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The purpose of this paper is to construct a task assignment model for U-shaped production lines with collaborative task, which is optimized by minimizing the number of workers and balancing the workload of the operators. The ultimate goal is to increase productivity by increasing the U-line balance and balancing the load on the operators.

First, task selection and update mechanism are analyzed and the task selection mechanism suitable for collaborative task is proposed. Second, M-COMOSAL is obtained by improving the original COMOSAL. Finally, The M-COMOSAL algorithm and the COMAOSAL algorithm are used to perform job assignment on the double-acting clutch U-shaped assembly line.

According to the allocation scheme obtained by M-COMSOAL, the beat can be adjusted according to the change of order demand. The final allocation scheme is superior to the COMSOAL algorithm in terms of number of workers, working time, production tempo and balance rate. In particular, compared with the old scheme, the new scheme showed a decrease of 16.7% in the number of employees and a 18.8% increase in the production line balance rate. Thus, the method is helpful to reduce the number of operators and balance the workload.

The new algorithm proposed in this paper for the assignment of collaborative task can minimize the number of workers and balance the load of operators, which is of great significance for improving the balance rate of U-shaped production lines and the utilization of personnel or equipment.

The purpose of this paper is to find the most efficient assembly line balancing solution across many heuristic line balancing methods, in assistance with a developed computer program.

In this paper, assembly line balancing problem was analyzed using t-shirt and knitted pants data. A computer program using MATLAB software for the solution of assembly line balancing problems has been developed. In this study, following heuristic assembly line balancing methods were applied: Hoffman method; position weight method; COMSOAL method; and Kilbridge and Wester method. A MATLAB program has been developed by taking into account of theoretical solution of all these methods. Later the program is developed further by analyzing solutions made manually and is made to verify the developed program.

Pre-studies which were conducted in order to decide which programming language would be the best choice for line balancing methods’ application came out with the result that MATLAB, from between C, C++, C# and Java, would be the best software choice. The main reason for this choice is that MATLAB is a powerful matrix operation software with a powerful user interface designing tool and has the tools to make development program to be used universally in every computer.

When the researches were investigated, it is clearly seen that, this study is the first research on using computer program for solving assembly line balancing problem.

Describes a systematic procedure for the design of a manufacturing assembly system, which has been developed in response to the problems associated with the allocation of tasks to workstations, under conditions of uncertainties (and, hence, risks) in some key system parameters. Adopts the methodology of stochastic modelling, whereby various probability distributions are integrated within a modified COMSOAL algorithm, as a means of addressing the uncertainties associated with key manufacturing assembly system variables, such as cycle time and task times. The proposed computer‐oriented methodology is code‐named CIMASD, and incorporates four basic objective criteria options: minimizing the number of workstations; minimizing the balance delay; minimizing the cycle time; or a combination of two or more. Discusses four variants of the CIMASD methodology, designed and equipped to reflect on various uncertainty circumstances under which manufacturing assembly system designs are performed in practice. Demonstrates the efficacy of the CIMASD methodology by applying two of its variants to a case study. Shows that the proposed methodology is capable of facilitating far more informative manufacturing system design than would otherwise be possible: CIMASD can incorporate effective cost saving features, which are useful in the planning, designing and scheduling of workstation tasks, in a typical manufacturing assembly system design.

Cycle time fluctuations in assembly lines are one of the important reasons of re‐balancing. As a result of re‐balancing of assembly lines, it will be necessary to change task sequences or equipment locations. The purpose of this paper is to find the task sequence which enables assembly line balancing (ALB) with minimum number of stations (NS) for different cycle times such that tasks and equipment or fixture locations remain unchanged.

In this paper a heuristic which consist of two stages is proposed to find a common task sequence for different cycle times in assembly lines.

It is shown that optimal NS for different cycle times can be achieved with a fixed task sequence.

The approach is limited to a single model case. Model variety together with cycle time variety can be investigated in further studies.

Assembly lines which require less time and cost for re‐balancing can be easily designed by the proposed approach.

ALB problem is handled with a new viewpoint. Also, it is observed that the proposed approach serves as a bridge between assembly line design and balancing. In this regard, it is thought to have an important place in the ALB literature.

