Automatic container wharf multi-ship operation analysis system and method

Abstract

The invention belongs to the technical field of automatic container wharf operation optimization, and particularly relates to an automatic container wharf multi-ship operation analysis system and method. Multi-dimensional data of TOS, ABB, U I monitoring stop time, bureau regulation and TOS peripheral systems are fused, a multi-ship operation analysis system is developed in an integrated mode, and the system comprises a data acquisition module, a multi-ship operation analysis database and a multi-ship operation analysis module. A multi-ship operation analysis system is developed based on a ship operation database, multiple pieces of ship operation data are automatically compared from time and ship dimensions, the defects that traditional wharf multi-ship comparison analysis data are incomplete in collection, long in manufacturing time and the like are overcome, the transparency of wharf ship production operation is enhanced, and multi-dimensional data support is provided for wharf production operation.

Description

Technical Field

[0001] The present invention belongs to the technical field of automated container terminal operation optimization, and in particular relates to an automated container terminal multi-ship operation analysis system and method. Background Art

[0002] In the field of automated terminal operation data management, effective analysis of vessel operation data is key to improving terminal operational efficiency. Although terminals have introduced core systems such as TOS and ECS, accumulating a wealth of operational data including vessel berthing and departure times, quay crane efficiency, and container volume statistics, data analysis for multi-vessel operations still relies on manual tools such as Excel. Under this traditional model, data is dispersed across different systems, forming "data silos." This results in incomplete multi-vessel data collection and time-consuming analysis report production, making it difficult to meet the real-time and accurate data management requirements of modern terminals.

[0003] With the development of automated terminals, production data is increasing dramatically, and the drawbacks of traditional data statistics models are becoming increasingly prominent. Manual statistics for comparing and analyzing multiple ships not only consumes a significant amount of manpower and resources, but is also prone to errors in data processing that affect the reliability of analysis results. This makes it impossible to provide timely, multi-dimensional data support for terminal production operations, and also hinders the transformation of automated terminals into intelligent ones. Therefore, a management and analysis system that can automatically collect, analyze, and compare multi-ship operation data is urgently needed. Summary of the Invention

[0004] The object of the present invention is to provide an automated container terminal multi-ship operation analysis system and method to solve the problems existing in the prior art.

[0005] To achieve the above objectives, the present invention provides the following technical solutions: an automated container terminal multi-ship operation analysis system that integrates multi-dimensional data from TOS, ABB, UI monitoring downtime, local dispatching, and TOS peripheral systems to develop an integrated multi-ship operation analysis system. The system includes a data acquisition module, a multi-ship operation analysis database, and a multi-ship operation analysis module.

[0006] The data acquisition module is used to collect real-time data on the berthing time, route data, shipping company data, ship name and voyage data, ship time efficiency data, quay crane efficiency data, auxiliary operation data, and operation downtime data of ships operating at the terminal;

[0007] The multi-vessel operation analysis database is used to classify and store various data collected by the data acquisition module for use by the multi-vessel operation analysis module;

[0008] The multi-ship operation analysis module is used to call the multi-ship operation analysis database, automatically capture all ship entries, route entries, container volume overviews, and operation overviews of terminal operations within two fixed time periods in the time dimension, analyze and compare the throughput, shipping production, and route efficiency within the two time periods, and form a year-on-year comparison. It also automatically filters operating ships within the time span in the ship dimension, compares and analyzes the ship's ship-time efficiency, quay crane efficiency, auxiliary operation time, operation downtime time and type, and provides targeted optimization directions for the overall terminal operation.

[0009] Preferably, the data stored in the multi-ship operation analysis database also includes the start and completion time of terminal operation ships, the number of opened lines, the total throughput, the import container volume, the export container volume, the unloaded container volume, the loaded container volume, the operation container volume, the number of operation hooks, the box hook coefficient, the berth time, the operation time, the comprehensive port time, peak efficiency, the number of refrigerated containers, the number of hazardous goods, and the over-limit number.

[0010] Preferably, the data acquisition module regularly crawls the berthing and unberthing times, start and completion times, navigation information, shipping company information, ship name and voyage information, throughput, import and export container volume, refrigerated container volume, hazardous goods volume, and over-limit volume from the bureau dispatching system; and collects opening and closing data and taxi movement data from the quay crane ABB during ship operation to calculate the ship's unloading container volume, loading container volume, operating container volume, and operating hook number.

