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How to Take Full Advantage of CBF for Stowage Planning

In our last article, we took a look at the merits of the client/server stowage planning system and checked how process improvement realizes cost reduction. In this article, let’s take a close look at specific cases in which solutions are created and operated for shipping companies. We will focus our attention on how stowage planning system uses CBF data that is received from outside.


What is CBF (Container Booking Forecast)?

CBF literally means data on booked container. When container ships sailing along a lane arrive at specific ports, unloading begins. Different cargoes have preset port of loading (POL) and port of discharging (POD). As was described in the previous article, a shipping company’s stowage planner should draw up stowage plans for different ports, and doing this obviously requires data for cargoes that are going to be uploaded from the specific ports. The numerical data about the cargoes that are going to be uploaded from different ports is called container booking quantities. The data includes the operator, POD, cargo size and type, and quantity of a specific cargo.

Then, why ‘forecast’ that tags along? The quantitative data that is delivered to a planner when a stowage planner draws up a stowage plan is nothing but a ‘forecast’. It is not finalized but forecast as long as a ship arrives to a port and actual uploading begins. If an unexpected situation develops after a stowage plan has been established, stowage volume may change or its type and size may change. So, a stowage plan created by a planner is based not on finalized data but on a forecast volume.


Reasons why CBF is not fully used in stowage planning

1. It is difficult to collect CBF data

As mentioned earlier, the terminals of different ports send CBF data to shipping companies. The CBF sent from different origins is more or less the same while it takes various electronic file formats such as e-mail, fax, and Excel. As there is no standard as to the form of CBF and its content, this causes inconveniences in exchanging data with other shipping companies. So, discussions are going on among shipping companies with a view to establishing a standard EDI-based format.

2. It is difficult to use CBF data

The stowage planner of a shipping company draws up a stowage plan based on CBF received from terminals.. Since the entire booked stowage which has been filed in CBF has to be loaded onto a ship, CBF and a filled-out stowage plan are indispensable. At this point, the problem is that CBF may not have been submitted as an electronic file and if it comes in as an electronic file which is different than is used in the system, verification wouldn’t be easy.

The stowage planner must either check two versions of data with his or her eyes or perform extra work to use an electronic verification. In the latter case, a system must come with an additional feature for processing CBF, while a user must manually enter CBF data to use the function. Then, how can one reduce this cumbersome work? We will see how this is possible with OPUS Stowage, the stowage planning software from CyberLogitec.


Effective ways to use CBF data

1. CBF data interface with the main system of a shipping company

In general, data on stowage can be verified at the contract stage and related data is stored in a shipping company’s main system. Through interface, OPUS Stowage processes the data into an appropriate form for the system. The data used in OPUS Stowage also exists in the shipping company’s database server, so CBF data can be taken through direct connection.

From a technical perspective, while a table view for CBF data is created in the shipping company’s database, OPUS Stowage operates internally with the data of the specific view alone. The advantage of this structure is that it allows a shipping company to easily conduct its data security management and reduces the additional workload that is generated for interface. Adopting the system becomes very simple, as it only has to process the data supplied by a shipping company for the afore-mentioned table view.

2. OCR-based CBF data analysis and processing

There is no designated form for data submitted via fax or in PDF, but data can be processed through image pattern analysis, as most shipping companies write data in similar forms before they send it. D-Cube, a solution from CyberLogitec, includes an OCR (Optical Character Recognition) engine and serves to analyze the pattern for documents exchanged with shipping companies and process it into data. Handwritten documents submitted via fax, emails, or image-converted PDF files can be automatically processed in connection with relevant solutions.

3. Improvement through automated CBF input

A number of shipping companies including Hanjin Shipping have created CBF interface with OPUS Stowage. Now able to take less time to collect, compare, and review CBF data, a stowage planner can focus on his or her main duties. It’s because the solution goes beyond just receiving quantitative data to enable automatic inputting of weight data for specific volumes of stowage.

Stowage planning system for Hanjin Shipping
Stowage planning system for Hanjin Shipping

This not only drastically reduces data input time, but also allows the stowage planner to create a stowage plan based on accurate data from the stage of pre-plan creation. In general, a pre-plan does not involve entering weight data accurately (due to possible changes and limited time), but uses average weight. Automatic inputting of accurate weight data not only promotes the convenience of a planner but also reduces variability and checks a ship’s restoring forces.

Also, as CBF data is processed into what can be used in OPUS Stowage, a planner uses the system-supplied verification at the point when a plan is created.