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Recovering the end-of-life (EOL) products helps companies reduce the purchasing cost for goods and materials that can be removed from EOL products and reused. This also contributes to the efforts aiming at reducing the environmental consequences of hazardous materials. Disassembly lines play a vital role in the disassembling process of EOL products...
Citations
... In practice multiple operators are often required at a workstation to handle different disassembly operations simultaneously; this feature is particularly important for disassembling large-size or high-volume End-of-Life products. Kucukkoc et al., (2020) extended the DLBP to account for more than one operator at the workstations; they developed a mixed-integer nonlinear programming model and an exact method for solving small-to medium-size instances. They did not consider resource limitations in their optimization model. ...
... Limited studies accounted for multi-manned and machinery resources. (Kucukkoc et al., 2020) is one of the first studies that accounted for multi-manned workstations in DLBPs. (Cevikcan et al., 2020) developed a heuristic algorithm and a new formulation to minimize the number of workers and workstations while accounting for multi-manned workstations; they do not take into account the machinery as a resource and assume that there are no restrictions on the available resources. ...
The increasing public awareness of environmental protection and the scarcity of rare earth elements have made closed-loop supply chains a necessity in many sectors. In particular, recycling components and parts from end-of-life consumer electronics have drawn the attention of both academics and practitioners. Disassembly line balancing improves the cost efficiency of recycling operations and hence helps waste management businesses that operate on very narrow profit margins. This study proposes a new mathematical formulation and hybrid metaheuristics to solve the Disassembly Line Balancing Problem (DLBP) considering multi-manned workstations and resource constraints. The transformed AND/OR graph is used for prioritizing disassembly tasks in the modeling process. The method is applied for optimizing a real-world case of laptop disassembly to showcase the usefulness of the proposed approach. The performance of the developed metaheuristics is evaluated for minimizing the number of workstations, operators, and machines involved in the disassembly operations. Further, the results are analyzed through sensitivity analysis. This study is concluded by providing practical insights and suggestions for the future development of DLBPs.
... Follow-up scholars have conducted extensive studies on DLBPs based on Pistolesi et al. [6], Wang et al. [7], and Yin et al. [8]. To improve the disassembly efficiency of stations, a disassembly line with multimanned stations was proposed by Cevikcan et al. [9], and its efficiency was proven to be superior to that of single-manned stations [10]. ...
... Equations (8) and (9) imply that a worker or robot can only disassemble one task at a time. Equation (10) indicates that a task in any operator should not be disassembled until the operator has completed all previous tasks assigned to him or it. Equation (11) indicates that the completion time of any task should be less than the end time of the station at which the task is located. ...
... h), this verifies the NPhard attribute of MPMMR-DLBP. Moreover, the solutions (2,10,4) and (3,0,5) obtained by POGE contain the three single-objective global optimal values obtained by GUROBI, especially the solution (2, 10, 4) can achieve the global optimum of SN and ON simultaneously, and the solving time of POGE is shorter than that of GUROBI, which further indicates the superior performance of POGE in solving the MPMMR-DLBP. ...
Disassembly production lines that employ shared stations with multiple workers and robots are ideal for addressing obsolete products with complex structures and hazardous parts. In this study, a multiproduct multi-man–robot disassembly line balancing problem (MPMMR-DLBP) is developed and its mixed-integer programming model (MIPM) is established to minimize the number of stations, idle balancing index of operators (workers and robots), and the number of operators. In addition, a problem-oriented group evolutionary (POGE) algorithm is proposed to efficiently solve the MPMMR-DLBP. The proposed POGE develops a new “1
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3” encoding mode and a heuristic decoding strategy based on the shortest time to complete tasks to construct a one-to-one correspondence between encoding sequences and disassembly schemes. Moreover, a reassociation evolution operation (REO) and a mapping crossover operation (MCO) are designed to generate new solutions and allow the population to evolve to the global optimum. Subsequently, the correctness of MIPM and the performance of POGE are verified using two small-scale cases. Finally, an actual MPMMR-DLBP for the mixed disassembly of refrigerators, microwave ovens, and dishwashers is optimized by POGE. A comparison of the optimized results with the other three common algorithms shows that the POGE is superior in the large-scale MPMMR-DLBP, and multiple optimized disassembly schemes are provided for decision makers.
... The existing literature mainly includes four layout forms: straight [17][18][19], U-type [20,21], two-sided [22,23], and parallel line [24] layouts. Furthermore, a large number of studies have focused on the straight layout [25]. ...
