ASSEMBLY LINE BALANCING BASE FRAME AND SUB ASSEMBLY EXCAVATOR USING GENETIC ALGORITHM METHODS

Bung Ayuning Syarifah, Dida Diah Damayanti, Widia Juliani

Abstract


In the company experienced an inachievement of production or lost demand. Based on the time each station has an inconsistency or no balance, so it can cause idle time. This occurs due to the allocation of workloads between work stations uneven so that there is unemployment in the operator and result in the buildup of WIP caused by a bottleneck  on a workstation with a time station Significant work between other workstations. Therefore, the assembly line balancing is done by doing the minimation of the workstation and allocating the workload on the workstation. The balance in the placement of work elements and workloads on an assembly line can impact the efficiency of the line. The  work station applied is a single model. The method used is a Meta-heuristic method of Genetic Algorithm used to balance the base frame assembly line and sub-assembly in the excavator assembly because this method can produce better solutions and Fast. In this research conducted 3 calculation scenario that is the condition to fulfill the time, the condition of utilization of existing workstations by utilizing 4 existing workstations and the condition increased demand 20%. So that the result of line efficiency in the scenario to fulfill the time at the base frame assembly of 100% of the actual condition of 60.45%, smoothing index of 0 so it can be said the line goes smoothly, balance delay of 0% then is said to be less idle time and the workstation has decreased from 4 workstations to 1 workstation, for a 100% sub-assembly line efficiency with the merging of each sub assembly into 1 workstation, smoothing index of 0 So it can be said the line goes smoothly, balance delay of 0% then it is said idle time is smaller. In the scenario utilization of  existing workstation is the utilization of 4 workstations that exist line efficiency in the base frame assembly of 90.49%. In the scenario of demand increase 20% line efficiency of 100% with the number of workstations as much as 1 workstation, on the sub-assembly line to 1 station with the line efficiency of 100%, smoothing index of 0 so it can be said Line goes smoothly, balance delay is 0% then it said idle time is smaller.

 

Keywords: 1 Assembly line balancing · 2 Genetic algorithm · 3 Single model


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