Some Studies on the Principles and Mechanisms for Loading and Unloading

Taleb-Ibrahimi et al. (1993) obtained results for long-term and operational planning. They discuss space allocation and storage strategies for export containers. Given the vessel arrival patterns and workloads they find space requirements. The minimum amount of storage space needed is determined at the strategic level. At the operational level, the problem of minimising and predicting the amount of work is discussed. Models are given that reflect the relationship between available handling effort, storage space and traffic demand.

Kim et al. (2000) discussed the problem of determining storage locations for export containers with a certain weight with the objective of minimizing the expected number of re-handles for the loading of containers on the ship. These re-handles occur for example if containers are stacked on top of heavier containers, which, as assumed by Kim et al. (2000), are needed first in the ship. A dynamic programming model is formulated to solve this problem. For making real time decisions, a decision tree is given, the performance of which is evaluated by comparing its solutions to the solutions of the dynamic programming model. Maximally, 5.5% of the decisions made with the decision tree are wrong. One of the decisions that have to be made at the tactical level is the determination of the number of transfer cranes necessary to ensure an efficient storage and retrieval process.

Lee et al. (2006) address a yard storage allocation problem in a transhipment hub with the objective of reducing re-shuffling and traffic congestion. They proposed a mixed integer programming model to minimize the number of cranes needed to handle the total workload. Two heuristics, a sequential method and column generation algorithm, were proposed and tested on generated instances: Other operational decisions include 1) determining which crane(s) should serve the ship trucks (seaside) and which crane(s) should serve the road trucks (landside), 2) determining where to store export containers, and 3) determining the order in which ship and road trucks are served.

Ng et al. (2005) studied the problem of scheduling a yard crane to perform a given set of loading/unloading jobs with different ready times. The objective was to minimize the sum of job waiting times. A branch and bound algorithm was proposed to solve the scheduling problem optimally. Efficient and effective algorithms are proposed to find lower bounds and upper bounds. The performance of the proposed branch and bound algorithm is evaluated by a set of test problems generated based on real life data. The results show that the algorithm can find the optimal sequence for most problems of realistic size.

Inter-terminal container transport

Inter-terminal container transport (ITCT) means that containers have to be transported from the stack to other modes of transportation, like barges, rail and road. In future, there is likely an increased need for container transport between the various modalities (rail, road, barge, sea),, Also, the transport between these modalities and other service centres (empty depot, DistiParks) will increase. Kozan (1997a) developed an analytically based computer simulation model to describe the container process at a rail container terminal. The major factors influencing the throughput time of containers, which is a function of cranes, stackers and transfer systems, are discussed by Kozan (1997a). The simulation model is combined with heuristic rules to describe the progress of containers in the system. Firstly, a cyclic heuristic rule is used to assign handling equipment to trains. This rule selects the first available resource beginning with the successor of the last resource seized. As a result, workloads are balanced and utilisation of handling equipment and throughput are higher. Secondly, a new heuristic rule is developed to dispatch trains to tracks. When a train enters the system there may or may not be a queue for the tracks. If there are no free tracks, the train will join the queue. Otherwise, the system sends trains first to track 1 and then to track 2 or 3 if they become available for track 1 and if they minimise total throughput time. In case more than one track is used, the train with the fewest number of containers will be unloaded first. A simulation model is developed by using data from a terminal in Australia. Due to cyclic train schedules a weekly simulation period was used.

Bostel et al. (1998) studied the allocation of containers on trains. Different models and solution methods are presented and tested on realistic data. It can be concluded that the number of container moves and the use and quantity of equipment can be minimized. Ballis et al. (1996) developed a simulation model that can be used in the design and evaluation of terminal facilities at the landside. Five heuristics are incorporated in the model to investigate the performance of the system. To obtain a realistic model, experiences of operations managers are included in the model. The comparison between different studies indicates that a shorter truck service time is feasible but this leads to an increase of traffic conflicts in the internal transport network.

