A customized furniture intelligent integration order platform management system and method

Abstract

The application discloses a customized furniture intelligent integrated order adjusting platform management system and method, and belongs to the technical field of industrial production data analysis. The system comprises a customized furniture order management module, an equipment control module, a data acquisition module, a data analysis module, an order adjusting module and an interactive module. The customized furniture order management module is used to obtain a cutting scheme after order adjustment of different customized furniture orders. The equipment control module is used to obtain a plurality of plate parts produced. The data acquisition module is used to acquire cutting data and time data. The data analysis module is used to store the cutting data and time data sent by the data acquisition module as historical data. A time analysis model is established to analyze the influence of the geometric shape of the cutting plate part in the raw material plate part on the cutting processing time. The order adjusting module is used to adjust the order adjusting quantity of the next batch of customized furniture orders. The interactive module is used to provide a man-machine interactive end.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of industrial production data analysis, in particular to a customized furniture intelligent integration order mixing platform management system and method. BACKGROUND

[0002] Traditional furniture production methods are difficult to meet the needs of small batch and multi-variety order demand. Order mixing production, as an efficient production mode, can reduce the switching frequency of production equipment and improve production efficiency by splitting and mixing furniture panels in multiple scattered orders and producing in batches according to group batch rules. The prior art optimizes the order mixing algorithm and order mixing production process, and increases the utilization rate of raw material panels, but does not consider the impact of order mixing on the production efficiency between devices. In the process of intelligent integration of customized furniture, a large amount of order data may lead to uneven allocation of production resources, affecting device utilization and production efficiency. The complex panels in the order will also make it difficult to accurately adjust the order mixing quantity, affecting the formulation and execution of the production plan. SUMMARY

[0003] The purpose of the present application is to provide a customized furniture intelligent integration order mixing platform management system and method to solve the problems raised in the background art.

[0004] To solve the above technical problems, the present application provides the following technical scheme: an indoor home design platform management method based on an intelligent model, the method comprising the following steps:

[0005] Step S1, determine different customized furniture orders of customers, and split the different customized furniture orders into a plurality of panels respectively. Re-layout the plurality of panels after splitting in the raw material panels to obtain the cutting scheme after order mixing of different customized furniture orders. Collect cutting data of each raw material panel in the cutting scheme. The cutting data includes the number of cutting panels in the raw material panel and the geometric shape of each cutting panel.

[0006] Step S2, according to the cutting scheme obtained in step S1, perform cutting processing on the raw material panels, and perform edge sealing, punching and slotting on the rough panel obtained after the cutting processing to obtain a plurality of panels for production. Collect time data in the cutting processing of the raw material panels. The time data includes the cutting processing time of each raw material panel.

[0007] Step S3, establish a database, store the cutting data collected in step S1 and the time data collected in step S2 as historical data. Based on the historical cutting data and historical time data in the database, a time analysis model is established to analyze the influence of the geometric shape of the cutting panel in the raw material panel on the cutting processing time.

[0008] Step S4, according to the work task, obtaining the processing time required for cutting the next batch of raw material plate parts; before cutting the next batch of raw material plate parts, according to the time analysis model established in step S3 and the processing time required for cutting the next batch of raw material plate parts, adjusting the order rolling quantity of the next batch of customized furniture orders;

[0009] Step S5, according to the order rolling quantity of the next batch of customized furniture orders, repeating steps S1-S4 until all customized furniture orders are completed.

[0010] An indoor home design platform management system based on an intelligent model, the system comprising a customized furniture order management module, a device control module, a data acquisition module, a data analysis module, an order rolling adjustment module and an interaction module;

[0011] The customized furniture order management module is used to determine different customized furniture orders of customers, and to separately disassemble different customized furniture orders into a plurality of plate parts, and to re-layout the plurality of disassembled plate parts in raw material plate parts to obtain a cutting scheme after order rolling of different customized furniture orders; the cutting scheme after order rolling of different customized furniture orders is sent to the device control module and the data acquisition module; different customized furniture orders of customers are sent to the order rolling adjustment module and the interaction module;

