Ferry Rusgiyarto S3-Student at Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia

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1 International Journal of Civil Engineering and Technology (IJCIET) Volume 8, Issue 10, October 2017, pp , Article ID: IJCIET_08_10_112 Available online at ISSN Print: and ISSN Online: IAEME Publication Scopus Indexed IMPORT CONTAINER INTER-ARRIVAL TIME AND HANDLING CHARACTERISTIC IN MARINE CONTAINER TERMINAL WITH EXTERNAL YARD A CASE STUDY OF JAKARTA INTERNATIONAL CONTAINER TERMINAL, INDONESIA Ferry Rusgiyarto S3-Student at Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia Ade Sjafruddin Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia Russ Bona Frazila Civil Engineering Post Graduate Department, ITB, Bandung 40132, Indonesia Suprayogi Faculty of Industrial Technology, ITB, Bandung 40132, Indonesia ABSTRACT Container traffic demand has been increased rapidly in recent years. It creates high occupancy in the container terminals across the country in Indonesia. To keep up the level of terminal service at the high demand in a modest way of capacity expansion, the terminal operator uses the external yard as one of the fastest and cheapest solutions with some limitations. The supporting yard is located outside of the terminal area and connected by the public road which is also used by non-container traffic. To find the optimum operation of terminal external yards system, the model will address several optimum issues such as location, capacity, and tariff of yards. The performance of a Terminal which operates the external yard needs to be analyzed to measure the benefit of the policy. Analysis of terminal container performance could be done by a deterministic or stochastic condition which was determined by the nature data. Proper analysis approach was needed to be observed based on real data characteristic. This paper aims to analyze the container inter-arrival time and handling characteristic of marine import container terminal. Container data record of the terminal operator was referred and analyzed. Statistical theory of chi-square test was used to analyze data editor@iaeme.com

2 Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi distribution characteristic. Based on the chi-square criteria, fitting data distribution was conducted for container inter-arrival time, service time, and dwell time data. The distribution data analysis result shown that the data was distributed among several distribution functions. It indicates that the performance analysis of the terminal should be done in stochastic condition approach. YOR and traffic on the connecting road have an important role in connection analysis between terminal and external yard. There is a problem to construct the equation, which correlated the terminal operation and the road due to different time cycle equilibrium. If the equation formulated in hourly, it cannot catch up the container movement characteristics in the terminal. Meanwhile, if the equation expressed in daily, it cannot catch up the road traffic characteristics. Based on the handling process review, It was indicated several choices for a container to pick a server. The container handling process at the terminal operating the external yard is a hard decision-making process. These problems could be addressed using Discrete Event Simulation model based on queueing theory. The simulation can accommodate the need of choosing server algorithm and different cycle time in the terminal and connecting road. The changes of external yards location, capacity and tariff can also be handled by the simulation when the alternatives policies will be done. Key words: Import Container, Handling Characteristic, Container Terminal, and External Yard. Cite this Article: Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi, Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia, International Journal of Civil Engineering and Technology, 8(10), 2017, pp INTRODUCTION 1.1. Background Container traffic demand has been increased rapidly in recent years. It creates high occupancy in the container terminals across the country in Indonesia. Increasing container traffic and land acquisition caused a problem for terminal expansion. The Container Terminal is a part of a logistic supply chain where transportation mode transfer is taken place. To keep up the level of terminal service at the high demand in a modest way of capacity expansion, the terminal operator uses the external yard as one of the fastest and cheapest solutions with some limitations. The supporting yard is located outside of the terminal area and connected by the public road which is also used by non-container traffic. To find the optimum operation of terminal external yards system, the model will address several optimum issues such as location, capacity, and tariff of yards. The Performance of a Terminal which operates the external yard needs to be analyzed to measure the benefit of the policy. Analysis of terminal container performance could be done by the deterministic or stochastic condition which is determined by the nature data. The appropriate analysis approach needs to be observed based on real data characteristic Objective The aim of this paper was to obtain import container inter-arrival time and handling characteristic in container terminal; and also to determine appropriate approach for performance analysis of terminal editor@iaeme.com

