Prediction apparatus for predicting operating time of device provided on ship, prediction method, and recording medium having prediction program recorded thereon

Abstract

Accurately predict the operating time of equipment installed on the ship. A prediction device (3) for predicting the operating time of a device installed on a ship (S) comprises a navigation plan acquisition unit (32) for acquiring a navigation plan of the ship (S), a weather information acquisition unit (34) for acquiring weather information of the route in the navigation plan, and an operating time prediction unit (35) for predicting the operating time of the device based on the weather information.

Description

Technology Field

[0001] The present invention relates to a prediction device for predicting the operating time of a device installed on a ship, a prediction method, and a recording medium recording a prediction program. Background Technology

[0002] Equipment such as tide devices or oil-water separators installed on ships operating at sea needs to be maintained (inspected or replaced with parts of the equipment) based on accumulated operating time. Patent Document 1 discloses a method for creating a maintenance plan based on daily operating time information of a marine engine, maintenance cycles for each unit part constituting the marine engine, maintenance history information, and the annual planned operating time of the marine engine. Prior art literature

[0003] Patent Document 1: Japanese Patent No. 4909175 The problem to be solved

[0004] Since maintenance cannot be performed during navigation, it is necessary to carry out maintenance before the vessel departs to prevent parts from reaching the maintenance timeline while sailing. However, because the operating conditions of a ship's equipment vary depending on the weather, the operating time of the equipment from departure to arrival at the destination is affected by the weather along the route. Consequently, it is difficult to determine whether maintenance is required based solely on the accumulated operating time of the equipment at the time of departure. Furthermore, if replacement parts cannot be obtained due to reasons such as forgetting to purchase them, and inferior substitutes are used, there is a risk that the lifespan of the equipment may actually be shortened.

[0005] The present invention was made to solve the above problem and has the objective of accurately predicting the operating time of equipment installed on a ship. means of solving the problem

[0006] The above problem of the present invention is solved by a prediction device for predicting the operating time of a device installed on a ship, comprising a navigation plan acquisition unit for acquiring a navigation plan of the ship, a weather information acquisition unit for acquiring weather information of a route in the navigation plan, and an operating time prediction unit for predicting the operating time of the device based on the weather information.

[0007] The above problem of the present invention is solved by a prediction method for predicting the operating time of a device installed on a ship, comprising a navigation plan acquisition process for acquiring a navigation plan of the ship, a weather information acquisition process for acquiring weather information of a route in the navigation plan, and an operating time prediction process for predicting the operating time of the device based on the weather information.

[0008] In a preferred embodiment of the present invention, the weather information is characterized by including at least one of weather, wind speed, wind direction, wave height, sea surface temperature, ocean current speed, and ocean current direction.

[0009] In a preferred embodiment of the present invention, the prediction device further comprises a material information acquisition unit for acquiring material information regarding the vessel and equipment, and the operating time prediction unit predicts the operating time of the equipment based on the weather information and the material information. Additionally, the prediction method further comprises a material information acquisition process for acquiring material information regarding the vessel and equipment, and the operating time prediction process predicts the operating time of the equipment based on the weather information and the material information.

[0010] In a preferred embodiment of the present invention, the operating time prediction unit is characterized by predicting the operating time of the device using a machine-learned operating time prediction model. In addition, the operating time prediction process is characterized by predicting the operating time of the device using a machine-learned operating time prediction model.

[0011] In a preferred embodiment of the present invention, the prediction device is characterized by further comprising a maintenance prediction unit that predicts whether maintenance is required of the device based on the predicted operating time. Additionally, the prediction method is characterized by further comprising a maintenance prediction process that predicts whether maintenance is required of the device based on the predicted operating time.

[0012] In the above embodiment, the device may be a freshwater device that produces fresh water from seawater.

[0013] In the above embodiment, the device may be an oil-water separator that separates oil from waste liquid.

