Automatic wharf single-ship operation analysis system and method

Abstract

The invention relates to the field of automatic container wharf operation optimization, in particular to an automatic container wharf single-ship operation analysis system and method, and the system development comprises the following modules: developing a quay crane unlocking and locking monitoring module in an ABB system; a TOS-ABB-FMS collaborative interaction module is developed on a U I monitoring interface; the input module is used when the development of the U I monitoring interface is stopped; a single-ship operation analysis system is developed based on a TOS data management platform, ship whole-process operation is automatically analyzed, and decision support is provided for wharf production efficiency optimization. Through integrated development of a single-ship operation analysis system, transparency of wharf ship production operation is enhanced, multi-dimensional optimization decision support is provided for wharf production, wharf ship operation efficiency can be effectively improved, and a new solution is provided for intelligent management of an automatic container wharf.

Description

Technical Field

[0001] This invention belongs to the field of automated container terminal operation optimization technology, specifically relating to an automated terminal single-ship operation analysis system and method. Background Technology

[0002] As a core component of modern port operations, the operational efficiency of automated container terminals directly determines the core competitiveness of a port, while precise analysis of various issues during ship operations is key to continuously improving the terminal's production and service capabilities.

[0003] Currently, terminals generally adopt a post-event analysis approach to address malfunctions and problems encountered during ship operations. This approach has significant limitations: on the one hand, the effectiveness of problem analysis is insufficient, making it difficult to respond in real time to dynamic changes during operations; on the other hand, manual statistical analysis is highly subjective, easily leading to a lack of data accuracy. This results in subsequent terminal optimization measures lacking clear objectives and even becoming delayed, severely restricting the improvement of terminal production capacity.

[0004] With the development of automated terminals, core systems such as TOS (Terminal Operating System) and ECS (Equipment Control System) are gradually being applied, leading to more comprehensive and accurate data collection for ship production operations. However, the utilization rate of this effective data at terminals is currently low, resulting in insufficient transparency in the analysis of the entire ship operation process. For example, key data such as operational efficiency, berthing and departure times, planned and unplanned stop times and durations, basic ship information, hourly single-bridge operation statistics, and single-ship operation records are still collected in a decentralized manner, failing to form a systematic integrated analysis.

[0005] Furthermore, existing technologies lack specialized analysis methods for single-ship operations, making it impossible to accurately break down and locate problems throughout the entire single-ship operation process. This results in low efficiency in terminal production optimization decisions and makes it difficult to meet the needs of intelligent management of automated container terminals.

[0006] Therefore, there is an urgent need for a system and method that can integrate multi-dimensional data and realize real-time analysis of the entire process of single-ship operations, in order to solve the current problems of data dispersion, analysis lag, and inefficient decision-making, and promote further improvement in the efficiency of automated container terminal operations. Summary of the Invention

[0007] The purpose of this invention is to provide an automated terminal single-ship operation analysis system and method to solve the problems existing in the prior art.

[0008] To achieve the above objectives, the present invention provides the following technical solution: an automated terminal single-vessel operation analysis system, which integrates TOS, ABB, and UI monitoring downtime data to construct a multi-dimensional database, and integrates and develops a single-vessel operation analysis system. This system realizes single-vessel operation analysis through the following steps:

[0009] Step 1: Develop a motion capture module for the quay crane in ABB to monitor the opening and closing time of the quay crane spreader, the type of workpiece, the workpiece number, and the movement time of the quay crane in real time, and connect the data to a multidimensional database;

[0010] Step 2: Develop a quay crane production downtime entry module in the UI monitoring interface. When the quay crane spreader production status continues for more than 3 minutes, the entry function is triggered. The dispatcher enters the downtime reason and then connects it to the multidimensional database.

[0011] Step 3: Combine the TOS and FMS systems to extract key time nodes and location data such as box collection and delivery for single-vehicle operations, and integrate them into a multi-dimensional database;

[0012] Step 4: Based on TOS and peripheral systems, acquire basic information about the vessel, berthing and departure information, and container volume information, and store them in a multidimensional database;

[0013] Step 5: The single-vessel operation analysis system calls upon a multi-dimensional database to conduct a full-process analysis of vessel information, container volume information, operation efficiency, and downtime data, providing support for optimization decisions.