[0011] Preferably, the operation stop time data is the stop time duration and stop reason of the quay crane. The data acquisition module combines the opening and closing data of ABB to capture the time interval when the single hook operation duration or empty hook duration of the quay crane during the production operation of the ship is greater than 3 minutes, and triggers the stop time entry module of the UI monitoring interface. The scheduling enters the stop time reason according to the basic stop time type, among which the single hook operation duration is the difference between the locking time of the quay crane constitutive operation and the unlocking time of the quay crane constitutive operation, and the empty hook duration is the difference between the locking time of the next hook operation and the unlocking time of this operation.

[0012] Preferably, the quay crane efficiency and ship efficiency include the container efficiency when berthing, the hook efficiency when berthing, the container efficiency when operating the ship, the hook efficiency when operating the ship, the number of ship operating hooks, the average single-bridge efficiency, and the M-line efficiency; the auxiliary operation time data is divided into start-up auxiliary time and unberthing auxiliary time, the start-up auxiliary time is the difference between the start time and the berthing time, the unberthing auxiliary time is the difference between the unberthing time and the completion time, and the auxiliary operation time includes the time when the loading and unloading workers bring the cable, the joint inspection, the loading and unloading, and the remote-controlled driver runs the quay crane.

[0013] Preferably, the KPI indicators of throughput include the total number of operating ships, import operation volume, and export operation volume within a fixed time period; the KPI indicators of shipping production include the average single bridge efficiency, M-line efficiency, average berthing time, average operation time, average berthing efficiency, and average operation ship efficiency within a fixed time period; the route efficiency is the KPI value of different routes within a fixed time period, including natural container volume, throughput (TEU), number of ships, single bridge efficiency, berthing efficiency, operation efficiency, and box-hook ratio.

[0014] The present invention also discloses a method for analyzing multi-ship operations at an automated terminal, which uses the automated container terminal multi-ship operations analysis system, including the following steps:

[0015] S1. Compare KPI data from two time periods from the time dimension:

[0016] S1.1 Identify two comparable time periods and enter them into the system;

[0017] S1.2 Set the number of operating lines in the system. The system will automatically screen and compare the KPI data of ships that have opened more operating lines than the set number during the set period, and analyze the KPI growth rate of different types of ships operating at the terminal during different periods.

[0018] S2. Statistical analysis of multiple specific ship operation data:

[0019] S2.1 uses berthing and unberthing times as a screening condition to filter out specific ships within a fixed time period. The system automatically collects and analyzes the specific efficiency of each ship and compares the trend of ship operating efficiency based on time.

[0020] The S2.2 system automatically captures and compiles detailed statistics on each vessel's downtime and displays them in charts, analyzing the main factors affecting multi-vessel operation efficiency.

[0021] S3. Statistical analysis of specific vessel operation data on a fixed route or multiple routes over a period of time: Enter the start time and select the route into the system. The system automatically compares and calculates the specific efficiency of each filtered vessel and outputs the main reasons for downtime that affect vessel efficiency, providing decision-making guidance for terminal managers to optimize route operation efficiency.

[0022] Compared with the methods in the prior art, the present invention has the following beneficial effects:

[0023] The present invention develops a data acquisition module, integrates multi-dimensional data such as TOS, ABB, and UI monitoring downtime, and accesses the multi-ship operation analysis database to realize the automatic collection and integration of multi-ship operation data at the terminal, effectively breaking the "data island" problem in traditional data management, eliminating the defects of incomplete data and time-consuming manual statistics, significantly improving the accuracy and efficiency of multi-ship operation analysis, and saving human resource costs.

