U-shaped Assembly Line Research Articles

Modeling and balancing of parallel U-shaped assembly line based on improved genetic algorithms

Aiming at the improvement of the efficiency of the assembly line in the intelligent manufacturing field, a parallel U-shaped assembly line balancing problem (PUALBP) appears. In this paper, a mathematical model of the PUALBP-I is established, and an improved genetic algorithm (IGA) is innovatively designed based on the allocation strategy. Combined with 56 classic examples, the IGA is used to solve the mathematical models of SUAL and PUAL respectively, and the balance results and the balance effect evaluation indicators are obtained. The comparison with Parallel U-line Heuristic (PUH) shows that the results of PUAL are better than SUAL, and verifies that the IGA is effective. The results demonstrate that the IGA in calculating large-scale problems is superior to the small-scale problems, which provides a useful reference for solving PUALBP.

An optimization model for sustainable multi-product multi-echelon supply chain networks with U-shaped assembly line balancing under uncertainty

This study presents an integrated supply chain network with suppliers, manufacturers, assemblers, and customers. The proposed model considers a U-shaped assembly line with three sustainability objective functions. We consider assumptions considering different types of raw materials, multiple products, location selection of manufacturers, location selection of assemblers, and capacity of suppliers. The problem is formulated non-linear and then linearized as a multi-objective model. Some cost and demand parameters are considered uncertain and are represented by fuzzy sets and theory. The proposed uncertain model is first converted to a multi-objective crisp model by applying the modified robust possibilistic programming approach. Then, the obtained crisp multi-objective model is solved by an interactive-fuzzy optimization approach in the literature. For computational study, some test problems are generated and solved using an original deterministic formulation and the crisp form of the uncertain formulation. The obtained results are analyzed and compared according to the objective function values. Finally, an extensive sensitivity analysis is performed on the parameters of the models.

Integer and constraint programming models for the straight and U-shaped assembly line balancing with hierarchical worker assignment problem

ABSTRACTThe solution to the assembly line balancing with the hierarchical worker assignment problem (ALBHWP) provides the optimal allocation of workers and tasks to the stations that minimise the total worker cost. In the ALBHWP, tasks differ in terms of the qualification requirements of workers, and the qualification levels of workers are hierarchical. In the hierarchical workforce structure, a lower qualified worker can be replaced by higher qualified ones with higher costs, while the vice versa is not applicable. This problem has only been studied for straight assembly lines so far. In this paper, we introduce the ALBHWP for U-shaped assembly lines. We developed integer and constraint programming models for solving the ALBHWP and compared their effectiveness using an extensive set of benchmark instances. We solved the ALBHWP for straight and U-shaped assembly lines comparatively. Constraint programming models have been statistically proven to provide better quality solutions faster than integer programming models. Besides, the CP model outperforms the only available metaheuristic in the literature for the S-ALBHWP in almost all problem sizes. Another observation is that a U-shaped line design is more cost-effective than a straight line design, but solving the ALBHWP for U-shaped lines is more difficult regarding computational complexity.

Balancing and scheduling human-robot collaborated assembly lines with layout and objective consideration

The recent Industry 4.0 trend, followed by the technological advancement of collaborative robots, has urged many industries to shift towards new types of assembly lines with human-robot collaboration (HRC). This type of manufacturing line, in which human skill is supported by robot agility, demands an integrated balancing and scheduling of tasks and operators among the stations. This study attempts to deal with these joint problems in the straight and U-shaped assembly lines while considering different objectives, namely, the number of stations (Type-1), the cycle time (Type-2), and the cost of stations, operators, and robot energy consumption (Type-rw). The latter type often arises in the real world, where multiple types of humans and robots with different skills and energy levels can perform the assembly tasks collaboratively or in parallel at stations. Additionally, practical constraints, namely robot tool changes, zoning, and technological requirements, are considered in Type-rw. Accordingly, different mixed-integer linear programming (MILP) models for straight and U-shaped layouts are proposed with efficient lower and upper bounds for each objective. The computational results validate the efficiency of the proposed MILP model with bounded objectives while addressing an application case and different test problem sizes. In addition, the analysis of results shows that the U-shaped layout offers greater flexibility than the straight line, leading to more efficient solutions for JIT production, particularly in objective Type-2 followed by Type-rw and Type-1. Moreover, the U-shaped lines featuring a high HRC level can further enhance the achievement of desired objectives compared to the straight lines with no or limited HRC.