[0014] Preferably, the data stored in the multidimensional database includes quay crane operation data, single-vehicle operation data, basic ship information, berthing and departure records, container volume statistics, and stopover details.

[0015] Preferably, the quay crane motion capture module can analyze and obtain the quay crane operation time, waiting time, and trolley movement time, wherein the operation time is the difference between the locking time and the unlocking time, and the waiting time is related to the time it takes for a single vehicle to arrive under the quay crane.

[0016] Preferably, the quay crane production downtime is divided into planned downtime and unplanned downtime. Planned downtime includes operations such as shell changing and pod cover installation, while unplanned downtime includes operations such as equipment failure and difficult operations.

[0017] Preferably, the key time nodes for single-vehicle operation include the time of issuing the container receiving instruction, the time of arriving at the QCTP, the time of alignment with the quay crane, the time of issuing the container delivery instruction, the time of arriving at the locking island, the time of completing the locking and unlocking, the time of arriving at the TP, the time of alignment with the yard crane, and the time of completing the container delivery.

[0018] Preferably, the vessel information includes vessel length, vessel width, deadweight (TEU), estimated and actual berthing and departure times, and estimated and actual arrival and departure times; the container volume information includes import and export container volume, and planned and actual start and completion times.

[0019] Preferably, the operational efficiency analysis indicators include berthing efficiency, hook efficiency, working vessel berthing efficiency, working vessel hook efficiency, number of working hooks on the vessel, single bridge efficiency, and M-line efficiency.

[0020] Preferably, the single-ship operation analysis system can statistically analyze the number of imported containers handled by the quay crane, the waiting time for hooking, the production downtime, and the percentage of downtime categories by hour.

[0021] This invention also discloses an automated terminal single-vessel operation analysis method. Using the aforementioned system, the method includes the following steps:

[0022] S1: Set the standard value for a single bridge (expected hourly workload of the quay crane) and the standard duration of downtime (total tolerable downtime per hour);

[0023] S2: Count the number of containers operated and the duration of downtime for each quay crane in hours;

[0024] S3: Use Boolean logic to filter out inefficient periods where the number of work boxes is less than the standard value for a single bridge and the downtime exceeds the standard duration;

[0025] S4: Analyzes downtime distribution during periods of low efficiency and automatically generates efficiency reports.

[0026] Preferably, the efficiency report includes the duration and frequency statistics of various types of downtime during periods of low efficiency, with the proportion of downtime due to equipment failure and the proportion of downtime due to difficult operations being the key analysis content.

[0027] Compared with existing methods, the beneficial effects of the present invention are as follows:

[0028] This invention integrates multi-dimensional data from TOS, ABB, and UI monitoring to construct a single-vessel operation analysis system. It enables real-time capture of quay crane actions, accurate recording of downtime causes, and integrated analysis of the entire process data. This solves the problems of poor timeliness and scattered data in traditional post-event analysis, enhances the transparency and data utilization of the entire vessel operation process, eliminates the subjectivity and bias of manual statistics, and provides objective and comprehensive information support for terminal production.

[0029] Meanwhile, by setting standard values ​​to filter inefficient periods and analyzing downtime distribution, the system can accurately identify key factors affecting operational efficiency, helping terminal managers to optimize operational processes, reduce unplanned downtime, and precisely plan downtime, continuously improving the efficiency of single-ship operations, promoting intelligent management and efficient operation of automated container terminals, and providing scientific decision support and new solutions for optimizing terminal production efficiency. Attached Figure Description

[0030] Figure 1 This is a flowchart illustrating the technical route of the present invention;

[0031] Figure 2 This is a sample diagram of the ship information card display style for the analysis system;

[0032] Figure 3This is a sample diagram showing the display style of the ship operation container quantity information card in the analysis system;

[0033] Figure 4 This is a sample diagram showing the display style of the ship operation efficiency card in the analysis system.