[0012] The device control module is used to control the device to cut the raw material plate parts according to the cutting scheme sent by the customized furniture order management module, to edge, punch and slot the rough plate parts obtained after cutting, and to obtain a plurality of plate parts produced;

[0013] The data acquisition module is used to collect cutting data of each raw material plate part in the cutting scheme according to the cutting scheme sent by the customized furniture order management module; the cutting data includes the number of cutting plate parts in the raw material plate parts and the geometric shape of each cutting plate part; and time data in the process of cutting the raw material plate parts is collected from the device control module; the time data includes the cutting processing time of each raw material plate part; the collected cutting data and time data are sent to the data analysis module;

[0014] The data analysis module is used to store the cutting data and time data sent by the data acquisition module as historical data; based on the historical cutting data and historical time data in the database, a time analysis model is established to analyze the influence of the geometric shape of the cutting plate parts in the raw material plate parts on the cutting processing time; the stored historical cutting data and historical time data are sent to the interaction module;

[0015] The kneading order adjusting module is configured to obtain a processing time required for cutting the next batch of raw material plates according to the work task; before cutting the next batch of raw material plates, adjust the number of the next batch of customized furniture orders according to the time analysis model established in the data analysis module and the processing time required for cutting the next batch of raw material plates; and send the number of the next batch of customized furniture orders to the interactive module.

[0016] The interactive module is configured to provide a human-computer interaction terminal, and the management personnel can adjust the work task on the human-computer interaction terminal, determine the processing time required for cutting the next batch of raw material plates, check different customized furniture orders of the customer and the kneading order situation of different customized furniture orders, and check the historical cutting data of each raw material plate and the historical time data in the cutting process of the raw material plate.

[0017] Compared with the prior art, the present application has the following beneficial effects: by establishing a time analysis model, analyzing the influence of the geometric shape of the cutting plate in the raw material plate on the cutting processing time, determining the complexity of the cutting scheme after kneading the order, and predicting the cutting processing time of each raw material plate after kneading the order, the production plan can be easily made and executed; by determining the total cutting processing time of the raw material plate in the customized furniture order, calculating the number of the next batch of customized furniture orders according to the work task, the resource allocation ability in the kneading order process of the customized furniture order is improved, and the utilization rate and production efficiency of the equipment are improved by adjusting the number of the kneading order. BRIEF DESCRIPTION OF DRAWINGS

[0018] Figure 1 is a structural schematic diagram of an indoor home design platform management system based on an intelligent model. DETAILED DESCRIPTION

[0019] The technical solutions in the embodiments of the present application will be described clearly and completely below with reference to the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative labor fall within the scope of protection of the present application.

[0020] Please refer to Figure 1 The present application provides a technical solution:

[0021] In the first embodiment of the present application: a customized furniture intelligent integrated kneading order platform management method is provided, which comprises the following steps:

[0022] Step S1, determine different custom furniture orders of customers, respectively disassemble different custom furniture orders into a plurality of board pieces, re-layout the plurality of disassembled board pieces in raw material board pieces to obtain a cutting scheme after the layout of different custom furniture orders; collect cutting data of each raw material board piece in the cutting scheme; the cutting data includes the number of cutting board pieces in the raw material board piece and the geometric shape of each cutting board piece.

[0023] It should be noted that the cutting board piece represents the board piece that needs to be cut in the raw material board piece, which is cut by cutting processing; since the ultimate goal is to obtain the board piece in the custom furniture order, and the board piece in the custom furniture order is obtained by cutting the raw material board piece, therefore the cutting board piece is the initial form of the board piece in the raw material board piece.

