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Abadi Ginting
Universitas Sumatera Utara
Industrial & Manufacturing Engineering

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PENJADWALAN PRODUKSI JOB SHOP DENGAN MENGGUNAKAN ALGORITMA TABU SEARCH PADA PT. XYZ Rencus Siburian; Abadi Ginting
Jurnal Teknik Industri USU Vol 4, No 2 (2013): JURNAL TEKNIK INDUSTRI USU
Publisher : Departemen Teknik Industri Universitas Sumatera Utara

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Abstract

The research was conducted at PT. XYZ which is a manufacturing company engaged in the manufacture of spare parts of screwpress and digester. The study was conducted only in the manufacture of spare parts of screwpress, namely protection nut, screw worm, cone guide, dismentling plate, cone, pin & coupling nut, strainer, extension shaft, intermediate gear, and flexible coupling. The flow pattern at PT. XYZ is job shop and produced by make to order, each product has a different process flow, sequence and timing of different processes, but through the facilities of the same engine, so may result in idle time on a machine and the accumulation of another job on the machine. PT. XYZ used production scheduling by FCFS rule that still result in a delay in the completion of orders and there was so much undone job because makespan values was too large. The purpose of this study was to minimize the makespan, namely the Tabu Search Algorithm. Results from this study is the reduction occurred from time to schedule company with Tabu Search Algorithm is from 141.22 hours or minutes become 132.14 8473.2 7928.4 hours or minutes. Relative Error shows that the savings obtained makespan between Tabu Search Algorithm with the method of company is 6.8715% and the value of Efficiency Index is 1.068715. It can be concluded that the Tabu Search Algorithm produces a smaller makespan than the company actual scheduling.
USULAN PEMILIHAN ALTERNATIF TIPE CRANE BERDASARKAN FAKTOR BIAYA DAN FISIK DI PT. XYZ Pandapotan Simarmata; Abadi Ginting
Jurnal Teknik Industri USU Vol 4, No 2 (2013): JURNAL TEKNIK INDUSTRI USU
Publisher : Departemen Teknik Industri Universitas Sumatera Utara

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Abstract

PT XYZ is a company concerned in the port services, one of which is the loading/unloading of goods using a mobile crane. Based on observations, a mobile crane company owned only one unit and installed capacity company are 92 tons per hour company while the load demand on average 157 tons per hour. From the above data shows that the company can not meet the load demand due to insufficient capacity. In an attempt to adjust the loading capacity and load demand is done with addition of capacity through addition of crane. Forecasting is used as a method to predict the loading demand in the future. Data of forecasting is used as reference in approximating the exact number of cranes. Based on the calculations, crane that needed to solve the problem are two units, so it required the addition one crane. The proposed alternative type of cranes are mobile crane 5 ton capacity and luffing crane 10 tons capacity. The best type of crane are selected using decision theory which use payoff approach, they are payoff profit and payoff risk. From the calculation, the best type of alternative criteria from the payoff profit is Luffing crane with a value 7.75, 10, 2.5, 2.5, while for the payoff risk, the best is mobile crane with a value 4.55; 3.5; 7; 1,75. The best type of crane based on comparative payoff is luffing crane. With the addition of luffing crane loading capacity of 10 tons to 276 tons of companies per hour and can meet the load demand loading/unloading and companies.
PENENTUAN KAPASITAS TERMINAL KAPAL PENGANGKUT CURAH KERING Aidil Kurniawan; Abadi Ginting
Jurnal Teknik Industri USU Vol 4, No 2 (2013): JURNAL TEKNIK INDUSTRI USU
Publisher : Departemen Teknik Industri Universitas Sumatera Utara

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (660.256 KB)

Abstract

PT. XYZ is a company engaged in the field of port services that serve the activity loading/unloading dry bulk vessels loaded. Based on the interview with the company known that the arrival of ships per day up to 5 ships with a length of service up to 3 days per vessel is still causing queues on dry bulk terminal. The research method used was the distribution of test data on the number of boat arrivals, the data between the time of arrival of the ship, and the ship service time approaches poisson and exponential distribution patterns to determine the queuing model used. The results obtained by the data of ship arrivals follow Poisson distribution and arrival time data between ship and ship service time follows an exponential distribution with the queuing model M/M/3: FIFO/∞/∞. Calculation of the attributes of the queue is known that λ = 0.7875 μ = 0.3168 with the average number of vessels in the queue Lq ≈ 3.3576 as 4 boats and ships an average time while the system is 7.4202 days. With the aspiration level of company that the average number of vessels in the queue no more than one vessel and the average ship time while the system is no more than 4 days, the queuing problem is solved by giving suggestions to increase the number of dock as much as 1 unit. With this addition then, the average number of vessels in the queue to be one ship, while the average time for the ship to be in the system to no more than 4 days. This condition states that the problem of queues at the dry bulk terminal is in the category as desired by the company.
Co-Authors Aidil Kurniawan Pandapotan Simarmata Rencus Siburian