[0024] At the same time, the multi-ship operation analysis method proposed by the system can automatically generate analysis reports from multiple dimensions such as time, ships, and routes, intuitively displaying key indicators and influencing factors such as throughput, efficiency, and downtime, providing terminal managers with timely and comprehensive data support, helping to quickly optimize operation plans and route management, promote the transformation of automated terminal operation data management to intelligent management, and improve the overall operation level of the terminal. BRIEF DESCRIPTION OF THE DRAWINGS

[0025] Figure 1 It is a technical route flow chart of the present invention;

[0026] Figure 2 Provide a style chart for comparing monthly ship data;

[0027] Figure 3 A chart showing the monthly data comparison of ships operating on seven lines;

[0028] Figure 4 Display style chart for box volume statistics of specific routes;

[0029] Figure 5 Display style charts for specific route efficiency statistics;

[0030] Figure 6 Provide statistical display style charts of auxiliary operation time for specific routes;

[0031] Figure 7 A statistical display style chart showing the duration of downtime for specific routes. DETAILED DESCRIPTION

[0032] It should be noted that, in the absence of conflict, the embodiments of the present invention and the features in the embodiments can be combined with each other.

[0033] In the description of the present invention, it should be understood that the terms "center", "longitudinal", "lateral", "up", "down", "front", "back", "left", "right", "vertical", "horizontal", "top", "bottom", "inside", "outside" and the like indicate orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, and are only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation on the present invention. In addition, the terms "first", "second" and the like are only used for descriptive purposes and cannot be understood as indicating or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, features defined as "first", "second" and the like may explicitly or implicitly include one or more of the features. In the description of the present invention, unless otherwise specified, "multiple" means two or more.

[0034] In the description of the present invention, it should be noted that, unless otherwise expressly specified or limited, the terms "installed," "connected," "connected," "fixedly connected," and "fixed connection" should be understood in a broad sense. For example, they can refer to fixed connections, detachable connections, or integral connections; they can refer to mechanical connections or electrical connections; they can refer to direct connections or indirect connections through an intermediate medium; and they can refer to internal connections between two components. Those skilled in the art can understand the specific meanings of the above terms in the present invention based on specific circumstances.

[0035] The specific implementation of the present invention is described in detail below with reference to the accompanying drawings and preferred embodiments.

[0036] like Figure 1 As shown in the figure, an automated multi-vessel operation analysis system integrates multiple data such as TOS, ABB, UI monitoring, local adjustment, and TOS peripheral systems, maintains a multi-vessel operation database, and integrates and develops a multi-vessel operation analysis system, including the following steps:

[0037] Step 1: Develop a data collection module to collect real-time data on the berthing time, route data, shipping company data, ship name and voyage data, ship time efficiency data, quay crane efficiency data, auxiliary operation data, operation downtime data, etc. of ships operating at the terminal.

[0038] Step 2: Classify and count the data and connect them to the multi-vessel operation analysis database for system call.

[0039] Step 3: The multi-vessel operation analysis system calls the database and automatically captures all vessel entries, route entries, container volume overviews, and operation overviews of terminal operations within two fixed time periods in the time dimension. It analyzes and compares the throughput, shipping production, and route efficiency within the two time periods and forms a year-on-year comparison.

[0040] Step 4: The multi-vessel operation analysis system calls the database to screen the operating ships within the time span or specific ships on fixed routes. From the ship dimension, it automatically compares and analyzes the ship-time efficiency, quay crane efficiency, auxiliary operation time, operation downtime time and type of specific ships, and provides targeted optimization directions for the overall terminal operation.

[0041] Furthermore, the established multi-ship operation analysis database specifically stores in real time the berthing and unberthing times, start and completion times, routes, number of lines opened, quay crane efficiency, ship efficiency, auxiliary operation time, operation downtime, shipping company, ship name and voyage number, total throughput, import container volume, export container volume, unloaded container volume, loaded container volume, operating container volume, number of operating hooks, box hook coefficient, berthing time, operating time, comprehensive port time, peak efficiency, number of refrigerated containers, number of hazardous goods, and over-limit quantity of ships operating at the terminal.

[0042] Furthermore, a data collection module is developed to regularly crawl the berthing and unberthing times, start and completion times, navigation information, shipping company information, ship name and voyage information, throughput, import and export container volume, refrigerated container volume, hazardous goods volume, and over-limit volume mentioned in step one in the bureau dispatching system.

[0043] Furthermore, the data acquisition module collects the opening and closing data and taxi movement data in the quay crane ABB during ship operation, and calculates the ship's unloading and loading container volume, operating container volume and number of operating hooks.