[0014] The above problem of the present invention is solved by a computer-readable recording medium that records a prediction program for enabling a computer to function as a prediction device for predicting the operating time of an equipment installed on a ship, wherein the prediction program is provided by a recording medium that enables a computer to function as a navigation plan acquisition unit for acquiring a navigation plan of the ship, a weather information acquisition unit for acquiring weather information of a route in the navigation plan, and an operating time prediction unit for predicting the operating time of the equipment based on the weather information. Effects of the invention

[0015] According to the present invention, the operating time of a device installed on a ship can be accurately predicted. Brief explanation of the drawing

[0016] FIG. 1 is a block diagram of a management system related to one embodiment of the present invention. Figure 2 is an example of a sea route. Figure 3 is an example of an area for acquiring route and weather information. Figure 4 is an example of a weather map showing wind speed and wind direction. Figure 5 is an example of a weather map showing wave height and wave direction. Figure 6 is an example of a weather map showing sea surface water temperature. Figure 7 is an example of a weather map showing ocean current speed and direction. Figure 8 is an example of device management information. Figure 9 is a flowchart illustrating the operation of a prediction device. Specific details for implementing the invention

[0017] Hereinafter, embodiments of the present invention will be described with reference to the accompanying drawings. Furthermore, the present invention is not limited to the following embodiments.

[0018] [System Configuration]

[0019] FIG. 1 is a block diagram of a management system (1) related to one embodiment of the present invention. The management system (1) is a system for managing a ship (S) and is equipped with a control terminal (2) and a prediction device (3).

[0020] The control terminal (2) is a terminal operated by the crew of the vessel (S), etc., and is equipped with an input device (not shown) such as a touch panel and a display device (not shown) such as a liquid crystal display. The control terminal (2) may be configured as a general-purpose computer or as a dedicated computer such as a control panel. Alternatively, the control terminal (2) may be configured integrally with the water supply device (4) or the oil-water separator (5). The control terminal (2) monitors the operating status of the water supply device (4) and the oil-water separator (5), and also controls the water supply device (4) and the oil-water separator (5) according to the operation of the input device.

[0021] [Configuration of the Prediction Device]

[0022] The prediction device (3) is a device that predicts the operating time of the tide device (4) and oil-water separator (5), which are installed on the ship (S). The prediction device (3) is installed outside the ship and is connected to communicate with the control terminal (2) via a network (N), such as the Internet. The prediction device (3) can be configured as a general-purpose computer and is managed, for example, by a management company that manages the ship (S) or by a manufacturer of the tide device (4) and oil-water separator (5).

[0023] The prediction device (3) is a hardware configuration and is equipped with a processor such as a CPU or GPU, a main memory device such as DRAM or SRAM (not shown), and an auxiliary memory device (31) such as an HDD or SSD. Various data, such as a prediction program (D1), an operating time prediction model (D2), and device management information (D3), are stored in the auxiliary memory device (31).

[0024] Additionally, the prediction device (3) is equipped with a navigation plan acquisition unit (32), a material information acquisition unit (33), a weather information acquisition unit (34), an operating time prediction unit (35), a maintenance prediction unit (36), and an external communication unit (37) as functional blocks. Each of these units may be implemented in hardware by logic circuits, etc., or may be implemented in software by the processor of the prediction device (3). In the latter case, the prediction program (D1) stored in the auxiliary memory device (31) may be implemented by the processor reading the prediction program (D1) stored in the main memory and executing it. The prediction program (D1) may be downloaded to the prediction device (3) via a network (N), or installed on the prediction device (3) via a computer-readable non-transient recording medium such as a CD-ROM on which the prediction program (D1) is recorded.

[0025] The navigation plan acquisition unit (32) acquires the navigation plan of the vessel (S). The navigation plan includes the vessel (S)'s departure port, destination, scheduled departure date, scheduled arrival date, etc., and in this embodiment, the crew of the vessel (S) inputs the navigation plan through the control terminal (2). The data of the input navigation plan is transmitted to the prediction device (3) and acquired by the navigation plan acquisition unit (32).