A sustainable uncertain integrated supply chain network design and assembly line balancing problem with U-shaped assembly lines and multi-mode demand

A sustainable uncertain integrated supply chain network design and assembly line balancing problem with U-shaped assembly lines and multi-mode demand

Models and algorithms for U-shaped assembly line balancing problem with collaborative robots

The collaborative robots (cobots) are increasingly being utilized in industries due to the advancement in the field of robotic technology and also due to the increase in labor costs. The cobots on the assembly line can be utilized to complete the tasks independently or assist the workers to complete the tasks. This study considers the U-shaped assembly line balancing problem with cobots, where several cobots with different purchasing costs are selected under the budget constraint. Three mixed-integer programming models are formulated to optimize the cycle time, and the built models are capable of solving the small-sized instances optimally. Two algorithms, artificial bee colony algorithm and migrating bird optimization algorithm, are developed and improved to tackle the large-sized instances, where new encoding scheme and decoding procedure are developed for this new problem. The computational tests demonstrate that the utilization of collaborative robots reduces the cycle time effectively in the assembly line. The comparative study on a set of instances shows that the proposed methodologies obtain competing performance in comparison with other 12 implemented algorithms.

Optimizing a U-Shaped Conveyor Assembly Line Balancing Problem Considering Walking Times between Assembly Tasks

This research deals with a U-shaped assembly line balancing problem in which items are fixed on the conveyor. Operators execute the assembly tasks without removing items from the conveyor as the assembly items are assumed to be unsuitable for manual handling. The operators have to walk beside the conveyor at the same speed as the conveyor while they execute assembly tasks. If the operators want to assemble other items, they may have to walk to other positions at their normal walking speed. Therefore, the cycle time of an operator should include assembly times and walking times between assembly tasks. In this research, a mathematical model of the proposed U-shaped conveyor assembly line balancing problem was developed. Given a number of operators, the mathematical model can optimize the sequence of tasks and allocation of tasks to workstations using the commercial software LINGO 17. Because LINGO 17 requires a long computing time, simulated annealing (SA), which can accept worse new solutions in the search procedure, is proposed. The experimental results show that the proposed SA can optimize the problem efficiently.

Robust optimization for the integrated worker-cell assignment and sequencing problem in a lean U-shaped assembly line

Worker-cell allocation and sequencing problems play a central role in the optimization of mixed-model U-shaped assembly lines. Since this production layout is related to worker performance, we should consider the different skills of workers and their impact on actual working times and the resulting uncertainty. Thus, this research contributes to assigning workforce and determining model sequences in a lean U-shaped line, while workers are heterogonous and task processing times are uncertain. In order to overcome the uncertainty, an efficient robust optimization model is exerted. This study simultaneously focuses on integrating worker-cell assignment and sequencing models, due to the increasing importance of which. To do this, a non-linear programming (NLP) model is formulated. The proposed model is corroborated in small and medium scales using a commercial solver. Then, the Lagrangian relaxation (LR) algorithm is used for large-scale instances, so that bounds with tiny gaps within a reasonable interval are ensured. According to the results, the LR algorithm outperforms the commercial solver without LR in large-scale instances. The result shows that considering the sequencing concept leads to an improvement of the optimal value by two fifths. Moreover, not only does the LR algorithm solve large instances in logical CPU time, but also it shows only one in twenty deviations from the exact solutions.

Robust counterpart mathematical models for balancing, sequencing, and assignment of robotic U-shaped assembly lines with considering failures and setup times

Robust counterpart mathematical models for balancing, sequencing, and assignment of robotic U-shaped assembly lines with considering failures and setup times

A Greedy Randomized Adaptive Search for Solving Chance-Constrained U-Shaped Assembly Line Balancing Problem

This paper discusses the U-shaped assembly line balancing problem in case of stochastic processing time. The problem is formulated using chance-constrained programming and the greedy randomized adaptive search procedure is used to solve the problem. In order to prove the efficiency of the proposed algorithm, 71 problems taken from well-known benchmarks are solved and compared with the theoretical lower bound and 13 of them were compared with another approach used to solve the same problem in another paper, which is beam search. The results show that 59 problems are the same as the theoretical aspiration lower bound. In addition, the results of 11 of 13 problems compared with beam search are the same and the results of 2 problems are better than beam search. The t-test statistics is applied and showed that there is no significance difference between the proposed algorithm and the theoretical lower bound thus, the proposed algorithm shows efficiency when compared with the aspired values of the theoretical lower bound.