[0044] Furthermore, the operation downtime data in step 1 is the downtime duration and downtime reason of the quay crane, that is, the single hook operation time of the quay crane during the production operation of the ship is captured by combining the ABB opening and closing data. z Or empty hook time t p When the time interval is greater than 3 minutes, the stop time entry module of the UI monitoring interface is triggered, and the dispatcher enters the stop time reason according to the actual situation of ship production and the basic type of stop time. Among them, the single hook operation time t z =t k -t b , t b is the locking time of the quay crane structural operation, t k is the unlocking time of the quay crane structural operation; the empty hook time t p =t bn -t k , where t bn The locking time for the next hook operation. Based on the operation downtime data after each ship's operation is completed, the direction for optimizing the overall operation of the ship can be analyzed.

[0045] Furthermore, the quay crane efficiency and ship efficiency described in step 1 mainly include the container efficiency when berthing, the hook efficiency when berthing, the container efficiency when operating the ship, the hook efficiency when operating the ship, the number of ship operating hooks, the average single bridge efficiency, and the M line efficiency, among which

[0046]

[0047] Furthermore,

[0048] Furthermore, the auxiliary operation time data in step one is divided into start-up auxiliary time and unberthing auxiliary time, where start-up auxiliary time = start-up time - berthing time, and unberthing auxiliary time = unberthing time - completion time. Auxiliary operation time includes stevedores bringing cables, joint inspections, loading and unloading, and remote-controlled drivers operating quay cranes. The less auxiliary operation time a ship has, the better the terminal's service to the ship.

[0049] Furthermore, the throughput KPI indicators mentioned in step 3 include but are not limited to the total number of operating ships, import operation volume, and export operation volume within a fixed time period; the shipping production KPI indicators include but are not limited to the average single bridge efficiency, M-line efficiency, average berthing time, average operating time, average berthing time efficiency, average operating ship time efficiency, etc. within a fixed time period.

[0050] Furthermore, the route efficiency comparison in step three means that the multi-vessel operation analysis system automatically calls the database to analyze the KPI values ​​of different routes within a fixed time period and form a month-on-month analysis.

[0051] Furthermore, the stoppage comparison analysis described in step 4 mainly includes the overall operation stoppage analysis of all screened ships, that is, the analysis system calls the database to statistically calculate and graphically display the number and duration of all quay crane production stoppages generated during the ship operation process.

[0052] Furthermore, based on the multi-vessel operation analysis system, in order to efficiently analyze the multi-vessel operation situation, the present invention proposes a system-based multi-vessel operation analysis method, comprising the following steps:

[0053] S1. Compare the KPI data of two periods of time from the time dimension.

[0054] S1.1 Determine two comparable time periods from a temporal perspective and enter them into the system.

[0055] S1.2 sets the number of operating lines N in the system. The system automatically filters and compares the KPI data of ships with more than N operating lines during the time period set in S1, and analyzes the KPI growth rate of different types of ships operating at the terminal during different time periods.

[0056] S2. Statistically analyze the operation data of multiple specific ships.

[0057] S2.1 uses berthing and unberthing times as the screening criteria to filter out specific ships within a fixed time period. The system automatically counts and analyzes the specific efficiency of each ship and compares the trend of ship operating efficiency based on time.

[0058] The S3.1 system automatically captures and compiles the detailed operational downtime of each vessel and displays it in charts, analyzing the main factors affecting the efficiency of multi-vessel operations.

[0059] S3. Statistically analyze the operational data of specific ships on a fixed route or multiple routes within a period of time. Enter the start time and select the route into the system. The system automatically compares and calculates the specific efficiency of each filtered ship and outputs the main reasons for ship downtime that affect ship efficiency, providing decision-making direction for terminal managers to optimize route operation efficiency.

[0060] Specific implementation method 1: Analyze the ship operation status of two months from a horizontal statistical perspective.

[0061] The decision maker confirms the two months for comparison and inputs them into the multi-vessel operation analysis system. The system automatically calculates the KPI indicators for the two months. The KPI indicators include: monthly number of operating ships, monthly ship imports and exports and total operation volume, cumulative average single bridge box efficiency, cumulative average single bridge hook efficiency, cumulative average M-line efficiency, cumulative average berthing time, cumulative average operation time, and cumulative average berthing and operation ship time efficiency. The display style diagram is as shown in the attached figure. Figure 2 As shown in the figure, compared with March, the cumulative number of operating ships in April decreased by 6.67%, the total operation volume increased by 18.09%, the average single-bridge box efficiency increased by 1.45%, and the berthing time and operation time increased by 8.54% and 11.81% respectively. This shows that there were more large ships operating in April. Although the number of ship operations was small, the operation volume was large.