[0024] It should be noted that the different custom furniture orders are respectively disassembled into a plurality of board pieces by the home design software, the board pieces of the same material in each custom furniture order are merged together to form a large board piece pool, according to the size and shape of the board piece, the board pieces in the board piece pool are re-laid by the board layout software, the number of cutting board pieces in each raw material board piece and the geometric shape of each cutting board piece are determined, the material utilization rate of each raw material board piece is maximized, the number of board piece splicing is reduced, and the optimal cutting scheme is generated; the cutting scheme includes each raw material board piece and the number and geometric shape of the cutting board piece in each raw material board piece; in this embodiment, the board pieces in the custom furniture order are of the same type of material, and the size specifications of the raw material board pieces are the same, each type of material and each size specification of the raw material board piece has a corresponding numerical control cutting machine for cutting processing; in this embodiment, a three-dimensional model of each raw material board piece is established by CAD software, and the geometric shape of the cutting board piece when cutting the raw material board piece is determined in the three-dimensional model.

[0025] Step S2, according to the cutting scheme obtained in step S1, cutting processing is performed on the raw material board piece, and edge sealing, punching and slotting are performed on the blank board piece obtained after the cutting processing to obtain a plurality of board pieces for production; time data in the cutting processing of the raw material board piece is collected; the time data includes the cutting processing time of each raw material board piece.

[0026] It should be noted that the cutting processing time of each raw material board piece represents the entire time from when the raw material board enters the numerical control cutting machine, starts cutting based on the geometric shape of the cutting board piece, to when the blank board piece consistent with the number of cutting board pieces is obtained.

[0027] Further, by processing each raw material plate, a plurality of plate pieces are obtained, and the method steps are as follows: according to the cutting scheme, the raw material plate is cut by using a numerical control cutting machine to obtain a cut blank plate, the edge of the obtained blank plate is edge sealed by a full-automatic cutting machine, the edge sealing, gluing and pressing and the edge trimming and polishing of the blank plate are completed, and the blank plate after edge sealing is punched and slotted by using a numerical control six-face drill to obtain a plurality of plate pieces in each customized furniture order.

[0028] Step S3, the cutting data collected in step S1 and the time data collected in step S2 are stored as historical data; based on the historical cutting data and the historical time data in the database, a time analysis model is established to analyze the influence of the geometric shape of the cutting plate in the raw material plate on the cutting time.

[0029] Specifically, based on the historical cutting data and the historical time data in the database, a time analysis model is established to analyze the influence of the geometric shape of the cutting plate in the raw material plate on the cutting time, and the method steps are as follows:

[0030] Step S31, the historical cutting data is analyzed, the total curvature of each cutting plate is determined according to the geometric shape of each cutting plate, and the total curvature set of each cutting plate in each raw material plate is obtained ; the historical time data is analyzed to determine the cutting time of each raw material plate ; wherein, ; represents the total curvature set of each cutting plate in the th raw material plate in the historical cutting data analysis; respectively represents the total curvature of each cutting plate in the th raw material plate; represents the number of raw material plates in the historical cutting data analysis; represents the number of cutting plates in the th raw material plate;

[0031] Wherein, according to the geometric shape of the cutting plate, the total curvature of the cutting plate is determined by determining the surface parameter equation of the cutting plate ; and respectively represent the coordinate parameters on the surface of the cutting plate; according to , the total curvature of the cutting plate is calculated :

[0032] ;

[0033] Wherein, represents the coordinate parameter a dot product of a second derivative vector of the direction and a unit normal vector; denotes a coordinate parameter a dot product of a second derivative vector of the direction and a unit normal vector; denotes a coordinate parameter a direction and a coordinate parameter a dot product of a mixed second derivative vector of the direction and a unit normal vector; denotes a coordinate parameter a square of a modulus of a tangent vector of the direction; denotes a coordinate parameter a square of a modulus of a tangent vector of the direction; denotes a coordinate parameter a direction and a coordinate parameter a dot product of a tangent vector of the direction; denotes a parameter.

[0034] Step S32, a time analysis model is established, the number of cutting plate pieces in the raw material plate piece and the total curvature of the cutting plate piece are taken as independent variables, and the cutting processing time length of the raw material plate piece is taken as a dependent variable, the influence of the geometric shape of the cutting plate piece in the raw material plate piece on the cutting processing time length is analyzed, and according to a calculation formula:

[0035] ; wherein, denotes an influence coefficient of the number of cutting plate pieces and the total curvature of the cutting plate piece on the cutting processing time length; the total curvature of the i-th cutting plate piece in the raw material plate piece; denotes an influence coefficient of other influence conditions on the cutting processing time length;

[0036] Step S33, the historical cutting data and the historical time data analysis result in step S31 are substituted into the calculation formula in step S32 for fitting, and the values of and are determined.