This paper briefly reviews the assembly line balancing techniques developed over the last 30 years. It attempts to establish the direction of research, to identify unexplored areas with potential for study and recommends future courses of action.

Outlines the specific characteristics of semiautomatic production lines which, in relative terms, are given less attention than other types of line. Suggests a methodology for balancing such lines, making comparison thereof with the traditional method of line balancing. Applies the method to a case which is a typical semiautomatic line.

This paper aims to discuss the sequence-dependent forward setup time (FST) and backward setup time (BST) consideration for the first time in two-sided assembly lines. Sequence-dependent FST and BST values must be considered to compute all of the operational times of each station. Thus, more realistic results can be obtained for real-life situations with this new two-sided assembly line balancing (ALB) problem with setups consideration. The goal is to obtain the most suitable solution with the least number of mated stations and total stations.

The complex structure it possesses has led to the use of certain assumptions in most of the studies in the ALB literature. In many of them, setup times have been neglected or considered superficially. In the real-life assembly process, potential setup configurations may exist between each successive task and between each successive cycle. When two tasks are in the same cycle, the setup time required (forward setup) may be different from the setup time required if the same two tasks are in consecutive cycles (backward setup).

Algorithm steps have been studied in detail on a sample solution. Using the proposed algorithm, the literature test problems are solved and the algorithm efficiency is revealed. The results of the experiments revealed that the proposed approach finds promising results.

The sequence-dependent FST and BST consideration is applied in a two-sided assembly line approach for the first time. A genetic algorithm (GA)-based algorithm with ten different heuristic rules was used in this proposed model.

Recognising the enormous potential of just‐in‐time (JIT) concepts for boosting productivity and quality, an increasing number of US and European firms consider adopting JIT concepts in manufacturing. However, the transfer of a manufacturing policy from traditional to JIT always requires radical structural changes in a production line design. One typical example of these changes is uniform assembly which does not allow high variability in the production schedules. Consequently, major hindrance to uniform assembly is a random fluctuation of task processing times in assembly line balancing. This article proposes a heuristic which takes into account stochastic task processing times and further develops a work assignment with the lowest expected total cost as well as an assignment with the highest work completion probability crucial for the success of JIT manufacturing.

Assembly lines are widely employed in manufacturing processes to produce final products in a flow efficiently. The simple assembly line balancing problem is a basic version of the general problem and has still attracted the attention of researchers. The type-I simple assembly line balancing problems (SALBP-I) aim to minimise the number of workstations on an assembly line by keeping the cycle time constant.

This paper focuses on solving multi-objective SALBP-I problems by utilising an artificial bee colony based-hyper heuristic (ABC-HH) algorithm. The algorithm optimises the efficiency and idleness percentage of the assembly line and concurrently minimises the number of workstations. The proposed ABC-HH algorithm is improved by adding new modifications to each phase of the artificial bee colony framework. Parameter control and calibration are also achieved using the irace method. The proposed model has undergone testing on benchmark problems, and the results obtained have been compared with state-of-the-art algorithms.

The experimental results of the computational study on the benchmark dataset unequivocally establish the superior performance of the ABC-HH algorithm across 61 problem instances, outperforming the state-of-the-art approach.

This research proposes the ABC-HH algorithm with local search to solve the SALBP-I problems more efficiently.

The purpose of this study is to develop a new mathematical model and an exact solution method for an assembly line rebalancing problem. When an existing assembly line has to be adapted to a new production context, the line balancing, resources allocation and component management solutions have to be revised. The objective is to minimize the number of modifications to be done in the initial line in order to reduce the time and investment needed to meet new production requirements. The proposed model is evaluated via a computational experiment. The obtained results the efficacy of the proposed method.

This paper develops a new mathematical model and an exact solution method for an assembly line rebalancing problem with the objective to minimize the number of modifications to be done in the initial line to reduce the time and investments needed to meet new production requirements.

The computational experiments show the efficacy of the proposed method.

These reconfiguration costs were analysed for different part-feeding policies that can be adopted in an assembly line.