KR102839800B1 - System for providing optimized stowage plan data with reflecting last order - Google Patents

Abstract

The present invention comprises: an information input unit for inputting first information about a container transported by a ship, second information about cargo loaded on the container, and third information about a transport route required for transporting the cargo; a loading plan unit for scheduling a loading plan for cargo loaded on the container based on the first to third information; an available space calculation unit for calculating available space of the container based on the first to third information; an additional loading capacity calculation unit for matching a container capable of loading the additional cargo based on the fourth information and the available space of the container when fourth information about additional cargo to be loaded on the container is input on the information input unit; a last order reflection unit for instructing loading of the additional cargo on a container matched by the additional loading capacity calculation unit; And the system for providing optimal loading plan data reflecting the last order, which includes a database section for storing the first to fourth information, the available space information of the container, and the optimal loading plan data reflecting the last order, and for visualizing the optimal loading plan data by classifying it so that it can be searched by port and container, has the effect of being able to reanalyze the stowage plan to calculate additional shipping capacity in order to reflect the last order, which is an additional order after the establishment of the optimal loading plan, and of being able to store the optimal loading plan data reflecting the last order and provide a web service having an analysis and visualization function.

Description

System for providing optimized storage plan data reflecting last order

The present invention relates to a system for providing optimal loading plan data reflecting the last order.

In the past, due to the increase in demand for container transportation due to the activation of international trade, the change in the maritime environment due to the enlargement of ships and the automation of container terminals, many problems have arisen due to the failure to manage the optimal route decision of container ships, such as the inability of existing container ship routes to accurately respond to the demand for container transportation, or the need to reorganize routes due to insufficient port handling capacity caused by the enlargement of ships.

Therefore, in order to effectively respond to the changing shipping environment, the need for technologies that can efficiently transport containers and efficient algorithms or systems for determining container ship routes is increasing.

Meanwhile, the container shipping industry is currently experiencing an unprecedented boom due to a surge in cargo volume, and to address the recent shortage of space and maximize profits, additional orders for new ships and the trend of larger ships are being implemented.

However, the problem of ship space shortage cannot be resolved in a short period of time due to factors such as the long time it takes to build new ships and shipping companies' concerns about oversupply.

Therefore, IT solutions are needed to shorten the time required to increase physical ship supply and alleviate concerns about a maritime economic downturn due to oversupply.

Furthermore, while container ships are becoming larger to achieve economies of scale, the actual space utilization rate is decreasing from 85% to 81%. Consequently, measures are needed to secure shipping companies' freight revenue by increasing space utilization and minimize potential costs through operational optimization.

The recent sudden recovery in the shipping industry has led to a severe shortage of not only ships but also ISO containers capable of transporting cargo. This shortage of available containers has led to a sharp rise in the price of new containers and, along with this, the price of used containers.

Containers are divided into used and unused sections, and unused containers are reused by placing them in the used section. However, due to the rapid increase in cargo volume, it is difficult to secure space to transport or place unused containers.

As a result, the shortage of containers in the used section is worsening, and the backlog of empty containers is worsening in unused ports, which is continuously increasing the cost of empty container facilities and hindering the efficiency of the logistics process.

Therefore, after creating a stowage plan centered on loaded containers, it is necessary to derive IT-based ship space that can additionally load empty containers.

Patent Publication No. 10-2002-0043317 (Published: June 10, 2002) Patent Publication No. 10-2010-0045499 (Published: May 3, 2010)

The purpose of the embodiments of the present invention for improving the aforementioned problems is to provide a system for providing optimal stowage plan data reflecting the last order, which is capable of calculating additional shipping capacity by reanalyzing a stowage plan to reflect the last order, which is an additional order after the establishment of the optimal stowage plan, and which stores the optimal stowage plan data reflecting the last order and provides a web service having an analysis and visualization function.

