Suprayogi .
Universitas Dian Nuswantoro Semarang

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MODEL SIMULASI ALUR PROSES PETI KEMAS IMPOR PADA PEMILIHAN LOKASI EXTERNAL YARD DI KAWASAN PENYANGGA PELABUHAN Rusgiyarto, Ferry; Frazilla, Russ Bona; Sjafruddin, Ade; ., Suprayogi
Jurnal Transportasi Vol 17, No 1 (2017)
Publisher : Jurnal Transportasi

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (1010.245 KB) | DOI: 10.26593/jt.v17i1.2705.%p

Abstract

Abstract Increasing container flows and lack of land development for the container terminal, cause yard sub-functions are located in the port buffer area. This condition emerges additional transportation cost and causes traffic problems on the access road. This paper deals with simulation model construction which will be used to find optimum external yard configuration location in the port buffer area. Discrete Event Simulation Model will be used to simulate import container flow processes in the port container terminal. The Objective function of the external yard location model is to minimize user transport cost and to maximize operator benefit. Jakarta International Container Terminal data is used to construct the model. Model concept is run based on the scenario assumption of 3 TPS’s and 30 day simulation period. Based on three replicants and five times running, the optimum result is 3 TPSs simultaneously operation. The model needs detail elaboration in associated to model objective function and model optimization constraint. It is required detail validation, in term of service time value, distribution pattern and arrival rate in each unit server modelled in the next step of the research. Nevertheless, the model gives unique and relatively consistent result value of each trial. It is indicated that the method can be used to solve the research objective. Keywords: simulation model, import container, location model, external yard  Abstrak Peningkatan arus peti kemas dan keterbatasan lahan terminal peti kemas menyebabkan beberapa subfungsi yard ditempatkan di kawasan penyangga pelabuhan. Kondisi ini menyebabkan tambahan biaya transportasi dan permasalahan lalulintas pada jalan akses. Makalah ini berkaitan dengan pembentukan model simulasi yang akan digunakan untuk menentukan lokasi optimum beberapa external yard di kawasan penyangga pelabuhan. Model Discrete Event Simulation digunakan dalam simulasi alur proses peti kemas impor. Fungsi tujuan model adalah minimasi biaya transportasi pengguna dan maksimasi keuntungan operator. Data peti kemas Jakarta International Container Terminal (JICT) digunakan untuk menyusun model. Konsep model dijalankan berdasarkan asumsi skenario tiga TPS dan 30 hari periode simulasi. Berdasarkan tiga replikasi dan lima percobaan running model, hasil optimum adalah pengoperasian tiga TPS bersamaan. Model perlu dielaborasi lebih lanjut terkait fungsi tujuan dan batasan model optimisasi. Diperlukan validasi rinci terhadap nilai waktu pelayanan, pola distibusi, dan tingkat kedatangan unit-unit pelayanan pada langkah selanjutnya dari penelitian. Walaupun demikian, model memberikan hasil yang unik dan relatif konsisten setiap percobaan. Hal ini mengindikasikan metode dapat digunakan untuk memecahkan tujuan penelitian. Kata-kata kunci: model simulasi, peti kemas impor, model lokasi, external yard
Vehicle Routing Problem with Backhaul, Multiple Trips and Time Window Ong, Johan Oscar; ., Suprayogi
Jurnal Teknik Industri Vol 13, No 1 (2011): JUNE 2011
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | Full PDF (276.788 KB) | DOI: 10.9744/jti.13.1.1-10

Abstract

Transportation planning is one of the important components to increase efficiency and effectiveness in the supply chain system. Good planning will give a saving in total cost of the supply chain. This paper develops the new VRP variants’, VRP with backhauls, multiple trips, and time window (VRPBMTTW) along with its problem solving techniques by using Ant Colony Optimization (ACO) and Sequential Insertion as initial solution algorithm. ACO is modified by adding the decoding process in order to determine the number of vehicles, total duration time, and range of duration time regardless of checking capacity constraint and time window. This algorithm is tested by using set of random data and verified as well as analyzed its parameter changing’s. The computational results for hypothetical data with 50% backhaul and mix time windows are reported.
Model Integrasi Penjadwalan Produksi Batch dan Penjadwalan Perawatan dengan Kendala Due Date ., Zahedi; Samadhi, TMA Ari; ., Suprayogi; Halim, Abdul Hakim
Jurnal Teknik Industri Vol 16, No 2 (2014): DECEMBER 2014
Publisher : Institute of Research and Community Outreach - Petra Christian University

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.9744/jti.16.2.73-82

Abstract

This paper discusses the integration model of batch production and preventive maintenance scheduling on a single machine producing an item to be delivered at a common due date. The machine is a deteriorating machine that requires preventive maintenance to ensure the availability of the machine at a desired service level. Decision variables of the model are the number of preventive maintenances, the schedule, length of production runs, as well as the number of batches, batch sizes and the production schedule of the resulting batches for each production run. The objective function of the model is to minimize the total cost consisting of inventory costs during parts processing, setup cost and cost of preventive maintenance. The results show three important points: First, the sequence of optimal batches always follows the SPT (short processing time). Second, variation of preventive maintenance unit cost does not influence the sequence of batches. Third, the first production run length from production starting time is smaller than the next production run length and this pattern continues until the due date. When in process inventory unit cost is increased, the pattern will continue until a specified cost limit, and beyond the limit the pattern will change to be the opposite pattern.