proposed model and the decomposition outperformed such procedure.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Asynchronous Mixed-Model Assembly lines are common production layouts dedicated to large-scale manufacturing of similar products. Cyclically scheduling such products is an interesting strategy to obtain high and stable throughput. In order to best optimise these lines, it is necessary to combine line balancing, model sequencing, and buffer allocation. However, few works integrate these three degrees of freedom, and evaluating steady-state performance as a consequence of these decisions is challenging. This paper presents a mathematical model that allows an exact steady-state performance evaluation of these lines, and hence their optimisation. While the combination of degrees of freedom is advantageous, it is also computational costly. An iterative decomposition procedure based on alternation between two mathematical models and on optimality cuts is also presented. The decomposition is tested against the proposed mathematical model in a 700-instance dataset. The developed methods obtained 142 optimal answers. Results show that the decomposition outperforms the monolithic mathematical model, in particular for larger and harder instances in terms of solution quality. The optimality cuts are also shown to help the decomposition steps in terms of solution quality and time. Comparisons to a sequential procedure further demonstrate the importance of simultaneously optimising the three degrees of freedom, as both the proposed model and the decomposition outperformed such procedure.
Lopes, Thiago Cantos; Sikora, Celso Gustavo Stall; Michels, Adalberto Sato; Magatão, Leandro
Mixed-model assembly lines balancing with given buffers and product sequence: model, formulation comparisons, and case study Journal Article
In: Annals of Operations Research, vol. 286, pp. 475–500, 2020, ISSN: 15729338, (accepted manuscript and data available in Links).
@article{Lopes2017,
title = {Mixed-model assembly lines balancing with given buffers and product sequence: model, formulation comparisons, and case study},
author = {Thiago Cantos Lopes and Celso Gustavo Stall Sikora and Adalberto Sato Michels and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2019_Mixed-model-assembly-lines-balancing-with-given-buffers-and-product-sequence-model-formulation-comparisons-and-case-study.pdf
https://celso-sikora.com/SupplementaryMaterial/Instances_Lopes_2017_ANOR.7z},
doi = {10.1007/s10479-017-2711-0},
issn = {15729338},
year = {2020},
date = {2020-01-01},
urldate = {2020-01-01},
journal = {Annals of Operations Research},
volume = {286},
pages = {475--500},
abstract = {Asynchronous assembly lines are productive layouts in which products move sequentially between stations when processing at current station is complete, and the following station is empty. When these conditions are not verified, downstream starvations and upstream blockages can occur. Buffers are often employed to minimize these problems, which are particularly relevant when the line is shared between a set of different products models (mixed-model lines). If the sequence of such models is cyclical, a steady-state production rate is eventually reached. However, determining (and, therefore, optimizing) such steady-state is challenging. This led to the development of indirect performance measures for mixed-model lines by many authors. In this paper, a direct performance measure is presented with a mixed-integer linear programming model and compared to previous formulations. The model is also applied to a practical case study and to a new dataset (with 1050 instances), allowing general assertions on the problem. All instances are solved with a universal solver and solutions are validated with a simulation software. Tests on the dataset instances confirmed the observations made on the case study: the proposed formulation produced solutions with higher production rate in 82% of the instances and tied the remaining ones, not being outperformed a single time. A triple interdependency of task balancing, product sequencing, and buffer allocation is demonstrated. Cyclical schedules show how buffers are able to compensate differences between models across stations and lead to the conclusion that the propagation of differences of models between stations can generate scheduling bottlenecks (blockages and starvation).},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Asynchronous assembly lines are productive layouts in which products move sequentially between stations when processing at current station is complete, and the following station is empty. When these conditions are not verified, downstream starvations and upstream blockages can occur. Buffers are often employed to minimize these problems, which are particularly relevant when the line is shared between a set of different products models (mixed-model lines). If the sequence of such models is cyclical, a steady-state production rate is eventually reached. However, determining (and, therefore, optimizing) such steady-state is challenging. This led to the development of indirect performance measures for mixed-model lines by many authors. In this paper, a direct performance measure is presented with a mixed-integer linear programming model and compared to previous formulations. The model is also applied to a practical case study and to a new dataset (with 1050 instances), allowing general assertions on the problem. All instances are solved with a universal solver and solutions are validated with a simulation software. Tests on the dataset instances confirmed the observations made on the case study: the proposed formulation produced solutions with higher production rate in 82% of the instances and tied the remaining ones, not being outperformed a single time. A triple interdependency of task balancing, product sequencing, and buffer allocation is demonstrated. Cyclical schedules show how buffers are able to compensate differences between models across stations and lead to the conclusion that the propagation of differences of models between stations can generate scheduling bottlenecks (blockages and starvation).
