Simulation method for designing panel furniture production line

Abstract

The present invention relates to the field of data processing technology, and in particular to a simulation method for designing a panel furniture processing production line. The method of the present invention comprises: obtaining historical panel production data and panel order requirements of customers; determining the production efficiency and production qualification rate of panels of different sizes on different equipment based on the historical panel production data; determining the production efficiency and production qualification rate of panels required by customers on different equipment based on the production efficiency and production qualification rate of historical panels; establishing constraints based on the panel order requirements; determining the panel processing production line of the customer through an optimization algorithm based on the constraints, and performing simulated production based on the panel processing production line. The present invention can reduce production costs to the maximum extent while meeting production task requirements.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and more specifically, to a simulation method for designing a panel furniture processing production line. Background Art

[0002] In the actual production of panel furniture, there are three main processes: cutting, edge banding and drilling. Generally, each process is equipped with multiple devices to cope with the production of panels for various orders. In actual production, manufacturers generally put all available production equipment into production directly according to customer order requirements to quickly complete customer orders within the specified time. However, this will result in low flexibility in production planning and uneven product quality produced by different equipment, and costs are difficult to control.

[0003] In recent years, with the rapid development of artificial intelligence technology, artificial intelligence technology has been applied in more and more fields, and artificial intelligence technology has also been applied in the production of panel furniture. For example, the Chinese patent application document with publication number CN109031948A discloses an optimization scheduling method for the production process of panel furniture products, which uses a corresponding optimization algorithm to schedule and optimize furniture production to ensure production efficiency, but it does not involve the control of production costs. In response to the problem of production cost control, the Chinese patent application document with publication number CN102183931B discloses a time-constrained mechanical processing production process optimization scheduling method, which uses a heuristic algorithm to optimize according to the time required for production and the electricity cost required for the production of each equipment, thereby simulating a low-cost equipment schedule and equipment work table that meets production requirements. Although it reduces the production cost to a certain extent, it is not suitable for the production optimization of panel furniture.

[0004] Therefore, how to design a panel furniture production line with minimized production costs according to customer order requirements is an urgent problem to be solved. Summary of the invention

[0005] In order to solve the above-mentioned technical problem of designing a panel furniture production line with low production cost according to the requirements of customer orders, the present invention provides the following solution.

[0006] The present invention provides a simulation method for designing a panel furniture processing production line, comprising: obtaining historical panel production data and panel order requirements of customers; determining the production efficiency and production qualification rate of panels of different sizes on different equipment according to the production efficiency and production qualification rate of the historical panels; determining the production efficiency and production qualification rate of panels required by customers on different equipment according to the production data of the historical panels; and establishing constraint conditions based on the panel order requirements, wherein the constraint conditions are:

[0007] ;

[0008] In the formula, represents the usage cost of the vth device in the wth link, represents the number of devices that customers need to use in the wth link, Indicates the number of type r plates in the customer's plate order represents the production qualification rate of the rth type of plate on the vth equipment in the wth link, represents the production efficiency of the r-th type of plate on the v-th device in the w-th link, T represents the maximum time to complete the plate production, Represents the total number of unused equipment in the wth link at present; according to the constraints, the customer's sheet metal processing production line is determined through the optimization algorithm, and simulated production is performed according to the sheet metal processing production line.

[0009] Beneficial effects: It can simulate a panel furniture processing production line that not only meets the customer's panel order requirements but also minimizes production costs, reducing the waste of resources and energy.

[0010] Furthermore, the production efficiency and production qualification rate of the plates required by the customer on different equipment are determined based on the production data of the historical plates, including: determining the plate with the smallest difference between the historical plates and the plates required by the customer based on the plate order demand, the difference including shape difference and size difference; and using the production efficiency and production qualification rate corresponding to the plate with the smallest difference as the production efficiency and production qualification rate of the plates required by the customer on different equipment.

[0011] Beneficial effect: By comprehensively considering the differences in shape and size of the two plates, the accuracy of determining the production efficiency and production qualification rate of the plates required by customers on different equipment is improved, thereby improving the accuracy of subsequent simulations.

[0012] Furthermore, the calculation expression for the difference between the plate required by the customer and the historical plate is:

[0013] ;

[0014] In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, It represents the mean of the length of the i-th type of plate from the customer and the length of the j-th type of plate from the history. It represents the mean value of the width of the i-th type of board provided by the customer and the width of the j-th type of board provided in history.

[0015] Furthermore, the calculation expression for the difference between the plate required by the customer and the historical plate is:

[0016] ;

[0017] In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, is the default value.

