A method and system for optimizing section cutting of a steel structure factory building based on Tekla

Abstract

The application relates to the technical field of data processing, and discloses a steel structure plant profile blanking optimization method and system based on Tekla. The method comprises the following steps: extracting component parameters based on Tekla, comparing with a standard database to distinguish rolled pieces and welded pieces; disassembling the welded pieces and correcting a list according to plate thickness; counting inventory to generate an available resource list; adopting a multi-level matching strategy to determine the demand for the rolled pieces; adopting plate cutting optimization to generate thin plate and thick plate cutting plans for the welded pieces, and processing variable cross-section webs through pair-by-pair complementary splicing, so as to determine the demand for coiled materials and steel plates; and constructing a dynamic optimization model integrating inventory and fund constraints, so as to output an optimal scheme under the fund limit constraint. The application improves the comprehensive utilization rate of materials, preferentially guarantees the supply of main components, reduces procurement and inventory costs, and provides scientific decision support for steel structure plant blanking.

Description

Technical Field

[0001] This invention belongs to the field of data processing technology, and in particular relates to a method and system for optimizing the cutting of steel structure factory profiles based on Tekla. Background Technology

[0002] The statements in this section are merely background information related to the present invention and do not necessarily constitute prior art.

[0003] In the construction of steel structure workshops, the planning and optimization of material usage directly determine the project cost and construction schedule. Furthermore, the different dimensional parameters and cross-sectional forms specified in the steel structure workshop component drawings necessitate different matching requirements for raw materials. However, existing material optimization methods often overlook the differentiated requirements of component design specifications, treating all components uniformly with a simple layout, failing to plan material sources according to component type. This leads to an imbalance between material supply and demand during actual construction, increasing unnecessary processing steps and material waste.

[0004] Furthermore, traditional optimization methods focus solely on the efficiency of layout in a single stage, failing to consider the construction schedule and the urgency of components, as well as upstream constraints such as inventory levels and phased funding approvals. This results in supply disruptions or inventory buildup even when the material preparation plan is optimal at the layout level, potentially exceeding funding limits. Consequently, the main structure may be forced to halt construction due to shortages of critical components, while materials for secondary components are stockpiled in advance, ultimately impacting overall construction efficiency and cost control. Summary of the Invention

[0005] To overcome the shortcomings of the prior art, this invention provides a method and system for optimizing the cutting of steel structure factory profiles based on Tekla. The aim is to automatically extract component information using Tekla and classify the components into two categories, rolled parts and welded parts, through data comparison: rolled parts can be directly cut from profiles, while welded parts need to be disassembled into sheet metal for further processing.

[0006] Differentiated optimization strategies are designed for the two types of components, while an inventory linkage mechanism and surplus material recycling are introduced to prioritize the material supply of the main components, forming a closed-loop decision-making process from design to production, and realizing the scientific planning and dynamic allocation of the overall material usage.

[0007] To achieve the above objectives, one or more embodiments of the present invention provide the following technical solutions:

[0008] In the first aspect, a method for optimizing the cutting of steel structure factory profiles based on Tekla is disclosed, including: automatically extracting component parameters based on Tekla, comparing the component parameters with a preset standard database, classifying the components into rolled parts and welded parts, parametrically disassembling the welded parts to generate a welded part disassembly list, correcting and updating the welded part disassembly list according to the thickness of the constituent plates, adjusting the plates that meet the conditions to rolled parts, and updating the rolling part cutting list and the welded part disassembly list;

[0009] Based on the updated rolling part cutting list and welded part disassembly list, the existing inventory of profiles, coils and steel in the warehouse is statistically analyzed and classified to generate a list of available inventory resources.

[0010] For the updated rolled parts blanking list, a multi-level matching strategy is used to generate a rolled parts blanking scheme and determine the required quantity of rolled parts. For the updated welded parts disassembly list, a plate cutting optimization strategy is used to generate a welded parts blanking scheme and determine the required quantity of coils and steel plates.

[0011] With the goal of optimal material cutting, a dynamic optimization model integrating inventory statistics and capital constraints is constructed for rolled and welded parts. Capital limit is used as a constraint to determine the optimal material cutting scheme under the capital limit and output the optimal material cutting scheme.

[0012] Secondly, a steel structure factory profile cutting optimization system based on Tekla is disclosed, including: a data acquisition and classification module, which is used to automatically extract component parameters based on Tekla, compare the component parameters with a preset standard database, classify the components into rolled parts and welded parts, perform parameterized disassembly of the welded parts to generate a welded part disassembly list, and correct and update the welded part disassembly list according to the thickness of the constituent plates, adjust the plates that meet the conditions to rolled parts, and update the rolled part cutting list and the welded part disassembly list;

[0013] The inventory statistics module is used to perform statistics and classification on the existing inventory of profiles, coils and steel in the warehouse based on the updated rolling part cutting list and welded part disassembly list, and generate a list of available inventory resources.

[0014] The rolled parts optimization module is used to generate rolled parts cutting schemes using a multi-level matching strategy for the updated rolled parts cutting list, and to determine the required quantity of rolled parts;

[0015] The weldment optimization module is used to generate a weldment cutting plan based on the updated weldment disassembly list, using plate cutting optimization strategies, and to determine the coil material requirement and steel plate requirement.

[0016] The capital constraint optimization module is used to construct a dynamic optimization model that integrates inventory statistics and capital constraints for rolled and welded parts with the goal of optimal material cutting. It uses the capital limit as a constraint to determine the optimal material cutting scheme under the capital limit and outputs the optimal material cutting scheme.

[0017] Thirdly, a computer device is disclosed, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to perform the steps of the method described above.

[0018] Fourthly, a computer-readable storage medium is disclosed having a computer program stored thereon, which, when executed by a processor, implements the steps of the method described above.

[0019] The above one or more technical solutions have the following beneficial effects:

[0020] This invention utilizes Tekla to automatically extract component information and compare it with a standard database, achieving accurate classification of rolled and welded parts and avoiding human error. It designs multi-level matching and plate cutting optimization strategies for the two types of components, deeply integrating with capital turnover constraints. While ensuring priority supply of the main load-bearing components, it dynamically allocates resources, significantly improving material utilization and reducing procurement and inventory costs. Simultaneously, through the recycling of surplus materials and the generation of alternative solutions, it achieves closed-loop decision-making throughout the entire process from design to production, effectively solving the problems of material supply and demand imbalance, main component downtime due to material shortages, and the disconnect between single-stage optimization and resource constraints in traditional material cutting schemes. This provides a scientific and efficient component cutting optimization solution for steel structure plant construction.