2019
Michels, Adalberto Sato; Lopes, Thiago Cantos; Sikora, Celso Gustavo Stall; Magatão, Leandro
A Benders' decomposition algorithm with combinatorial cuts for the multi-manned assembly line balancing problem Journal Article
In: European Journal of Operational Research, vol. 278, no. 3, pp. 796–808, 2019, ISSN: 03772217, (accepted manuscript available in Links).
@article{Michels2019,
title = {A Benders' decomposition algorithm with combinatorial cuts for the multi-manned assembly line balancing problem},
author = {Adalberto Sato Michels and Thiago Cantos Lopes and Celso Gustavo Stall Sikora and Leandro Magatão},
url = {https://celso-sikora.com/publications/Michels_2019_A-Benders-decomposition-algorithm-with-combinatorial-cuts-for-the-multi-manned-assembly-line-balancing-problem.pdf},
doi = {10.1016/j.ejor.2019.05.001},
issn = {03772217},
year = {2019},
date = {2019-11-01},
urldate = {2019-11-01},
journal = {European Journal of Operational Research},
volume = {278},
number = {3},
pages = {796--808},
abstract = {Multi-manned assembly lines are commonly found in industries that manufacture large-size products (e.g. automotive industry), in which multiple workers are assigned to the same station in order to perform different operations simultaneously on the same product. Although the balancing problem of multi-manned assembly lines had been modelled before, the previously presented exact mathematical formulations are only able to solve few small-size instances, while larger cases are solved by heuristics or metaheuristics that do not guarantee optimality. This work presents a new Mixed-Integer Linear Programming model with strong symmetry break constraints and decomposes the original problem into a new Benders' Decomposition Algorithm to solve large instances optimally. The proposed model minimises the total number of workers along the line and the number of opened stations as weighted primary and secondary objectives, respectively. Besides, feasibility cuts and symmetry break constraints based on combinatorial Benders' cuts and model's parameters are applied as lazy constraints to reduce search-space by eliminating infeasible sets of allocations. Tests on a literature dataset have shown that the proposed mathematical model outperforms previously developed formulations in both solution quality and computational processing time for small-size instances. Moreover, the proposed Benders' Decomposition Algorithm yielded 117 optimal results out of a 131-instances dataset. Compared to previously presented methods, this translates to 19 and 25 new best solutions reached for medium and large-size instances, respectively, of which 19 and 23 are optimal solutions.},
note = {accepted manuscript available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Multi-manned assembly lines are commonly found in industries that manufacture large-size products (e.g. automotive industry), in which multiple workers are assigned to the same station in order to perform different operations simultaneously on the same product. Although the balancing problem of multi-manned assembly lines had been modelled before, the previously presented exact mathematical formulations are only able to solve few small-size instances, while larger cases are solved by heuristics or metaheuristics that do not guarantee optimality. This work presents a new Mixed-Integer Linear Programming model with strong symmetry break constraints and decomposes the original problem into a new Benders' Decomposition Algorithm to solve large instances optimally. The proposed model minimises the total number of workers along the line and the number of opened stations as weighted primary and secondary objectives, respectively. Besides, feasibility cuts and symmetry break constraints based on combinatorial Benders' cuts and model's parameters are applied as lazy constraints to reduce search-space by eliminating infeasible sets of allocations. Tests on a literature dataset have shown that the proposed mathematical model outperforms previously developed formulations in both solution quality and computational processing time for small-size instances. Moreover, the proposed Benders' Decomposition Algorithm yielded 117 optimal results out of a 131-instances dataset. Compared to previously presented methods, this translates to 19 and 25 new best solutions reached for medium and large-size instances, respectively, of which 19 and 23 are optimal solutions.
Lopes, Thiago Cantos; Michels, Adalberto Sato; Sikora, Celso Gustavo Stall; Magatão, Leandro
Balancing and cyclical scheduling of asynchronous mixed-model assembly lines with parallel stations Journal Article
In: Journal of Manufacturing Systems, vol. 50, pp. 193–200, 2019, ISSN: 02786125, (accepted manuscript available in Links).