3 Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia This objective related to container terminal which was operated external yard to handle a situation where the container demand exceeds yard terminal capacity. The performance analysis approach choice will be a deterministic or stochastic condition. The method to calculate the performance parameter of the terminal will be analytical or simulation method Methodology This paper used secondary data collected from operator terminal which was classified into container handling process and time monitoring in the terminal. Container handling process data was used to identify service diagram flow process of the container in the terminal, connecting road, external yard, and consignee location. Time monitoring data of the container was used to analyze the distribution of inter-arrival time, service time and dwell time of container. Statistical theory of chi-square test was used to determine the best distribution of the data. Chi square test was a statistic test to compare observed data with a distribution density function. The method of performance analysis of terminal would be determined based on the data and handling process characteristic. Descriptive data analysis was used to obtain the data and handling process characteristics. The analysis was done by identifying the needs and criteria of the model, comparing the weaknesses and advantages of some existing models, and proposing methods that were probably to solve the problems. 2. PREVIOUS STUDY The earlier study on the increasing capacity of container terminal services more emphasizes the importance of container terminal operators. On macro-correlation analysis with other external systems (Road Network, Dry Port, ICD, etc.), the approach was considered the terminal as an isolated place or terminal as a single node. It is very rare to find a study which integrates the processes within terminals by surrounding road as well as sub terminal systems that are outside the terminal area (such as ICD, Dry Ports, etc.), including considering the impact on terminal performance and road connections. Performance analysis of the terminal that operates the external yard connected by the public road was related to the selection of the optimum configuration of the terminal and supporting yard. The optimization objective would maximize benefits and minimize costs. One such analysis is the facility location model. The location problem of Inland Container Depot was investigated by Yuanquan Xu (1999) with Facility Location Model approach which applied a discrete choice model to describe user competition in service location selection ([8]). The study conducted by Xu has not considered the stochastic condition of the traffic flow of the network. The study developed by Huynh (2005) and Moini (2010) tried to optimize the container terminal subsystem in the yard area ([4], [5]). Meanwhile, the study developed by Guan (2009) tried to model the queue at the terminal gate to get the method of evaluating the impact of the gate policy on gate operating costs ([2]). Their study did not consider the road network performance yet. Dougherty (2010) tried to see the impact of the gate operational policy on the road network around the container terminal but has not considered the impact of container terminals performances policy ([7]). Summary of the previous related study is shown in Table editor@iaeme.com

4 Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi Name Yuanquan Xu, 1999 [8] Liu, 2004 [1] Huynh, 2005 [4] Guan, 2009 [2] Park, 2009 [6] Moini, 2010 [5] Dougherty, 2010 [7] Coverage area Regional Network - ICD Container Terminal Container Terminal Container Terminal Gate Container Terminal Container Terminal Access Road Network Table 1 Previous study Method Description Discrete Choice Based Facility Location Model with Tabu Algorithm Simple Additive Weighting Method based on Simulation Heuristic Ad-hoc and Simulation Multi-server Queueing Model Simulation Analytic and Simulation Simulation Objective ICD site selection with maximization of Revenue and Cost difference Determination of optimum AGV amount for two yards layout with minimizing Average Idle Rate (AIR) of ship and yard crane Truck turn time minimization with the addition of RTG and truck appointment system Truck queue reduction at the gate by appointment system The addition of equipment investment to get the optimum level of service Dwelling Time Reduction with truck appointment system Shift peak period of container truck traffic by appointment system The above study has not met the need for methods to measure terminal performance associated with external yard operating policies. It was related to the variable and condition of travel time in connecting road, location and external yard capacity which had an impact the terminal performance. Yard Occupancy Ratio (YOR) and connecting road traffic as parameters for operator decision-making process not included in the previous analysis yet. A possible approach to measuring the performance changes of terminal due to external yard operation need to be elaborate based on inter-arrival time and handling characteristic. An analytical and a simulation approach will be analyzed to choose an appropriate method. 3. DATA ANALYSIS Data analysis was conducted for throughput data, service time data, and dwell time data of the import container. Record data from Jakarta International Container Terminal, Indonesia was analyzed. Import container data recorded at the quay, yard, and gate for three months of April 2016 May 2016 was used in the analysis editor@iaeme.com