[0021] Advantages of additional aspects of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0022] The accompanying drawings, which form part of this invention, are used to provide a further understanding of the invention. The illustrative embodiments of the invention and their descriptions are used to explain the invention and do not constitute an improper limitation of the invention.

[0023] Figure 1 This is a flowchart of the steel structure factory profile cutting optimization method based on Tekla according to Embodiment 1 of the present invention;

[0024] Figure 2 This is a schematic diagram showing the splicing of global optimization and alternative solutions for rolled parts according to Embodiment 1 of the present invention;

[0025] Figure 3 This is a schematic diagram of the blanking process for the welded thin plate according to Embodiment 1 of the present invention;

[0026] Figure 4This is a schematic diagram of the cutting process for a thick plate welded component according to Embodiment 1 of the present invention;

[0027] Figure 5 This is a schematic diagram of the trapezoidal web member structure according to Embodiment 1 of the present invention. Detailed Implementation

[0028] It should be noted that the following detailed descriptions are exemplary and intended to provide further illustration of the invention. Unless otherwise specified, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention pertains.

[0029] It should be noted that the terminology used herein is for the purpose of describing particular implementations only and is not intended to limit the exemplary implementations of the present invention.

[0030] Where there is no conflict, the embodiments and features in the embodiments of the present invention can be combined with each other.

[0031] Example 1

[0032] Figure 1 This invention provides a flowchart of a steel structure factory profile cutting optimization method based on Tekla. Tekla automatically extracts component information, and through data comparison, components are categorized into rolled parts and welded parts. Rolled parts can be directly cut from profiles, while welded parts require disassembly into sheet metal for further processing. Different optimization strategies are designed for the characteristics of the two types of components. Rolled parts employ a multi-level matching strategy including precise matching, near-optimal matching, surplus material reuse matching, and global optimization alternatives. Welded parts employ a sheet metal cutting optimization strategy including thin plate cutting, thick plate cutting, and variable cross-section web splicing. Simultaneously, an inventory linkage mechanism and surplus material recycling are introduced, prioritizing existing inventory and dynamically allocating material resources. With the goal of prioritizing the material supply for main components and maximizing the overall material utilization rate, the multi-level matching model and sheet metal cutting optimization model are used to iteratively calculate and obtain the optimized cutting scheme that meets component requirements and has the highest overall utilization rate. This forms a closed-loop decision-making process from design to production, achieving scientific planning and dynamic allocation of overall material cutting usage.

[0033] like Figure 1 As shown, this embodiment discloses a method for optimizing the cutting of steel structure factory profiles based on Tekla, including:

[0034] Step S1: Based on Tekla, automatically extract component parameters, compare the component parameters with a preset standard database, classify components into rolled parts and welded parts, perform parametric disassembly of welded parts to generate a welded part disassembly list, and correct and update the welded part disassembly list according to the thickness of the constituent plates. Specifically, this includes:

[0035] Based on the parametric information extracted by Tekla, the component parameters are identified according to the profile spatial coordinate information to determine whether the component is a vertically arranged load-bearing component.

[0036] The component's specifications, cross-sectional dimensions, and material information are matched against a pre-set standard database item by item. If a match is successful, it is determined to be a rolled part and included in the rolled part cutting list; otherwise, it is determined to be a welded part.

[0037] The welded parts are parametrically disassembled, and their constituent plates are identified based on their geometric features. The size and material information of each plate are extracted, and a disassembled list of the welded parts is generated.

[0038] Iterate through each component plate in the welded part disassembly list, query the plate thickness d, and if d is an odd number and d≠3mm or d≠25mm, then change the plate type from welded part to rolled part.

[0039] The specific implementation steps are as follows:

[0040] Step S1.1: Based on the parametric information extracted by Tekla, identify the component parameters according to the profile spatial coordinate information and generate a list of profiles to be cut, specifically including:

[0041] Based on the parametric information of the Tekla model, the specifications, materials, and dimensions of the steel profiles of each component in the steel structure workshop are automatically extracted via API interface. Batch statistics are used to aggregate the quantities of components with the same specifications. The spatial length of each component is calculated based on the start point (startPoint.X, startPoint.Y, startPoint.Z) and end point (endPoint.X, endPoint.Y, endPoint.Z) coordinates of the model's parametric information. ,in, , , .

[0042] During data preprocessing, missing data is supplemented and redundant data is deleted to ensure data integrity. The type of profile is identified based on its specification prefix. Identification rules can be based on common naming conventions or custom mapping relationships. For example, prefixes such as "H" or "HW" identify H-beams, "PIP" identify round steel pipes, and "PL" or "B" identify connecting plates. Other profile types follow the same logic, expanded according to actual coding rules.

[0043] For length values ​​that are not whole decimeters or centimeters, the nearest whole decimeter or centimeter is used to round them to a uniform order of magnitude. The quantity of components of the same specification is counted in batches, the weight and area are calculated, and a list of profiles to be cut is generated.

[0044] Step S1.2: Automatically identify the main load-bearing components by analyzing the spatial pose characteristics of the components. The specific identification rule is: if and only if , and In such cases, the component is determined to be a vertically arranged load-bearing member. As the core of the structural load, this type of component is given priority in material preparation and inventory allocation to ensure the stability of the main structure's material supply.

[0045] Step S1.3: Compare the component parameters with the preset standard database to classify the components into rolled parts and welded parts. Specifically, this includes: based on the initial list of profiles to be cut, matching the component specifications, cross-sectional dimensions and material information with the standard data stored in the preset standard database item by item.

[0046] If the specifications and model of the component exist in the database, and its cross-sectional dimensions, material and other parameters meet the relevant regulations, then the component is determined to be a rolled part, and can be directly cut using standard profiles and included in the rolled part cutting list; otherwise, it is determined to be a welded part.

[0047] It should be understood that the default standard database contains at least standard specifications and models, and also stores parameters such as standard cross-sectional dimensions, material grades and dimensional information corresponding to each specification, which are used to compare the attributes of components in multiple dimensions and determine their types.

[0048] Step S1.4: Parametrically disassemble the welded parts, specifically including: identifying the corresponding component plates according to the geometric features corresponding to the specifications and models of the welded parts, extracting the original dimensions and material information of each component plate after disassembly, counting the number and dimensions of plates of the same material and thickness, and generating a welded parts disassembly list containing the processing numbers of the plates.

[0049] The specific disassembly rules are as follows: When disassembling H-beams and I-beams, identify the connection boundary between the two flanges and one web; when disassembling T-beams, identify the connection boundary between the two flanges and one web; when disassembling box-section steel, identify the connection boundary between the two flanges and two webs.