[0034] Figure 5 For the UI interface, input the data when the quay crane is stopped;

[0035] Figure 6 This is a sample diagram showing the display style of the ship operation comparison analysis card in the analysis system;

[0036] Figure 7 The system automatically filters out style images for periods of low efficiency;

[0037] Figure 8 This is a style diagram for analyzing downtime during periods of system inefficiency. Detailed Implementation

[0038] It should be noted that, unless otherwise specified, the embodiments and features described in the present invention can be combined with each other.

[0039] In the description of this invention, it should be understood that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicating orientations or positional relationships based on the orientations or positional relationships shown in the accompanying drawings, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation on this invention. Furthermore, the terms "first," "second," etc., are used for descriptive purposes only and should not be construed as indicating or implying relative importance or implicitly specifying the number of indicated technical features. Thus, features defined with "first," "second," etc., may explicitly or implicitly include one or more of that feature. In the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0040] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," "linking," "fixed connection," and "fixed connection" should be interpreted broadly. For example, they can refer to a fixed connection, a detachable connection, or an integral connection; they can refer to a mechanical connection or an electrical connection; they can refer to a direct connection or an indirect connection through an intermediate medium; and they can refer to the internal connection of two components. Those skilled in the art will understand the specific meaning of the above terms in this invention based on the specific circumstances.

[0041] The specific embodiments of the present invention will now be described in detail with reference to the accompanying drawings and preferred embodiments.

[0042] like Figure 1 As shown, an automated single-vessel operation analysis system integrates multiple data sources, including TOS, ABB, and UI monitoring, maintains a multi-dimensional database, and the integrated development of the single-vessel operation analysis system includes the following steps:

[0043] Step 1: Develop a motion capture module for quay cranes in ABB to monitor in real time the opening and closing time of spreader, quay crane work box type, work box number, start and end time of vehicle relocation, etc. during the quay crane loading, unloading, and vehicle relocation processes. Calculate the single hook operation time, empty hook time, quay crane waiting time, quay crane movement time, and production overtime time, and store the data in a multidimensional database.

[0044] Step 2: Develop a quay crane production downtime entry module in the production UI monitoring system to record the specific reasons for quay crane downtime in real time, and to statistically analyze the production downtime types and durations of each quay crane by hour, storing the data in a multidimensional database.

[0045] Step 3: Based on the TOS and FMS systems, intercept the data streams of single-vehicle and container operations, capture the key time nodes and locations of single-vehicle and container operations, and store the operation time node data of each container into a multi-dimensional database.

[0046] Step 4: Based on TOS and its peripheral systems, capture information such as ship information, berthing and departure information, and container volume information for each vessel and store them in a multidimensional database.

[0047] Step 5: The single-vessel operation analysis system calls upon a multi-dimensional database to conduct a centralized, end-to-end analysis of the vessel information, container volume information, operation efficiency, and downtime comparisons for each operating vessel, providing information for terminal operators to make optimization decisions.

[0048] Furthermore, the single-hook operation time t mentioned in step one... z =t k -t b , where t b t is the locking time for the constitutive work of the quay crane. k The unlocking time for the quay crane constitutive work; the empty hook duration t p =t bn -t k , where t bn Locking time for the next hooking operation; waiting time for the quay crane. Where t a The arrival time of a single vehicle operating under the quay crane; production overtime duration. When the single hook operation time and empty hook time exceed 3 minutes, the excess time is recorded as the production overtime time, indicating that the quay crane is operating slowly due to some reason during the production operation, resulting in a decrease in the efficiency of the quay crane.

[0049] Furthermore, the quay crane production downtime entry module described in step two is triggered when a non-zero production timeout duration exists in the multidimensional database. The module automatically displays a downtime entry interface on the UI, as shown in the attached image. Figure 5 As shown, the start time of the stop is the corresponding opening and closing time captured by the quay crane motion capture module, and the dock dispatcher enters the corresponding stop type in real time according to the on-site operation conditions.