In order to achieve the above object, a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention comprises: an information input unit for inputting first information about a container transported by a ship, second information about cargo loaded on the container, and third information about a transport route required for transporting the cargo; a loading plan unit for scheduling a loading plan for cargo loaded on the container based on the first information to the third information; an available space calculation unit for calculating available space of the container based on the first information to the third information; an additional loading space calculation unit for matching a container capable of loading the additional cargo based on the fourth information and the available space of the container when fourth information about additional cargo to be loaded on the container is input on the information input unit; a last order reflection unit for instructing loading of the additional cargo on a container matched by the additional loading space calculation unit; And it is characterized by including a database section that stores the first to fourth information, the available space information of the container, and the optimal loading plan data reflecting the last order, and classifies and visualizes the optimal loading plan data so that it can be searched by port and container.

The above loading planning unit generates an optimal container loading plan for each transport section based on the first to third information, and the available space calculation unit calculates available space (Cargo Mix) that can be additionally loaded in transport sections where cargo is not 100% present in the entire transport section.

The above available space is calculated based on cargo weight, cargo size, cargo characteristics, and transport section as attributes, and the cargo characteristics are characterized by including a Reefer or hazardous cargo code.

In addition, the system for providing optimal loading plan data reflecting the last order according to one embodiment of the present invention is characterized by further including an information disclosure unit that distributes optimal loading plan data visualized by the database unit on the web.

A system for providing optimal loading plan data reflecting a last order according to one embodiment of the present invention can calculate additional shipping capacity by reanalyzing a stowage plan to reflect a last order, which is an additional order after establishing an optimal loading plan, and can store optimal loading plan data reflecting a last order and provide a web service having an analysis and visualization function.

In addition, one embodiment of the present invention can maximize the profits of shipping companies and increase the convenience of shippers by establishing a flexible loading plan for early confirmation of loading and unloading cargo and additional orders to enhance the safety of international trade transactions.

In addition, one embodiment of the present invention can increase the consistency of the plan by providing confirmation information to subsequent work such as truck dispatching once the work order is determined, reduce logistics costs such as dispatching areas and port waiting, maximize port efficiency, and advance the implementation of a smart port. In addition, it can help alleviate phenomena such as a shortage of experienced navigators due to the effect of avoidance of maritime work and avoidance of work such as stowage planning that requires 24-hour management.

In addition, one embodiment of the present invention can increase the accuracy of cargo information, such as by strengthening security laws, by increasing the consistency between cargo information and actual cargo status, and can enable the establishment of a more optimized loading plan by applying big data, AI, etc., to predict factors affecting operation in advance.

In addition, one embodiment of the present invention has the effect of reducing fuel costs, suppressing CO2 emissions, helping to respond to carbon emission regulations, and enabling immediate decision-making support for fleet operation.

FIG. 1 is a block diagram illustrating a system for providing optimal loading plan data reflecting a last order according to one embodiment of the present invention.
FIG. 2 is a diagram showing the structure of a system for providing optimal loading plan data reflecting a last order according to one embodiment of the present invention.
FIG. 3 is a diagram showing an example of use by a user, an administrator, and a shipping company of a system for providing optimal loading plan data reflecting a last order according to one embodiment of the present invention.
FIG. 4 is a diagram illustrating the operation of a system for providing optimal loading plan data reflecting a last order according to one embodiment of the present invention.
FIG. 5 is a diagram showing the operation of an additional shipping capacity calculation unit of an optimal loading plan data provision system reflecting a last order according to one embodiment of the present invention.
FIGS. 6A to 6G are diagrams showing screens on the web in which an optimal loading plan data provision system reflecting a last order according to one embodiment of the present invention is implemented.

The present invention as described above will be described in detail through the attached drawings and examples.

It should be noted that the technical terms used in the present invention are used merely to describe specific embodiments and are not intended to limit the present invention. Furthermore, unless specifically defined otherwise herein, the technical terms used herein should be interpreted as having a meaning generally understood by those skilled in the art to which the present invention pertains, and should not be interpreted in an excessively broad or narrow sense. Furthermore, if a technical term used herein is incorrect and fails to accurately express the spirit of the present invention, it should be replaced with a technical term that can be correctly understood by those skilled in the art. Furthermore, general terms used herein should be interpreted according to their dictionary definitions or according to the context, and should not be interpreted in an excessively narrow sense.