[0050] Taking H-beams as an example, their specifications are represented as H×B×t. w ×t f After disassembly, the dimensions of the flange are: length, width, and thickness (B). f The plate has a web dimension of width (H-2×t). f Thickness is t w For example, H350*200*6*10, the H-beam is disassembled into two flanges that are 200mm wide and 10mm thick, and a web that is (350-2*10) wide and 6mm thick.

[0051] Step S1.5: Traverse each component plate in the welded part disassembly list, query the thickness d of each component plate, and if the disassembly plate thickness is... satisfy For odd-numbered thicknesses, and mm If the part type is mm, the component type is changed from welded to rolled, removed from the welded part disassembly list, and added to the rolled part blanking list; otherwise, the component is retained as a welded part.

[0052] Based on design requirements or processing feasibility, the weldment disassembly list can be automatically adjusted to ensure that the blanking method matches the actual manufacturing conditions. After adjustment, the rolled part blanking list and the weldment disassembly list are updated.

[0053] By performing a secondary screening of the thickness of the component plates in the disassembly list of welded parts, plates that meet the criteria are modified from welded parts to rolled parts, thus achieving a more refined determination of component type. This modification can transform components that originally required disassembly and subsequent welding into rolled parts that can be directly cut from standard profiles, avoiding welding deformation and weld quality risks, and improving material utilization and processing quality.

[0054] Meanwhile, automation adjustments are made based on design requirements or the feasibility of processing technology, further enhancing the adaptability of the material cutting scheme to actual production conditions and improving the engineering practical value of the scheme.

[0055] Step S2: Generate a list of available inventory resources, including: counting the inventory quantity of various standard-length profiles in the warehouse, determining the list of available raw material lengths based on whether the warehouse is activated, prioritizing the use of existing inventory to meet the cutting needs of rolled parts, and formulating a supplementary procurement plan for any shortfall.

[0056] The sheet metal is categorized into thin and thick plates based on thickness, and each is matched with a preset width or length standard value. The inventory of coils or steel plates is tallied, and existing materials in the warehouse are prioritized. If insufficient, a supplementary procurement plan is initiated. Finally, an inventory list of available resources is generated, which includes a list of available profiles for rolled parts and a list of available sheet metal for welded parts.

[0057] To determine the inventory status of rolled components in the warehouse, the inventory quantity of rolled parts is confirmed, and the inventory quantities of 6m, 9m, and 12m standard-length profiles are counted to determine the list of available raw material lengths. Different processing methods are adopted according to the inventory activation status. If the warehouse is not activated or the inventory is invalid, a fixed list in descending order [12, 9, 6] is used as the available raw material lengths. If the warehouse is activated and the inventory is valid, the inventory lengths are sorted in descending order, and regular lengths are added before deduplication and sorting to form the list of available raw material lengths.

[0058] During the matching process, existing inventory is used first to meet the cutting requirements: when the length of the cutting profile exceeds 12m, 12m standard-length profiles are used for cutting and matching first. The remaining part is calculated to supplement the inventory based on the principle of being slightly longer than the requirement. For the part with insufficient inventory, a supplementary procurement plan is formulated in accordance with the no-warehouse rule.

[0059] Regarding the inventory of welded sheet metal in the warehouse, when determining the list of available sheet metal, statistics are compiled according to thickness classification. Sheets with a thickness d≤12mm are considered thin sheets, and rolls with preset width standard values ​​of 1.25m, 1.5m, and 1.8m are matched. The standard width of each roll and the corresponding inventory length of the roll are counted to determine the inventory quantity of the roll.

[0060] Plates with a thickness d > 12mm are considered thick plates. They are matched with steel plates of preset widths of 2m, 2.2m, and 2.5m, and preset lengths of 9m and 12m. The standard width and length of each steel plate are calculated to determine the steel plate inventory. Existing materials in the warehouse are checked and used first; a supplementary procurement plan is only initiated when the existing inventory of specifications or quantities is insufficient.

[0061] After completing the above statistics, a list of available inventory resources is generated, including: inventory of rolled parts, inventory of coils, and inventory of steel plates.

[0062] Step S3: For the updated rolling part blanking list, a multi-level matching strategy is used to generate a rolling part blanking scheme and determine the required quantity of rolling components, including: using recursive dynamic programming and backtracking algorithms to find combinations that include the total length of reserved gaps equal to the target length of the fixed-length profile, performing precise matching, and realizing zero-surplus material layout;

[0063] If not all matching is completed, the remaining components are sorted in descending order of length. With the goal of minimizing excess material and the number of welding operations, near-optimal matching is performed to generate grouping schemes, and splicing mode is used for ultra-long components. When the overall excess material rate exceeds the threshold and the component does not bear dynamic load, global optimization is initiated to dynamically determine the length of the fixed-length profile and generate alternative schemes. Material utilization is ensured through segmentation and threshold constraints. The required quantity of rolled components is determined based on the actual quantity of each specification of profile consumed in the final cutting scheme.

[0064] The specific implementation steps are as follows:

[0065] Step S3.1: Based on the updated rolling part blanking list, perform precise zero-surplus material matching and perform zero-surplus material layout for components that meet the length combination. Specifically, this includes: using recursive dynamic programming and backtracking algorithm to find combinations from the rolling part blanking components whose total reserved gap length is equal to the target length of the fixed-length profile.

[0066] The algorithm employs a two-branch search strategy of "including the current component to be cut" and "skipping the current component to be cut", traversing the list of components to be cut in order.

[0067] Specifically, before matching, a pre-filter is performed, retaining only unused components whose length does not exceed the specified profile length. The profile length is set to... Among them, the fixed length of the profile The values ​​are 6, 9, and 12.

[0068] Accurate combination search is achieved based on recursive dynamic programming and backtracking algorithm: Starting from the specified index startIndex, the list of components to be cut is traversed in ascending order of index, and the search is carried out by a two-branch strategy of "including the current component to be cut" and "skipping the current component to be cut".

[0069] During the recursive process, the total length of the current component combination is first calculated using combination.Sum(p => p.Length). If equal to the length of the standard profile ,Right now , To prevent uneven warping of the flame-retardant cut edges, a pre-reserved gap length is set, ranging from 200mm to 500mm. The excess material (Mex) is set to 0, and the combination is returned. .

[0070] Prioritize adding the currently unloaded component to the group and continue recursively. If a match is found in the branch, return the result directly; otherwise, cancel the selection using current.RemoveAt and continue searching in the branch that does not contain the currently unloaded component.