[0050] Furthermore, the key time nodes for container operations mentioned in step three include: the time and location of the container receiving instruction, the time and location of the vehicle arriving at the QCTP, the time and location of the vehicle interacting with the quay crane, the time and location of the vehicle completing the receiving, the time and location of the vehicle delivering the container, the time and location of the vehicle arriving at the locking island, the time and location of the vehicle completing the padlock removal, the time and location of the vehicle arriving at the yard TP, the time and location of the vehicle interacting with the yard crane, and the time and location of the vehicle completing the delivery task.

[0051] Furthermore, the ship information analysis described in step five involves the analysis system automatically calling a multidimensional database to obtain and display the ship's length, beam, deadweight (TEU), estimated berthing and departure times, actual berthing and departure times, estimated arrival and departure times, and actual arrival and departure times.

[0052] Furthermore, the container volume information analysis mentioned in step five involves the analysis system automatically calling a multidimensional database to statistically analyze and display the import and export container volume information, planned start time, planned completion time, actual start time, and actual completion time for this voyage.

[0053] Furthermore, the operational efficiency analysis described in step five involves the analysis system automatically calling a multidimensional database to calculate and display the ship's berthing efficiency, berthing hook efficiency, operational ship berthing efficiency, operational ship hook efficiency, number of operational hooks, average single-bridge efficiency, and M-line efficiency.

[0054] Furthermore, the downtime comparison analysis described in step five mainly includes overall ship operation downtime analysis and ship hourly downtime comparison analysis. Overall ship operation downtime analysis involves the analysis system calling a multi-dimensional database to statistically calculate and graphically display the total number and duration of all quay crane production downtime generated during ship operations. Ship hourly downtime comparison analysis involves the analysis system breaking down the number and duration of quay crane production downtime within each hourly segment of ship operations.

[0055] Furthermore, based on the single-vessel operation analysis system, in order to specifically improve the efficiency of single-vessel operations, this invention proposes a single-vessel operation analysis method, including the following steps:

[0056] S1. Set the standard value e for single-bridge operation of vessels. sStandard duration of stop time t cs The standard value for a single quay crane refers to the expected hourly workload of the quay cranes during ship operations, while the standard duration of downtime refers to the total downtime that the terminal can tolerate per hour during ship operations.

[0057] S2. Starting from the start of ship operations, calculate the number of containers handled and the duration of downtime for each quay crane during the ship operations, in hours.

[0058] S3. Compare the hourly single-bridge workload with the single-bridge standard value, and compare the hourly total quay crane downtime with the standard downtime duration. Set Boolean logic to filter out periods during the overall ship operation that are less than the single-bridge standard value but greater than the standard downtime duration, and define them as inefficient periods.

[0059] S4. For periods of low efficiency, compare and analyze the ship downtime within that hour and automatically generate an efficiency report to help decision-makers address key issues in production operations.

[0060] Specific implementation method one: Automatically generate ship operation card display.

[0061] Based on the vessel's operational progress, the single-vessel operation analysis system displays vessel operation cards in real time. These cards primarily include four aspects: vessel information, container volume information, operational efficiency, and downtime comparison.

[0062] Vessel information refers to the vessel's length, beam, voyage number, deadweight (TEU), estimated berthing and departure times, actual berthing and departure times, estimated arrival and departure times, and actual arrival and departure times. This information is collected periodically from the TOS data management platform and stored in a multidimensional database. It is then displayed on the single-vessel operation analysis system platform, as shown in the attached image. Figure 2 As shown.

[0063] Container volume information refers to the import and export container volume information for this voyage, as well as the planned start time, planned completion time, actual start time, and actual completion time of vessel loading and unloading. This data is captured periodically by the TOS data management platform and stored in a multidimensional database, then displayed on the single-vessel operation analysis system platform. The display format is shown in the attached image. Figure 3 As shown.

[0064] Operational efficiency refers to the following metrics: berthing efficiency, hook efficiency, operating efficiency, number of hooks operated by the vessel, average single-bridge efficiency, and M-line efficiency.