@article{Lopes2019a,
title = {Balancing and cyclical scheduling of asynchronous mixed-model assembly lines with parallel stations},
author = {Thiago Cantos Lopes and Adalberto Sato Michels and Celso Gustavo Stall Sikora and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2019_Balancing-and-cyclical-scheduling-of-asynchronous-mixed-model-assembly-lines-with-parallel-stations.pdf},
doi = {10.1016/j.jmsy.2019.01.001},
issn = {02786125},
year = {2019},
date = {2019-01-01},
urldate = {2019-01-01},
journal = {Journal of Manufacturing Systems},
volume = {50},
pages = {193--200},
abstract = {This paper considers two optimization problems commonly associated to mixed-model assembly lines: balancing task-station assignments and sequencing/scheduling different product models in a cyclical manner. Cyclical scheduling for this particular problem variant is challenging, and multiple approaches have been previously employed by different authors. This paper presents a new mixed-integer linear programming formulation to optimize the steady-state of these lines. Tests on a 36-instance benchmark demonstrated that the proposed model significantly outperformed the previous literature formulation. Furthermore, it is shown that common scheduling rules (often used in simulators) do not necessarily converge to optimal cyclical schedules even when the optimal launch order is used. Tests have also demonstrated that parallelism can allow a marginally increasing value for workstations: doubling (tripling) stations in a line with parallelism can often offer more than double (triple) the optimal throughput of lines without parallelism.},
note = {accepted manuscript available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
This paper considers two optimization problems commonly associated to mixed-model assembly lines: balancing task-station assignments and sequencing/scheduling different product models in a cyclical manner. Cyclical scheduling for this particular problem variant is challenging, and multiple approaches have been previously employed by different authors. This paper presents a new mixed-integer linear programming formulation to optimize the steady-state of these lines. Tests on a 36-instance benchmark demonstrated that the proposed model significantly outperformed the previous literature formulation. Furthermore, it is shown that common scheduling rules (often used in simulators) do not necessarily converge to optimal cyclical schedules even when the optimal launch order is used. Tests have also demonstrated that parallelism can allow a marginally increasing value for workstations: doubling (tripling) stations in a line with parallelism can often offer more than double (triple) the optimal throughput of lines without parallelism.
2018
Michels, Adalberto Sato; Lopes, Thiago Cantos; Sikora, Celso Gustavo Stall; Magatão, Leandro
The Robotic Assembly Line Design (RALD) problem: Model and case studies with practical extensions Journal Article
In: Computers and Industrial Engineering, vol. 120, pp. 320–333, 2018, ISSN: 03608352, (accepted manuscript available in Links).
@article{Michels2018,
title = {The Robotic Assembly Line Design (RALD) problem: Model and case studies with practical extensions},
author = {Adalberto Sato Michels and Thiago Cantos Lopes and Celso Gustavo Stall Sikora and Leandro Magatão},
url = {https://celso-sikora.com/publications/Michels_2018_The-Robotic-Assembly-Line-Design-RALD-problem-Model-and-case-studies-with-practical-extensions.pdf},
doi = {10.1016/j.cie.2018.04.010},
issn = {03608352},
year = {2018},
date = {2018-06-01},
urldate = {2018-06-01},
journal = {Computers and Industrial Engineering},
volume = {120},
pages = {320--333},
abstract = {Spot welding assembly lines are widely present in the automotive manufacturing industry. The procedure of building the vehicle's body employs several robots equipped with spot welding tools. These robots and tools are a quite costly initial investment, requiring an efficient and conscious line design that meets product demands and minimises implementation expense at the same time. In this paper, the Robotic Assembly Line Design (RALD) problem is proposed and studied based on practical characteristics from an automotive company located in Brazil. A Mixed-Integer Liner Programming (MILP) formulation is developed allowing: (i) station paralleling, (ii) equipment selection, and (iii) multiples robots per workstation. The mathematical model aims at minimising the total cost at the desired production rate, which involves robots, tools and facilities. The proposed model considers dead time during a cycle, space constraints, task assignment restrictions, and parallelism possibilities. Dead time is an unproductive and fixed work-piece handling time included in the capacitated transporter robots' movement time. Computational experiments were performed in order to evidence the parameters' influence over the optimal line design solution. In addition, practical case studies were conducted with parameters collected from a real-world robotic welding assembly line located on the outskirts of Curitiba-PR (Brazil), reaching optimality. Compared to the strictly serial lines, the model led to great advantages by allowing parallel stations in the production system, making it possible to evaluate an expected trade-off between the production rate and the total cost; reductions of several hundred thousand dollars on the production layout cost can be achieved by the company, as indicated by the studied cases.},