[0071] The traversal order is controlled by incrementing the index to avoid duplicate combinations, and backtracking is used to promptly undo invalid selections, ensuring efficient and accurate searching. Once an exact matching combination that meets the conditions is found, the algorithm terminates immediately and returns the result; otherwise, it returns null. Components from successfully matched exact combinations are removed from the list of components to be cut, resulting in an updated list of components to be cut.

[0072] Step S3.2: If not all components are matched, execute the near-optimal matching strategy. After completing the precise zero-residual-material matching, the remaining list of materials to be cut is arranged in descending order of length. With the goal of minimizing residual material and minimizing the number of welding operations, a recursive dynamic programming algorithm is used to generate near-optimal matching groups.

[0073] During the recursive search process, the remaining material length of the current combination is calculated in real time and compared with the existing best results in real time. Finally, the combination with the smallest remaining material and the fewest profiles is retained as the near-optimal group.

[0074] For profiles exceeding the maximum target length of a single raw material, a multi-segment splicing method is adopted. Specifically, after completing the zero-residue matching in step S3.1, for the remaining profiles that cannot achieve a perfect fit, a near-optimal matching is performed with the goal of minimizing excess material and the number of welding operations.

[0075] Arrange the remaining profiles in descending order, set the reserved gap length f=500mm, and use a recursive dynamic programming algorithm to find the grouping scheme with the minimum amount of leftover material and the fewest welding times.

[0076] In the recursive search, if the total length of the current combination (including the reserved seam) does not exceed the length of the raw material... If the condition is met, add it to the combination and continue recursively; if the limit is exceeded, remove the last added profile and switch to a branch that does not contain that component.

[0077] After each effective combination is generated, the remaining material length is calculated. The current combination is compared with the existing best result. If the current surplus material is smaller, or the number of profiles is less when the surplus material is the same (absolute difference < 0.001), the current combination is updated to a near-optimal combination. The total length of raw materials and the surplus material length of the optimal combination are calculated. A grouping object containing the cutting profile information, target length, and surplus material information is created. The corresponding cutting profile is marked as cut and the cutting profile list is further updated. The above process is repeated to continue searching for the next near-optimal combination until there are no more feasible matches.

[0078] Finally, a list of all near-optimal matching groups corresponding to the total length of the raw materials is returned.

[0079] For profiles exceeding the maximum target length of a single raw material (e.g., 12m), the system automatically switches to splicing mode, prioritizing the selection of a 12m long standard-length raw material as the base segment. The required length of the supplementary segment is calculated based on the difference, and other lengths of raw materials are matched from available inventory or procurement plans for combination. The problem of cutting extra-long components is solved by increasing controlled welding points, avoiding additional procurement and transportation costs caused by custom-made oversized profiles.

[0080] Step S3.3: When the overall residual material rate exceeds the preset threshold and all rolled parts to be processed are not used as components to bear dynamic loads, global optimization and alternative solutions are initiated.

[0081] The length and number of standard profiles to be cut are dynamically determined based on the length distribution characteristics of the components to be cut from the rolled parts. The method for dynamically determining the length of standard profiles in global optimization is as follows: if there are components with a length exceeding 9 meters, the length of standard profiles is uniformly set to 12 meters; otherwise, the total length of all components to be cut, including the reserved gap, is calculated, divided by 9 meters and 12 meters respectively to obtain the remainder, and the length corresponding to the smaller remainder is selected as the length of standard profile.

[0082] Arrange the rolled parts to be cut on each raw material in sequence. For rolled parts to be cut that cannot be fully accommodated, divide them and put the divided parts into the current fixed length profile and the subsequent fixed length profile respectively. After all rolled parts to be cut are processed, save the effective grouping scheme into the alternative scheme list.

[0083] Specifically: when the overall residual rate ( - ) / More than 10%, When the total length is fixed and all rolled parts to be cut are not to be used as components to bear dynamic loads, the global optimization process is initiated to generate alternative solutions.

[0084] Set the set of components to be cut into rolled parts as follows Reserved seam length .

[0085] Scenario A: Excessively long components exist: Calculate the total length of all rolled components to be cut. The components are sorted in descending order of length, and it is determined whether there are any rolled parts exceeding 9 meters in length awaiting cutting. If so, the length of the fixed-length profiles is determined. The standard height is set at 12 meters.

[0086] like The target length is then uniformly set as follows:

[0087]

[0088] Scenario B: No extra-long components: Calculate the total length of the cut profile including the seam, divide it by the raw material lengths of 9 meters and 12 meters respectively, and obtain the remainders e1 and e2. Compare the remainders and select the fixed-length profile corresponding to the smaller remainder as the target length. .

[0089] like First, calculate the total length including the seam. :

[0090]

[0091] set up ,but:

[0092]

[0093] Based on the selected target length Calculate the total number of standard length raw materials and round up:

[0094]

[0095] Let the total remaining blank length after the first N-1 raw materials are consumed be . If the remaining total length of the material is If the length is less than 6 meters, use 6-meter raw materials; if it is between 6 and 9 meters, use 9-meter materials; if it is greater than or equal to 9 meters, use 12-meter materials.

[0096] The blanking profiles are arranged sequentially on each raw material, and the process is repeated until all blanking profiles are matched or the raw materials are used up.

[0097] like Figure 2 As shown, let the current number be... The target length of the root raw material is The total length of the blanking profiles used is The total length of the reserved seams that have been generated is ,in The number of components on the current raw material, and the available space of the current raw material. for:

[0098]

[0099] Current profiles to be processed +1 length satisfy:

[0100]

[0101] Mark the current profile to be processed as already cut, when The current available space for raw materials is insufficient to handle the length of the profile to be processed, but the current available space for raw materials meets the threshold requirement: Cut the profile to be processed into sections: , ;Will Save the current raw material list. Proceed to the next raw material processing.

[0102] Among them, minimum utilization threshold According to the "Code for Construction of Steel Structures" GB50755-2012, the diameter should not be less than 600mm unless otherwise specified in the design. When the profile is a round steel pipe, the diameter d of the round steel pipe should be used for judgment. If d ≤ 500mm, the diameter should not be less than 500mm; if 500mm < d ≤ 1000mm, the diameter should not be less than d; if d > 1000mm, the diameter should not be less than 1000mm.

[0103] After all the blanking profiles have been processed, the corresponding procurement and consumption information will be output according to whether the warehouse inventory is enabled: if the no-inventory mode is enabled, the demand for each specification of rolled parts will be output directly; if the inventory mode is enabled, the inventory consumption of rolled parts and the replenishment procurement of rolled components will be output simultaneously.