[0018] Furthermore, the preset value is 2.

[0019] Beneficial effect: By flexibly adjusting the preset value according to actual needs, the accuracy of the difference calculation between the two plates is improved.

[0020] Furthermore, the production efficiency and production qualification rate of plates of different sizes on different equipment are determined based on the historical plate production data, including: clustering the sizes of historical plates; and taking the production efficiency of the center point of the cluster as the production efficiency of all plates in the cluster on the equipment.

[0021] Beneficial effect: By taking into account the different production efficiencies of plates on different equipment in the same link, the accuracy of the subsequent production efficiency of the plates required by customers is improved.

[0022] Furthermore, K-Means clustering algorithm is used for clustering.

[0023] Furthermore, the equipment includes: a cutting machine, an edge banding machine and a drilling machine.

[0024] Furthermore, the plate order requirements include: order delivery time, plate size and corresponding quantity.

[0025] Furthermore, the production data includes: the size of the plate, the production efficiency and production quality of the plate on different equipment.

[0026] Beneficial effect: By considering the production quality of the plate on different equipment, the accuracy of the subsequent calculation of the production time of the plate in different links is improved.

[0027] The beneficial effect of the present invention is that the present invention determines the production efficiency and production qualification rate of the plates required by the customer through the production data of the historical plates, thereby improving the accuracy of the subsequent simulated production. Furthermore, the plate production and processing production line is determined according to the established constraint conditions, and the plate production and processing production line finally obtained can minimize the use cost of the equipment under the premise of ensuring the production task requirements, thereby reducing the waste of resources and energy, reducing production costs, and improving production efficiency. BRIEF DESCRIPTION OF THE DRAWINGS

[0028] By reading the following detailed description with reference to the accompanying drawings, the above and other objects, features and advantages of the exemplary embodiments of the present invention will become readily understood. In the accompanying drawings, several embodiments of the present invention are shown in an exemplary and non-limiting manner, and the same or corresponding reference numerals represent the same or corresponding parts, wherein:

[0029] Figure 1 is a schematic diagram schematically showing a panel furniture processing production line according to an embodiment of the present invention;

[0030] Figure 2 It is a flowchart schematically showing a simulation method for a panel furniture production line according to an embodiment of the present invention. DETAILED DESCRIPTION

[0031] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of the present invention.

[0032] The specific embodiments of the present invention are described in detail below with reference to the accompanying drawings.

[0033] Figure 1 Schematic diagram schematically showing a panel furniture processing production line according to an embodiment of the present invention.

[0034] Depend on Figure 1 It can be seen that in the panel furniture processing production line, there are four links: cutting, edge banding, drilling and sorting, and the number of equipment in each link is also different. In this embodiment, the simulation of the panel furniture processing production line mainly involves the three links of cutting, edge banding and drilling. In other optional embodiments, the link of sorting can also be added during the simulation. Among them, each link corresponds to a type of equipment, for example, the cutting link of the board corresponds to the cutting machine, the edge banding link of the board corresponds to the edge banding machine, and the drilling link of the board corresponds to the drilling machine.

[0035] Figure 2It is a flowchart schematically showing a simulation method for a panel furniture production line according to an embodiment of the present invention.

[0036] Depend on Figure 2 It can be seen that the simulation method for designing a panel furniture processing production line of the present invention includes:

[0037] S101. Obtain historical plate production data and customers' plate order requirements.

[0038] It can be understood that historical boards are boards that have completed production and processing.

[0039] In this embodiment, the historical production data of the plate includes the size of the plate, the production efficiency of the plate on different equipment, and the production quality (e.g., qualified production, unqualified production). The production qualification rate of the plate on different equipment can be determined according to the production quality of the plate on different equipment. By considering the production qualification rate of the plate on different equipment, the accuracy of the subsequent calculation of the production time occupied by the plate in different links is improved.

[0040] The types of equipment in the panel furniture processing production line may include: cutting machines, edge banding machines and drilling machines.

[0041] The customer's sheet metal order requirements may include: the time of order delivery, the size of the sheet metal, and the corresponding quantity. According to the time of customer order delivery, the maximum time (i.e., time threshold) for completing sheet metal production may be determined. In one embodiment, when determining the maximum time for completing sheet metal production, the time interval between two links may be taken into account to improve the accuracy of the simulation.

[0042] S102, determining the production efficiency and production qualification rate of plates of different sizes on different equipment according to the historical plate production data.

[0043] Specifically, first, the historical plates are clustered according to their sizes, and then the production efficiency corresponding to the center point of the cluster is used as the production efficiency of all the plates in the cluster on the equipment.

