Washing machine roller stamping part production optimization method and system based on big data

Abstract

The invention relates to a washing machine roller stamping part production optimization method and system based on big data, and relates to the field of intelligent production technologies, and the method comprises the steps: obtaining an external detail order; determining a required production type and a corresponding required production quantity according to the external detail order; determining a typesetting planning region corresponding to the required production type according to a preset region matching relationship; and according to the required production quantity and the typesetting planning area, performing arrangement simulation to determine a used cutting combination, and according to the used cutting combination, processing the raw material. The stamping part has the effect of reducing waste of raw materials for stamping part production so as to reduce the stamping part production cost.

Description

Technical Field

[0001] The present application relates to the field of intelligent production technology, and in particular to a method and system for optimizing the production of washing machine drum stamping parts based on big data. Background Art

[0002] Washing machine drum stamping parts refer to parts used in the manufacture of washing machine drums that are processed through a stamping process, mainly including the outer shell and inner drum of the washing machine drum.

[0003] Before the production of washing machine drum stamping parts, the plate needs to be laid out and cut to obtain raw material plates that can meet the requirements of stamping production. At present, in general, the staff will first lay out and determine the raw material plates of various types of stamping parts. When stamping parts need to be processed, the plates only need to be processed according to the processing volume.

[0004] In the above-mentioned related technologies, generally when receiving external orders, there will be multiple types of stamping parts that need to be produced. At this time, the layout and cutting of each type of plate are independent of each other. There may be a situation where the remaining materials of some types of stamping parts can be used for the production of other types of stamping parts. That is, there is a waste of raw materials, which leads to an increase in the production cost of stamping parts. There is still room for improvement. Summary of the invention

[0005] In order to reduce the waste of raw materials in stamping parts production and thus lower the production cost of stamping parts, the present application provides a method and system for optimizing the production of washing machine drum stamping parts based on big data.

[0006] In the first aspect, the present application provides a method for optimizing the production of washing machine drum stamping parts based on big data, which adopts the following technical solutions: A method for optimizing the production of washing machine drum stamping parts based on big data, comprising: Get external detail order; Determine the required production type and corresponding required production quantity based on external detailed orders; Determine the layout planning area corresponding to the required production type based on the preset area matching relationship; Randomly select any number of demand production types to construct a product type combination, and randomly generate the number of simulation types according to the demand production types in the product type combination; According to the number of simulated types and the corresponding layout planning areas, a type layout scheme is randomly arranged on the preset original plate area to output a type layout scheme, and a type layout scheme in which all plate planning areas are within the original plate area and the plate planning areas do not overlap is defined as a valid layout scheme for the product type combination; Randomly generate a number of scheme selections according to each valid typesetting scheme, and combine the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination; Determine the simulated production quantity of each demand production type according to the number of scheme selections and the number of simulated types of each demand production type in the effective typesetting scheme; The effective cutting combination when the simulated production quantity of each demand production type is not less than the corresponding demand production quantity is defined as a reasonable cutting combination, and the original demand quantity is determined by summing up the selected quantities of the solutions in the reasonable cutting combination; The original demand quantity with the smallest value is determined according to a preset sorting rule, and a reasonable cutting combination corresponding to the original demand quantity is defined as a use cutting combination, and the raw materials are processed according to the use cutting combination.

[0007] Optionally, the step of randomly arranging the simulated types and the corresponding layout planning areas on the preset original plate area to output the type layout plan includes: Determine the regional feature points corresponding to the layout planning area according to the preset feature matching relationship; Determine the point spacing distance according to the regional feature points and the contour points on the contour line of the layout planning area, and define the point spacing distance with the smallest value as the reference spacing distance; A layout planning area is randomly selected to arrange the regional feature points on the original plate area, and a do not disturb area is defined according to the regional feature points and the reference distance; Update the area on the original plate area except the Do Not Disturb area to the new original plate area, and select the layout planning area again for layout according to the new original plate area, until all layout planning areas are arranged to output the type layout plan.

[0008] Optionally, the step of randomly selecting a layout planning area to arrange the regional feature points on the original plate area includes: A virtual position point is randomly generated on the original plate area, and a virtual spacing distance is determined according to the virtual position point and the contour point of the contour line of the original plate area; A virtual position point whose virtual spacing distance is not less than the reference spacing distance of the current layout planning area is defined as a valid position point; A valid position set is formed according to all valid position points, and the regional feature points of the layout planning area are arranged only within the valid position set.

[0009] Optionally, after the effective layout plan is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: In each valid layout plan, valid layout plans with the same required production type and the same number of corresponding simulation types are defined as similar layout plans; In similar layout schemes, the regional gap distance is determined according to each layout planning area, and the average of all regional gap distances is calculated to determine the regional mean distance; The regional mean distance with the largest value is determined according to the sorting rules, and the other similar layout schemes other than the effective layout scheme corresponding to the regional mean distance are deleted.