[0104] Output the total length of the profiles to be cut and the specific cutting plans for all groups in graphical form. Each cutting plan should include the specifications and quantity of the profiles used in that group, the cutting position of each profile on the raw material, the corresponding remaining material length, and the number of welding joints. If alternative plans are generated during the execution of the plan, the details of the alternative plan groups should be output simultaneously.

[0105] Step S4: For the updated weldment disassembly list, use a plate cutting optimization strategy to generate a weldment cutting plan, determining the coil material requirement and the steel plate requirement, including:

[0106] For thin plate components, with a preset width standard value as the target, a thin plate cutting plan is generated through dynamic precise assembly and approximate assembly and the introduction of a cutting edge adjustment mechanism. The roll material demand is determined based on the actual roll material length consumed in the plan.

[0107] For thick plate components, using preset width and length standard values ​​as targets, if the total width of the plates to be arranged is not greater than the maximum standard width, they are directly arranged in a forward direction; otherwise, a permutation and combination algorithm is used to recursively select plate combinations whose total width is exactly equal to the standard value to form a precise arrangement. The remaining plates are then used for approximate arrangements by superimposing their length and width in descending order to generate the main scheme.

[0108] After the main plan is generated, if the surplus material rate exceeds the threshold and there is no dynamic load, the alternative plan is activated: divide the total length of all plates by two preset length standard values ​​respectively, take the length corresponding to the smaller remainder as the target length of the raw material, use the target width of the main plan, and then arrange them row by row in the order from top to bottom and from left to right. When the available length of the current row is less than the minimum utilization threshold, the line is broken, the extra-long plates are cut off and the remaining part is transferred to the next row for recursive processing until all plates are arranged, and a thick plate cutting plan is generated. The steel plate demand is determined according to the actual consumption in the plan.

[0109] The specific implementation steps are as follows:

[0110] Step S4.1 Based on the updated welded component disassembly list, for thin plate components with a thickness d not greater than 12mm in the welded component disassembly list, material optimization configuration is performed with the preset width standard value Wsp (1.25m, 1.5m, 1.8m) as the target.

[0111] like Figure 3 As shown, the process involves filtering unassigned thin-plate components to generate a list of sheet metal to be cut, iterating through their widths, and calculating the target width based on the cutting process parameters. These parameters include a 50mm cutting gap between plates, b=100mm for the top and bottom cutting edges of the sheet metal, and the target width. The calculation formula is: ， Where, in the formula, This represents the total width of the sheet metal parts currently being cut within the group. This refers to the number of boards in the group.

[0112] Set the constraint as target width This is equal to the preset width standard value Wsp. A dynamic cutting edge adjustment mechanism is introduced during the assembly process: when the difference between the target width and the actual width of the cut material is within the range of 100-200mm, this difference is evenly distributed to the upper and lower cutting edges to ensure that the adjusted cutting edge b remains within a reasonable range of 50-100mm. The cut materials that meet the constraints are combined into effective groups, and the specifications of the matching raw materials are determined: the width is taken as the target width within the group. The length is taken as the maximum length of the cutting board within the group, Limax, and the cutting boards are arranged sequentially along the width direction of the raw material board.

[0113] For the remaining unassigned boards, proceed to the approximate assembly stage: sort the boards in descending order of length and then in descending order of width, select the widest board as the seed component, and iterate through the preset width standard value Wsp for matching.

[0114] Based on the seed component, candidate blanking plates are progressively stacked. Each time a new blanking plate is added, the total width of the current combination is recalculated. The total width of the current combination is accumulated in real time, and the calculation formula is as follows: ；

[0115] If the total width of the current combination does not exceed the preset width standard value, the new cutting board is retained; otherwise, it is skipped. If the remaining width is less than the width of the narrowest cutting board, the process is terminated early. Record the remaining width corresponding to each combination under each preset width standard value, select the one with the smallest remaining width as the optimal combination, and use the preset width standard value of this group as the target width. After deleting the cutting board ID of this group from the candidate cutting boards, repeat the above steps until all candidate cutting boards have been combined.

[0116] Summarize all the optimal combinations of steel plates, target widths of raw materials, and allocation status; create a cutting plan; and calculate the area used, total area of ​​raw materials, area of ​​surplus material, and material utilization rate. Record the width, length, and dynamically adjusted cutting edge parameters of each raw material; and summarize the detailed information of each cut plate in the group.

[0117] Step S4.2: For thick plate components with a thickness d greater than 12mm in the welded component disassembly list, optimize the material configuration with the preset width standard value Wsp (2m, 2.2m, 2.5m) and preset length standard value (9m, 12m) as the target.

[0118] For sheet materials of the same thickness, first calculate the total width and total length of all sheet materials to be arranged. Based on the relationship between the total width and the preset standard width value, handle thick plate components in different cases:

[0119] For sheet metal of the same thickness, when the total width is no more than 2.5m, the width of the raw material is taken as the minimum standard width that is greater than the total width, and the length of the raw material is taken as the minimum standard length that is greater than the total length. The sheet metal is arranged sequentially along the width direction of the raw material.

[0120] When the total width is greater than 2.5m, the permutation and combination algorithm is used first to select the combination of boards whose total width is exactly equal to 2m, 2.2m or 2.5m to form a precise combination. If a precise match cannot be made, the combination is transferred to an approximate combination. The cut boards are stacked in descending order of length and width, and the combination closest to the target length and target width is selected to generate the main scheme. The remaining materials are included in the connecting board list.

[0121] After the main scheme is generated, the ratio of the total area of ​​the surplus material to the total area of ​​the raw materials is calculated. If it exceeds 10% and the steel profiles formed by combining the cut plates are not used to bear dynamic loads, the alternative scheme is activated.

[0122] Target length of raw materials The target length is determined based on the total length of all the boards to be laid out and cut: Calculate the remainders obtained by dividing the total length by 9m and 12m respectively, and select the length corresponding to the smaller remainder. .

[0123] The list of materials to be cut, the list of raw materials, and the alternative schemes are initialized, and the materials to be cut are arranged in descending order according to length first and width second.

[0124] During the layout process, strictly follow the layout order from top to bottom and from left to right. Leave a cutting seam a between adjacent plates with a width of 50mm. Leave a fixed cutting edge of 100mm at both the top and bottom ends of the plate.

[0125] like Figure 4 As shown, the available length of the current row The calculation method is as follows: ,in For the target length of the raw material, This is the sum of the lengths of the boards already arranged in the current row. This represents the number of boards that have been arranged.