5 Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia 3.1. Container Inter-Arrival Time Data Based on the data record, inter-arrival time and throughput data can be calculated and fitted. Inter-arrival time is a time between consecutive containers to arrive the server. It can be calculated based on: where: = i container inter-arrival time at server b = i container arrival time at server b = i+1 container inter-arrival time at server b = mean value of inter-arrival time of container at server b Fiatb = distribution function of inter-arrival time of container at server b Throughput is one of the parameters that indicate terminal performance, where the higher throughput shows, the higher the performance. Container throughput during three months was 223,179 boxes (at Quay); 223,164 box (at Yard) and 213,330 box (at Gate). The result of distribution inter-arrival time data fitting is shown in Table 2. Inter-Arrival Time Quay and Container Yard Terminal Gate Table 2 Container inter-arrival time Distribution Function Fitting Normal (0.63,4.86) Triangular (-2.83,0.05,304.00) Mean (minute) (1) (2) Standard Deviation (minute) Based on the throughput, it was indicated when the process starts, the service subsystem still empty, and when the process end, there was a container left in the service subsystem Container Service Time A container terminal is a facility where cargo containers were transferred between different transport vehicles, for onward transportation. The transshipment may be between container ships and land vehicles, for example, trains or trucks. The service time of container of a server was a time needed to enter and leave the server. It can be calculated based on: (3) where: = i container service time at server b = i container entry time at server b = i container exit time at server b = mean value of container service time at server b Fstb = distribution function of container service time at server b (4) editor@iaeme.com

6 Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi The container service in the terminal starts from the vessel discharge into terminal exit gate. It was consist of several types of equipment handling such as quay crane, internal truck, yard crane and external truck. Data records collected from terminal operators were vessel discharge time, lift off time at the yard, and exit time at the terminal gate. It was shown that the service time dominated in the yard. Time used by the container in the yard depends on several factors considered to terminal operator and consignee characteristics. Characteristics of service time of terminal are shown in Table 3. Service Time Quay Container Yard Transfer Container Yard Gate Transfer Table 3 Container inter-arrival time Distribution Function Fitting Log Logistic (0.77,9.43,2.08) Inv Gauss (3.92,4,2934 ; -0.30) Mean (minutes) 3.61 (days) Standard Deviation (minutes) 3.74 (days) 3.3. Dwell Time Data Container dwell time at the terminal was calculated based on the time needed by the container, from it was unloaded from the vessel until it passed the terminal exit gate. The distribution function analysis result of waiting time is shown in Figure 1. Characteristics of container waiting time data from March 2016 to May 2016 show an average value of days with a standard deviation of days. Based on the data recording the distribution function fitting with chi-square approach, the container waiting time was distributed exponentially with average value days and deviation standard days. Container dwell time was a parameter which can be used to measure the performance of the container terminal complement to a throughput. Moini (2010), was identified several factors affecting the container dwell time in a marine container terminal ([5]). These factors consist of factors within and outside the authority of the terminal operator. Analysis of data distribution confirms the stochastic condition of inter-arrival time, service time, and container dwell time. This condition indicates an analysis with a stochastic approach was an appropriate to analyze terminal performance editor@iaeme.com