[0037] It should be noted that other influence conditions include the influence of the response time length or the wear degree of the numerical control cutting machine on the cutting process; by establishing the time analysis model, the influence of the geometric shape (i.e., the total curvature) of the cutting plate piece in the raw material plate piece on the cutting processing time length is analyzed, the historical cutting data and the historical time data are analyzed, and is taken as a training parameter of , and is taken as a training parameter of , and is taken as a training parameter of ​the training parameters of the neural network are substituted into the calculation formula of step S32 respectively to perform fitting, and the values of the parameters are determined according to the least square method and Based on the geometric shapes corresponding to each board piece after being disassembled according to each customized furniture order, the total curvature of each board piece is obtained; and the total curvature data of all board pieces after being disassembled is obtained, the cutting processing time of each raw material board piece after being disassembled is predicted, so as to facilitate the formulation and execution of production plan; and it is especially suitable for the scheme with high complexity of cutting scheme after disassembly.

[0038] Step S4, according to the work task, the processing time required for cutting the next batch of raw material board pieces is obtained; before cutting the next batch of raw material board pieces, according to the time analysis model established in step S3 and the processing time required for cutting the next batch of raw material board pieces, the disassembly quantity of the next batch of customized furniture orders is adjusted.

[0039] Specifically, the method for adjusting the disassembly quantity of the next batch of customized furniture orders is: according to the work task, the processing time required for cutting the next batch of raw material board pieces is obtained ; different customized furniture orders of customers in the next batch are obtained, the priority of the customized furniture orders is sorted according to the order time of the customized furniture orders, and the number of cutting board pieces in each customized furniture order and the geometric shape of each cutting board piece are determined, the next batch of customized furniture orders is disassembled according to the priority, the cutting processing time of each raw material board piece after disassembly is predicted according to the established time analysis model, the cutting processing time of each raw material board piece after disassembly is accumulated to obtain the total cutting processing time of all raw material board pieces after disassembly, and the disassembly quantity of the next batch of customized furniture orders is calculated according to and the total cutting processing time of all raw material board pieces after disassembly , the disassembly quantity of the next batch of customized furniture orders is adjusted to ; wherein, satisfies the condition formula: ; wherein, represents the total cutting processing time of all raw material board pieces after disassembly of customized furniture orders.

[0040] Step S5, according to the disassembly quantity of the next batch of customized furniture orders, steps S1-S4 are repeated until all customized furniture orders are completed.

[0041] In this implementation, the next batch of customized furniture orders consists of 20 orders. Based on the order placement time, these orders are prioritized and processed to determine the required number of raw material panels and the corresponding cutting panels for each raw material panel. This yields the number of cutting panels and the total curvature of each cutting panel; the total curvature is determined based on the geometry of the cutting panels. Using a time analysis model, the processing time for each raw material panel after processing is predicted. The processing times for each raw material panel after processing are then summed to obtain the total processing time for all raw material panels after processing. The total processing time for cutting all raw material panels after order processing was analyzed, and it was found that the total processing time for cutting all raw material panels after order processing for the first 15 custom furniture orders met the requirements. Based on the given conditions and formulas, the order quantity for the next batch of customized furniture will be adjusted to 15.

[0042] It should be noted that by determining the total processing time for raw material panels in a custom furniture order, and calculating the number of orders to be processed for the next batch of custom furniture orders based on the work tasks, the resource allocation capability during the order processing of custom furniture orders is improved, thus meeting different production needs.

[0043] Furthermore, a human-machine interface is provided, allowing managers to adjust work tasks, determine the processing time required for the next batch of raw material panels, view different customized furniture orders from customers and the order processing status of different customized furniture orders; and view the cutting data of each raw material panel and the time data during the raw material panel cutting process through the establishment of a database.