[0026] The information acquisition unit (33) acquires information regarding the vessel (S), the water supply device (4), and the oil-water separator (5). Specifically, the information includes the type, size, and age of the vessel (S), the manufacturing number and quantity of water tanks of the water supply device (4), and the manufacturing number and quantity of wastewater treatment tanks of the oil-water separator (5). In this embodiment, the manufacturing number of the water supply device (4) or the oil-water separator (5) is transmitted from the control terminal (2) along with data of the navigation plan, and the information acquisition unit (33) acquires other information, such as the type of the vessel (S), by comparing the corresponding manufacturing number with an external server of the manufacturing company.

[0027] The weather information acquisition unit (34) acquires weather information for the route in the navigation plan of the vessel (S). For example, as shown in FIG. 2, let’s assume the navigation plan is to depart from port (A) on March 1 and arrive at port (B) on March 3. In that case, the weather information acquisition unit (34) acquires weather information (forecast) for March 1 to March 3 in the area (R) shown as a diagonal line including the route (P) shown in FIG. 3.

[0028] In addition, the route (P) may be a standard route for navigation from port (A) to port (B), or it may be determined by the crew of the vessel (S). Furthermore, the width of the area (R) can be appropriately set by taking into account the difference between the route (P) and the actual route of the vessel (S).

[0029] Weather information can be obtained through a network (N) from weather information providers, such as the Korea Meteorological Administration. The types of weather are not specifically limited as long as they affect the operating status of the equipment, but examples include weather, wind speed, wind direction, wave height, sea surface temperature, ocean current speed, and ocean current direction.

[0030] Weather, wind speed, wind direction, wave height, ocean current speed, and ocean current direction affect the load (vessel speed) of the main engine of the vessel (S). For example, when there is a strong headwind, the load on the main engine tends to increase, and when the wave height is high, the load on the main engine tends to decrease in order to operate at a low speed. In addition, if the vessel (S) is a cargo ship, after operating at a low speed, it may switch to high-speed operation to recover from schedule delays. The sea surface temperature affects the amount of tides in the tide device (4).

[0031] Examples of weather information are illustrated in FIGS. 4 to 7. FIG. 4 is an example of a weather map showing wind speed and wind direction, FIG. 5 is an example of a weather map showing wave height and wave direction, FIG. 6 is an example of a weather map showing sea surface temperature, and FIG. 7 is an example of a weather map showing ocean current speed and ocean current direction. In addition, FIGS. 4 to 7 are schematic weather maps, and in reality, more detailed information is provided.

[0032] The operating time prediction unit (35) predicts the operating time of the tide device (4) and the oil-water separator (5) based on weather information and material information. In this embodiment, the operating time prediction unit (35) predicts the operating time of the tide device (4) and the oil-water separator (5) using a machine-learned operating time prediction model (D2). That is, the operating time prediction unit (35) inputs the weather information acquired by the weather information acquisition unit (34) and the material information acquired by the material information acquisition unit (33) into the operating time prediction model (D2), and accordingly, acquires the operating time of the tide device (4) and the oil-water separator (5) output from the operating time prediction model (D2) as a prediction result.

[0033] The operating time prediction model (D2) is generated, for example, as follows. First, for multiple vessels that have previously navigated the route in the navigation plan of the vessel (S), training data (training data set) is created by matching the actual operating times of the tide device and the oil-water separator with the equipment information and the actual weather information in the route. Then, the operating time prediction model (D2) is generated by machine learning an artificial intelligence model, such as a neural network, using the training data. The weather information in the training data may be information obtained by extracting the area of ​​a predetermined range including the route from a weather map, and for example, if the route is the route (P) shown in FIG. 3, it may be weather information in the area (R). Additionally, when generating an operating time prediction model (D2) specialized for a specific equipment, the equipment information may be omitted from the training data.

[0034] The maintenance prediction unit (36) predicts whether maintenance is required for the water supply device (4) and the oil-water separator (5) based on the operating time predicted by the operating time prediction unit (35) (hereinafter referred to as “predicted operating time”). In this embodiment, the maintenance prediction unit (36) predicts whether inspection or replacement is required for each part of the water supply device (4) and the oil-water separator (5) by referring to the equipment management information (D3).