Complete container terminals

In previous sections, problems for individual types of material handling equipment are discussed. Within a container terminal it is obvious that in order to obtain an efficient terminal, it is also necessary to address all problems in an integrated manner. The methods and algorithms obtained by optimising the single processes can be used as a base to the optimisation of processes in the entire terminal.

Gambardella et al. (1998) showed how operations research techniques can be used to generate resource allocation plans. These plans can be used by terminal managers to determine the best management strategies. Ramani (1996) develops an interactive planning model to analyse container port operations and to support its logistics planning. It is assumed that all unloading operations are completed before loading operations are started. In the simulation model of Yun et al. (1999) an object-oriented approach is used. The performance of a simple model, in which many design parameters affecting the performance are changed, is observed. A decision support system for the capacity planning of container terminals has been developed by Van Hee et al. (1988). Several mathematical models, each describing parts of the complete process, are incorporated in this system. The system can support decisions at the strategic and tactical level. Kozan (1997b) compared analytical and simulation planning models for a complete terminal. It was stated that containers arrive at the seaside in batches, namely on the ship, and not alone. Consequently, a batch-arrival multi-server queuing model is developed and compared with a simulation model. The results of this comparison indicate that, at a 95% level of significance, there exists little difference between the models. However, before implementing the analytical model, long-term data collection is necessary.

Kozan (2000) examined the problem of minimisation of handling and travelling times of import and export containers from the time the ship arrives at the port until the time they are leaving the terminal and vice versa. The complete trajectory that containers go through from the ship to road or rail terminals via storage areas is included into a network model. Improvements in operational methods are not incorporated in this model. The objective of the model was to minimise total throughput time. The model is, however, subject to several constraints. Firstly, the expected number of containers moved from node i to node j in a time interval larger than or equal to the minimum amount of containers required in node j within this time interval. Secondly, space constraints at node j should be met. Further, the sum of containers moved to each section of the stack should equal the total number of containers moving into the stack. Also, the sum of containers moved into the stack should equal the sum of containers moved out of the stack. The incoming flow in each node should equal the outgoing flow of containers. Finally, the total number of containers moved should equal the number of containers unloaded from the ship and no more than the maximum number of equipment available is used. It is shown that the expected number of moves per container is the average of the maximum stack height and the minimum stack height. It is explained that this model can be used as decision tool in the context of investment appraisals of multimodal container terminals.

Container Terminal Operations

Operations at Singapore port

The port of Singapore handled more than 182 million tonnes of cargo in 2007 thereby occupying first rank in the world in terms of throughput, Through continual infrastructure development and growth in world trade, Singapore has become the port with the largest container throughput in the world (Chou, 2002 and Singapore, 2009). Singapore has unique geographical position in the terms of having natural deep water harbour. No other port in the South East Asian region is close to Singapore in terms of number of ship calls and containers handled. The Port of Singapore holds the title of world’s busiest container port. The port is set to grow by 12.5% in the year 2008 bringing the total throughput of the port up to 29, 918, 20 TEUs. This growth is largely due to the influx of intra-Asia and Asia-Europe trade.

Figure ý3. Container throughput at Singapore

Singapore’s strategic location has made it a giant in the shipping industry. 20% of the world’s transhipment trade passes through the Port of Singapore. In 2007, transhipments accounted for 5% more than the total of imports and exports of Singapore. It can be seen from Figure ý3.that the throughput has increased from 15,571.10 TEUs in the year 2001 to 29,918.20 TEUs container in year 2008.

The Port of Singapore is one of the busiest ports in the world serving more than 500 shipping routes, and connecting over 700 ports world-wide. The port typically handles 800 ships on site at any one time.