Additionally, singular expressions used in the present invention include plural expressions unless the context clearly dictates otherwise. In the present invention, terms such as "consist of" or "include" should not be construed to necessarily include all of the components or steps described in the invention, and should be construed to mean that some of the components or steps may not be included, or that additional components or steps may be included.

Additionally, terms including ordinal numbers, such as "first" and "second," used in the present invention may be used to describe components, but the components should not be limited by these terms. The terms are used solely to distinguish one component from another. For example, without departing from the scope of the present invention, a first component could be referred to as a second component, and similarly, a second component could also be referred to as a first component.

Hereinafter, a preferred embodiment of the present invention will be described in detail with reference to the attached drawings. Regardless of the drawing numbers, identical or similar components are given the same reference numbers, and redundant descriptions thereof will be omitted.

Furthermore, when describing the present invention, detailed descriptions of related known technologies will be omitted if they are deemed to obscure the gist of the present invention. Furthermore, it should be noted that the attached drawings are intended solely to facilitate understanding of the spirit of the present invention and should not be construed as limiting the spirit of the present invention.

FIG. 1 is a block diagram illustrating a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention, FIG. 2 is a diagram showing the structure of a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention, FIG. 3 is a diagram showing examples of use by a user, an administrator, and a shipping company for a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention, FIG. 4 is a diagram showing the operation of a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention, FIG. 5 is a diagram showing the operation of an additional shipping space calculation unit of a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention, and FIGS. 6a to 6g are diagrams showing screens on a web on which a system for providing optimal loading plan data reflecting a last order according to an embodiment of the present invention is implemented.

Before explaining the present invention, the flow of container cargo will be explained.

The flow of export container cargo from shipper to vessel has the following characteristics:

Generally, the flow of export container cargo varies depending on whether it is FCL (full container load) or LCL (less than a container load), with different container loading routes and methods.

FCL is container cargo where one shipper fills one container, while LCL is container cargo where one shipper cannot fill one container, so cargo from multiple shippers is loaded together in one container.

In the case of FCL (full container load) cargo, when the shipper requests shipment to a shipping company, the shipping company contacts the container transport company contracted with it and assigns an empty container to the exporter's company or the location of the cargo, unless otherwise specified by the shipper.

Cargo (full container) that has completed loading is finally loaded onto a ship after going through procedures such as transportation and customs clearance.

Because each shipping company has large shippers and these shippers have a large number of transport contracts, shipping companies develop operational plans based on these large shippers. Large shippers handle Full Container Loads (FCL) rather than Less than a Container Load (LCL).

When a shipping company and a shipper enter into a transportation contract, the shipping company usually sends empty containers to the shipper according to the number of full containers on the scheduled shipping date, so the demand for containers is determined by the shipper's transportation contract.

Export and import volumes vary globally by region. Regions with higher exports than imports use more empty containers than they supply, while regions with lower exports than imports import more empty containers than they supply.

Due to this imbalance in supply and demand of empty containers, shipping companies forecast short-term and long-term demand for empty containers and establish redistribution plans.

In addition, containers are equipment that divides the used and unused sections and reuses unused containers by placing them in the used section. However, due to a sudden increase in cargo volume, it may become difficult to secure space to transport or place unused containers.

This will exacerbate the shortage of containers in used areas and the backlog of empty containers in unused ports, which will lead to a continuous increase in the cost of empty container facilities, raising concerns that this will hinder the efficiency of the logistics process.

Furthermore, it can be said that it is an environment where it is difficult to utilize the available space of empty containers when additional orders occur.