[0044] For example, in the material cutting process, the historical plates produced and processed by each material cutting machine are clustered separately. Assuming that one of the material cutting machines is clustered according to the size of the historical plates, 6 clusters are obtained, and the center point of one of the clusters is a plate with a size of 20cm×40cm. The production efficiency of this plate is used as the production efficiency of all plates in this cluster on this material cutting machine. Similarly, the production efficiency of plates in other clusters corresponding to this material cutting machine is determined in the same way.

[0045] It can be understood that after clustering is completed, the production efficiency of the plates in the same cluster on the same equipment is close. By using the production efficiency corresponding to the center point of the cluster as the production efficiency of all the plates in the cluster on the equipment, the accuracy of the subsequent determination of the production efficiency of the plates required by the customer can be improved.

[0046] Furthermore, the time required to complete the production and processing of the plate in each link is different, that is, the production efficiency is different. Furthermore, in the same link, different equipment has different production efficiency and production qualification rate. Even the same type of equipment will have different production efficiency and production qualification rate due to factors such as usage time. Therefore, by considering the different production efficiency of plates on different equipment in the same link, the accuracy of obtaining the production efficiency of historical plates is improved.

[0047] In this embodiment, the sizes of historical plates are clustered by using a K-Means clustering algorithm model. In other optional embodiments, those skilled in the art may also select a suitable clustering method according to actual needs.

[0048] Thus, the production efficiency of different sizes of historical plates on different equipment is obtained.

[0049] Furthermore, the production qualification rate of each type of historical plate on different equipment is determined. Specifically, the calculation expression of the production qualification rate is as follows:

[0050] ;

[0051] In the formula, It represents the production qualification rate of the s-th type of plate on the v-th equipment, It represents the number of qualified plates of type s produced on the vth equipment. Represents the total number of the s-th type of board produced on the v-th type of equipment.

[0052] Thus, the production qualification rates of plates of different sizes in the historical plates on different equipment are obtained.

[0053] S103, determining the production efficiency and production qualification rate of the plates required by the customer on different equipment according to the production efficiency and production qualification rate of the historical plates.

[0054] Specifically, according to the sizes of various plates in the customer's plate order requirements, determine the plate with the smallest difference between the historical plates and the plate required by the customer, and use the cluster to which the plate with the smallest difference belongs as the cluster of the plates required by the customer, that is, use the production efficiency corresponding to the cluster to which the plate with the smallest difference belongs as the production efficiency of the plates required by the customer. For example, if the customer's plate order requirements include plate A with a size of 20cm×40cm, calculate the differences between the customer's plate A and various plates in the historical plates, and if the difference between plate B in the historical plates and plate A required by the customer is the smallest, use the production efficiency of the cluster to which plate B belongs as the production efficiency of plate A required by the customer on the equipment.

[0055] It is understandable that in the cutting process, if there are 6 cutting machines, then sheet A should have 6 production efficiencies, that is, sheet A has different production efficiencies on different cutting machines. By considering the different production efficiencies of sheets on different equipment in the same process, the accuracy of obtaining the production efficiency of the sheets required by customers is improved.

[0056] In this embodiment, the difference between the two plates includes a size difference and a shape difference.

[0057] Specifically, the calculation expression for the difference between the two plates is as follows:

[0058] ;

[0059] In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, It represents the mean of the length of the i-th type of plate from the customer and the length of the j-th type of plate from the history. It represents the mean value of the width of the i-th type of board provided by the customer and the width of the j-th type of board provided in history.

[0060] in, Indicates the difference in length and width (i.e., size difference) between the two plates. represents the shape difference between the two sheets, Used to quantify the length, width and shape differences between two plates to the same order of magnitude.

[0061] It can be understood that if the difference between the length and width of two plates is large, and the difference between the shapes of the two plates is also large, it indicates that the difference between the two plates is large.

[0062] In an optional embodiment, the calculation expression of the difference between the two plates can also be:

[0063] ;

[0064] In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, is the default value.

[0065] in, Indicates the shape difference between the two plates. The greater the shape difference, the greater the difference between the two plates. It reflects the relationship between the shape difference between the two plates and the difference between the two plates.

[0066] In one embodiment, The value of is 2. In other optional embodiments, those skilled in the art can set the preset value according to actual needs. By flexibly adjusting the preset value according to actual needs, the accuracy of the difference calculation between the two plates is improved.

[0067] By comprehensively considering the size and shape differences between the two boards, the accuracy of finding the board with the smallest difference between the historical boards and the board required by the customer is improved, thereby improving the accuracy of subsequent panel furniture processing production line simulation.

