VALUE STREAM MAPPING OF OCEAN IMPORT CONTAINERS: A PROCESS CYCLE EFFICIENCY PERSPECTIVE

International cargo transportation is majorly dependent on marine transport, which moves 80% of the international cargo. With the increase in vessel size and the same yard area available for container transportation, it is important to study the processes and understand the efficiency of the container operations process. This research paper aims to review the import container transportation process and understand the process cycle efficiency through lean six sigma concepts. The process is evaluated from the operations process perspective and documentation process at one of the ports of India. The research has been designed by conducting an industry expert review on the process of container transportation from vessel berthing to gate out for import containers, utilising lean six sigma principles such as value stream mapping (VSM) and process cycle efficiency. The results have contributed to the existing knowledge in identifying the waste in the container handling process and demonstrated the inefficiency in the system from the perspective of waiting time of containers due to customs examination, scanning, and inter-terminal handling and movement. The process cycle efficiency of 40% is calculated by analysing the detailed time of handling containers from vessel berthing to gate out. A new future value stream mapping is proposed considering the process cycle efficiency. Future studies will focus on studying this process for export containers and benchmarking the results with the top-performing ocean ports globally.

Dwell Time Estimation of Import Containers as an Ordinal Regression Problem

The optimal stacking of import containers in a terminal reduces the reshuffles during the unloading operations. Knowing the departure date of each container is critical for optimal stacking. However, such a date is rarely known because it depends on various attributes. Therefore, some authors have proposed estimation algorithms using supervised classification. Although supervised classifiers can estimate this dwell time, the variable “dwell time” takes ordered values for this problem, suggesting using ordinal regression algorithms. Thus, we have compared an ordinal regression algorithm (selected from 15) against two supervised classifiers (selected from 30). We have set up two datasets with data collected in a container terminal. We have extracted and evaluated 35 attributes related to the dwell time. Additionally, we have run 21 experiments to evaluate both approaches regarding the mean absolute error modified and the reshuffles. As a result, we have found that the ordinal regression algorithm outperforms the supervised classifiers, reaching the lowest mean absolute error modified in 15 (71%) and the lowest reshuffles in 14 (67%) experiments.

The Level of Efficiency in Handling Container Traffic at Penang Port: A Simulation Study

The six-month period (January 1995 - June 1995) data was extracted from "Pelabuhan Kontena" (PELKON) system and tested using SIMAN simulation process. Among the data available from the PELKON system are: arrival time of a ship, departure time of a ship, operation time for loading and unloading, total number of equipment used, number of containers unloaded, number of containers loaded, size of a ship, country of registration, last port of call, and next port of call. The arrival pattern of large ships (having a capacity to carry 507 or more containers) and small ships (having a capacity to carry less than 507 containers) follows Weibull distribution and Log-normal distribution, respectively. As a whole, there is no significant differences between the number of ships recorded by the PELKON data and the simulation process. A number of experimental studies such as acquiring less Port Crane, improve­ment of management service and integrated Prime Mover operation have been carried out to determine the effect on the container handling operations. The findings show that when one of the four port cranes did not work, the number of export containers decreased by 14.2% and 11.5% for import containers, If the services had been upgraded by 25%, the average time for unloading export containers could be shortened by 27.1% and the average time for loading import containers could be reduced by 7.9%. If the movement of prime movers had been integrated, the handling of export containers could be upgraded by 8.0% and 4.3% for import containers.