Accordingly, the system for providing optimal loading plan data reflecting the last order according to one embodiment of the present invention, as illustrated in FIG. 1, builds a platform for providing optimal loading plan service by reanalyzing the stowage plan to reflect the last order, which is an additional order after establishing the optimal loading plan, so that additional shipping capacity can be calculated, and stores optimal loading plan data reflecting the last order through the platform and provides a web service having an analysis and visualization function.

The above platform provides container search information sharing and provision services (cargo characteristic information, container transport information, container search information workflow, risk management) and optimal loading plan services that can accommodate last orders (data hub/analysis platform (artificial intelligence/machine learning)/service hub/cloud service/optimal loading plan management service). At this time, data is provided from a big data portal server, service linkage is performed with a smart logistics business platform, and various information and services can be provided by linking with public and private APIs (transportation/administration, urban management, education, industrial economy/safety/environment).

The above platform builds Azure and AWS on its own to provide services, and utilizes IaaS (Infrastructure as a Service) or SaaS (Software as a Service).

At this time, SaaS (Software as a Service) refers to an application service that operates in a cloud environment so that software can be used on the web.

Additionally, Infrastructure as a Service (IaaS) allows users to rent IT infrastructure, such as servers, storage, and network equipment. Users can simply utilize the infrastructure they need in a cloud environment without having to build their own data center. Using this rented infrastructure, users can install an operating system, applications, and other services, then run their desired services. It provides services typically offered by traditional data centers, such as virtual servers and data storage. Users can combine these services to run or operate applications.

Meanwhile, at the loading port, the cargo stowage plan, or cargo loading chart, is a document prepared by the chief mate, referencing the loading instructions, before unloading begins. This plan outlines the stowage locations for each cargo hatch, ensuring proper unloading. However, actual loading often deviates from this plan. Therefore, after loading is complete, the actual cargo stowage status is compiled by hold, re-drafted, and sent to the next port. At the discharge port, this plan is used as a reference for unloading operations.

For container ships, loading planning is largely conducted onshore, focusing on the containerized cargo's handling and operational characteristics. The container terminal or shipping company's operations management department develops a pre-stowage plan based on the vessel's previous loading port's loading plan and information about the cargo to be unloaded at the port. The plan is then communicated to the vessel, with the vessel's input reflected before the final plan is developed.

As illustrated in FIG. 2, the optimal loading plan data provision system reflecting the last order according to one embodiment of the present invention includes an information input unit (10), a loading plan unit (20), an available space calculation unit (30), an additional loading capacity calculation unit (40), a last order reflection unit (50), a database unit (60), and an information disclosure unit (70).

The above information input section (10) inputs first information about a container transported by a ship, second information about cargo loaded in the container, and third information about a transportation route required for transporting the cargo.

The above information input unit (10) receives information on containers, cargo, and transport routes, as well as vessel information, for designing an optimal loading plan. To this end, the information input unit (10) may include a loading plan information input module (not shown) for receiving first to third information as input, including shipping company information, shipper information, cargo type and quantity information, basic information and voyage information of the vessel, departure and arrival port information, sailing direction information and port information, date information, etc., and an optimal loading plan information input module (not shown) for checking available space information and additionally receiving fourth information, including shipping company information, shipper information, cargo type and quantity information, basic information and voyage information of the vessel, departure and arrival port information, sailing direction information and port information, date information, etc.

The loading planning unit (20) schedules the loading plan of cargo loaded into containers based on the first to third information input by the information input unit (10). In addition, the loading planning unit (20) can generate an optimal container loading plan for each transport section based on the first to third information input by the information input unit (10). For example, the loading planning unit (20) provides a service that transports cargo for a partial section using an existing shipping company's transport route, optimizes a necessary transport route, optimizes cargo transport using a part of a newly created transport route, optimizes the operation of transport equipment including ships, and designs a loading plan to minimize and optimize the yard storage time and cost in a container terminal. This loading planning unit (20) performs optimal planning and scheduling for container transport using artificial intelligence technology.