In most resource recycling enterprises, waste electrical and electronic equipment (WEEE) recycling is performed in a multi-parallel disassembly line layout with mixed-product disassembly mode. Thus, this study constructs a mixed-integer non-linear programming (MINLP) and implements a multi-objective improved ant lion optimizer (MIALO) to minimize four objectives, namely, the number of shared workstations, workstation load balancing, demand, and hazard indices, of the mixed-product multi-parallel disassembly line balancing problem (MPDLBP). For MIALO, the ant population initialization and population interaction operations are improved to enhance the global optimization capability of MIALO. In addition, the Pareto and non-dominated sorting genetic algorithm (NSGA-II) are integrated to maintain the number of population. Furthermore, the MINLP is solved by GUROBI 9.1.1, and the results are compared with those of MIALO to verify the correctness of MIALO. To further demonstrate the performance of MIALO, the MIALO is compared with four existing algorithms. Finally, the MIALO is applied to optimize a multi-parallel disassembly case of WEEE. Then, several productive disassembly schemes are provided to recycle waste TV sets.
... Disassembly line is an efficient way for remanufacturing (Yin et al., 2023). In this context, disassembly line balancing problem (DLBP) can be stated as the allocation of disassembly tasks to workstations while satisfying various constraints (Altekin, 2017;Kucukkoc et al., 2020). Having led to the development of various solution methods for DLBP, some physical and operational aspects of the disassembly line such as the team-oriented line design and multi-skill workers assignment are highlighted to present the motivations of this study. ...
... Various studies have been conducted to solve DLBP via exact techniques (Altekin, 2017;Cil, 2021;Kucukkoc et al., 2020). On the other hand, numerous heuristics and meta-heuristic solutions have been developed due to NP-complete nature of DLBP. ...
... Cevikcan et al. (2020) addressed DLBP with multi-manned stations and attempted to minimize the numbers of workers and workstations. Kucukkoc et al. (2020) developed an iterative mixed-integer linear programming model to minimize the cycle time and number of stations for DLBP with Type-E. While the existing studies related to multi-manned DLBP have focused on the complete disassembly of waste products, Yin et al. (2023) handled a partial disassembly for avoiding invalid work and labour waste. ...
... However, in this study, there was an assumption that all workers were homogeneous and perform all tasks in a fixed time. On the other hand, Kucukkoc et al. (2020) proposed linear and non-linear models in which the DALBP in a Type E station where many workers work. In another study, Yılmaz and Yazıcı (2022) considered teamwork and worker heterogeneity, which is an effective method in the use of time and resources, in multi-objective DALBPs. ...
Purpose
Although disassembly balancing lines has been studied for over two decades, there is a gap in the robotic disassembly. Moreover, combination of problem with heterogeneous employee assignment is also lacking. The hazard related with the tasks performed on disassembly lines on workers can be reduced by the use of robots or collaborative robots (cobots) instead of workers. This situation causes an increase in costs. The purpose of the study is to propose a novel version of the problem and to solve this bi-objective (minimizing cost and minimizing hazard simultaneously) problem.
Design/methodology/approach
The epsilon constraint method was used to solve the bi-objective model. Entropy-based Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) and Preference Ranking Organization methods for Enrichment Evaluation (PROMETHEE) methods were used to support the decision-maker. In addition, a new criterion called automation rate was proposed. The effects of factors were investigated with full factor experiment design.
Findings
The effects of all factors were found statistically significant on the solution time. The combined effect of the number of tasks and number of workers was also found to be statistically significant.
Originality/value
In this study, for the first time in the literature, a disassembly line balancing and employee assignment model was proposed in the presence of heterogeneous workers, robots and cobots to simultaneously minimize the hazard to the worker and cost.
... Their solution procedure is done using lingo 17 solver. Kucukkoc et al. (2020) introduced a linear and nonlinear model for the type E of the MALBP. Roshani and Giglio (2020) developed a tabu search algorithm for solving the cost-oriented MALBP. ...
... Regarding the exact methods, Li et al. (2020) and Li et al. (2019c) developed the branch, bound and remember algorithms to optimize the number of stations. There also are many studies on mixed-integer linear programming (MILP) models (Altekin and Akkan 2012;Altekin et al. 2008;Koc et al. 2009;Kucukkoc et al. 2020;Liu et al. 2019;Mete et al. 2018;Paksoy et al. 2013) to formulate the problem mathematically. However, MILP model is weak in solving large-size instances due to excessive computational time requirements. ...