[0044] In one embodiment, after the raw material panels are cut to obtain blank panels, the obtained blank panels need to be edge-banded. The task indicates that the next batch of customized furniture orders will be processed by rolling and cutting before the edge-banding of the current blank panels is completed. At this time, according to the task, the processing time required for cutting the next batch of raw material panels is obtained. Based on the processing time required for cutting the next batch of raw material panels and the total processing time for cutting all raw material panels after rolling, the number of rolls for the next batch of customized furniture orders is calculated and adjusted, thereby improving the utilization rate and production efficiency of the CNC cutting machine.

[0045] In another embodiment, the manager adjusts the work tasks through the human-computer interaction terminal and determines the processing time required for the next batch of raw material panels to be cut. At this time, based on the processing time required for the next batch of raw material panels to be cut manually determined by the manager and the total processing time for all raw material panels after the order is rolled, the number of orders to be rolled for the next batch of customized furniture orders is calculated and adjusted.

[0046] Please seeFigure 1 In the embodiment, a customized furniture intelligent integration order adjusting platform management system is provided, which comprises a customized furniture order management module, a device control module, a data acquisition module, a data analysis module, an order adjusting module and an interactive module.

[0047] The customized furniture order management module is configured to determine different customized furniture orders of customers, disassemble different customized furniture orders into a plurality of plate pieces respectively, re-layout the plurality of disassembled plate pieces in raw material plate pieces to obtain a cutting scheme after order adjustment of different customized furniture orders, send the cutting scheme after order adjustment of different customized furniture orders to the device control module and the data acquisition module, and send different customized furniture orders of customers to the order adjusting module and the interactive module.

[0048] The device control module is configured to control the device to perform cutting processing on the raw material plate pieces according to the cutting scheme sent by the customized furniture order management module, perform edge sealing, punching and slotting on the blank plate pieces obtained after the cutting processing, and obtain a plurality of plate pieces for production.

[0049] The data acquisition module is configured to acquire cutting data of each raw material plate piece in the cutting scheme according to the cutting scheme sent by the customized furniture order management module, wherein the cutting data comprises the number of cutting plate pieces in the raw material plate piece and the geometric shape of each cutting plate piece, and acquire time data of the raw material plate piece in the cutting processing from the device control module, wherein the time data comprises the cutting processing time length of each raw material plate piece, and send the acquired cutting data and time data to the data analysis module.

[0050] The data analysis module is configured to store the cutting data and time data sent by the data acquisition module as historical data, establish a time analysis model based on the historical cutting data and historical time data in the database, analyze the influence of the geometric shape of the cutting plate piece in the raw material plate piece on the cutting processing time, and send the stored historical cutting data and historical time data to the interactive module.

[0051] The order adjusting module is configured to obtain the processing time length required for cutting the next batch of raw material plate pieces according to the work task, adjust the order quantity of the next batch of customized furniture orders according to the time analysis model established in the data analysis module and the processing time length required for cutting the next batch of raw material plate pieces before cutting the next batch of raw material plate pieces, and send the order quantity of the next batch of customized furniture orders to the interactive module.

[0052] The interaction module is configured to provide a human-computer interaction terminal, and an administrator can adjust a work task on the human-computer interaction terminal, determine a processing time length required for cutting a next batch of raw material plates, check different customized furniture orders of a customer and order mixing of different customized furniture orders, and check historical cutting data of each raw material plate and historical time data in a cutting process of the raw material plate.

[0053] Further, the data analysis module comprises a historical data analysis unit, a model management unit and an intelligent calculation unit.

[0054] The historical data analysis unit is configured to analyze the historical cutting data to obtain a number of cut plates in each raw material plate and a geometric shape of each cut plate, determine a total curvature of each cut plate according to the geometric shape of each cut plate, and obtain a total curvature set of each cut plate in each raw material plate, and analyze the historical time data to determine a cutting processing time length of each raw material plate.