[0126] If the current row has available length If the length of the material to be cut is less than the preset minimum utilization threshold c, a line break operation is triggered; if the length of the material to be cut is... Less than This indicates that the board can be completely placed in the current row without exceeding the width boundary. At this point, an object containing coordinate position information is created and the current layout state is updated.

[0127] If the current length of the material to be cut is Greater than Then, the board is cut off at the remaining length position of that row, with a length of... Insert part of it into the current line, with a remaining length of The portion moves to the next line to continue the arrangement.

[0128] After the layout is completed, alternative plans are generated. This includes calculating indicators such as the used area of ​​the panels, the total area of ​​raw materials, the area of ​​surplus materials, and the material utilization rate, and setting parameters such as raw material dimensions, panel list, location list, surplus material area, and material utilization rate. If an alternative plan is successfully generated, it is attached to the main plan and marked as "Alternative Plan Available"; if the generation fails, it is marked as "No Alternative Plan Available".

[0129] The minimum utilization threshold shall comply with the process specifications of GB50205-2001 "Code for Acceptance of Construction Quality of Steel Structures". The spacing between the flange splice joints and web splices of welded H-beams shall not be less than 200mm. The flange splice length c shall not be less than twice the plate width; the web splice width shall not be less than 300mm and the length shall not be less than 600mm.

[0130] Step S4.3: If the roof beams and side columns of the portal frame in the updated welded component disassembly list are trapezoidal web members with the same cross-sectional shape and geometric dimensions, the trapezoidal web members shall be processed by first pairing them together to form rectangular plates, and then including them in the conventional cutting and blanking process according to their thickness and material. Specifically, this includes:

[0131] Perform geometric analysis on the trapezoidal web member. If the two short sides are parallel, record the length of the parallel side directly. If they are not parallel, construct the parallel side by extending the second longest side and drawing a perpendicular line.

[0132] Two trapezoidal webs of the same specifications are aligned and spliced ​​together along their diagonal waists to form a rectangular plate. The length of the rectangular plate is equal to the length of the vertical side, and the width is equal to the sum of the lengths of the two parallel sides. The spliced ​​rectangular plate is included in the batch of cutting plates of the same thickness and material, and is arranged and cut together with other rectangular plates. When the processing quantity is odd, the even-numbered parts are paired up, and the remaining single pieces are supplemented separately as rectangular post-processing.

[0133] like Figure 5 As shown, geometric feature analysis is performed on the trapezoidal web member extracted by Tekla to determine whether its two short sides are parallel. If the two short sides are parallel, the lengths PL and DL of the two parallel sides are recorded respectively, and the length of the perpendicular side is determined to be TL.

[0134] If the two shorter sides are not parallel, the second longest side is selected as the reference and extended outward along its original direction until the required length is reached or the boundary conditions are met. Starting from the endpoint of the second shortest side, a perpendicular line segment is drawn towards the second longest side, ensuring that the perpendicular line segment intersects the second longest side precisely at the foot of the perpendicular, thus constructing a new parallel side. The length of the newly formed parallel side is denoted as PL, and the length of the extended second longest side is denoted as TL.

[0135] After completing the above geometric processing, two trapezoidal web members of the same specifications are aligned in opposite directions along their diagonal sides and spliced ​​together to form a complete rectangular plate. The length of this rectangular plate is equal to TL, and the width is equal to the sum of PL and DL. The resulting rectangular plate is included in a batch of cutting plates of the same thickness and material, and is used together with other rectangular plates for overall layout and cutting.

[0136] When the processing quantity is odd, the web plates of the even-numbered portions are first paired up and spliced ​​into complete rectangular plates according to the above rules, and then used for overall layout and cutting; for the remaining single trapezoidal web plate, it is supplemented into a rectangle and then processed separately, without being spliced ​​in pairs.

[0137] Step S4.4, the matching process for reusing surplus material, is as follows: Receive the main layout scheme and the list of connecting plates, and select connecting plates whose thickness deviation from the existing surplus material plates is less than 0.1mm for matching. After successful matching, use the size of the surplus material as a benchmark to generate a list of cutting connecting plates in descending order of length and width; if the size of the surplus material is smaller than the minimum specification of the connecting plate, skip that scheme.

[0138] The rules for determining the type of leftover material are as follows: when the cut plates in the same group are of equal length and there is leftover material after they are arranged, it is determined to be rectangular leftover material, the length of which is equal to the width of the raw material, and the width is the difference between the length of the raw material and the length of the cut plate minus the cutting seam; all other cases are determined to be stepped leftover material.

[0139] The layout strategy is as follows: For rectangular scrap, the connecting plates are arranged sequentially along the width of the scrap; for stepped scrap, the plates are divided into multiple rectangular areas according to the maximum width, and the plates are arranged starting from the largest area. During layout, the starting position and the maximum width of the current row are initialized. The cutting connecting plates are traversed in sequence, their dimensions are extracted, and then the plates are placed in their original orientation and rotated 90 degrees. The cumulative length within the row is dynamically calculated.

[0140] If the material exceeds the length of the remaining material, a newline is created; if it exceeds the width, the material is skipped. After successful adaptation, a position object with coordinates is generated, updating the placed area, weight, and remaining space. Finally, the actual coordinates of the remaining material plate and connecting plate are overlaid in the visualization interface, dynamically presenting the layout effect and statistical data.

[0141] After all welded parts are processed, output the cutting plan for all thin and thick plates in the form of a diagram. The thin plate cutting plan should include the width and length of the raw materials used in each group, the arrangement position of each plate on the raw materials, the dynamically adjusted cutting edge parameters, the area of ​​leftover material and the material utilization rate, and determine the roll material requirement.

[0142] The thick plate cutting plan should include the specifications of each group of raw materials, the cutting coordinates of each plate, the severance record, the area of ​​leftover material, and the utilization rate. If alternative plans are generated, the target length of the raw materials, the width of the most frequent cut, the layout list, and the statistics of leftover material for the alternative plans should be output simultaneously. In addition, detailed results of leftover material reuse should be output, including the classification of rectangular and stepped leftover materials, the secondary layout coordinates of the connecting plates, and the space utilization rate, to determine the steel plate requirement.

[0143] Step S5: With optimal material cutting as the goal, construct a dynamic optimization model that integrates inventory statistics and capital constraints for rolled parts and welded parts. Take the unit procurement cost of existing profiles, plates, and materials of different specifications in the warehouse, as well as the capital turnover limit, as constraints to determine the optimal material cutting scheme under capital constraints.