The available space calculation unit (30) calculates the available space of a container based on the first to third information input by the information input unit (10). In addition, the available space calculation unit (30) calculates the available space (Cargo Mix) that can be additionally loaded in a transport section where the cargo is not 100% available in the entire transport section. At this time, the available space is calculated based on cargo weight, cargo size, cargo characteristics, and transport section as attributes. Here, the cargo characteristics may include a reefer or hazardous cargo code.

The above-mentioned additional loading capacity calculation unit (40) is a device for calculating additional loading capacity through reanalysis of the final stowage plan. When fourth information on additional cargo to be loaded in a container is input into the information input unit (10), the fourth information and the available space of the container are used to match containers in which the additional cargo can be loaded. That is, the above-mentioned additional loading capacity calculation unit (40) analyzes the data of the previously confirmed stowage plan to derive additional loading quantity and cargo type, and allows additional bookings to be accepted for appropriate cargo. Through this, the present invention can maximize sales and improve operational efficiency of existing container shipping companies by calculating available capacity through data analysis in addition to the process of deciding whether to accept bookings based on slot allocation by port that is preemptively confirmed during route planning. Furthermore, it can increase the efficiency of the terminal's yard operation, shorten the time for rewriting the loading plan, enable the final loading plan to be shared with the terminal before the CCT (Cargo Closing Time), and reduce the number of cargoes that violate the CCT due to delayed loading plan creation to zero, thereby increasing the terminal's yard operation plan and operational efficiency.

The above last order reflection unit (50) is a device for accepting last orders, and instructs the loading of additional cargo to a container matched by the additional shipping capacity calculation unit (40). That is, the above last order reflection unit (50) uses the result matched by the additional shipping capacity calculation unit (40) to instruct the placement and loading of additional cargo to an actual container.

The above last order reflection section (50) is actually executed to load additional cargo according to the location and time of the shipper who needs a container with available space.

The above database section (60) stores the first to fourth information, information on available space of containers, and optimal loading plan data reflecting the last order, and visualizes the optimal loading plan data by classifying it so that it can be searched by port and container.

The above database unit (60) stores information for calculating the available space of a container, various information (first information to fourth information) input through the information input unit (10), information calculated through the available space calculation unit (30) and the additional loading capacity calculation unit (40), etc. For example, the database unit (60) is implemented in the form of a DB Pool (Database Pool), so that such various pieces of information can be managed by dividing them into multiple modules. In this case, the database unit (60) may include a cargo information storage module (not shown) that stores various information (first information to fourth information) input through the information input unit (10), an additional loading information storage module (not shown) that stores information calculated through the available space calculation unit (30) and the additional loading capacity calculation unit (40), and a loading plan storage module (not shown) that stores a loading plan or an optimal loading plan for cargo loaded in a container.

In addition, the database unit (60) may further include a visual interface module (not shown) that visualizes and classifies optimal loading plan data so that it can be searched by port and container.

The information disclosure unit (70) above distributes the optimal loading plan data visualized by the database unit (60) on the web. The information disclosure unit (70) graphically processes the optimal loading plan data visualized by the database unit (60) so that shipping companies and shippers can easily understand it visually and utilize it as operational data. The information disclosure unit (70) can disclose information on the resulting route, schedule, and cost on the web. Through this, the present invention can provide an integrated optimal loading plan website capable of accepting last orders.

Meanwhile, as illustrated in FIG. 3, for the optimal loading plan data provision system reflecting the last order according to one embodiment of the present invention, the user logs in on the platform, creates a last order, inputs cargo information/enters basic vessel information, searches for a vessel (corresponding to the data at the time of input), searches for the last order status, selects date and sailing information, searches for results after sensitivity analysis, selects date and sailing information/selects last order items, searches for available space results and demand matching results, selects sailings, departure ports, and arrival ports, selects date, vessel, sailing, sailing direction, and port in the Bay Plan Viewer (shipping location map), and selects date, vessel, sailing, sailing direction, and port in the S.A Result Viewer (displays the Optimal Stow results).