[0055] The model management unit is configured to establish a time analysis model, take the number of cut plates in the raw material plate and the total curvature of the cut plate as independent variables, and take the cutting processing time length of the raw material plate as a dependent variable, and analyze an influence of the geometric shape of the cut plate in the raw material plate on the cutting processing time length.

[0056] The intelligent calculation unit is configured to fit the influence of the geometric shape of the cut plate of the raw material plate on the cutting processing time length according to the historical cutting data and the historical time data analysis result in the historical data analysis unit.

[0057] Further, the order mixing adjustment module comprises a work task management unit and an order mixing quantity adjustment unit.

[0058] The work task management unit is configured to obtain the processing time length required for cutting the next batch of raw material plates according to the work task, and send the processing time length required for cutting the next batch of raw material plates to the order mixing quantity adjustment unit.

[0059] The order mixing quantity adjustment unit is configured to obtain different customized furniture orders of a customer in a next batch from the customized furniture order management module, sort priorities of the customized furniture orders, and determine a number of cut plates and a geometric shape of each cut plate in each customized furniture order, mix the next batch of customized furniture orders according to the priorities, predict a cutting processing time length of each plate in the customized furniture order according to the established time analysis model, accumulate the cutting processing time length of each plate to obtain a total cutting processing time length of the plates in the raw material plate in the customized furniture order, calculate and adjust a mixing quantity of the next batch of customized furniture orders according to the processing time length required for cutting the next batch of raw material plates and the total cutting processing time length of all raw material plates after the order mixing.

[0060] In the embodiment, the custom furniture order management module determines different custom furniture orders of the customer, and determines the cutting scheme after the order of each custom furniture order is adjusted.

[0061] The custom furniture order management module determines different custom furniture orders of the customer, and determines the cutting scheme after the order of each custom furniture order is adjusted.

[0062] The equipment control module controls the equipment to cut the raw material plate according to the cutting scheme sent by the custom furniture order management module, and performs edge sealing, punching and slotting on the blank plate obtained after cutting to obtain a plurality of plate pieces produced.

[0063] The data acquisition module acquires cutting data and time data of each raw material plate during the cutting process.

[0064] The historical data analysis unit in the data analysis module analyzes the historical cutting data and historical time data, and sends the historical data analysis result to the model management unit. The model management unit establishes a time analysis model to analyze the influence of the geometric shape of the cutting plate in the raw material plate on the cutting time. The intelligent calculation unit fits the influence of the geometric shape of the cutting plate in the raw material plate on the cutting time in the model management unit. The historical cutting data and historical time data are sent to the interactive module.

[0065] The work task management unit in the order adjustment module obtains the processing time required for cutting the next batch of raw material plates according to the work task. The work task management unit in the order adjustment module obtains the processing time required for cutting the next batch of raw material plates according to the work task. The order adjustment module adjusts the order quantity of the next batch of custom furniture orders. The order adjustment module adjusts the order quantity of the next batch of custom furniture orders.

[0066] When the management personnel adjusts the work task in the human-computer interaction end of the interactive module and determines the processing time required for cutting the next batch of raw material plates, the processing time required for cutting the next batch of raw material plates is sent to the order adjustment module.

[0067] Finally, it should be noted that the above only describes the preferred embodiments of the present application and is not intended to limit the present application. Although the present application has been described in detail with reference to the foregoing embodiments, those skilled in the art will appreciate that the technical solutions described in the foregoing embodiments can be modified or some technical features thereof can be replaced by equivalent features. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application shall be included in the protection scope of the present application.