Multi-objective parallel adjacent U-shaped assembly line balancing collaborated by robots and normal and disabled workers

This paper emphasises the parallel adjacent U-shaped assembly line balancing problem in which the collaborative work forces in the system comprise human workers and robots. Apart from normal workers, disabled workers are also hired to enable the company to enjoy corporate tax benefits from the government. Five objectives related to the system as a whole and another three interacting entities are optimised simultaneously. A mathematical model is formulated for the first time for this type of layout. Due to the NP-hard nature of the problem, a reference point based evolutionary algorithm, namely non-dominated sorting teaching-learning-based optimisation (NSTLBO III), is proposed to solve medium- and large-sized problems. The performances of NSTLBO III are benchmarked in the sense of Pareto efficiency with two well-known multi-objective evolutionary algorithms, i.e. non-dominated sorting genetic algorithm (NSGA III) and multi-objective evolutionary algorithm based on decomposition (MOEA/D). The experimental results show that NSTLBO III surpasses its contestants significantly concerning the convergence to the true Pareto front.

Solving stochastic multi-manned U-shaped assembly line balancing problem using differential evolution algorithm

The U-shaped assembly lines help to have more flexibility than the straight assembly lines, where the operators can perform tasks in both sides of the line, the entrance and the exit sides. Having more than one operator in any station of the line can reduce the line length and thereby affects the number of produced products. This paper combines the U-shaped assembly line balancing problem with the multi-manned assembly line balancing problem in one problem. In addition, the processing times of the tasks are considered as stochastic, where they are represented as random variables with known means and variances. The problem is formulated as a mixed-integer linear programming and the cycle time constraints are formulated as chance-constraints. The proposed algorithm for solving the problem is a differential evolution algorithm. The parameter of the algorithm is optimized using experimental design and the computational results are done on 71 adapted problems selected from well-known benchmarks.

Balancing a U-Shaped Assembly Line with a Heuristic Algorithm Based on a Comprehensive Rank Value

An aim of sustainable development of the manufacturing industry is to reduce the idle time in the product-assembly process and improve the balance efficiency of the assembly line. A priority relationship diagram is obtained on an existing assembly line in the laboratory by measuring the task time of the chassis model, analyzing the product structure, and designing the assembly process. The type-E balance model of the U-shaped assembly line is established and solved by a heuristic algorithm based on the comprehensive rank value. The type-E balance problem of the U-shaped assembly-line plan of the chassis model is obtained, and the production line layout is planned. Combining instances to compare the results of the heuristic algorithm, genetic algorithm, and simulated annealing, comparison of the results shows that the degree of load balancing is slightly higher than genetic algorithm and simulated annealing. The balance efficiencies obtained by the heuristic algorithm are smaller than the genetic algorithm and simulated annealing. The calculation time is significantly less than the genetic algorithm and simulated annealing, and the scale of instances has little effect on the calculation time. The results verify that the model and the algorithm are effective. This study provides a reference for the entire process of the U-shaped assembly-line, type-E balance and the assembly products in laboratories.

A genetic algorithm-based robust approach for type-II U-shaped assembly line balancing problem

U-shaped assembly lines are widely used to implement just-in-time manufacturing. U-shaped assembly line balancing problem is important to improve productivity. Most of the studies ignore uncertainty such as operation times. This study applies robust optimisation method to deal with type-II U-shaped assembly line balancing problem (UALBP-2) under uncertainty. A mathematical programming model is proposed with interval task operation times, and a genetic algorithm is developed to deal with it. A robust solution is defined as the most frequent solution falling within a pre-specified percentage of the optimal solution for different sets of scenarios. The experimental results are compared with the expected solution to verify the feasibility and effectiveness of the robust method.

A genetic algorithm-based robust approach for type-II U-shaped assembly line balancing problem

A genetic algorithm-based robust approach for type-II U-shaped assembly line balancing problem

Balancing of parallel U-shaped assembly lines with a heuristic algorithm based on bidirectional priority values

Aiming at improving assembly line efficiency and flexibility, a balancing method of parallel U-shaped assembly line system is proposed. Based on the improved product priority diagram, the bidirectional priority value formula is obtained. Then, assembly lines are partitioned into z-q partitions and workstations are defined. After that, the mathematical model of the parallel U-shaped assembly line balancing problem is established. A heuristic algorithm based on bidirectional priority values is used to solve explanatory examples and test examples. It can be seen from the results and the effect indicators of the assembly line balancing problem that the heuristic algorithm is suitable for large balancing problems. The proposed method has higher calculation accuracy and shorter calculation time. The balancing effect of the parallel U-shaped assembly line is better than that of single U-shaped assembly line, which verifies the superiority of the parallel U-type assembly line and effectiveness of the proposed method. It provides a theoretical and practical reference for parallel U-type assembly line balancing problem.

