Design method and system of ship part tray data

Abstract

The invention provides a ship part tray data design method and system. The method comprises the following steps: S1, collecting part data; s2, preprocessing the part data; s3, key elements of the part data are extracted; and S4, after parts are configured based on fusion of the key elements, the parts are collected, and tray data are produced. According to the ship part tray data design method and system provided by the invention, the parts are collected into the daily tray, the parts are distributed according to the production plan and the process sequence, and the tray supply mode is determined, so that the production efficiency can be effectively improved, and the material waiting time is shortened. By providing information such as the size, weight, gravity center and grabbing point of the part, the robot can be helped to efficiently grab and assemble the part, the requirement of an assembly robot production line is met, and the production automation degree is improved. Through the fusion analysis of the multi-dimensional information of the part, the demand value of the part can be evaluated more accurately, the stock management of the part is optimized, and the production cost is reduced.

Description

Technical Field

[0001] This application relates to the field of shipbuilding technology, and more specifically, to a design method and system for ship parts pallet data. Background Technology

[0002] In the shipbuilding industry, nesting is a crucial process connecting design and production. Its core involves optimizing the layout of the designed parts on steel plates, simulating the actual components. The key value of this process lies in two aspects: First, scientific nesting maximizes the utilization rate of steel plates, reduces waste, and significantly lowers material costs in shipbuilding. Second, by grouping and nesting the parts, the arrangement of different parts on the same steel plate is clarified, providing clear guidance for the subsequent sorting and transfer of the actual parts after cutting, ensuring the orderly progress of the production process.

[0003] However, the traditional method of assembling parts in the current shipbuilding industry relies solely on limited two-dimensional information such as plate thickness, material, ship number, and section number. This assembly logic is no longer suitable for the technological requirements of lean manufacturing in modern shipbuilding, and specifically presents the following key problems:

[0004] The traditional method of supplying parts in a daily palletized supply model is ineffective in supporting lean manufacturing. As shipbuilding becomes increasingly lean, this model has become the mainstream production organization method. It requires parts to be strictly collected, nested, cut, and processed according to the production plan's time nodes and process sequence, and then accurately delivered to the corresponding workstations to achieve the production goal of "on-demand supply and zero inventory turnover." However, traditional parts collection methods do not establish a correlation between parts and the production plan, failing to provide crucial information related to production rhythm for nesting decisions. This leads to a disconnect between the cutting and delivery of parts after nesting and the production plan, easily resulting in premature stockpiling or supply delays, severely hindering the efficient implementation of the daily palletized supply model.

[0005] The inability to meet the technical adaptation requirements of small assembly robot production lines: To improve the automation level of shipbuilding, small assembly robot production lines have been widely used in parts assembly. These lines have strict adaptation requirements for the geometric features, physical properties, and structural characteristics of the parts. Only parts combinations that meet the robot's grasping parameters and assembly space requirements can ensure the stability of robot grasping, the accuracy of assembly, and the continuous operating efficiency of the production line. However, traditional nesting methods for parts collection do not incorporate key attribute information such as the geometric dimensions, weight, and structural characteristics of the parts. This can lead to the collected parts combinations exceeding the robot's operational capabilities, resulting in problems such as robot production line downtime for adjustments and assembly accuracy deviations, thus failing to fully realize the production efficiency of the automated production line.

[0006] In summary, the traditional method of nesting parts collection, due to its single collection dimension and insufficient information coverage, has become a technical bottleneck restricting the advancement of lean production and the release of the efficiency of automated production lines in the shipbuilding industry. There is an urgent need for an improved technical solution for nesting parts collection that can overcome the above limitations in order to meet the production needs of modern shipbuilding for high efficiency, precision and automation. Summary of the Invention

[0007] The purpose of this application is to provide a design method and system for ship parts pallet data, which can provide theoretical support for the nesting, cutting and distribution of ship hull parts, and meet the production needs of modern shipbuilding for high efficiency, precision and automation.

[0008] Firstly, a method for designing pallet data for ship parts is provided, including the following steps:

[0009] S1. Collect part data;

[0010] S2. Preprocess the part data;

[0011] S3, Key elements for extracting part data;

[0012] S4. After configuring the parts based on the key elements, collect the parts and generate pallet data.

[0013] In one feasible approach, in step S1, the data source for the part data includes at least a 3D model design system, a design management system, and a production management system to obtain multi-dimensional part information.