[0010] Optionally, after the original demand quantity is determined, the washing machine drum stamping parts production optimization method based on big data also includes: Determine whether there are at least two reasonable cutting combinations with the same and minimum original demand quantity; If there are not at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as the used cutting combination; If there are at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as the alternative cutting combination; The excess production quantity is determined by performing difference calculation based on the simulated production quantity of each required production type in the alternative cutting combination and the corresponding required production quantity; Construct a historical interval with the current time point as the end point and a width of the preset historical length on the preset time axis, and determine the historical production quantity in the historical interval according to the current demand production type; Calculate based on each historical production quantity to determine the historical production proportion of each demand production type; The single excess parameter is determined by calculating the historical production ratio and the corresponding current excess production quantity, and the combined excess parameter is determined by summing up all the single excess parameters; The combined redundant parameter with the largest value is determined according to the sorting rule, and the candidate cutting combination corresponding to the combined redundant parameter is determined as the used cutting combination.

[0011] Optionally, after the combined redundant parameters are determined, the washing machine drum stamping parts production optimization method based on big data further includes: Determine whether there are at least two candidate cutting combinations with the same and largest combination redundant parameters; If there are not at least two candidate cutting combinations with the same and largest combined redundant parameters, the candidate cutting combination corresponding to the largest combined redundant parameter is determined as the used cutting combination; If there are at least two candidate cutting combinations with the same combined redundant parameters and the largest, the candidate cutting combination corresponding to the largest combined redundant parameter is defined as the waiting cutting combination; Determine the number of single board types in the combination waiting for cutting according to the required production types in each valid layout plan; The mean type quantity is determined by performing mean calculation according to the number of all single board types, and the waiting cutting combination corresponding to the mean type quantity with the smallest value is determined as the used cutting combination.

[0012] In the second aspect, the present application provides a washing machine drum stamping parts production optimization system based on big data, which adopts the following technical solutions: A big data-based washing machine drum stamping parts production optimization system, including: Acquisition module, used to obtain external detailed orders; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the required production type and the corresponding required production quantity according to the external detailed order; The processing module determines the layout planning area corresponding to the required production type according to the preset area matching relationship; The processing module randomly selects any number of demand production types to construct a product type combination, and randomly generates a number of simulation types according to the demand production types in the product type combination; The processing module randomly arranges the simulated types and the corresponding layout planning areas on the preset original plate area to output a type layout plan, and defines a type layout plan in which all the plate planning areas are within the original plate area and the plate planning areas do not overlap as a valid layout plan for the product type combination; The processing module randomly generates a number of scheme selections according to each valid typesetting scheme, and combines the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination; The processing module determines the simulated production quantity of each demand production type according to the number of scheme selections and the number of simulated types of each demand production type in the effective typesetting scheme; The processing module defines the effective cutting combination when the simulated production quantity of each demand production type determined by the determination module is not less than the corresponding demand production quantity as a reasonable cutting combination, and performs sum calculation based on the solution selection quantity in the reasonable cutting combination to determine the original demand quantity; The processing module determines the original demand quantity with the smallest value according to a preset sorting rule, defines a reasonable cutting combination corresponding to the original demand quantity as a use cutting combination, and processes the raw materials according to the use cutting combination.

[0013] In a third aspect, the present application provides a computer storage medium capable of storing corresponding programs, which has the characteristics of reducing the waste of raw materials in stamping parts production to reduce the production cost of stamping parts, and adopts the following technical solutions: A computer-readable storage medium stores a computer program that can be loaded by a processor and execute any of the above-mentioned methods for optimizing the production of washing machine drum stamping parts based on big data.

[0014] In summary, the present application includes at least one of the following beneficial technical effects: 1. In the production process of washing machine drum stamping parts, the raw material plates can be reasonably arranged according to the actual order situation, so that the raw material plates used can be minimized while meeting the production requirements, reducing the waste of raw materials and reducing production costs; 2. According to the production status of various types of stamping parts under historical orders, a reasonable combination of solutions can be selected. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 It is a flow chart of the production optimization method of washing machine drum stamping parts based on big data.

[0016] Figure 2 It is a module flow chart of the production optimization method of washing machine drum stamping parts based on big data. DETAILED DESCRIPTION

[0017] In order to make the purpose, technical solutions and advantages of this application more clear, the following Figure 1-Figure 2 It should be understood that the specific embodiments described herein are only used to explain the present application and are not used to limit the present application.

[0018] The embodiments of the present application are further described in detail below in conjunction with the drawings in the specification.

[0019] The present application embodiment discloses a method for optimizing the production of washing machine drum stamping parts based on big data, referring to Figure 1 The method flow of the washing machine drum stamping parts production optimization method based on big data includes the following steps: Step S100: Obtain external detailed orders.

[0020] External detailed orders are orders received from outside for the production and manufacturing of washing machine drum stamping parts.

[0021] Step S101: Determine the required production type and the corresponding required production quantity according to the external detailed order.

[0022] The required production type refers to the type of stamping parts that need to be produced, and the required production quantity refers to the quantity of each type of stamping parts that need to be produced.

[0023] Step S102: Determine the layout planning area corresponding to the required production type according to the preset area matching relationship.