[0062] The decision maker determines the number of operations to be compared N and enters it into the system. Based on the above comparative analysis, the data of ships with more than 7 lines of terminal operations within two months are compared and analyzed. The system displays the following figure: Figure 3 As shown, there were 8 ships operating more than 7 lines in April, and 3 ships operating in March. The average single-bridge efficiency increased by 2.22%, but the M-line efficiency decreased by 1.44% month-on-month. The efficiency at berthing and the efficiency during operation both decreased by more than 10% month-on-month, indicating that the production organization guarantee for the company's important ships in April was weaker than that in March, especially the guarantee for the efficiency of the M-line and the overall ship time efficiency.

[0063] From the above two comparisons, it can be seen that the overall ship operation in April was better than that in March, but the operation and organization of large ships should be further optimized to ensure the improvement of efficiency in subsequent large ship operations.

[0064] Specific implementation method 2: Analyze the ship operation status of a specific route from a vertical statistical perspective.

[0065] For key routes and newly opened routes operated by terminal companies, once selected in the multi-vessel operation analysis system, the system automatically collects statistics and displays the operation status of fixed routes. Specific statistics include vessel name and voyage, container volume, efficiency, auxiliary operation time, and operation downtime. For example, the FE4 route for April 2023 is selected for display and analysis.

[0066] Box quantity statistics. The system automatically generates box quantity statistics analysis display, the style diagram is as shown in the attached Figure 4 As shown, there were three operations on the FE4 route in April, with a total import and export container volume of 18,942 containers, and the average container hook coefficient of the three vessels was 1.15.

[0067] Efficiency statistics. The system automatically analyzes the efficiency of each voyage, as shown in the attached figure. Figure 5 shown.

[0068] Auxiliary operation time statistics. The system automatically captures the ship's berthing, departure, start and completion time, calculates the auxiliary operation time and displays it. The style diagram is as shown in the attached figure. Figure 6 As shown in the figure, the average auxiliary operation time of the three voyages in April was 1.05 hours, indicating that the terminal has a high service capacity for this route, and the ships can operate as soon as they dock and leave as soon as they are completed.

[0069] Operation downtime statistics. Integrate the operation downtime of each voyage of the route, and the system automatically generates the operation downtime statistics chart of the route, as shown in the attached figure. Figure 7 As shown in the figure, the factors that have the greatest impact on the efficiency of the FE4 route in April are FMS fleet failure, equipment failure and difficult operations. The terminal should subsequently address these three types of problems to improve the terminal's service level and customer satisfaction on this route.

[0070] It should be pointed out that for ordinary technicians in this technical field, several improvements and modifications can be made without departing from the principles of the present invention, and these improvements and modifications should also be considered as the scope of protection of the present invention.

Claims

1. An automated container terminal multi-ship operation analysis system, characterized by: Integrate multi-dimensional data from TOS, ABB, UI monitoring downtime, local dispatching, and TOS peripheral systems to develop a multi-vessel operation analysis system, which includes a data acquisition module, a multi-vessel operation analysis database, and a multi-vessel operation analysis module. The data acquisition module is used to collect real-time data on the berthing time, route data, shipping company data, ship name and voyage data, ship time efficiency data, quay crane efficiency data, auxiliary operation data, and operation downtime data of ships operating at the terminal; The multi-vessel operation analysis database is used to classify and store various data collected by the data acquisition module for use by the multi-vessel operation analysis module; The multi-ship operation analysis module is used to call the multi-ship operation analysis database, automatically capture all ship entries, route entries, container volume overviews, and operation overviews of terminal operations within two fixed time periods in the time dimension, analyze and compare the throughput, shipping production, and route efficiency within the two time periods, and form a year-on-year comparison. It also automatically filters operating ships within the time span in the ship dimension, compares and analyzes the ship's ship-time efficiency, quay crane efficiency, auxiliary operation time, operation downtime time and type, and provides targeted optimization directions for the overall terminal operation.