[0014] In one feasible approach, the part data includes at least basic information, process information, production information, production line information, and material information.

[0015] In one feasible approach, the basic information includes at least the ship number, section number, drawing number, part number, name, quantity, plate thickness, material, and geometric dimensions; the process information includes at least the assembly stage, assembly process, and processing equipment; the production information includes at least the production plan, pallet number, and delivery time; the production line information includes at least the production line name, production line capacity, production line processing type, and production line operating status; and the material information includes at least steel inventory information and steel arrival status information.

[0016] In one feasible approach, the preprocessing includes at least cleaning, deduplication, and format conversion of the acquired part data.

[0017] In one feasible approach, in step S3, based on preset rules or machine learning algorithms, information reflecting part nesting is extracted from the preprocessed part data. Key elements.

[0018] In one feasible approach, the key elements are determined based on part priority, part processing complexity, part urgency, and robot construction characteristics.

[0019] The priority of a part is assessed based on its position in the hull structure and the stress conditions it experiences; the processing type of a part is determined based on its geometric characteristics and processing capabilities, thereby determining the processing complexity; the part delivery plan is determined based on the part's production plan and process sequence, thereby determining the urgency of the part's demand; and the type of robot construction production line is determined based on the part's size, weight, center of gravity, and gripping points, thereby determining the robot's construction characteristics.

[0020] In one feasible approach, step S4, when fusing parts, includes the following: setting pallet configuration requirements for part fusing based on the needs of the production pallet.

[0021] In one feasible approach, in step S4, parts are grouped into different pallets based on part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and part fusion configuration requirements, and pallet data required for the robot production line is generated.

[0022] According to a second aspect of this application, a design system for ship parts pallet data is also provided, for performing the design method for ship parts pallet data provided in the first aspect, comprising:

[0023] The data acquisition module is used to collect part data from multiple data sources;

[0024] The data preprocessing module is used to preprocess the multi-dimensional information of the collected parts.

[0025] The key element extraction module is used to extract key elements that reflect the nesting of parts from the preprocessed part data.

[0026] The parts fusion module is used to fuse the key elements of the extracted parts nesting and configure the parts collection method;

[0027] The parts aggregation module aggregates parts into different pallets based on part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and part fusion configuration requirements, and generates pallet data required by the robot production line.

[0028] Compared with the prior art, the beneficial effects of this application are as follows:

[0029] This application provides a method and system for refined classification of ship parts based on multi-dimensional information fusion for lean manufacturing. By grouping parts into daily pallets and distributing them according to production plans and process sequences, and determining the pallet supply model, production efficiency can be effectively improved and material waiting time reduced. By providing information such as part size, weight, center of gravity, and gripping points, robots can efficiently grasp and assemble parts, meeting the needs of assembly robot production lines and improving the degree of production automation. Through the fusion analysis of multi-dimensional information on parts, the demand value of parts can be more accurately assessed, parts inventory management can be optimized, and production costs can be reduced. Attached Figure Description

[0030] Figure 1 This is a flowchart of the design method for ship parts pallet data according to an embodiment of the present invention.

[0031] Figure 2 This is a schematic diagram of the design system for ship parts pallet data according to an embodiment of the present invention. Detailed Implementation

[0032] The specific embodiments of the present invention will be further described in detail below with reference to the accompanying drawings. These embodiments are for illustrative purposes only and are not intended to limit the scope of the invention.

[0033] In the description of this invention, it should be noted that the terms "center," "longitudinal," "lateral," "upper," "lower," "front," "rear," "left," "right," "vertical," "horizontal," "top," "bottom," "inner," and "outer," etc., indicate the orientation or positional relationship based on the orientation or positional relationship shown in the accompanying drawings. They are used only for the convenience of describing the invention and for 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. Therefore, they should not be construed as limitations on the invention. Furthermore, the terms "first" and "second" are used for descriptive purposes only and should not be construed as indicating or implying relative importance.

[0034] In the description of this invention, it should be noted that, unless otherwise explicitly specified and limited, the terms "installation," "connection," and "linking" 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 can understand the specific meaning of the above terms in this invention according to the specific circumstances.

[0035] Furthermore, in the description of this invention, unless otherwise stated, "a plurality of" means two or more.

[0036] According to the first aspect of this application, see Figure 1 First, a design method for ship parts pallet data is provided, including the following steps:

[0037] S1. Collect part data;

[0038] S2. Preprocess the part data.