[0144] Based on the generated material cutting and splitting scheme, the total procurement capital required for the scheme is calculated. The specific calculation method is as follows: multiply the difference between the demand for rolled components and the inventory of rolled parts by the unit price of rolled components, multiply the difference between the demand for steel plates and the inventory of steel plates by the unit price of steel plates, and multiply the difference between the demand for coils and the inventory of coils by the unit price of coils. Add these three together and then subtract the product of the scrap quantity and the scrap price. The result is the total procurement capital.

[0145] Total procurement investment = (Demand for rolled components - Inventory of rolled parts) Unit price of rolled components + (steel plate demand - steel plate inventory) Steel plate unit price + (coil demand - coil inventory) Unit price of rolled material - amount of waste Scrap material prices.

[0146] Based on the calculation results, the feasibility of the material cutting and splitting scheme is determined: if the total procurement investment exceeds the preset capital turnover limit, the scheme is deemed infeasible and eliminated.

[0147] For multiple feasible splitting schemes, the optimal one is selected with the goal of minimizing the total procurement capital investment. If the capital investment of the current optimal scheme still exceeds the capital turnover limit, the material cutting strategy is dynamically adjusted, the group combination is adjusted, and a new material cutting scheme is generated accordingly. The above evaluation process is iteratively executed until a scheme that meets the capital constraints is obtained or the preset iteration limit is reached.

[0148] In addition, when the capital turnover limit is insufficient to meet the procurement needs of all components, the procurement and cutting of the main load-bearing components shall be prioritized in accordance with the principle of prioritizing the main components, so as to ensure the stability of the supply of key structural materials.

[0149] Example 2

[0150] Based on the method of Embodiment 1, the purpose of this embodiment is to provide a steel structure factory profile cutting optimization system based on Tekla, including: a data acquisition and classification module, used to automatically extract component parameters based on Tekla, compare the component parameters with a preset standard database, classify the components into rolled parts and welded parts, perform parameterized disassembly of the welded parts to generate a welded part disassembly list, and correct and update the welded part disassembly list according to the thickness of the constituent plates, adjust the plates that meet the conditions to rolled parts, and update the rolled part cutting list and the welded part disassembly list;

[0151] The inventory statistics module is used to perform statistics and classification on the existing inventory of profiles, coils and steel in the warehouse based on the updated rolling part cutting list and welded part disassembly list, and generate a list of available inventory resources.

[0152] The rolled parts optimization module is used to generate rolled parts cutting schemes using a multi-level matching strategy for the updated rolled parts cutting list, and to determine the required quantity of rolled parts;

[0153] The weldment optimization module is used to generate a weldment cutting plan based on the updated weldment disassembly list, using plate cutting optimization strategies, and to determine the coil material requirement and steel plate requirement.

[0154] The capital constraint optimization module is used to construct a dynamic optimization model that integrates inventory statistics and capital constraints for rolled and welded parts with the goal of optimal material cutting. It uses the capital limit as a constraint to determine the optimal material cutting scheme under the capital limit and outputs the optimal material cutting scheme.

[0155] Example 3

[0156] The purpose of this embodiment is to provide a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the steps of the above-described method.

[0157] Example 4

[0158] The purpose of this embodiment is to provide a computer-readable storage medium.

[0159] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, performs the steps of the above method.

[0160] The steps and methods involved in the apparatus of the above embodiments correspond to those in Embodiment 1. For specific implementation details, please refer to the relevant description section of Embodiment 1. The term "computer-readable storage medium" should be understood as a single medium or multiple media including one or more instruction sets; it should also be understood as including any medium capable of storing, encoding, or carrying an instruction set for execution by a processor and enabling the processor to perform any of the methods in this invention.

[0161] Those skilled in the art will understand that the modules or steps of the present invention described above can be implemented using general-purpose computer devices. Optionally, they can be implemented using computer-executable program code, thereby allowing them to be stored in a storage device for execution by a computer device, or they can be fabricated as separate integrated circuit modules, or multiple modules or steps can be fabricated as a single integrated circuit module. The present invention is not limited to any particular combination of hardware and software.

[0162] While the specific embodiments of the present invention have been described above in conjunction with the accompanying drawings, this is not intended to limit the scope of protection of the present invention. Those skilled in the art should understand that various modifications or variations that can be made by those skilled in the art without creative effort based on the technical solutions of the present invention are still within the scope of protection of the present invention.

Claims

1. A method for optimizing the cutting of steel structure factory profiles based on Tekla, characterized in that, include: Based on Tekla's automatic extraction of component parameters, the component parameters are compared with a preset standard database to classify components into rolled parts and welded parts. Welded parts are parametrically disassembled to generate a welded part disassembly list. The welded part disassembly list is then corrected and updated according to the thickness of the constituent plates. Plates that meet the conditions are adjusted to rolled parts, and the rolled part blanking list and welded part disassembly list are updated. Based on the updated rolling part cutting list and welded part disassembly list, the existing inventory of profiles, coils and steel in the warehouse is statistically analyzed and classified to generate a list of available inventory resources. For the updated rolled parts blanking list, a multi-level matching strategy is used to generate a rolled parts blanking scheme and determine the required quantity of rolled parts. For the updated welded parts disassembly list, a plate cutting optimization strategy is used to generate a welded parts blanking scheme and determine the required quantity of coils and steel plates. For the updated rolling part blanking list, a multi-level matching strategy is adopted to generate rolling part blanking schemes and determine the required quantity of rolling components, including: finding combinations that include the total length of reserved gaps equal to the target length of fixed-length profiles through recursive dynamic programming and backtracking algorithms, performing precise matching, and realizing zero-surplus material layout; If not all matching is completed, the remaining components are sorted in descending order of length. With the goal of minimizing excess material and the number of welding operations, near-optimal matching is performed to generate grouping schemes, and splicing mode is used for ultra-long components. When the overall excess material rate exceeds the threshold and the component does not bear dynamic load, global optimization is initiated to dynamically determine the length of the fixed-length profile and generate alternative schemes. Material utilization is ensured through segmentation and threshold constraints. The required quantity of rolled components is determined based on the actual quantity of each specification of profile consumed in the final cutting scheme. Based on the updated weldment disassembly list, a plate cutting optimization strategy is used to generate a weldment cutting plan, determining the required quantities of coil material and steel plates, including: For thin plate components, with a preset width standard value as the target, a thin plate cutting plan is generated through dynamic precise assembly and approximate assembly and the introduction of a cutting edge adjustment mechanism. The roll material demand is determined based on the actual roll material length consumed in the plan. For thick plate components, with preset width and length standard values ​​as the target, if the total width of the plates to be arranged of the same thickness is not greater than the maximum standard width, they are directly arranged in the forward direction; otherwise, the permutation and combination algorithm is used to recursively filter the plate combinations whose total width is exactly equal to the standard value to form a precise assembly. The remaining plates are transferred to the approximate assembly by superimposing the length and width in descending order to generate the main scheme, and the leftover materials are included in the connecting plate list. After the main scheme is generated, if the surplus material rate exceeds the threshold and there is no dynamic load, the alternative scheme is activated: divide the total length of all plates by two preset length standard values ​​respectively, take the length corresponding to the smaller remainder as the target length of the raw material, use the target width of the main scheme, and then arrange them row by row in the order from top to bottom and from left to right. When the available length of the current row is less than the minimum utilization threshold, the row is broken. The extra-long plates are cut off and the remaining part is transferred to the next row for recursive processing until all plates are arranged. A thick plate cutting plan is generated, and the steel plate demand is determined according to the actual consumption in the plan. Receive the main scheme and the list of connecting plates, classify the scrap materials according to their shape, adopt different arrangement strategies, prioritize the arrangement of connecting plates on the scrap material plates, generate a secondary utilization scheme and update the scrap material library to achieve closed-loop recycling of scrap materials. With the goal of achieving the optimal material cutting scheme, a dynamic optimization model integrating inventory statistics and capital constraints is constructed for rolled and welded parts. The unit procurement cost of existing profiles, plates, and materials of different specifications in the warehouse, as well as the capital turnover limit, are used as constraints to determine the optimal material cutting scheme under capital constraints and output the optimal material cutting scheme.