Claims

1. A method for managing a customized furniture intelligent integrated order platform, characterized in that: The method includes the following steps: Step S1: Determine the custom furniture orders to be processed, break down each custom furniture order into several panels, rearrange each panel in several raw material panels to obtain a cutting plan after processing each custom furniture order; collect the cutting data of each raw material panel in the cutting plan; the cutting data includes the number of panels to be cut in each raw material panel and the geometry of each panel. Step S2: According to the cutting plan obtained in Step S1, each raw material board is cut, and the resulting blank board is edge-sealed, drilled, and grooved to obtain several produced boards; time data of the cutting process of each raw material board is collected; the time data includes the cutting time of each raw material board; specifically: according to the cutting plan, a CNC cutting machine is used to cut the raw material board to obtain several cut boards, each cut board corresponding to a blank board. The edges of the obtained blank boards are edge-sealed by a fully automatic cutting machine, and the edges of the blank boards are glued, pressed, trimmed, and polished. Then, a CNC six-sided drill is used to drill and groove the edge-sealed blank boards to obtain several boards from different customized furniture orders; Step S3: Establish a database, storing the cutting data collected in Step S1 and the time data collected in Step S2 as historical data; based on the historical cutting data and historical time data in the database, establish a time analysis model to analyze the impact of the geometry of the raw material sheet on the cutting processing time; the specific method steps are as follows: Step S31: Analyze the historical cutting data, determine the total curvature of each cut plate according to its geometry, and obtain the total curvature set of each cut plate in each raw material plate. Analyze historical time data to determine the processing time for each raw material panel. ;in, ; The first step in the analysis of historical segmentation data The total curvature set of all cut plates in a raw material plate; They represent the first The total curvature of each cut plate in a raw material plate; This indicates the number of raw material plates analyzed from historical cutting data. Indicates the first The number of cut plates in a raw material plate; Step S32: Establish a time analysis model to determine the number of cut plates in the raw material plates. and the total curvature of the cut sheet As an independent variable, the material cutting time of the raw material panels As the dependent variable, the influence of the geometry of the cut sheet in the raw material sheet on the cutting time is analyzed, according to the calculation formula: ;in, This represents the influence coefficients of the number of cut plates and the total curvature of the cut plates on the cutting processing time. Indicates the first of the raw material sheet parts The total curvature of each cut plate; This represents the influence coefficient of other influencing conditions on the material cutting processing time; Step S33: Substitute the historical cutting data and historical time data analysis results from step S31 into the calculation formula of step S32 for fitting, and determine... and The value; Step S4: Based on the task, obtain the processing time required for cutting the next batch of raw material panels; before cutting the next batch of raw material panels, adjust the number of orders for the next batch of customized furniture based on the time analysis model established in step S3 and the processing time required for cutting the next batch of raw material panels. Step S5: Based on the order quantity of the next batch of customized furniture orders, repeat steps S1-S4 until all customized furniture orders are completed.

2. The intelligent integrated order management method for customized furniture as described in claim 1, characterized in that: The method for adjusting the order quantity for the next batch of custom furniture orders is as follows: Based on the work task, determine the processing time required for cutting the raw material panels for the next batch. ; Obtain different custom furniture orders from customers in the next batch. Prioritize the custom furniture orders based on their order placement time, and determine the number and geometry of the cut panels in each order. Collate the next batch of custom furniture orders according to priority. Based on the established time analysis model, predict the processing time for each raw material panel after collating. Summate the processing times for each raw material panel after collating to obtain the total processing time for all raw material panels after collating. Based on the total processing time for all raw material panels after the initial batch of custom furniture orders, calculate the quantity of materials to be processed for the next batch of custom furniture orders. The order quantity for the next batch of custom furniture will be adjusted to... ;in, Formula that satisfies the condition: ;in, Indicates will The total time for cutting all raw material panels after a custom furniture order is finalized.

3. The intelligent integrated order management method for customized furniture according to claim 2, characterized in that: The task described refers to the process of processing all the raw panels in this batch, from the start of edge banding to obtaining all the panels. During this process, the processing of the next batch of customized furniture orders is completed, thereby obtaining the processing time required for the next batch of raw material panels. Based on the processing time required for the next batch of raw material panels and the total processing time for all raw material panels after processing, the number of processing orders for the next batch of customized furniture orders is calculated and adjusted.

4. The intelligent integrated order management method for customized furniture as described in claim 3, characterized in that: It provides a human-machine interface, which allows managers to adjust work tasks, determine the processing time required for the next batch of raw material panels, and view different customized furniture orders from customers and the order processing status of different customized furniture orders. By establishing a database, we can view the historical cutting data of each raw material sheet and the historical time data of the raw material sheet cutting process.