[0039] S3, Key elements for extracting part data;

[0040] S4. After configuring the parts based on the key elements, collect the parts and generate pallet data.

[0041] In one feasible approach, in step S1, the data source for the part data includes at least a 3D model design system, a design management system, and a production management system to obtain multi-dimensional part information.

[0042] In one feasible approach, the part data includes at least basic information, process information, production information, production line information, and material information.

[0043] Specifically, the basic information includes at least the ship number, section number, drawing number, part number, name, quantity, plate thickness, material, and geometric dimensions; the process information includes at least the assembly stage, assembly process, and processing equipment; the production information includes at least the production plan, pallet number, and delivery time; the production line information includes at least the production line name, production line capacity, production line processing type, and production line operating status; and the material information includes at least steel inventory information and steel arrival status information.

[0044] In one feasible approach, in step S2, the preprocessing includes at least cleaning, deduplication, and format conversion of the acquired part data to ensure the accuracy and consistency of the part data.

[0045] Specifically, data cleaning includes at least the following: processing erroneous, missing, and abnormal data in the multi-dimensional information of the collected parts. For obviously erroneous data, such as material parameters not matching design standards or dimensional data exceeding reasonable ranges, corrections are made in accordance with ship design industry standards and the application scenarios of the parts. For missing key information, such as necessary dimensional parameters and material certification information, it is improved by linking to the design specification library or supplementing the data collection terminal. For redundant data without practical significance, such as invalid fields in duplicate records or redundant parameters unrelated to ship design, they are filtered and removed to ensure the validity and accuracy of the retained data.

[0046] Deduplication includes at least the following: Due to the diversity of parts information collection channels, it is easy for multi-dimensional information about the same part to be repeatedly collected and stored. For example, multiple duplicate records may be generated for the same part due to different personnel or different entry times. By establishing a unified data deduplication rule, using the unique identifier of the part, such as the part drawing number or exclusive code, as the core benchmark, and combining auxiliary features such as part model specifications and key dimensions, the collected information is compared and analyzed to identify and delete duplicate information records. This avoids confusion in information retrieval during the design process due to data redundancy and reduces the burden of subsequent product structure tree node data management.

[0047] Format conversion includes at least the following: Multi-dimensional information about parts from different data acquisition channels typically uses different data formats, such as text, tables, and proprietary formats generated by specific software. However, modeling software and product structure tree management systems used in ship design have unified requirements for data formats. Based on the format specifications of ship design-related software and systems, part information in different formats is uniformly converted into a standard format, such as conforming to common data exchange formats like XML and JSON, or a proprietary format adapted to the design system requirements. This ensures that multi-dimensional part information can flow and be accessed smoothly across different design stages and systems, guaranteeing data consistency and compatibility.

[0048] Preprocessing operations such as cleaning, deduplication, and format conversion can effectively eliminate various data problems in the multi-dimensional information of parts, ensuring that the data entering the ship design stage has a high degree of accuracy and consistency.

[0049] In one feasible approach, in step S3, based on preset rules or machine learning algorithms, information reflecting part nesting is extracted from the preprocessed part data. Key elements.

[0050] In one feasible approach, the key elements are determined based on part priority, part processing complexity, part urgency, and robot construction characteristics.

[0051] Specifically, the priority of parts is assessed based on factors such as their position within the ship's structure and the stress they experience. The processing type of a part is determined based on its geometric characteristics and machinability, thus defining its processing complexity. The part's delivery plan is determined based on factors such as the production schedule and process sequence, thus determining the urgency of the part's demand. Finally, the type of robotic construction line is determined based on factors such as the part's size, weight, center of gravity, and gripping points, thus defining the robotic construction characteristics.

[0052] In one feasible approach, step S4, when merging parts, includes the following: setting pallet configuration requirements for part merging based on the needs of production pallets, such as daily pallets, production line pallets, basic distribution channels, etc.

[0053] In one feasible approach, in step S4, based on factors such as part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and the configuration requirements for part fusion, parts are grouped into different pallets, and pallet data required for the robot production line is generated.

[0054] According to the second aspect of this application, such as Figure 2 As shown, a design system for ship parts pallet data is also provided, for executing the design method for ship parts pallet data provided in the first aspect, including:

[0055] The data acquisition module is used to collect part data from multiple data sources.