Hybrid meta-heuristic algorithms for U-shaped assembly line balancing problem with equipment and worker allocations

Hybrid meta-heuristic algorithms for U-shaped assembly line balancing problem with equipment and worker allocations

Messtechnisch unterstützte Quantifizierung der Repetitionsbelastung des Hand-Arm-Systems bei manuellen Arbeitsprozessen an modernen Montagearbeitsplätzen und deren Bewertung

Measurement-based evaluation of the repetitive strain on the hand-arm system during manual work processes at modern assembly workplaces Objective: On both modern assembly lines and U-shaped lines, the workplaces comprise multiple workstations or work processes with differing requirements. This presents difficulties for recognition and assessment of the repetitive nature of the activity as a whole. This paper presents the measurement of repetitive strains on the upper extremities on real-case U-shaped assembly line systems. Methods: In a field study, a total of 24 workers in six plants in the metalworking and electrical engineering sectors were analysed at 18 different U-shaped assembly line workplaces. Movements of the hand-arm system and muscular activity of the hand flexor muscles (M. carpi ulnaris) and the trapezius muscles were recorded at each workplace over a period of between 1 and 2 hours by means of the CUELA measurement system and surface electromyography (EMG). Results: The medians of the angular velocities of the wrist varied between the different workplaces from a low of 2.4 °/s to a high of 20.5 °/s. Correspondingly, the average movement frequencies of the wrist lay between 0.23 and 0.43 Hz. Conversely, the micropause components (angular velocity < 1 °/s for Δt > 0.5 s) reached values between 13.5 % and 1.6 % of the working time. Without any evident relation to the kinematics, the surface EMG of the forearm flexors exhibited on average a dynamic (P90) load of around 20 % of the individual maximal voluntary EMG activity (MVE). At half of the workplaces however, the micro pauses (time component EMGRMS < 0.5 % MVE) totalled only 10 % or less of the recorded working time. Conclusions: Repetitive strains on the hand-arm system were also quantified in the field at workplaces differing in their degree of automation and with alternating workstations. Although the dynamic forces that must be applied at modern assembly lines are generally quite moderate, the associated repetitive strains are often high. This must be taken into particular consideration when planning job rotation on assembly lines. Keywords: assembly line – manual work processes – U-shaped assembly line – repetitive strain – workload analysis based on measured data

Integration of balancing and preventive maintenance in straight and U-shaped resource-dependent assembly lines: MILP model and memetic algorithm

In enterprises, machines are subject to some unavailable periods resulting in production halts. The consideration of preventive maintenance (PM) and resource assignment in straight and U-shaped assembly lines is of paramount importance. Hence, this paper aims to tackle the integration of PM and balancing problems in straight and U-shaped resource-dependent assembly lines via two new mixed-integer linear programming (MILP) models and a memetic algorithm. In the MILP models, the optimal PM intervals of all machines and all PM scenarios are determined according to the maximization of the availability. In the memetic algorithm, a multi-attribute solution representation, including heuristic rule matrix, task separator set and machine assignment permutation, is designed to build a feasible solution. For this multi-attribute solution representation, this algorithm respectively designs different crossover, mutation and local search operators to exploit the space around the solutions. Finally, five comparison experiments are conducted to prove the effectiveness of the MILP models in small-scale instances and the superiority of the improvements and memetic algorithm in all instances.

Assembly line balance research methods, literature and development review

With the continuous upgrading of the manufacturing system, the assembly line balancing problem (ALBP) is gradually complicated, and the researches are constantly deepened in the application theory and solution methods. In order to clarify the research direction and development status of assembly line balancing, 89 articles are read and studied. We classify ALBPs to construct the network structure of research from horizontal classification and vertical thinking. The ALBP framework is horizontally given according to the number of models (i.e. the number of products), the layout shape of the assembly line, and the data of task time. The “seven steps for scientific paper” is vertically proposed according to the research steps to comb the research path of scientific and technological literature. The horizontal and vertical extension crosses and constructs the network structure of the ALBP. Any horizontal problem intersects with any step of the vertical “seven steps for scientific paper” to form a research point. We analyze 89 articles according to the development path from the straight line to U-shaped line and then to two-sided U-shaped/parallel U-shaped assembly line, summarize the research algorithm of assembly line balance and count the number of articles, and point out the latest research direction and algorithm development trend of assembly line balance.