Table ý3.Characteristics of Singapore Container Port (2007)

Ports/

TerminalsNumber of BerthsNumber of TerminalsGantry

CranesTerminal Area (acre)Yard capacity (TEUs/day)Singapore5441188 3875,000Table ý3. shows the characteristics of Singapore container port in terms of throughput, number of berths, terminals, and gantry cranes, terminal area, and yard capacity (Singapore, 2007). There are four terminals in Singapore; namely Tanjong Pagar, Keppel, Brani, and Pasir Panjang. In order to handle continuous growth, the Port of Singapore is in the process of automating the cargo handling process within its terminals, The Port has developed integrated technology systems and software to facilitate electronic transfer of trade data and vessel clearance. This has encouraged international carriers and ship-management companies to set up regional offices in Singapore. The Port of Singapore Authority (PSA) has become an international identity in container stevedoring with representation in several major ports including Italy, China and Belgium.

The Port of Singapore manages the highest volume of containerized cargo than any other port in the world. Due to technological advances that are utilized within the Port of Singapore, greater volumes of cargo are able to pass through the Port of Singapore. The port of Singapore Authority has been investing over $7 billion to develop 26 berths over four phases at Pasir Panjang Terminal. When fully developed, the state-of-the-art Pasir Panjang Terminal will be able to handle 36 million TEUs a year. The terminal has the world’s first remotely operated Bridge Cranes which will speed up container handling in the yard and further maximise yard utilization by stacking containers nine storey high. Built by a consortium comprising Mitsui Engineering and Shipbuilding and Keppel Engineering, these cranes will substantially boost worker productivity, by enabling each crane operator to manage a number of cranes. The Pasir Panjang terminal can handle an average of 750,000 TEUs a year, 25% more containers than PSA’s other terminals; and one operate can operate several cranes.

In order to overcome the growing shortage of skilled labor and improve productivity the Port of Singapore Authority (PSA) is considering the design of the most advanced automated terminal system. PSA plans to operate hundreds of AGVs under a sophisticated traffic management schedule for container movements. A contract for 5 prototype AGVs was awarded to Kamag of Germany and Mitsui of Japan. The vehicles were designed to be able to accelerate from 0 to 5 mph in under 10 seconds, with the top speed of 15.5 mph ¨C loaded or unloaded. They can accept either 20- or 40-foot containers with 50 tons maximum payload and can operate independent of the weather conditions. The pilot AGV system started in the late 1994 at Brani Terminal and was completed in 1997. In May 1998, PSA signed another agreement for the phase II program to develop and test AGV systems for container terminal operations. The completion date for phase II is scheduled for 2002. It is expected that with the use of AGVs each berth will be able to handle 25% or more containers that the PSA currently handles.

Operations at container terminals in India

Indian Railway's strategic initiative to containerize cargo transport put India on the multi-modal map for the first time in 1966. Since then, India has made good progress in container transportation facilities. Given the continental distances in India (almost 3,000 km from North to South and East to West), rail transport is seen as cost effective option for all cargo over medium and long distances, especially if the cost of inter-modal transfers could be reduced (KPMG, 2007). Containerized multi-modal door-to-door transport provided the ability to deliver variety of cargo at the doorstep at the clients. Though the first ISO marine container had been handled in India at Cochin as early as 1973, it was in 1981 that the first ISO container was moved inland by the Indian Railways to India's first Inland Container Depot (ICD) at Bangalore, also managed by the Indian Railways. Expansion of the network to 7 ICDs by 1988 saw the increase in the handling of containers, and along the way, a strong view had emerged that there was a need to set up a separate pro-active organization for promoting and managing the growth of containerization in India. Presently, containerized cargo represents about 30% by value of India’s external trade, and this proportion is likely to grow as containerization increasingly penetrates the general cargo trades and increases its share from the current 68% to levels that are comparable to international levels. With increased penetration, and growth in India’s trade, container traffic is projected to grow from 4.5 million TEUs per annum in 2005 to around 21 million TEUs by 2015 (World Bank, 2007). There is a movement of 30 percent of EXIM containers by rail, and the remaining is transported by road.