In addition, the shipper will go through the process of confirming the space to be used, selecting the space to be used, and matching the available space results with the demand, and the administrator can go through the process of adding/modifying/deleting users after logging in as an administrator and selecting a company code, and the process of modifying/add/deleting companies after logging in and viewing company information.

As illustrated in FIGS. 4 and 5, the optimal loading plan data provision system reflecting the last order according to one embodiment of the present invention goes through a login process (logging in to the optimal loading calculation service platform), an input data selection process (selecting data required for securing additional loading from the data hub), an additional ship space securing calculation process (selecting an objective function and constraints for optimization, and selecting an optimization engine), an optimization calculation process (using an integer calculation engine such as Cplex), an optimization/sensitivity analysis process (repeating and verifying optimization while changing the objective function and constraints) (see FIG. 5), a last order reflection plan creation process (changing an optimized dispatch plan into a web service), a bay plan distribution process (distributing a loading plan that accepts the last order through the web), and a data storage and disclosure process (disclosing the bay plan and ship location information through the web).

FIG. 6a is a web screen for logging into the optimal loading plan data provision system reflecting the last order, FIG. 6b is a screen showing information for selecting a vessel to be loaded, FIG. 6c is a screen for looking up information on available space for loading, FIG. 6d is a screen for confirming available space for loading, FIG. 6e is a screen showing result information for selecting loading and available space for loading, FIG. 6f is a screen for selecting view results with Bay Plan, and FIG. 6g is a screen showing the result of confirming additional loading with Bay Plan. At this time, VVD (Vessel Voyage Direction) is information indicating vessel code, voyage number, and sailing direction.

The system for providing optimal loading plan data reflecting the last order according to one embodiment of the present invention configured as described above can calculate additional shipping capacity by reanalyzing the stowage plan to reflect the last order, which is an additional order after establishing the optimal loading plan, and can store optimal loading plan data reflecting the last order and provide a web service having an analysis and visualization function.

In addition, one embodiment of the present invention can maximize the profits of shipping companies and increase the convenience of shippers by establishing a flexible loading plan for early confirmation of loading and unloading cargo and additional orders to enhance the safety of international trade transactions.

In addition, one embodiment of the present invention can increase the consistency of the plan by providing confirmation information to subsequent work such as truck dispatching once the work order is determined, reduce logistics costs such as dispatching areas and port waiting, maximize port efficiency, and advance the implementation of a smart port. In addition, it can help alleviate phenomena such as a shortage of experienced navigators due to the effect of avoidance of maritime work and avoidance of work such as stowage planning that requires 24-hour management.

In addition, one embodiment of the present invention can increase the accuracy of cargo information, such as by strengthening security laws, by increasing the consistency between cargo information and actual cargo status, and can enable the establishment of a more optimized loading plan by applying big data, AI, etc., to predict factors affecting operation in advance.

In addition, one embodiment of the present invention has the effect of reducing fuel costs, suppressing CO2 emissions, helping to respond to carbon emission regulations, and enabling immediate decision-making support for fleet operation.

Meanwhile, the method for operating the optimal loading plan data provision system reflecting the last order according to the present invention may be implemented in the form of program commands that can be executed through various computer means and recorded on a computer-readable medium. The computer-readable medium may include program commands, data files, data structures, etc., either singly or in combination. The program commands recorded on the medium may be those specially designed and configured for the present invention or may be those known and usable by those skilled in the art of computer software. Examples of the computer-readable recording medium include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, magneto-optical media such as floptical disks, and hardware devices specially configured to store and execute program commands such as ROMs, RAMs, and flash memories. Examples of program commands include not only machine language codes generated by a compiler, but also high-level language codes that can be executed by a computer using an interpreter, etc. The above hardware devices may be configured to operate as one or more software modules to perform the operations of the present invention, and vice versa.

