Time and space multi-manned assembly line balancing problem using genetic algorithm

Purpose: Time and Space assembly line balancing problem (TSALBP) is the problem of balancing the line taking the area required by the task and to store the tools into consideration. This area is important to be considered to minimize unplanned traveling distance by the workers and consequently unplanned time waste. Although TSALBP is a realistic problem that express the real-life situation, and it became more practical to consider multi-manned assembly line to get better space utilization, few literatures addressed the problem of time and space in simple assembly line and only one in multi-manned assembly line. In this paper the problem of balancing bi-objective time and space multi-manned assembly line is proposed Design/methodology/approach: Hybrid genetic algorithm under time and space constraints besides assembly line conventional constraints is used to model this problem. The initial population is generated based on conventional assembly line heuristic added to random generations. The objective of this model is to minimize number of workers and number of stations. Findings: The results showed the effectiveness of the proposed model in solving multi-manned time and space assembly line problem. The proposed method gets better results in solving real-life Nissan problem compared to the literature. It is also found that there is a relationship between the variability of task time, maximum task time and cycle time on the solution of the problem. In some problem features it is more appropriate to solve the problem as simple assembly line than multi-manned assembly line. Originality/value: It is the first article to solve the problem of balancing multi-manned assembly line under time and area constraint using genetic algorithm. A relationship between the problem features and the solution is found according to it, the solution method (one sided or multi-manned) is definedPeer Reviewe

Line balancing optimization under robot location and worker-station assignment considerations: A case study of a dishwasher factory

The focus of this article is on the line balancing work planned on the assembly line of a Dishwasher Factory. The main motivation is to make the assembly line more stable by grouping similar jobs and to increase the number of dishwashers produced per shift. In addition to these basic objectives, this study aims to rearrange the number of operators, optimize work-stock area and balance the man power at the stations. We propose a novel integer programming model that takes into account the location selection of stations, elevators and robots and the decisions of assigning jobs and workers to stations and use a commercial solver to solve the problem exactly. In the light of the outputs obtained from the solution of the problem, the current system and the improved system results were compared. First, the increase of dishwasher production capacity under current operational guidelines was evaluated and then the effect of grouping jobs on cycle time was evaluated. Based on the results of the sensitivity analysis, different results were proposed to optimize the current tempo, cycle time and number of workers. The results indicate that the number of workers can be reduced by 36%, while the number of dishwashers produced per shift can be increased by up to 52%, when all other inputs of the problem are fixed. Compared to the current practice, in the solution proposed to the manufacturing firm, the number of stations opened with similar jobs grouped was reduced by 68%, the number of fields that could be used by the stations was kept the same, the number of workers was reduced by 10% and the cycle time was improved by 4.34 seconds and the number of machines produced per shift increased by 43%

A mathematical model and genetic algorithm-based approach for parallel two-sided assembly line balancing problem

Copyright © 2015 Taylor & Francis. This is an Accepted Manuscript of an article published by Taylor & Francis in Production Planning & Control on 27 April 2015, available online: http://dx.doi.org/10.1080/09537287.2014.994685Assembly lines are usually constructed as the last stage of the entire production system and efficiency of an assembly line is one of the most important factors which affect the performance of a complex production system. The main purpose of this paper is to mathematically formulate and to provide an insight for modelling the parallel two-sided assembly line balancing problem, where two or more two-sided assembly lines are constructed in parallel to each other. We also propose a new genetic algorithm (GA)-based approach in alternatively to the existing only solution approach in the literature, which is a tabu search algorithm. To the best of our knowledge, this is the first formal presentation of the problem as well as the proposed algorithm is the first attempt to solve the problem with a GA-based approach in the literature. The proposed approach is illustrated with an example to explain the procedures of the algorithm. Test problems are solved and promising results are obtained. Statistical tests are designed to analyse the advantage of line parallelisation in two-sided assembly lines through obtained test results. The response of the overall system to the changes in the cycle times of the parallel lines is also analysed through test problems for the first time in the literature

The Time and Space Assembly Line Balancing Problem: modelling two new space features

The Time and Space Assembly Line Balancing Problem (TSALBP) is a natural evolution of the well known Simple Assembly Line Balancing Problem that also takes into consideration the space required by the machinery and assembly parts of the product. The present work proposes a more realistic space allocation approach. Firstly, it allows consecutive workstations to share a reasonable amount of space without an additional time cost. And secondly, assigning tasks that need the same machinery together so that not every workstation needs be fully equipped. In addition, a mathematical programming model and an intuitive heuristic for the problem taking into account these innovative features are developed and tested on an adapted widely used set of data for the typical TSALBP.Outgoin