Container corporation of India

Container Corporation of India (CONCOR) is a public sector was set up in March, 1988 with the objective of developing multimodal logistics support for India’s international and domestic containerised cargo and trade. Its operations are directed towards efficient, economical and expeditious handling and transit of containerised goods by rail through India. Although more than 90 per cent of its inland transport service is by rail. Road and coastal shipping services are also provided according to the market demand. The company`s core business is characterized by three distinct activities that of a carrier, a terminal operator, and a warehouse operator. The company provides a single-window facility coordinating with all the different agencies and services involved in the containerized cargo trade right from customs, gateway ports, and railways, to road haulers, consolidators, forwarders, custom house agents and shipping lines. It has value-added services like linking of road or short lead rail shuttle services to long lead point-to-point train services (hub and spoke services), integrated freight terminals, coastal shipping, transportation of perishable products from source to end-user, and total logistics solutions.

CONCOR terminals are equipped with the most modern, sophisticated and state of art cargo and container handling equipment like rail-mounted gantry crane (RMGC), tyred mounted gantry crane (RTGC) and loaded and empty handling reach stackers. Besides, it has over 5,200 state-of-the-art high-speed bogies, low-height container flat-wagons in service. The company has a total of 57 terminals, of which 48 are export-import container depots, and there are nine exclusive domestic container depots. The customs bonded inland container depots are dry ports in the hinterland and serve to bring all port facilities including customs clearance to the customer`s doorstep. Till 2005, CONCOR was a sole service provider for rail transportation of containers The Company has a large fleet (about 8,000) of owned and leased containers. These are not just general purpose boxes, but include various special type of containers such as tank containers, open tops, high cube 22ft. containers etc. to facilitate the carriage of all types of cargo. Over the years, CONCOR has diversified into several container logistics activities. It has recently partnered with Maersk for taking up the construction of third container terminal at the Jawaharlal Nehru Port at Nhava Sheva in Mumbai.

Financials

Container Corporation of India registered a 24% growth in net profits to Rs 1,692.40 million for the quarter ended March, 2007 from Rs 1,362.20 million for the quarter ended March, 2006. Net sales rose 18.74% to Rs 8,081.20 million for the quarter ended March, 2007 compared with Rs 6,805.60 million for the quarter ended March, 2006. Total income rose 18.12% to Rs 8,229.5 million in the quarter ended March, 2007, from Rs 6,967.1 million for the quarter ended March, 2006. The earnings per share (EPS) of the company stood at Rs 26.04 in the quarter ended March, 2007. Container Corporation of India Ltd Company has posted a net profit of Rs 2018.336 million for the quarter ended June 30, 2008 as compared to Rs 1870.923 million for the quarter ended June 30, 2007. Total Income has increased from Rs 8134.720 million for the quarter ended June 30, 2007 to Rs 8681.145 million for the quarter ended June 30, 2008.

CONCOR recorded 16.5% rise Year on Year (YoY) in throughput to 618,534 TEU led by strong growth in domestic volumes at 38.3% YoY to 113,786 TEU. For the first time in six years, the company has recorded such high growth in domestic throughput. This is mainly due to premium service of dedicated rakes, that is, running point to point schedules. Also, an increase in the share of non-bulk cargo triggered an increase in containerization, boosting domestic volumes. On the other hand, EXIM volume grew by 12.6% to 504,748 TEU, below the expectations mainly because the company ran empty rakes due to unfavourable import export mix. This will continue due to appreciation of rupee affecting exports. CONCOR has started giving lucrative discounts for export volumes to combat higher empty rakes.

Physical performance

Company's operations have seen the traffic grow from a level of total 594118 TEUs in 1995-96 to 2105266 TEUs in 2006-07.where the international traffic have grown from 349141 TEUs in 1995-96 to 1715661 TEUs in 2006-07 and domestic traffic have grown from 244977 TEUs to 389605 TEUs in 2006-07. Total traffic handled by CONCOR, separately for international and domestic streams, during the last decade clearly brings out the success story of CONCOR's growth as shown in Figure ý3. (see Raghuram, 2007).