7 Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia 0,30 Expon(3,5816) Shift=+0, ,25 0,20 0,15 0,10 0,05 0, ,0% 5,0% 90,0% 0,23 10,78 > Figure 1 Fitting of Container dwell time distribution 3.4. Container Handling Process in Terminal with External Yard Container handling process was identified from the operator of container terminal interview survey and customs clearance literature review. It was assumed that inspection of the customs could be conducted at the terminal or the external yard. Container imports movement from the ship into the consignee location, going through several processes in the terminal and on the road network. The container process is shown in Figure 2. Import container handling process in the terminal was consist of: Container lifts-off is the container unloading process from transport mode (vessel, truck, etc.) to a temporary storage. Container lifts-on is the container loading process into transport mode from temporary storage. Container transfer is the shifting of the container from one location into another. Customs check is the checking of the container by customs and quarantine officer in charge. Container un-stuffing is discharging the load from a container whose cargoes are owned by more than one consignee, to be stored in the terminal warehouse editor@iaeme.com

8 Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi Figure 2 Container handling process at terminal external yard system The container would wait the customs clearance and delivery in the yard, in which, container temporarily store. The storage location was usually an open field equipped with an electric power plug for reefer-containers, whereas for dry-containers, it only an open field without an electric power plug. The Container will transfer to the external yard if terminal yard occupancy ratio (YOR) exceed the number that was defined by the terminal operator. JICT operator terminal decides 0.85 as YOR threshold value. YOR as a parameter for decision making has a role in connection analysis between terminal and external yard. Traffic on the connecting road plays an important role for terminal operators when making decisions on selecting the appropriate yards. YOR and traffic have stochastic conditions in nature. There was a problem to construct the equation, which correlated the terminal operation and the road due to different time cycle equilibrium. If the equation formulated in hourly unit, it cannot catch up editor@iaeme.com

9 Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia the container movement characteristics in the terminal. Meanwhile, if the equation expressed in a daily of equilibrium, it cannot catch up the road traffic characteristics. The identification of the container handling process at the terminal which operating the external yard shows a hard decision-making process. It mainly related to the process from vessel discharge into the consignee location. This process would, therefore, involve a model that integrates the process of the terminal the external yard the user location which connected with the public road. The condition of interarrival and service time that was stochastic made the problem more complicated. The Stochastic Facility Model formulation with queue interaction approach which was occurring at several locations of the service candidate will provide 2N combinations of existing facilities or not, make it difficult to integrate the optimization algorithm because there are 2N equations (Z. Drezner, H.W. Hamacher, 2001) ([3]). The simulation method with discrete event simulation approach could be used to solve complex system problems. Simulation is also able to overcome the problem of time cycle difference in the inside of the terminal and the connecting road. The simulation can model the system inside the terminal with the daily analysis period and the connecting road with the hourly analysis period, as well as the condition of the arrival interval and the time of the stochastic container service. A simulation approach was a method if, the analytic approach becomes difficult to be used ([1], [4], [5], [6], [7]) Discrete Event Simulation Discrete Event Simulation utilizes a mathematical/logical model of a physical system that portrays state changes at precise points in simulated time. Both the state changes and the time at which the change occurs needs accurate description. Customers waiting for service and the management of parts inventory were typical domains of discrete event simulation. Based on definition and characteristics above, discrete event simulation can be used to obtain container terminal performance due to the operation of external yard outside the terminal. This method can solve the problem of time cycle uniformity within the terminal and in the connecting road. This approach is also able to consider the stochastic condition of arrival rate and travel time of traffic in connecting road. The disadvantage of this method was the simulation approach would result in a range value rather than in a deterministic value. The other weakness was the simulation time, where this process would take a long time if a lot of the scenarios were considered Queueing Theory The Queue is one of the transportation problems that occur due to a disturbance in the process of movement of traffic flow (human and vehicle) by the existence of a service activity to be passed, such as taking entrance ticket and payment at the gate. There are three main components in the queue theory to explain the queue mechanism, namely: arrival rate (λ), departure or service level (µ), and line discipline. The container terminal is a combination of several services to the container, so in general, the process analysis can be approached by queuing theory. The entity will be served in the terminal service system that can consist of a single or multiple lane services. The multi-lane queuing model has the following queue equation as follows: editor@iaeme.com