Disassembly is the first and vital step in recycling and remanufacturing end-of-life products. Disassembly lines are utilized frequently due to high productivity and suitability. This research studies the disassembly line balancing problem on the U-shaped disassembly lines, which have higher flexibility than the traditional straight disassembly lines. A mixed-integer linear programming (MILP) model is developed to formulate the AND/OR precedence relationships with the objective of minimizing the number of stations. This model is also extended to a mixed-integer nonlinear programming model to optimize four objectives. To tackle this NP-hard problem effectively, a two-phase artificial bee colony algorithm and a bee algorithm are proposed and improved. In these algorithms, the first phase selects the stations with less loads on the last two stations for the purpose of achieving the optimal number of stations. The second phase hierarchically optimizes multiple objectives to achieve better line balances. Case studies show that the proposed MILP model obtains optimal solutions in terms of station number for the small-size instances, and the U-shaped disassembly lines obtain better fitness values than the straight disassembly lines. The comparative study demonstrates that the proposed methodologies perform competing performances in comparison with other 13 re-implemented algorithms, including tabu search algorithm, iterated local search algorithm, genetic algorithm, particle swarm optimization, three artificial bee colony algorithms and the original bee algorithm.
... The first type (DLBP-I) is to determine the minimum number of workstations for a given cycle time, which is usually carried out during the design and installation stage for the disassembly industry. The second type (DLBP-II) is to minimize the cycle time with a fixed number of stations, which is usually optimized for the existing line to improve the disassembly flexibility [10]. Almost all research on DLP is devoted to Type-I and extended the optimization goals to other aspects based on this to make it more realistic for disassembly companies. ...
The disassembly industry is still labor-intensive, and for the disassembly of products with similar assembly structures, achieving mixed disassembly of these products on the same disassembly line is a more economical solution and very popular in disassembly companies. When large-volume end-of-life (EOL) products are disassembled on the two-sided disassembly line, there is uncertainty in the disassembly time during the disassembly process due to the differences in the recovery quality of EOL products. Therefore, a stochastic mixed-integer programming model is formulated that considers workstation activation cost, workload smoothness index between workstations, and total hazard index considering the order of hazardous task removal. Then, a multi-objective genetic flatworm algorithm is developed in which two different mechanisms for new individual generation are embedded, namely the flatworm genetic operations and the regeneration operations. The effectiveness of the model and the efficiency of the algorithm are verified by the disassembly cases of the printer and the classical mixed-model on the two-sided disassembly line. Finally, the proposed model and algorithm are applied to the disassembly of multiple types of cars, which proves their practical industrial application value.
... The studies considering the multi-manned workstations for the disassembly lines are presented as follow. Kucukkoc et al. (2019) developed a non-linear optimization model for the multimanned DALBP problem with Type-E objectives, which are the minimization of cycle time and number of stations. An iterative mixed-integer linear programming model was proposed for the large-sized problems. ...
... The first two objectives are similar to the Type-E objectives in ALBP, which are the number of stations and cycle time. Despite the considered objectives conflict with each other, they provide advantages to boost line efficiency (Kucukkoc et al. 2019). The third objective is to minimize the maximum workload imbalance between workers and ...
The disassembly line plays a vital role to recover the products for remanufacturing enterprises. For this reason, designing and balancing of the disassembly line are important to utilize the economic and tactical benefits. This study explores a multi-objective disassembly line balancing problem (MODLBP) from a different point of view by considering the workers’ heterogeneity and the multi-manned stations where the group-based worker assignment strategy is implemented. Although the MODLBP has been attracting attention in the last decade, to the best of our knowledge, this is the first study investigating the addressed problem in the current form. To further analyze the problem, first, it is described by focusing on the tactical level strategies and operational level scenarios. Subsequently, a novel multi-objective optimization model is formulated with three objectives, that of minimizing overall cost, cycle time, and workload imbalance. On one hand, the improved augmented ϵ-constrained (AUGMECON2) method is used to obtain the Pareto-optimal solutions for small-sized problems. On the other hand, a set of algorithms based on the non-dominated sorting genetic algorithm-II is implemented to gain managerial insights regarding the strategies and scenarios for large-sized problems. A computational study is conducted based on the generated problems to reveal the prominent differences between strategies in terms of performance metrics. According to the computational results, high-quality solutions are achieved when the group-based assignment strategy is realized. Besides, it is revealed from scenario analysis that the training of workers leads to considerable improvements in the system performance.
... Their solution procedure is done using lingo 17 solver. Kucukkoc et al. (2020) introduced a linear and nonlinear model for the type E of the MALBP. Roshani and Giglio (2020) developed a tabu search algorithm for solving the cost-oriented MALBP. ...