[0035] FIG. 8 is an example of equipment management information (D3). The equipment management information (D3) includes the equipment's construction number, model number, consumable name, replacement standard time, and accumulated operating time. The replacement standard time is the time (maintenance cycle) from when the corresponding part is replaced until it needs to be replaced again. The accumulated operating time is the accumulated time the equipment has operated since the corresponding part was replaced, and the prediction device (3) periodically obtains this from the control terminal (2) of the vessel (S).

[0036] For example, if the predicted operating time was 15 hours, the accumulated operating time of part (A) during the navigation of the vessel (S) exceeds the replacement standard time. Therefore, the maintenance prediction unit (36) predicts that the part (A) needs to be replaced.

[0037] The prediction result is transmitted from the prediction device to the control terminal (2) and displayed on the display device of the control terminal (2). Accordingly, the crew of the vessel (S) can identify the parts that require maintenance.

[0038] In addition, the prediction by the operating time prediction unit (35) and the maintenance prediction unit (36) may be performed before the vessel (S) sails or during the vessel (S) sails. Furthermore, even if the above prediction is performed before the vessel (S) sails, if the weather forecast changes or the route changes during the vessel (S) sails, it is preferable to perform information acquisition by the sailing plan acquisition unit (32), the equipment information acquisition unit (33), and the weather information acquisition unit (34) during the sailing, and to perform the prediction by the operating time prediction unit (35) and the maintenance prediction unit (36).

[0039] The external communication unit (37) can communicate with an external contact (T) through a network (N) or another network. For example, as described above, if it is predicted by the maintenance prediction unit (36) that a part (A) needs to be replaced, the external communication unit (37) can communicate with an external contact (T) and take measures such as delivering the part (A) to the nearest port of call. In this embodiment, the external contact (T) is, for example, a ship management company, a replacement parts seller, a product manufacturing company, etc.

[0040] [Processing Order]

[0041] FIG. 9 is a flowchart illustrating the operation of a prediction device (3). In the prediction device (3), a navigation plan acquisition unit (32) acquires a navigation plan of the vessel (S) from the control terminal (2) of the vessel (S) (navigation plan acquisition process (S1)). At the same time, a material information acquisition unit (33) acquires material information regarding the vessel (S), the tide device (4), and the oil-water separator (5) from the control terminal (2) (material information acquisition process (S2)). Subsequently, a weather information acquisition unit (34) acquires weather information of the route in the navigation plan of the vessel (S) (weather information acquisition process (S3)). Subsequently, an operation time prediction unit (35) predicts the operation time of the tide device (4) and the oil-water separator (5) based on the weather information and material information (operation time prediction process (S4)). In addition, the maintenance prediction unit (36) predicts whether maintenance is required for the water supply device (4) and the oil-water separator (5) based on the predicted operating time (maintenance prediction process (S5)).

[0042] In addition, the order of processes S1 to S3 is not particularly limited. Furthermore, if each process is executed by a computer, the operator of each process is not limited to the above. For example, at least a portion of processes S1 to S5 may be executed by a control terminal (2).

[0043] [Brief Summary]

[0044] As described above, in this embodiment, the operating time of each device of the tide device (4) and oil-water separator (5) is predicted using a machine-learned operating time prediction model (D2) based on weather information of the route in the navigation plan. Therefore, the operating time of the device affected by the weather can be accurately predicted. In addition, the need for maintenance of the device can be predicted based on the predicted operating time.

[0045] [Variation Example]

[0046] Although embodiments of the present invention have been described above, the present invention is not limited to the above embodiments, and various modifications are possible without departing from the spirit thereof.

[0047] In the above embodiments, a water supply device and an oil-water separator are exemplified as equipment installed on a vessel, but the present invention is not limited thereto. The equipment may be a main component such as an engine, but the present invention is primarily intended for auxiliary components.

[0048] In the above embodiment, the operating time prediction unit (35) predicts the operating time of the device based on weather information and material information, but if the operating time prediction model (D2) is a model specialized for a specific material, the operating time prediction unit (35) may predict the operating time of the device based only on weather information. In this case, the material information acquisition unit (33) may be omitted.

