QUEUEING SYSTEM PRODUCTIVITY ANALYSIS IN FROZEN FISH FILLET PROCESS INDUSTRY (CASE STUDY AT PT. GTS, WEST JAVA) - Machfud dan Arviano Haryanto Sahar (Department of Agroindustrial Technology, Bogor Agricultural University, 2008)
ABSTRACTFishing industries are one of Indonesia huge source for Indonesia capital income, and Indonesia is one of the biggest exporter of fisheries commodity in the global market. In order to maintain and to expand its market, a study based on modern science is held to help the development of fishing industry in Indonesia. Performance of queuing system in a production line can be an indicator for effectivity and efficiency in the production system. PT. GTS is one of Indonesian companies that has a well known reputation in exporting frozen fish fillet.Analysis technique that was used in this research was Monte Carlo simulation and line balancing model. Queuing system in the frozen fish fillet production line is composed by 13 work stations and 4 of the stations are a join work station (which handle material from all of production line). This queuing system simulation named SAPFIB “Sistem Antrian Produksi Fillet Ikan Beku”, consists of three models and four sub models. Those models are queuing model that simulate queuing condition of receiving station to panning and after curing station (Model A), line balancing model at freezing station (Model B), and model that simulate queuing system at packing station (Model C).The result for the main model simulation in the real state are balking in after curing station, queuing in the freezing station and there is no queuing in packing station. In order to improve the performance of production line, two scenario of queuing system were developed. The two scenario are changing the rate of incoming material (X’s scenario) and changing the composition of operator in each work station (Y’s scenario). The simulation of X’s as well as Y’s scenario showed that those scenario increase the server utilization and the processed material and the balking condition became zero. The Y’ s scenario is better than X’s scenario in term of the queuing condition. The Y’s scenario reduced the ice’s cost and speed up the flow time. Keywords: Queuing, Simulation, Frozen Fish Fillet