In addition, a contamination-resistant coating layer made of a contamination-preventing coating composition may be applied to the upper surface of the loading plan section (20) to improve contamination resistance.

The above-mentioned anti-fouling coating composition contains sulfolaurate and cocamidopropyl betaine in a molar ratio of 1:0.01 to 1:2, and the total content of sulfolaurate and cocamidopropyl betaine is 1 to 10 wt% with respect to the entire aqueous solution.

The molar ratio of the above sulfolaurate and cocamidopropyl betaine is preferably 1:0.01 to 1:2. If the molar ratio is outside the above range, the coating properties of the antifouling coating composition may be reduced or the moisture absorption on the surface may increase after coating, resulting in the problem of the coating film being removed.

The above sulfolaurate and cocamidopropyl betaine are preferably present in an amount of 1 to 10 wt% of the total aqueous composition. If the amount is less than 1 wt%, there is a problem that the applicability of the antifouling coating composition is reduced, and if the amount is more than 10 wt%, crystal precipitation is likely to occur due to an increase in the thickness of the coating film.

Meanwhile, the method for applying the composition for coating the contamination-resistant coating on the upper surface of the loading plan section (20) is preferably by spraying. In addition, the final coating film thickness on the upper surface of the loading plan section (20) is preferably 900 to 2300 Å. If the thickness of the coating film is less than 900 Å, there is a problem of deterioration in the case of high-temperature heat treatment, and if it exceeds 2300 Å, there is a disadvantage of easy occurrence of crystal precipitation on the coating surface.

In addition, the present composition for anti-pollution coating can be prepared by adding 0.1 mol of sulfolaurate and 0.05 mol of cocamidopropyl betaine to 1000 ml of distilled water and then stirring.

The reason why the ratio of the above components and the thickness of the coating film are numerically limited as above is that the inventor of the present invention analyzed the test results through repeated failures and showed the optimal anti-pollution coating effect at the above ratio.

The upper surface of the above information input section (10) may be coated with an environmental air freshener material mixed with functional oil that helps with sterilization and stress relief for the user.

The mixing ratio of the fragrance material and the functional oil is 95 to 97 wt% of the fragrance material and 3 to 5 wt% of the functional oil, and the functional oil is composed of 55 wt% of Styrax oil and 45 wt% of sage oil.

Here, it is preferable that the functional oil be mixed in an amount of 3 to 5 wt% with respect to the air freshener. If the mixing ratio of the functional oil is less than 3 wt%, the effect is minimal, and if the mixing ratio of the functional oil is more than 3 to 5 wt%, the effect is not significantly improved, but the economic feasibility is reduced. Styrax oil has a balsamic scent and is effective in psychologically purifying the mind and treating headaches, depression, etc., and sage oil is effective in sterilizing, repelling insects, and relieving stress. Therefore, when the air freshener mixed with such functional oil is coated on the upper surface of the information input unit (10), it is possible to obtain effects such as sterilizing the information input unit (10) and alleviating user stress, etc.

The reason for limiting the composition of the environmental air freshener and functional oil and limiting the numerical mixing ratio is that the inventor analyzed the test results through repeated failures and found that the optimal effect was achieved with the above-mentioned composition and numerical limited ratio.

A sound-absorbing layer can be formed on the inner surface of the case (not shown) that constitutes the above database section (60).

Natural fiber nonwoven fabric can be used as the above sound-absorbing layer.

The thickness of the above sound-absorbing layer is preferably 0.7 to 16 mm. If the thickness of the above sound-absorbing layer is less than 0.7 mm, sufficient sound-absorbing effect is not obtained, and if it exceeds 16 mm, sufficient space with the case is not secured, which may increase the temperature of the database section (60), which is not preferable.

It is preferable that the unit weight of the above sound-absorbing layer be 15 to 700 g/m ² . If it is less than 15 g/m ² , sufficient sound-absorbing effect cannot be obtained, and if it exceeds 700 g/m ² , the lightness of the database section (60) cannot be secured, so it is not preferable.