2. The automated container terminal multi-ship operation analysis system according to claim 1, characterized in that: The data stored in the multi-ship operation analysis database also includes the start and completion time of terminal operation ships, the number of opened lines, the total throughput, the import container volume, the export container volume, the unloaded container volume, the loaded container volume, the operation container volume, the number of operation hooks, the box hook coefficient, the berth time, the operation time, the comprehensive port time, peak efficiency, the number of refrigerated containers, the number of hazardous goods, and the number of oversized containers.

3. The automated container terminal multi-ship operation analysis system according to claim 1, characterized in that: The data acquisition module regularly crawls the berthing and unberthing time, start and completion time, navigation information, shipping company information, ship name and voyage information, throughput, import and export container volume, refrigerated container volume, hazardous goods volume, and over-limit volume from the bureau dispatching system; and collects opening and closing data and taxi movement data from the quay crane ABB during ship operation to calculate the ship's unloading container volume, loading container volume, operating container volume and operating hook number.

4. The automated container terminal multi-ship operation analysis system according to claim 1, characterized in that: The operation stop time data includes the stop time duration and the reason for the stop time of the quay crane. The data acquisition module combines the opening and closing data of ABB to capture the time interval when the single hook operation duration or empty hook time of the quay crane during the production operation of the ship is greater than 3 minutes, and triggers the stop time entry module of the UI monitoring interface. The scheduling enters the stop time reason according to the basic stop time type. The single hook operation duration is the difference between the locking time of the quay crane's constitutive operation and the unlocking time of the quay crane's constitutive operation, and the empty hook time is the difference between the locking time of the next hook operation and the unlocking time of this operation.

5. The automated container terminal multi-ship operation analysis system according to claim 1, characterized in that: The quay crane efficiency and ship efficiency include the container efficiency when berthing, the hook efficiency when berthing, the container efficiency when operating the ship, the hook efficiency when operating the ship, the number of ship operating hooks, the average single-bridge efficiency, and the M-line efficiency; the auxiliary operation time data is divided into start-up auxiliary time and unberthing auxiliary time, the start-up auxiliary time is the difference between the start time and the berthing time, and the unberthing auxiliary time is the difference between the unberthing time and the completion time. The auxiliary operation time includes the time when the loading and unloading workers bring the cables, joint inspections, loading and unloading the ship, and the remote-controlled driver runs the quay crane.

6. The automated container terminal multi-ship operation analysis system according to claim 1, characterized in that: The KPI indicators of throughput include the total number of operating ships, import operation volume, and export operation volume within a fixed time period; the KPI indicators of shipping production include the average single-bridge efficiency, M-line efficiency, average berthing time, average operation time, average berthing efficiency, and average operating ship efficiency within a fixed time period; the route efficiency is the KPI value of different routes within a fixed time period, including natural container volume, throughput (TEU), number of ships, single-bridge efficiency, berthing efficiency, operation efficiency, and box-hook ratio.

7. A method for analyzing multi-ship operations at an automated terminal, characterized by: The automated container terminal multi-ship operation analysis system according to any one of claims 1 to 6 comprises the following steps: S1. Compare KPI data from two time periods from the time dimension: S1.1 Identify two comparable time periods and enter them into the system; S1.2 Set the number of operating lines in the system. The system will automatically screen and compare the KPI data of ships that have opened more operating lines than the set number during the set period, and analyze the KPI growth rate of different types of ships operating at the terminal during different periods. S2. Statistical analysis of multiple specific ship operation data: S2.1 uses berthing and unberthing times as a screening condition to filter out specific ships within a fixed time period. The system automatically collects and analyzes the specific efficiency of each ship and compares the trend of ship operating efficiency based on time. The S2.2 system automatically captures and compiles detailed statistics on each vessel's downtime and displays them in charts, analyzing the main factors affecting multi-vessel operation efficiency. S3. Statistical analysis of specific vessel operation data on a fixed route or multiple routes over a period of time: Enter the start time and select the route into the system. The system automatically compares and calculates the specific efficiency of each filtered vessel and outputs the main reasons for downtime that affect vessel efficiency, providing decision-making guidance for terminal managers to optimize route operation efficiency.

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