Optimizing Assembly Line Balancing: A Simulation Approach Free Essay Example

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Abstract

The advantages of assembly line balancing provide in knowledge is well known and it is one of the most important topics in literature. There are many ways to solve the assembly line balancing problem, one of the techniques that frequently used in assembly line balancing is a simulation approach. In this paper, the power converter assembly line consists of 27 major tasks that are assigned to 19 workstations is studied. The line balancing problem is solved by using two heuristics methods and then, by using simulation, the results from both methods are compared and the best method is chosen.

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Keywords: assembly line balancing problem; heuristics; simulation.

INTRODUCTION

Assembly line consists of more than one workstations where each workstation has their own set of tasks. Generally, a part of the product moves from one workstation to another workstation until it completes as a finished product. The process to create a complete product requires each workstation to perform their job and must follow a set of pre-determined precedence flow[1].

During processes stage of production, two main activities are focused in order to optimize the assembly line. Determining the optimum automation level is the first activity in the assembly. The aim of this activity is to apply the appropriate automation level in assembly in order to balance the investment in automation and the output. The second activity is assigning the assembly tasks into workstations, such that every workstation has equal or almost equal loading task. This activity is usually known as the assembly line balancing [2].

Assembly line balancing (ALB) is the way of assigning a group of tasks to be processed by strictly follows the precedence flow to the point that all workstations have been roughly equal allocated time to complete their tasks. The objective of the ALB is to minimize the idle time of the assembly line and at the same time, it is able to improve the efficiency of line production via the reduction of the number of workstations, the reduction of the cycle time, or a combination of both [3].

There are many industrial problems where the assembly line balancing problem is one of them. It is a complex problem that has to consider two important aspects which are performances and costs. The assembly line performances are generally related to its throughput, i.e. the number of products per unit time that can be completed. Then, the number of resources (workers and equipment) required to finish all tasks is known as costs. The assembly line balancing problem is basically a trade-off problem between performances and costs [4].

A group of tasks is allocated to workstations under a few imperatives during the line balancing include

each task is assigned to one and only one workstation;

the total processing time of the tasks of any workstation must less or equal to cycle time; and

each task must follow the precedence relationship strictly and cannot be violated [5].

Because of high capital requirements, numerous researches can be found in literature, which has been done with the end goal in their mind to describe and unravel the mystery of assembly line balancing. The simulation model has been used in some of these researches to execute the experimentations on the actual system and to find the ways to improve the system. An integrated line balancing and simulation-based evaluation method were used by Driscoll and Abdel-Shafi [6] to solve the assembly line balancing problem. The variation in line speed, mixed product processing and physical make-up of stations was studied.

By using the heuristic method similar to the ranked positional weight method, line balancing under certain balance confidence was performed. Then, carry out the simulation of four layouts to analyze the performance of the layouts. Some parameter such as idle time, lost time and so forth were used to compare the performance between layouts. McMullen and Frazier [7] presented 23 different heuristics for seven line balancing problems. They simulated these production lines and then use the outputs of simulation to decide which assembly line balancing heuristics would be the best choice for their problem. The line configurations in a mixed-model PC camera assembly line for varying the levels of demand were derived by Mendes, Ramos, Simaria, and Vilarinho [8] using simulated annealing metaheuristic. Simulation models use the results of the metaheuristic and then compare the flow time and resource utilization as performance measures and provided operational support and help to fine-tune line configurations.