The fineness of the fibers constituting the above-mentioned sound-absorbing layer is preferably in the range of 0.7 to 23 decitex. If it is less than 0.7 decitex, it is difficult to absorb low-frequency noise and cushioning properties are also reduced, so it is not preferable. If it is more than 23 decitex, it is difficult to absorb high-frequency noise, so it is not preferable.

The tensile strength of the nonwoven fabric of the above sound-absorbing layer is formed to be 9 kgf/㎠, and the noise reduction coefficient (NRC) is formed to be 0.670.

Since the above-mentioned sound-absorbing layer is provided on the inner surface of the case of the database unit (60), noise of the database unit (60) can be reduced.

The reason for limiting the components of the nonwoven fabric, thickness, weight, fineness, etc. that constitute the sound-absorbing layer and limiting the numerical value of the composition ratio is that the inventor analyzed the test results through repeated failures and found that the optimal sound-absorbing effect was achieved with the above-mentioned components and numerical ratios.

The above has illustrated and described preferred embodiments of the present invention. However, the present invention is not limited to the above-described embodiments, and anyone skilled in the art will be able to make various modifications without departing from the scope of the present invention as defined by the appended claims.

10: Information input section 20: Loading planning section
30: Available space calculation section 40: Additional shipping space calculation section
50: Last order reflection section 60: Database section
70: Information Disclosure Department

Claims (4)

An information input unit in which first information about a container transported by a ship, second information about cargo loaded in the container, and third information about a transportation route required for transportation of the cargo are input;
A stowage planning unit that schedules a stowage plan for cargo loaded into the container based on the first to third information;
An available space calculation unit that calculates the available space of the container based on the first to third information;
When fourth information on additional cargo to be loaded in the container is entered in the information input section, an additional loading space calculation section that matches a container in which the additional cargo can be loaded based on the fourth information and the available space of the container;
A last order reflection unit that instructs the loading of the additional cargo into a container matched by the additional shipping capacity calculation unit; and
A system including a database unit that stores the first to fourth information, the available space information of the container, and the optimal loading plan data reflecting the last order, and classifies and visualizes the optimal loading plan data so that it can be searched by port and container.
The above available space is calculated based on the cargo weight, cargo size, cargo characteristics, and transportation section as attributes, and the cargo characteristics include Reefer or hazardous cargo codes.
The above database section further includes a visual interface module that visualizes and classifies optimal loading plan data so that it can be searched by port and container.
The above system goes through the following steps: login process (login to the optimal loading calculation service platform), input data selection process (selection of data required to secure additional shipments from the data hub), additional ship space acquisition calculation process (selection of objective function and constraints for optimization, selection of optimization engine), optimization calculation process (use of Cplex integer calculation engine), optimization/sensitivity analysis process (repetition and verification of optimization while changing objective function and constraints), last order reflection plan creation process (change of optimized dispatch plan to web service), bay plan distribution process (distribution of loading plan accepting last order through web), data storage and disclosure process (disclosure of bay plan and ship location information through web).
A system for providing optimal loading plan data reflecting a last order, characterized in that a contamination-resistant coating layer composed of a contamination-preventing coating composition is applied to the upper surface of the loading plan section, wherein the contamination-resistant coating composition contains sulfolaurate and cocamidopropyl betaine in a molar ratio of 1:0.01 to 1:2, and the total content of sulfolaurate and cocamidopropyl betaine is 1 to 10 wt% with respect to the entire aqueous solution.
In the first paragraph,
The above loading planning unit generates an optimal container loading plan for each transportation section based on the first to third information,
The above available space calculation unit is a system for providing optimal loading plan data reflecting the last order, characterized in that it calculates available space (Cargo Mix) that can be additionally shipped in a transportation section where cargo is not 100% in the entire transportation section.
delete In the first paragraph,
A system for providing optimal loading plan data reflecting the last order, characterized in that it further includes an information disclosure unit that distributes optimal loading plan data visualized by the above database unit on the web.