[0068] In other optional embodiments, the difference between the two plates may also be determined by comparing the difference in area between the two plates.

[0069] Furthermore, the production qualification rate of the plate with the smallest difference on different equipment is used as the production qualification rate of the plate required by the customer on different equipment.

[0070] In this way, we can obtain the production efficiency and production qualification rate of various plates in the customer's plate orders on different equipment.

[0071] It is understandable that the above process of determining the production efficiency and production qualification rate of the plates required by the customer is actually to predict the production data of the plates required by the customer based on the production data of the historical plates. Determining the production efficiency and production qualification rate of the plates required by the customer through the production data of the historical plates improves the accuracy and pertinence of the subsequent simulated production.

[0072] S104: Establish constraint conditions based on the plate order demand.

[0073] Specifically, constraints are established based on the customer's board order requirements and their corresponding production data and unused equipment. In this embodiment, the constraints may include production time constraints, production cost constraints, and equipment quantity constraints. Specifically, since each link in the actual production of panel furniture is equipped with multiple devices to cope with the production and processing of multiple board orders, there will be used equipment and unused equipment in each link, and the equipment quantity constraint is established according to the number of unused equipment; further, since the equipment corresponding to each link is different, the production efficiency and production qualification rate corresponding to the production and processing of boards of different equipment are also different, and the production time constraint is established according to the production efficiency, production qualification rate of various boards on different equipment and the maximum time required for customer board production; further, since the number of equipment used in each link is different, the corresponding use cost is also different, therefore, the production cost constraint is established based on minimizing the production cost. For example, in the cutting link, there are three unused cutting machines, and considering the production cost constraint, only two cutting machines may be used.

[0074] Furthermore, the use cost of the equipment may include the purchase cost, maintenance cost and energy consumption cost of the equipment, wherein the energy consumption cost includes electricity cost and fuel cost. In one embodiment, the use cost of the equipment is the corresponding energy consumption cost. In another embodiment, the maintenance cost and the energy consumption cost may be comprehensively considered as the use cost of the equipment. For example, the use cost of the equipment is one-third of the maintenance cost and two-thirds of the energy consumption cost. Those skilled in the art may set it according to actual needs.

[0075] Specifically, in this embodiment, the constraints are:

[0076] ;

[0077] In the formula, represents the usage cost of the vth device in the wth link, represents the number of devices that customers need to use in the wth link, represents the quantity of the rth type of sheet in the customer's sheet order, represents the production qualification rate of the rth type of plate on the vth equipment in the wth link, represents the production efficiency of the r-th type of plate on the v-th device in the w-th link, T represents the maximum time to complete the plate production, Represents the total number of unused devices in the wth link.

[0078] In the above constraints, Represents the production cost constraint, which is the objective function to be achieved in the end. Specifically, for the customer's sheet metal order demand, if two cutting machines are used in the first link, the use cost of these two cutting machines is calculated; if three drilling machines are used in the second link, the use cost of these three drilling machines is calculated; if two edge banding machines are used in the third link, the use cost of these two edge banding machines is calculated. Finally, the total use cost corresponding to these three links is accumulated to obtain the production cost of this equipment combination (i.e. sheet metal processing production line).

[0079] Further, Represents the production time constraint. Specifically, if three cutting machines are used in the first link (i.e., the cutting link), the largest production time among the production times corresponding to the three cutting machines is selected as the production time of the first link. Similarly, the production time of other links is counted, and then the production time of each link is summed up to obtain the production time of producing plates of this size. Similarly, the production time of plates of other sizes required by the customer is obtained, and then the production time of all the customer's plates is summed up to obtain the production time for the customer to complete the plate order.

[0080] S105 . Determine the customer's sheet metal processing production line through an optimization algorithm according to the constraint conditions, and perform simulated production according to the sheet metal processing production line.

[0081] Determine the cost of using different numbers of equipment in each link, combine the number of currently idle equipment in each link and the delivery time of customer orders, and use the optimization algorithm to find the equipment combination with the lowest production cost, thereby determining the customer's sheet metal processing production line.