2. The method for optimizing the cutting of steel structure factory profiles based on Tekla as described in claim 1, characterized in that, Based on Tekla's automatic extraction of component parameters, the component parameters are compared with a preset standard database to classify components into rolled parts and welded parts. Welded parts are parametrically disassembled to generate a welded part disassembly list, which is then corrected and updated according to the thickness of the constituent plates. The specific steps are as follows: Based on the parametric information extracted by Tekla, the component parameters are identified according to the profile spatial coordinate information to determine whether the component is a vertically arranged load-bearing component. The component's specifications, cross-sectional dimensions, and material information are matched against a pre-set standard database item by item. If a match is successful, it is determined to be a rolled part and included in the rolled part cutting list; otherwise, it is determined to be a welded part. The welded parts are parametrically disassembled, and their constituent plates are identified based on their geometric features. The size and material information of each plate are extracted, and a disassembled list of the welded parts is generated. Iterate through each component plate in the welded part disassembly list, query the plate thickness d, and if d is an odd number and d≠3mm or d≠25mm, then change the plate type from welded part to rolled part.

3. The method for optimizing the cutting of steel structure factory profiles based on Tekla as described in claim 1, characterized in that, Generate a list of available inventory resources, including: Calculate the inventory of various standard-length profiles in the warehouse, determine the list of available raw material lengths based on whether the warehouse is in use, prioritize meeting the needs of rolled parts with existing inventory, and formulate a supplementary procurement plan for any shortfall. The sheet metal is categorized into thin and thick plates based on thickness, and each is matched with a preset width or length standard value. The inventory of coils or steel plates is tallied, and existing materials in the warehouse are prioritized. If insufficient, a supplementary procurement plan is initiated. Finally, an inventory list of available resources is generated, which includes a list of available profiles for rolled parts and a list of available sheet metal for welded parts.

4. The method for optimizing the cutting of steel structure factory profiles based on Tekla as described in claim 1, characterized in that, The method for dynamically determining the standard profile length in global optimization is as follows: if there are components with a length exceeding 9 meters, the standard profile length is uniformly set to 12 meters; otherwise, calculate the total length of all components to be cut, including reserved gaps, divide it by 9 meters and 12 meters respectively to obtain the remainder, and select the length corresponding to the smaller remainder as the standard profile length.

5. The method for optimizing the cutting of steel structure factory profiles based on Tekla as described in claim 1, characterized in that, This also includes, if the roof beams and side columns of the portal frame in the updated welded component disassembly list are trapezoidal web members with the same cross-sectional shape and consistent geometric dimensions, the trapezoidal web members will be processed by first pairing them together to form rectangular plates, and then including them in the conventional cutting and blanking process according to their thickness and material. Specifically, this includes: Perform geometric analysis on the trapezoidal web member. If the two short sides are parallel, record the length of the parallel side directly. If they are not parallel, construct the parallel side by extending the second longest side and drawing a perpendicular line. Two trapezoidal webs of the same specifications are aligned and spliced ​​together along their diagonal waists to form a rectangular plate. The length of the rectangular plate is equal to the length of the vertical side, and the width is equal to the sum of the lengths of the two parallel sides. The spliced ​​rectangular plate is included in the batch of cutting plates of the same thickness and material, and is arranged and cut together with other rectangular plates. When the processing quantity is odd, the even-numbered parts are paired up, and the remaining single pieces are supplemented separately as rectangular post-processing.

6. A Tekla-based steel structure factory profile cutting optimization system, used to implement the Tekla-based steel structure factory profile cutting optimization method as described in any one of claims 1-5, characterized in that, include: The data acquisition and classification module is used to automatically extract component parameters based on Tekla, compare the component parameters with a preset standard database, classify components into rolled parts and welded parts, parametrically disassemble welded parts to generate a welded part disassembly list, and correct and update the welded part disassembly list according to the thickness of the constituent plates, adjust the plates that meet the conditions to rolled parts, and update the rolled part blanking list and the welded part disassembly list. The inventory statistics module is used to perform statistics and classification on the existing inventory of profiles, coils and steel in the warehouse based on the updated rolling part cutting list and welded part disassembly list, and generate a list of available inventory resources. The rolled parts optimization module is used to generate rolled parts cutting schemes using a multi-level matching strategy for the updated rolled parts cutting list, and to determine the required quantity of rolled parts; The weldment optimization module is used to generate a weldment cutting plan based on the updated weldment disassembly list, using plate cutting optimization strategies, and to determine the coil material requirement and steel plate requirement. The capital constraint optimization module is used to construct a dynamic optimization model that integrates inventory statistics and capital constraints for rolled and welded parts with the goal of achieving the optimal material cutting scheme. It takes the unit procurement cost of existing profiles, plates, and materials of different specifications in the warehouse, as well as the capital turnover limit, as constraints to determine the optimal material cutting scheme under capital constraints and output the optimal material cutting scheme.

7. A computer device, comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that, When the processor executes the program, it implements the steps of the Tekla-based steel structure factory profile cutting optimization method as described in any one of claims 1-5.

8. A computer-readable storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it performs the steps of the Tekla-based steel structure factory profile cutting optimization method as described in any one of claims 1-5.

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