[0065]

[0066] By periodically calculating container data in a multidimensional database, the operational container volume of each quay crane and vessel is determined. Combined with actual berthing and departure data, and actual start and completion data from the multidimensional database, various efficiency indicators are periodically calculated and displayed in the single-vessel analysis system. The display format is shown in the attached figure. Figure 4 As shown.

[0067] Downtime comparison refers to the classification and statistical analysis of all downtime during ship operations within a single-ship analysis system, providing a clear visual representation of the factors affecting a single ship's operational efficiency. When a quay crane operation generates downtime during ship operations—specifically, when the single-hook operation time and empty hook time of the quay crane exceed 3 minutes—a downtime is triggered. The quay crane downtime entry module in the UI monitoring interface automatically pops up, as shown in the attached image. Figure 5 As shown, after confirming the actual working conditions against the data, the dispatcher records the stop times according to their type and reason. Stop times are categorized into planned and unplanned stop times, with a total of 18 planned stop times, 88 unplanned stop times, and 3 non-operational stop times. After the quay crane stop times are entered, they are stored in a stop time table in a multidimensional database. Once the vessel is fully completed, the stop time duration and frequency for each type of stop time for each quay crane are statistically analyzed and displayed in a pie chart. T i To display the total duration of the i-th type of stop during the entire ship operation in the stop time module of the single-ship analysis system, the display format is as shown in the attached figure. Figure 6 As shown.

[0068] In addition, from another perspective, vessels can pre-enter planned downtime for operations such as shell changing, hatch cover installation, and oversized operations before commencing work. After the vessel completes its operations, the estimated downtime is adjusted based on the actual downtime, thereby improving the reliability of the overall operation plan for the next voyage.

[0069] Specific Implementation Method 2: Using the cyclical analysis method for low-efficiency periods of automated terminal ship operations proposed in this invention, the efficiency of terminal ship production operations can be effectively improved.

[0070] Based on an automated terminal operation analysis system, this invention employs a cyclical analysis method for inefficient periods to analyze the causes of downtime during vessel operations, identify and resolve the main issues affecting vessel operational efficiency, and continuously eliminate potential influencing factors to improve the efficiency of individual vessel operations. The method is as follows:

[0071] For vessels that have completed their operations, set a standard value e for a single bridge operation. s =Single-bridge efficiency of ships, standard downtime T cs=Number of quay cranes in operation × 3. In post-event analysis, the standard value for a single quay crane is set as the efficiency of a single quay crane on the vessel. An average efficiency less than this value over an hour is considered to have lowered the overall efficiency of the vessel, and is one of the necessary conditions for a period of low efficiency. In addition, another necessary condition for a period of low efficiency is that the production overtime within the hour exceeds the standard downtime, i.e., T. ci ≤T cs , T ci t represents the cumulative production overtime duration of ship operations within the i-th hour segment. cij This represents the cumulative production overtime of the j-th quay crane within the i-th hour segment. The present invention sets a standard downtime duration T. cs =Number of quay cranes in operation × 3, indicating that the terminal can tolerate a cumulative production overtime of 3 minutes for a single quay crane within an hour. Taking the union of the two necessary conditions yields the inefficient periods in overall vessel operations. For these inefficient periods, the analysis system calls the downtime table in the multidimensional database to extract and display the percentage of downtime during these inefficient periods.

[0072] This example uses a cyclic analysis method to analyze the "Hyundai Dublin" vessel. The standard value for single-axle efficiency is taken as 24.61 TEUs / hour, rounded up to 25 TEUs / hour; the standard downtime is T. cs =30 minutes. After taking the union, the system automatically filters out inefficient time periods and highlights them in red, as shown in the attached image. Figure 7 As shown in the attached figure, terminal managers can analyze the percentage of downtime within a given hourly period. Figure 8 As shown, the failure rate of single-vehicle equipment was 53.77% during this hourly period. Therefore, the dock should improve the stability of equipment use and the maintenance efforts in subsequent operations.