note = {accepted manuscript available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Spot welding assembly lines are widely present in the automotive manufacturing industry. The procedure of building the vehicle's body employs several robots equipped with spot welding tools. These robots and tools are a quite costly initial investment, requiring an efficient and conscious line design that meets product demands and minimises implementation expense at the same time. In this paper, the Robotic Assembly Line Design (RALD) problem is proposed and studied based on practical characteristics from an automotive company located in Brazil. A Mixed-Integer Liner Programming (MILP) formulation is developed allowing: (i) station paralleling, (ii) equipment selection, and (iii) multiples robots per workstation. The mathematical model aims at minimising the total cost at the desired production rate, which involves robots, tools and facilities. The proposed model considers dead time during a cycle, space constraints, task assignment restrictions, and parallelism possibilities. Dead time is an unproductive and fixed work-piece handling time included in the capacitated transporter robots' movement time. Computational experiments were performed in order to evidence the parameters' influence over the optimal line design solution. In addition, practical case studies were conducted with parameters collected from a real-world robotic welding assembly line located on the outskirts of Curitiba-PR (Brazil), reaching optimality. Compared to the strictly serial lines, the model led to great advantages by allowing parallel stations in the production system, making it possible to evaluate an expected trade-off between the production rate and the total cost; reductions of several hundred thousand dollars on the production layout cost can be achieved by the company, as indicated by the studied cases.
Lopes, Thiago Cantos; Michels, Adalberto Sato; Sikora, Celso Gustavo Stall; Molina, Rafael Gobbi; Magatão, Leandro
Balancing and cyclically sequencing synchronous, asynchronous, and hybrid unpaced assembly lines Journal Article
In: International Journal of Production Economics, vol. 203, pp. 216–224, 2018, ISSN: 09255273, (accepted manuscript and data available in Links).
@article{Lopes2018,
title = {Balancing and cyclically sequencing synchronous, asynchronous, and hybrid unpaced assembly lines},
author = {Thiago Cantos Lopes and Adalberto Sato Michels and Celso Gustavo Stall Sikora and Rafael Gobbi Molina and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2018_Balancing-and-cyclically-sequencing-synchronous-asunchronous-and-hybrid-unpaced-assembly-lines.pdf
https://celso-sikora.com/SupplementaryMaterial/Instances_Lopes_2018_Balancing_Syn_Asyn_Hyb.7z},
doi = {10.1016/j.ijpe.2018.06.012},
issn = {09255273},
year = {2018},
date = {2018-01-01},
urldate = {2018-01-01},
journal = {International Journal of Production Economics},
volume = {203},
pages = {216--224},
abstract = {Mixed-model assembly lines are product-oriented production layouts often employed for large scale manufacturing of similar products. The unpaced variant of these lines employs a conveyor to discretely move pieces between stations either synchronously or asynchronously. Workload balancing and product sequencing are common optimization problems associated with these lines. While many works detail balancing and sequencing separately, few explicitly combine these degrees of freedom. Furthermore, hybrid (i.e. partly synchronous and partly asynchronous) lines are not explicitly described by previous optimization models. This paper presents a mixed-integer linear programming model capable of representing such unpaced lines and explicitly combine balancing, sequencing and cyclical scheduling. The application of the proposed method to a new dataset demonstrates the advantages of simultaneously balancing and sequencing lines, generating more efficient solutions than previously described models for 238 out of 240 instances. These results implied, however, in greater computational costs required to combine the degrees of freedom. Furthermore, a direct performance comparison study between synchronous, asynchronous, and hybrid lines is conducted. This allows line designers and managers to explicitly evaluate economical trade-offs between these line types.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Mixed-model assembly lines are product-oriented production layouts often employed for large scale manufacturing of similar products. The unpaced variant of these lines employs a conveyor to discretely move pieces between stations either synchronously or asynchronously. Workload balancing and product sequencing are common optimization problems associated with these lines. While many works detail balancing and sequencing separately, few explicitly combine these degrees of freedom. Furthermore, hybrid (i.e. partly synchronous and partly asynchronous) lines are not explicitly described by previous optimization models. This paper presents a mixed-integer linear programming model capable of representing such unpaced lines and explicitly combine balancing, sequencing and cyclical scheduling. The application of the proposed method to a new dataset demonstrates the advantages of simultaneously balancing and sequencing lines, generating more efficient solutions than previously described models for 238 out of 240 instances. These results implied, however, in greater computational costs required to combine the degrees of freedom. Furthermore, a direct performance comparison study between synchronous, asynchronous, and hybrid lines is conducted. This allows line designers and managers to explicitly evaluate economical trade-offs between these line types.