[0082] Furthermore, when the optimization algorithm obtains multiple sheet metal processing production lines, these sheet metal processing production lines can be presented to customers, allowing them to choose according to their actual needs. Of course, it is also possible to combine the subsequent orders of other customers to determine the sheet metal processing production line for the current customer by judging in which link the next customer uses a larger number of equipment, thereby improving the flexibility and efficiency of sheet metal processing production. For example, for the sheet metal order demand of the current customer, three sheet metal processing production lines are obtained through the optimization algorithm. At this time, according to the sheet metal order demand of the next customer, it is determined that the sheet metal of the next customer takes up more time in the drilling link. Then, the sheet metal processing production line that occupies the least number of drilling machines among the above three sheet metal processing production lines can be selected as the sheet metal processing production line for the current customer, thereby improving the flexibility and efficiency of sheet metal processing production, and thus increasing profits.

[0083] In this embodiment, the optimization algorithm adopts a heuristic algorithm. In other optional embodiments, those skilled in the art can make a selection according to actual needs.

[0084] In the description of this specification, “plurality” means at least two, such as two, three or more, etc., unless otherwise clearly and specifically defined.

[0085] Although this specification has shown and described a number of embodiments of the present invention, it will be apparent to those skilled in the art that such embodiments are provided by way of example only. Those skilled in the art will conceive of many modifications, changes and alternatives without departing from the ideas and spirit of the present invention. It should be understood that in the practice of the present invention, various alternatives to the embodiments of the present invention described herein may be employed.

Claims

1. A simulation method for designing a panel furniture processing production line, characterized in that: include: Obtain historical sheet production data and customers’ sheet order requirements; Determine the production efficiency and production qualification rate of plates of different sizes on different equipment according to the historical plate production data; Determine the production efficiency and production qualification rate of the plates required by the customer on different equipment based on the production efficiency and production qualification rate of the historical plates; A constraint condition is established based on the plate order demand, wherein the constraint condition is: ； In the formula, represents the usage cost of the vth device in the wth link, Represents the production cost constraint, which means that it can minimize the value of the objective function to be achieved. represents the number of devices that customers need to use in the wth link, represents the quantity of the rth type of sheet in the customer's sheet order, represents the production qualification rate of the rth type of plate on the vth equipment in the wth link, represents the production efficiency of the r-th type of plate on the v-th device in the w-th link, T represents the maximum time to complete the plate production, represents the total number of unused devices in the w-th link at present, w represents the w-th link, v represents the v-th device, and r represents the r-th type of board; According to the constraints, the customer's sheet metal processing production line is determined through an optimization algorithm, and simulated production is performed based on the sheet metal processing production line.

2. The simulation method for panel furniture processing production line design according to claim 1, characterized in that: The production efficiency and production qualification rate of the plates required by the customer on different equipment are determined based on the production efficiency and production qualification rate of the historical plates, including: determining the plate with the smallest difference between the historical plates and the plates required by the customer based on the plate order demand, the difference including shape difference and size difference; and using the production efficiency and production qualification rate corresponding to the plate with the smallest difference as the production efficiency and production qualification rate of the plates required by the customer on different equipment.

3. The simulation method for designing a panel furniture processing production line according to claim 2, characterized in that: The calculation expression for the difference between the plate required by the customer and the historical plate is: ； In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, It represents the mean of the length of the i-th type of plate from the customer and the length of the j-th type of plate from the history. It represents the mean value of the width of the i-th type of board provided by the customer and the width of the j-th type of board provided in history.

4. The simulation method for designing a panel furniture processing production line according to claim 2, characterized in that: The calculation expression for the difference between the plate required by the customer and the historical plate is: ； In the formula, represents the difference between the customer's i-th plate and the historical j-th plate, Indicates the length of the i-th type of board of the customer, Indicates the width of the customer's i-th plate, represents the length of the jth type of plate in history, represents the width of the j-th plate in history, is the default value.

5. The simulation method for designing a panel furniture processing production line according to claim 4, characterized in that: The preset value is 2.

6. The simulation method for designing a panel furniture processing production line according to claim 1, characterized in that: The production efficiency and production qualification rate of plates of different sizes on different equipment are determined according to the production data of historical plates, including: clustering the sizes of historical plates; and taking the production efficiency of the center point of the cluster as the production efficiency of all plates in the cluster on the equipment.

7. The simulation method for designing a panel furniture processing production line according to claim 6, characterized in that: K-Means clustering algorithm is used for clustering.

8. The simulation method for designing a panel furniture processing production line according to claim 1, characterized in that: The equipment includes: a cutting machine, an edge banding machine and a drilling machine.

9. The simulation method for designing a panel furniture processing production line according to claim 1, characterized in that: The plate order requirements include: order delivery time, plate size and corresponding quantity.

10. The simulation method for designing a panel furniture processing production line according to claim 1, characterized in that: The production data includes: the size of the plate, the production efficiency of the plate on different equipment, and the production quality.

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