[0073] Using the above method, the main types of downtime during low-efficiency hours of the same vessel operation are analyzed cyclically, and the factors affecting low efficiency are continuously eliminated in subsequent vessel operations to ensure a steady improvement in vessel efficiency.

[0074] It should be noted that those skilled in the art can make various improvements and modifications without departing from the principles of this invention, and these improvements and modifications should also be considered within the scope of protection of this invention.

Claims

1. An automated terminal single-vessel operation analysis system, characterized in that: A multi-dimensional database is constructed by integrating downtime data from TOS, ABB, and UI monitoring. A single-vessel operation analysis system is then developed, which performs single-vessel operation analysis through the following steps: Step 1: Develop a motion capture module for the quay crane in ABB to monitor the opening and closing time of the quay crane spreader, the type of workpiece, the workpiece number, and the movement time of the quay crane in real time, and connect the data to a multidimensional database; Step 2: Develop a quay crane production downtime entry module in the UI monitoring interface. When the quay crane spreader production status continues for more than 3 minutes, the entry function is triggered. The dispatcher enters the downtime reason and then connects it to the multidimensional database. Step 3: Combine the TOS and FMS systems to extract key time nodes and location data such as box collection and delivery for single-vehicle operations, and integrate them into a multi-dimensional database; Step 4: Based on TOS and peripheral systems, acquire basic information about the vessel, berthing and departure information, and container volume information, and store them in a multidimensional database; Step 5: The single-vessel operation analysis system calls upon a multi-dimensional database to conduct a full-process analysis of vessel information, container volume information, operation efficiency, and downtime data, providing support for optimization decisions.

2. The system according to claim 1, characterized in that: The multidimensional database stores data including quay crane operation data, single-vehicle operation data, basic ship information, berthing and departure records, container volume statistics, and stopover details.

3. The system according to claim 1, characterized in that: The quay crane motion capture module can analyze and obtain the quay crane operation time, waiting time, and trolley movement time. The operation time is the difference between the locking time and the unlocking time, and the waiting time is related to the time it takes for a single vehicle to arrive under the quay crane.

4. The system according to claim 1, characterized in that: The downtime of the quay crane is divided into planned downtime and unplanned downtime. Planned downtime includes operations such as shell changing and hatch cover installation, while unplanned downtime includes operations such as equipment failure and difficult operations.

5. The system according to claim 1, characterized in that: The key time nodes for single-vehicle operation include the time of issuing the container receiving instruction, the time of arriving at QCTP, the time of alignment with the quay crane, the time of issuing the container delivery instruction, the time of arriving at the locking island, the time of completing the locking and unlocking, the time of arriving at TP, the time of alignment with the yard crane, and the time of completing the container delivery.

6. The system according to claim 1, characterized in that: The vessel information includes the vessel length, beam, deadweight (TEU), estimated and actual berthing and departure times, and estimated and actual arrival and departure times; the container volume information includes import and export container volume, and planned and actual start and completion times.

7. The system according to claim 1, characterized in that: The operational efficiency analysis indicators include berthing efficiency, berthing hook efficiency, working vessel berthing efficiency, working vessel hook efficiency, number of working hooks on a vessel, single bridge efficiency, and M-line efficiency.

8. The system according to claim 1, characterized in that: The single-ship operation analysis system can statistically analyze the number of imported containers handled by the quay crane, the waiting time for hooking, the production downtime, and the percentage of downtime by category, by hour.

9. A method for analyzing single-vessel operations at an automated terminal, characterized in that: The method of using the system of any one of claims 1-8 includes the following steps: S1: Set the standard value for a single bridge and the standard duration of the stop time; S2: Count the number of containers operated and the duration of downtime for each quay crane in hours; S3: Use Boolean logic to filter out inefficient periods where the number of work boxes is less than the standard value for a single bridge and the downtime exceeds the standard duration; S4: Analyzes downtime distribution during periods of low efficiency and automatically generates efficiency reports.

10. The method according to claim 9, characterized in that: The efficiency report includes statistics on the duration and frequency of various types of downtime during periods of low efficiency, with equipment failure downtime and difficult operation downtime being the key analysis content.

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