5. A customized furniture intelligent integrated order management platform system for implementing the customized furniture order management method according to any one of claims 1-4, characterized in that: The system includes a customized furniture order management module, an equipment control module, a data acquisition module, a data analysis module, a sample order adjustment module, and an interaction module. The customized furniture order management module is used to identify different customized furniture orders from customers, break down each customized furniture order into several panels, rearrange the disassembled panels in the raw material panels to obtain the cutting plan after the customized furniture order is processed; send the cutting plan after the customized furniture order is processed to the equipment control module and the data acquisition module; and send the different customized furniture orders from customers to the processing adjustment module and the interaction module. The equipment control module is used to control the equipment to cut raw material panels according to the cutting plan sent by the customized furniture order management module, and to seal, drill holes and groove the blank panels obtained after cutting to obtain several produced panels. The data acquisition module is used to collect cutting data of each raw material board in the cutting plan sent by the customized furniture order management module; the cutting data includes the number of cut boards in the raw material board and the geometry of each cut board; The system collects time data from the equipment control module during the raw material sheet cutting process; the time data includes the cutting time of each raw material sheet; and sends the collected cutting data and time data to the data analysis module. The data analysis module is used to store the cutting data and time data sent by the data acquisition module as historical data; based on the historical cutting data and historical time data in the database, a time analysis model is established to analyze the impact of the geometry of the cutting plate in the raw material plate on the cutting processing time; and the stored historical cutting data and historical time data are sent to the interaction module. The order adjustment module is used to obtain the processing time required for cutting the next batch of raw material panels according to the work task; before cutting the next batch of raw material panels, the order quantity for the next batch of customized furniture orders is adjusted according to the time analysis model established in the data analysis module and the processing time required for cutting the next batch of raw material panels. Send the order quantity for the next batch of customized furniture to the interaction module; The interactive module provides a human-machine interface, allowing managers to adjust work tasks, determine the processing time required for the next batch of raw material panels, view different customized furniture orders from customers and the order processing status of different customized furniture orders, and view historical cutting data and historical time data of each raw material panel during the raw material panel cutting process.

6. The customized furniture intelligent integrated order management platform system according to claim 5, characterized in that: The data analysis module includes a historical data analysis unit, a model management unit, and an intelligent computing unit; The historical data analysis unit is used to analyze historical cutting data to obtain the number of cut plates in each raw material plate and the geometry of each cut plate. Based on the geometry of each cut plate, the total curvature of each cut plate is determined, and the total curvature set of each cut plate in each raw material plate is obtained respectively. Analyze historical time data to determine the cutting time for each raw material panel; The model management unit is used to establish a time analysis model, taking the number of cut plates and the total curvature of the cut plates in the raw material plates as independent variables, and the cutting time of the raw material plates as dependent variables, to analyze the influence of the geometry of the cut plates in the raw material plates on the cutting time. The intelligent computing unit is used to fit the influence of the geometry of the raw material plate cutting board on the cutting time in the model management unit based on the historical cutting data and historical time data analysis results in the historical data analysis unit.

7. The customized furniture intelligent integrated order management platform system according to claim 6, characterized in that: The kneading order adjustment module includes a task management unit and a kneading order quantity adjustment unit; The task management unit is used to obtain the processing time required for cutting the next batch of raw material panels based on the task; and to send the processing time required for cutting the next batch of raw material panels to the order quantity adjustment unit. The order repackaging quantity adjustment unit is used to obtain different customized furniture orders from customers in the next batch from the customized furniture order management module, sort the priority of the customized furniture orders, determine the number of cut panels and the geometry of each cut panel in each customized furniture order, repack the next batch of customized furniture orders according to priority, predict the cutting processing time of each panel in the customized furniture order based on the established time analysis model, accumulate the cutting processing time of each panel to obtain the total cutting processing time of the panels in the customized furniture order in the raw material panels, calculate the repackaging quantity of the next batch of customized furniture orders and adjust it based on the processing time required for cutting the raw material panels in the next batch and the total cutting processing time of all raw material panels after repackaging.

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