2017
Sikora, Celso Gustavo Stall; Lopes, Thiago Cantos; Schibelbain, Daniel; Magatão, Leandro
Integer based formulation for the simple assembly line balancing problem with multiple identical tasks Journal Article
In: Computers & Industrial Engineering, vol. 104, pp. 134–144, 2017, ISSN: 03608352, (accepted manuscript available in Links).
@article{Sikora2017a,
title = {Integer based formulation for the simple assembly line balancing problem with multiple identical tasks},
author = {Celso Gustavo Stall Sikora and Thiago Cantos Lopes and Daniel Schibelbain and Leandro Magatão},
url = {https://celso-sikora.com/publications/Sikora_2017_Integer-based-formulation-for-the-simple-assembly-line-balancing-problem-with-multiple-identical-tasks.pdf},
doi = {10.1016/j.cie.2016.12.026},
issn = {03608352},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {Computers & Industrial Engineering},
volume = {104},
pages = {134--144},
abstract = {Assembly lines, especially those with welding procedures, can present several tasks with the same properties. These tasks can be treated as tasks with replicas, simplifying the problem. A Mixed Integer Linear Programming model is presented for the Simple Assembly Line Balancing Problem with Multiple Identical Tasks (or Repeated Tasks). Integer variables were used to define the number of identical tasks performed in each station. Along with variable reduction rules, the compact formulation presents only a fraction of the variables of equivalent binary models when several repeated tasks are present. Three instances inspired in real assembly lines and adapted benchmark problems with repeated tasks are used to compare the formulations. Using a universal solver, the integer formulation outperformed the binary formulation for the vast majority of instances and achieved competitive results in relation to the efficient procedure SALOME-2 (a dedicated algorithm based on branch-and-bound for Simple Assembly Line Balancing Problem). Grouping identical tasks proved to simplify the problem, allowing the procedure to solve larger instances.},
note = {accepted manuscript available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Assembly lines, especially those with welding procedures, can present several tasks with the same properties. These tasks can be treated as tasks with replicas, simplifying the problem. A Mixed Integer Linear Programming model is presented for the Simple Assembly Line Balancing Problem with Multiple Identical Tasks (or Repeated Tasks). Integer variables were used to define the number of identical tasks performed in each station. Along with variable reduction rules, the compact formulation presents only a fraction of the variables of equivalent binary models when several repeated tasks are present. Three instances inspired in real assembly lines and adapted benchmark problems with repeated tasks are used to compare the formulations. Using a universal solver, the integer formulation outperformed the binary formulation for the vast majority of instances and achieved competitive results in relation to the efficient procedure SALOME-2 (a dedicated algorithm based on branch-and-bound for Simple Assembly Line Balancing Problem). Grouping identical tasks proved to simplify the problem, allowing the procedure to solve larger instances.
Sikora, Celso Gustavo Stall; Lopes, Thiago Cantos; Magatão, Leandro
Traveling worker assembly line (re)balancing problem: model, reduction techniques, and real case studies Journal Article
In: European Journal of Operational Research, vol. 259, no. 3, pp. 949–971, 2017, ISSN: 0377-2217, (accepted manuscript available in Links).