10 Ferry Rusgiyarto, Ade Sjafruddin, Russ Bona Frazila and Suprayogi Where: λ = Average arrival rate of containers (box/minutes), µ = Average service time (minutes/box), S = Channel number. ρ = Server utility (ρ<1). If, λ and µ have different statistical distributions, various queuing models should be applied. The discrete event simulation model construction based on queueing theory has two variables i.e. arrival rate and service time. Entity comes to a server and will be served if the server available throughout the service time. If the container come and the server still serves another entity, the entity will wait in the queue line. Arrival rate (λ) and service time (µ) would be a probabilistic to represent the interarrival and service time in the field. Based on the container handling process review, it was indicated several choices for a container to pick server such as customs clearance lane, internal or external yard, etc. Parameters derived from the queueing theory such as waiting time, the number of a queue, etc., can be used to construct the switching algorithm. In this condition, discrete event simulation based on queueing theory can be used to handle simulation process in container terminal with the external yard as described. 4. CONCLUSION Container data record from terminal operator was referred and analyzed. Based on chi-square test criteria, fitting data distribution was conducted for an inter-arrival time, service time, and dwell time data. The data was distributed in several distribution functions. It indicated that the performance analysis should be done by a stochastic approach. Terminal YOR and traffic on the connecting road have an important role in connection analysis between terminal and external yard. Location, capacity, and tariff are issues to be addressed when optimizing the terminal and supporting yards. There was a problem to construct the equation, which correlated the terminal operation and the road due to different time cycle equilibrium. If the equation formulated in hourly unit, it cannot catch up the container movement characteristics in the terminal. Meanwhile, if the equation expressed in daily of equilibrium, it cannot catch up the road traffic characteristics. This problem can be addressed using simulation model. Discrete event simulation can be used to obtain container terminal performance due to the operation of the yard. The simulation can accommodate the need of choosing server algorithm and different cycle time in the terminal and connecting road. The changes of location, capacity, and tariff can also be handled by the simulation when the alternatives policies will be done. ACKNOWLEDGEMENTS The authors would like to acknowledge The Ministry of Research, Technology and Higher Education for the Doctoral Dissertation Research Grant 2017 (Hibah Penelitian Disertasi Doktor 2017), and also, Jakarta International Container Terminal (JICT) for the data support of the paper. (5) editor@iaeme.com

11 Import Container Inter-Arrival Time and Handling Characteristic In Marine Container Terminal with External Yard A Case Study of Jakarta International Container Terminal, Indonesia REFERENCES [1] C.I. Liu, H. Julia, K. Vukadinovic, P. Ioannou, Automated Guided Vehicle System for Two Container Yard Layouts, Transportation Research Part C 12, [2] C.Q. Guan, Analysis of Marine Container Terminal Gate Congestion, Truck Waiting Cost, and System Optimization, Ph.D. Thesis, New Jersey Institute of Technology, [3] John Current, Mark Daskin, and David Schilling, Discrete Network Location Models, in Facility Location: Applications and Theory, Edited by Z. Drezner and H.W. ISBN , 2001, pp [4] N. Huynh, Methodologies for reducing truck turn time at marine container terminals, Ph.D. Thesis, The University of Texas, [5] N. Moini, Modelling the Interrelationship between Vessel and Truck Traffic at Marine Container Terminals, Ph.D. Thesis, University of New Jersey, [6] Nam-Kyu Park, Branislav Dragović, A Study of Container Terminal Planning, FME Transactions VOL. 37, No 4, Belgrade, 2009, pp [7] P.S. Dougherty, Evaluating the Impact of Gate Strategies on A Container Terminal's Roadside Network Using Microsimulation the Port Newark-Elizabeth Case Study, M.Sc. Thesis, University of New Jersey, [8] Muhammad Aksar, Shirly Wunas, M. Saleh Pallu and Misliah Idrus, Model Development of Operational Services of Major Commercial Ports in Indonesia (Case Study: Makassar Container Terminal). International Journal of Civil Engineering and Technology, 8(8), 2017, pp [9] Yuanquan Xu, A Discrete Choice Based Facility Location Model for Inland Container Depots, Ph.D. Thesis, West Virginia University, editor@iaeme.com