Papers by Keyword: Assembly Line Balancing

Abstract: Assembly line balancing of Type-E problem (ALB-E) is an attempt to assign the tasks to the various workstations along the line so that the precedence relations are satisfied and some performance measures are optimised. A majority of the recent studies in ALB-E assume that any assembly task can be assigned to any workstation. This assumption lead to higher usage of resource required in assembly line. This research studies assembly line balancing of Type-E problem with resource constraint (ALBE-RC) for a single-model. In this work, three objective functions are considered, i.e. minimise number of workstation, cycle time and number of resources. In this paper, an Elitist Non-dominated Sorting Genetic Algorithm (NSGA-II) has been proposed to optimise the problem. Six benchmark problems have been used to test the optimisation algorithm and the results are compared to multi-objective genetic algorithm (MOGA) and hybrid genetic algorithm (HGA). From the computational test, it was found NSGA-II has the ability to explore search space, has better accuracy of solution and also has a uniformly spaced solution. In future, a research to improve the solution accuracy is proposed to enhance the performance of the algorithm.

Abstract: Two-sided assembly lines are widely applied in plants for producing large-sized high volume products, such as trucks and buses. Since the two-sided assembly line balancing problem (TALBP) is NP-hard, it is difficult to get an optimal solution in polynomial time. Therefore, a novel swarm based heuristic algorithm named gravitational search algorithm (GSA) is proposed to solve this problem with the objective of minimizing the number of mated-stations and the number of stations simultaneously. In order to apply GSA to solving the TALBP, an encoding scheme based on the random-keys method is used to convert the continuous positions of the GSA into the discrete task sequence. In addition, a new decoding scheme is implemented to decrease the idle time related to sequence-dependent finish time of tasks. The corresponding experiment results demonstrate that the proposed algorithm outperforms other well-known algorithms.

Abstract: This research develops a heuristic algorithm for assembly line balancing problem (ALBP) of stitching lines in footwear industry. The proposed algorithm can help to design the stitching line with workstations, machines and operators for the production of every new product model. Rank-positional-weighted heuristics and hybrid genetic algorithms are proposed to solve ALBP. First, the heuristics assign tasks and machines to workstations. This solution is then used as an initiative population for hybrid genetic algorithm for further improvement. Real data from footwear manufacturers and experimental designs are used to verify the performance of the proposed algorithm, comparing with one existing bidirectional heuristic. Results indicate that when the size and shape of shoes increase, the proposed genetic algorithm achieves better solution quality than existing heuristics.Production managers can use the research results to quickly design stitching lines for short production cycle time and high labor utilization.

Abstract: Assembly sequence planning (ASP) and assembly line balancing (ALB) problems are two essential problems in the assembly optimization. This paper proposes an ant colony algorithm for integrating assembly sequence planning and assembly line balancing, to deal with the two problems on parallel, and resolve the possible conflict between two optimization goals. The assembly sequence planning problem and the assembly line balancing problem are discussed, the process of the proposed ant colony algorithm is investigated. The results can provide a set of solutions for decision department in assembly planning.

Abstract: As for the typeIassembly line balancing problem in complex products, the mathematical model of optimization goal is established with its optimization goal of minimizing the number of workstations as well as minimizing the differences in assembly complex relationship, and with the introduction of the framework of cultural evolution, a multi-cultural particle swarm algorithm is presented. The algorithm used arranged code so that the particle can still be able to meet the job constraints after its been decoded; using crowded distance to sort operator and remove the extra particles, in order to ensure a uniform distribution of the Pareto front; in order to improve the efficiency of the convergence of the algorithm, we adjust the flight parameters of particle basing on the dynamic changes in crowding distance. Through the comparison of standard test problems with other algorithms, we indicate the effectiveness of the proposed algorithm.

Abstract: This paper presents a multi-objective genetic algorithm to solve the U-shaped assembly line balancing problem. The performance criteria for the number of workstations and the variation of workload are considered. The results of experiments show that the proposed model produced as good or even better line efficiency of workstation integration and improved the variation of workload.

Abstract: An improvement ant colony optimization(ACO) is proposed to solve the simple assembly line balancing problem of type-1 (SALBP-1) which aims to minimize the number of workstations for a given cycle time of assembly line. In the algorithm, three heuristic factors and two pheromones: (1) the pheromone between task and station, (2) the pheromone among tasks, are introduced to design the selection mechanism which is used to select task for station. The task assignment mechanism is proposed to assign suitable tasks to station. Ants select task based on selection mechanism, and then assign suitable one to station according to assignment mechanism. The result of literature test problems indicates the effectiveness of the proposed algorithm.

Abstract: Assembly Line Balancing (ALB) comprises ordering of tasks among workstations to satisfy precedence constraints and objective functions. Due to the specific features of an aircraft, such approach is not fully suitable for the case of an aircraft Final Assembly Line (FAL). Where, the number of workstations relates to technological criteria rather than to a calculation aiming to minimize a specific parameter. Workload smoothing is addressed once the FAL configuration is defined. To improve current practices, a methodological approach was taken to address the conceptual modeling of an aircraft assembly line.

Abstract: Lean Production, which was born in manufacturing industry, is considered to be the most suitable production mode for the modern manufacturing enterprises. This paper investigates the application of Lean Production Thinking in the assembly technology, and proposes the concept of Lean Assembly. The Lean Assembly could be described as follows: Eliminating all wastes in assembly process through certain management tools and technologies. There are three sub goals of Lean Assembly: zero inventories, high flexibility, zero defects. What’s more, this paper studies several key technologies, such as assembly line balancing, mixed-model scheduling, part supplying, assembly cell, virtual assembly etc.

Abstract: This study discusses construct an Integer Nonlinear Programming (INLP) mathematical model is presented to solve the Two-Sided assembly line balancing problem (TALB) of Type-3. The mathematical models proposed in this paper are constructed by the syntax of Lingo, and the built-in “global solver” is selected as the solving method to conduct the searching of global optimum solutions. Therefore, the Type-3 of TALB for optimal distribution by the mathematical models proposed in this study to be solved. This study creates a highly repeated characteristic because of the adoption of Lingo packaged software. Finally, the tests are carried out on a well-known benchmark set of problem, and experimental results demonstrate that the proposed model is efficient.