[0056] The data preprocessing module is used to preprocess the multi-dimensional information of the collected parts.

[0057] The key element extraction module is used to extract key elements that reflect the nesting of parts from the preprocessed part data.

[0058] The parts fusion module is used to merge the key elements of the extracted parts nesting and configure the parts aggregation method.

[0059] The parts aggregation module aggregates parts into different pallets based on part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and part fusion configuration requirements, and generates pallet data required by the robot production line.

[0060] In summary, the design method and system for ship parts pallet data provided in this application offer a refined classification method and system for ship parts based on multi-dimensional information fusion for lean manufacturing. By aggregating parts into daily pallets and distributing them according to production plans and process sequences, the pallet supply model can be determined, effectively improving production efficiency and reducing material waiting time. By providing information such as part size, weight, center of gravity, and gripping points, robots can efficiently grasp and assemble parts, meeting the needs of assembly robot production lines and improving the degree of production automation. Through the fusion analysis of multi-dimensional information on parts, the demand value of parts can be more accurately assessed, parts inventory management can be optimized, and production costs can be reduced.

[0061] The above description is only a preferred embodiment of the present invention. It should be noted that for those skilled in the art, several improvements and substitutions can be made without departing from the technical principles of the present invention, and these improvements and substitutions should also be considered within the scope of protection of the present invention.

Claims

1. A method for designing pallet data for ship parts, characterized in that, Includes the following steps: S1. Collect part data; S2. Preprocess the part data; S3, Key elements for extracting part data; S4. After configuring the parts based on the key elements, collect the parts and generate pallet data.

2. The method for designing ship parts pallet data according to claim 1, characterized in that, In step S1, the data source for the part data includes at least a 3D model design system, a design management system, and a production management system to obtain multi-dimensional part information.

3. The method for designing ship parts pallet data according to claim 1, characterized in that, The part data includes at least basic information, process information, production information, production line information, and material information.

4. The method for designing ship parts pallet data according to claim 3, characterized in that, The basic information includes at least the ship number, section number, drawing number, part number, name, quantity, plate thickness, material, and geometric dimensions; the process information includes at least the assembly stage, assembly process, and processing equipment; the production information includes at least the production plan, pallet number, and delivery time; the production line information includes at least the production line name, production line capacity, production line processing type, and production line operating status; and the material information includes at least steel inventory information and steel arrival status information.

5. The method for designing ship parts pallet data according to claim 1, characterized in that, The preprocessing includes at least cleaning, deduplication, and format conversion of the collected part data.

6. The method for designing ship parts pallet data according to claim 1, characterized in that, In step S3, based on preset rules or machine learning algorithms, information reflecting part nesting is extracted from the preprocessed part data. key elements.

7. The method for designing ship parts pallet data according to claim 6, characterized in that, The key elements are determined based on the priority of the parts, the complexity of the parts processing, the urgency of the parts demand, and the characteristics of robot construction. The priority of a part is assessed based on its position in the hull structure and the stress conditions it experiences; the processing type of a part is determined based on its geometric characteristics and processing capabilities, thereby determining the processing complexity; the part delivery plan is determined based on the part's production plan and process sequence, thereby determining the urgency of the part's demand; and the type of robot construction production line is determined based on the part's size, weight, center of gravity, and gripping points, thereby determining the robot's construction characteristics.

8. The method for designing ship parts pallet data according to claim 1, characterized in that, In step S4, when fusing parts, the following is included: setting the pallet configuration requirements for part fusing according to the needs of the production pallet.

9. The method for designing ship parts pallet data according to claim 8, characterized in that, In step S4, based on part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and part fusion configuration requirements, parts are grouped into different pallets, and pallet data required for the robot production line is generated.

10. A design system for ship parts pallet data, characterized in that, A design method for executing the ship parts pallet data according to any one of claims 1 to 9 includes: The data acquisition module is used to collect part data from multiple data sources; The data preprocessing module is used to preprocess the multi-dimensional information of the collected parts. The key element extraction module is used to extract key elements that reflect the nesting of parts from the preprocessed part data. The parts fusion module is used to fuse the key elements of the extracted parts nesting and configure the parts collection method; The parts aggregation module aggregates parts into different pallets based on part priority, processing complexity, delivery urgency, robot construction characteristics, pallet capacity, and part fusion configuration requirements, and generates pallet data required by the robot production line.

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