Figure ý3. Total traffic handled at CONCOR terminals

Case study at ICD, Tughlakabad, New Delhi

The ICD Tughlakabad is the largest dry port in South Asia and the leading centre for importers and exporters of the Northern Region of India. This ICD began functioning at Tughlakabad, New Delhi in 1993. It is situated near Okhla Industrial Area and is spread over 44 hectares of land. It has three storied administrative block that houses Offices of Customs, CONCOR, Bank, and Shipping Lines. Four full length rail lines are available in the customs area which brings the containers by train from Gateway ports such as Mumbai, Nhava Sheva, Chennai, besides bringing the containers by road from other ports such as Haldia, Calcutta and Kandla,

A part of CONCOR terminal at Tughlakabad is shown in Figure ý3., it can be seen that there are four rail tracks available out of which three are shown loaded with trains. Gantry cranes, shuttle trucks, and a part of the storage yard are also shown in Figure ý3.. Details of equipments and facilities available at CONCOR are given in the next section.

Figure ý3. ICD, Tughlakabad, New Delhi

Facilities and Equipment

ICD, Tughlakabad as shown in Figure ý3. is equipped with most modern facilities and it has the following infrastructure facilities for operations located inside the custom bonded area (CONCOR, 2007).

4 full train-length rail lines can serve full loaded trains with 45 wagons ( the wagons used here is high speed bogie container flat wagons)

6,000 square meters. covered warehouse space for imports which is sufficient to accommodate cargo of 160 TEUs

110,000 square meters covered warehouse space for export cargo which is sufficient to accommodate a cargo of 240 TEUs

1,500 square meters of especially reserved space for LCL consolidation.

Open space for stacking of 5,000 loaded containers

Open space for stacking 6,000 empty containers.

Six hectares parking area to accommodate 400 trailers

Fully computerised import and export documentation

Administrative building of 8,000 sq. mtrs. of built up area housing officers of CONCOR, customs, bank, shipping lines, CHAs, surveyors, transporters, Business Centre, etc.

Computerised weighbridge facility

Container repair facilities

Two rail mounted gantry cranes each of capacity of 40 tonnes service at the rail side

Three Rubber Tier diesel powered Gantry Cranes each with a capacity of 40 tonnes service at the yard side

Eight loaded reach stackers (40 tonnes)

Six empty reach stackers (16 tonnes).

25 internal trucks

With these ultra-modern facilities, ICD, Tughlakabad has developed into the largest hub of multi-modal centre in the Indian sub-continent.  Containers meant for ICDs: Patparganj, Faridabad and Gari Harsaru are first brought at ICD, Tughlakabad by rail and then transported to their respective destinations.

The traffic volume at lCD, Tughlakabad is increasing every year. With the increase in volumes, the numbers of reach stackers/cranes are also likely to be enhanced. CONCOR presently owns 3600 Containers. About 8000 containers are taken on operation lease bringing the total population to about 12000. While acquiring new containers, CONCOR is also replacing its old containers, which have either out-lived their life or are beyond repair.

Figure ý3. Schematic of ICD, Tughlakabad.

A schematic of ICD, Tughlakabad, New Delhi is shown in Figure ý3..

Loading-unloading operations at ICD, Tughlakabad

Containers arrive to the terminal by train and trucks, and are stored in the storage area (yard side). The containers then leave the terminal by the same means to reach their final destinations. Various operations at ICD, Tughlakabad can be divided into three parts as follows.

Rail Side operations

The rail yards are characterized by the number of available tracks for unloading/loading, the distribution of load types processed and the rates of arrival for trains and outgoing loads. A rail mounted gantry cranes provides an important operation associated with loading and unloading trains. Approximately 7 to 8 trains are loaded-unloaded in a day. Numbers of trains to be handled varies from time to time (CONCOR, 2008). Each train consists of 45 Bogie containers flat wagons (Hadi, 1998). The particulars of Bogie Container flat wagon can be seen in Appendix B. Each train is described by a line that contains the transport mode, a unique identity (ID), an arrival day and time, and the numbers of containers to be loaded and unloaded. Then the attributes of all containers to be loaded and unloaded follow, that is, a unique container ID, size, destination, weight, information on the type (empty, refrigerated, dangerous content, oversized), as well as pick-up information (which mode of transport will pick it up on what day).