@article{Sikora2017b,
title = {Traveling worker assembly line (re)balancing problem: model, reduction techniques, and real case studies},
author = {Celso Gustavo Stall Sikora and Thiago Cantos Lopes and Leandro Magatão},
url = {https://celso-sikora.com/publications/Sikora_2017_Traveling-worker-assembly-line-rebalancing-problem-model-reduction-techniques-and-real-case-studies.pdf},
doi = {10.1016/j.ejor.2016.11.027},
issn = {0377-2217},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {European Journal of Operational Research},
volume = {259},
number = {3},
pages = {949--971},
abstract = {The assembly line balancing problem arises from equally dividing the workload among all workstations. Several solution methods explore different variants of the problem, but no model includes all characteristics real assembly lines might contain. This paper presents a mixed integer linear programming model that solves the Traveling Worker Assembly Line Balancing Problem (TWALBP). In this problem, the tasks' balancing along with the assignment of workers to one or more workstations is determined for a given layout. The assignment flexibility is solved with a traveling salesman problem formulation integrated in the balancing model. Adapted standard datasets and three real case scenarios are used as benchmark sets. These scenarios present particularities such as human and robotic workers, assignment restrictions, zoning constraints, automatic and common tasks. The model successfully determines the tasks' assignments and the routing of every worker for a layout aware optimization of assembly lines. Better quality balancing solutions were achieved allowing workers to perform tasks at multiple stations, showing a trade-off between assignment flexibility and movement time.},
note = {accepted manuscript available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
The assembly line balancing problem arises from equally dividing the workload among all workstations. Several solution methods explore different variants of the problem, but no model includes all characteristics real assembly lines might contain. This paper presents a mixed integer linear programming model that solves the Traveling Worker Assembly Line Balancing Problem (TWALBP). In this problem, the tasks' balancing along with the assignment of workers to one or more workstations is determined for a given layout. The assignment flexibility is solved with a traveling salesman problem formulation integrated in the balancing model. Adapted standard datasets and three real case scenarios are used as benchmark sets. These scenarios present particularities such as human and robotic workers, assignment restrictions, zoning constraints, automatic and common tasks. The model successfully determines the tasks' assignments and the routing of every worker for a layout aware optimization of assembly lines. Better quality balancing solutions were achieved allowing workers to perform tasks at multiple stations, showing a trade-off between assignment flexibility and movement time.
Lopes, Thiago Cantos; Sikora, C G S; Molina, Rafael Gobbi; Schibelbain, Daniel; Rodrigues, L C A; Magatão, Leandro
Balancing a robotic spot welding manufacturing line: An industrial case study Journal Article
In: European Journal of Operational Research, vol. 263, no. 3, pp. 1033–1048, 2017, ISSN: 03772217, (accepted manuscript and data available in Links).
@article{Lopes2017a,
title = {Balancing a robotic spot welding manufacturing line: An industrial case study},
author = {Thiago Cantos Lopes and C G S Sikora and Rafael Gobbi Molina and Daniel Schibelbain and L C A Rodrigues and Leandro Magatão},
url = {https://celso-sikora.com/publications/Lopes_2017_Balancing-a-robotic-spot-welding-manufacturing-line-An-industrial-case-study.pdf
https://celso-sikora.com/SupplementaryMaterial/Instances_Lopes_2017_Robotic_Spot_Welding.7z},
doi = {10.1016/j.ejor.2017.06.001},
issn = {03772217},
year = {2017},
date = {2017-01-01},
urldate = {2017-01-01},
journal = {European Journal of Operational Research},
volume = {263},
number = {3},
pages = {1033--1048},
abstract = {Resistance spot welding is an important procedure used in the automobile manufacturing industry. After stamping, sheets of metal are mostly welded together to build the car's body. Many of the industrial robots found in assembly lines are spot welders. Process characteristics include accessibility limitations, the need to move between welding points and (when there are multiple robots per station) potential interferences between robots. The combination of such characteristics is not present in classical models for the assembly line balancing problem. In this paper, the balancing problem of robotic spot welding manufacturing lines is presented and modeled based on a real-world car factory on the outskirts of Curitiba, Brazil. The studied line has 42 robots that perform over 700 welding points on the later stages of the body-shop. The model was developed with Mixed Integer Linear Programming (MILP) techniques, validated with empirical data, and solved with a universal solver. The optimized balancing achieved a cycle time reduction of up to 6.6% compared to the as-is configurations. The total movement time was observed not to be necessarily minimized during the optimization process, implying that trade-offs exist between movement times and the number of welding points performed.},
note = {accepted manuscript and data available in Links},
keywords = {},
pubstate = {published},
tppubtype = {article}
}
Resistance spot welding is an important procedure used in the automobile manufacturing industry. After stamping, sheets of metal are mostly welded together to build the car's body. Many of the industrial robots found in assembly lines are spot welders. Process characteristics include accessibility limitations, the need to move between welding points and (when there are multiple robots per station) potential interferences between robots. The combination of such characteristics is not present in classical models for the assembly line balancing problem. In this paper, the balancing problem of robotic spot welding manufacturing lines is presented and modeled based on a real-world car factory on the outskirts of Curitiba, Brazil. The studied line has 42 robots that perform over 700 welding points on the later stages of the body-shop. The model was developed with Mixed Integer Linear Programming (MILP) techniques, validated with empirical data, and solved with a universal solver. The optimized balancing achieved a cycle time reduction of up to 6.6% compared to the as-is configurations. The total movement time was observed not to be necessarily minimized during the optimization process, implying that trade-offs exist between movement times and the number of welding points performed.