[0049] In addition, in the above embodiment, the operating time prediction unit (35) predicts the operating time of the device using a machine-learned operating time prediction model (D2), that is, using artificial intelligence, but the operating time of the device may be predicted without using artificial intelligence. In this case, for example, the operating time of the assistant device can be calculated using the following formula.

[0050] Operating Time = Required Quantity / Estimated Tide

[0051] Here, the required quantity is calculated as average consumption × number of sailing days × α. α is a safety factor and is set to account for the period immediately after departure and immediately before arrival (reserve days) when the tide device cannot be used. In addition, the tide forecast amount can be predicted from the engine load and sea surface temperature, and the engine load depends on the weather (especially wave height and wind speed).

[0052] In addition, in the above embodiment, the maintenance prediction unit (36) of the prediction device (3) automatically predicts whether maintenance is required for the device, but the prediction device (3) may also predict the operating time of the device by the operating time prediction unit (35), and the user (a crew member of the vessel (S), etc.) may determine whether maintenance is required for the device based on the predicted operating time. Explanation of the symbols

[0053] 1: Management System 2: Control terminal 3: Prediction device 31: Secondary storage 32: Navigation Plan Acquisition Section 33: Record Information Acquisition Department 34: Weather Information Acquisition Department 35: Operating Time Prediction Unit 36: Maintenance Forecasting Department 4: Assistant device 5: Oil-water separator D1: Prediction program D2: Uptime Prediction Model D3: Device Management Information N: Network P: Route R: Area S: Ship

Claims

Claim 1 A prediction device for predicting the operating time of a tide device that produces fresh water from seawater installed on a ship, comprising a navigation plan acquisition unit for acquiring a navigation plan of the ship, a weather information acquisition unit for acquiring weather information of a route in the navigation plan, and an operating time prediction unit for predicting the operating time of the tide device based on the weather information. Claim 2 In claim 1, the weather information is a prediction device comprising at least one of weather, wind speed, wind direction, wave height, sea surface temperature, ocean current speed, and ocean current direction. Claim 3 A prediction device according to claim 1 or 2, further comprising a description information acquisition unit for acquiring description information regarding the vessel and the tide device, and the operating time prediction unit for predicting the operating time of the tide device based on the weather information and the description information. Claim 4 In claim 1 or 2, the operating time prediction unit is a prediction device that predicts the operating time of the assistant device using a machine-learned operating time prediction model. Claim 5 A prediction device according to claim 1 or 2, further comprising a maintenance prediction unit that predicts whether maintenance is required for the assistant device based on the predicted operating time. Claim 6 A prediction method for predicting the operating time of a tide device that produces fresh water from seawater installed on a ship, comprising: a navigation plan acquisition process for acquiring a navigation plan of the ship; a weather information acquisition process for acquiring weather information of a route in the navigation plan; and an operating time prediction process for predicting the operating time of the tide device based on the weather information. Claim 7 In paragraph 6, the above weather information is a prediction method comprising at least one of weather, wind speed, wind direction, wave height, sea surface temperature, ocean current speed, and ocean current direction. Claim 8 A prediction method according to claim 6 or 7, further comprising a process for acquiring information on the vessel and the tide device, wherein the operating time prediction process predicts the operating time of the tide device based on the weather information and the information on the vessel. Claim 9 In claim 6 or 7, the operating time prediction process predicts the operating time of the assistant device using a machine-learned operating time prediction model. Claim 10 A prediction method according to claim 7, further comprising a maintenance prediction process that predicts whether maintenance is required for the assistant device based on the predicted operating time. Claim 11 A computer-readable recording medium having a prediction program recorded therein for functioning a computer as a prediction device for predicting the operating time of a tide device for producing fresh water from seawater installed on a ship, wherein the prediction program comprises a navigation plan acquisition unit for acquiring a navigation plan of said ship, a weather information acquisition unit for acquiring weather information of a route in said navigation plan, and a recording medium for functioning a computer as an operating time prediction unit for predicting the operating time of said tide device based on said weather information. Claim 12 delete Claim 13 delete Claim 14 delete Claim 15 delete

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