[0024] The layout planning area is the area of ​​the original plate that the stamping parts of the required production type need to occupy. This area includes the size and shape. Stamping parts of different required production types have different sizes and shapes, and the corresponding layout planning areas are also different. The area matching relationship between the two can be determined and entered in advance by the staff.

[0025] Step S103: randomly selecting any number of demand production types to construct a product type combination, and randomly generating a number of simulation types according to the demand production types in the product type combination.

[0026] The product type combination is a combination of randomly selected demand production types, and the number of simulation types is the number of randomly selected demand production types. For example, there are two demand production types A and B. At this time, the number of simulation types can be 2 A and 0 B, or 3 A and 1 B. There are countless combinations, and you can just randomly select them. In order to ensure that the selected combination can be cut as much as possible in the subsequent process, the number of selected simulation types cannot be higher than the preset fixed number, where the fixed number is the maximum number of stamping materials of the demand production type that can be cut from an original plate. Therefore, different demand production types correspond to different fixed numbers, and the specific number is entered by the staff according to the actual situation.

[0027] Step S104: Randomly arrange the simulated types and the corresponding layout planning areas on the preset original plate area to output a type layout plan, and define the type layout plan in which all plate planning areas are within the original plate area and the plate planning areas do not overlap as a valid layout plan for the product type combination.

[0028] The original plate area is the entire area of ​​the original plate that has not been cut. The simulation of the plate layout situation can be achieved by placing the layout planning areas of each required production type in the product type combination in the original plate area according to the number of simulated types. The type layout plan is the layout plan obtained after typesetting. When all plate planning areas are within the original plate area and the plate planning areas do not overlap, it means that the original plate can be better cut into the original material of stamping parts that meet each required production type according to the type layout plan. At this time, it is defined as a valid layout plan to distinguish different types of layout plans, which is convenient for subsequent analysis.

[0029] Step S105: randomly generating a number of scheme selections according to each valid typesetting scheme, and combining the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination.

[0030] The number of scheme selections is the number of single valid typesetting schemes selected, that is, a simulated selection of the original sheet material of a single valid typesetting scheme; the effective cutting combination is a combination of valid typesetting schemes and the corresponding number of scheme selections, which is a combination of schemes for unified processing of the entire original sheet material.

[0031] Step S106: Determine the simulated production quantity of each required production type according to the scheme selection quantity and the simulated type quantity of each required production type in the valid typesetting scheme.

[0032] The materials of stamping parts that can be cut out from the original sheet corresponding to a single effective layout scheme are different. At this time, the number of materials that can be obtained for stamping parts of a required production type can be obtained by multiplying the number of scheme selections by the number of simulation types of each required production type in the scheme and summing them up, which is also the simulated production quantity. For example, there are two effective layout schemes, the first one is 3 A and 1 B, and the second one is 3 A and 1 C. At this time, the number of scheme selections for the first effective layout scheme is 5, and the number of scheme selections for the second effective layout scheme is 10. Then, the material that can be obtained for stamping parts with required production type A is 45, the material that can be obtained for stamping parts with required production type B is 5, and the material that can be obtained for stamping parts with required production type C is also 5.

[0033] Step S107: define the effective cutting combination when the simulated production quantity of each required production type is not less than the corresponding required production quantity as a reasonable cutting combination, and perform sum calculation based on the solution selection quantity within the reasonable cutting combination to determine the original required quantity.

[0034] When the simulated production quantity of each required production type is not less than the corresponding required production quantity, it means that the raw materials of each type of stamping parts can meet the demand. At this time, the corresponding effective cutting combination is defined as a reasonable cutting combination to distinguish different effective cutting combinations, which is convenient for subsequent analysis; the original demand quantity is the number of original plates required, and an effective layout plan corresponds to an original plate. Therefore, the original demand quantity can be determined by adding the number of selected plans.

[0035] Step S108: determining the original required quantity with the smallest value according to a preset sorting rule, defining a reasonable cutting combination corresponding to the original required quantity as a used cutting combination, and processing the raw materials according to the used cutting combination.

[0036] The sorting rule is a method set by the staff to sort the size of values, such as the bubbling method. The sorting rule can be used to determine the original demand quantity with the smallest value, that is, the number of original plates required to meet the production requirements is the least. Therefore, the corresponding reasonable cutting combination is defined as the use of cutting combinations for raw material processing, which reduces the use of original plates, thereby reducing production costs and achieving production cost optimization of washing machine drum stamping parts.

[0037] The steps of randomly arranging the simulated types and the corresponding layout planning areas on the preset original plate area to output the type layout plan include: Step S200: determining the regional feature points corresponding to the layout planning area according to a preset feature matching relationship.

[0038] The regional feature point is a fixed position point on the typesetting planning area. Generally, the regional feature point is the center point of the typesetting planning area. The specific position is determined in advance by the staff and the feature matching relationship is established.

[0039] Step S201: determining the point spacing distance according to the regional feature points and the contour points on the contour line of the layout planning area, and defining the point spacing distance with the smallest value as the reference spacing distance.

[0040] The point spacing distance is the straight-line distance between the regional feature point and the contour point on the contour line of the layout planning area. The benchmark spacing distance is defined to distinguish different point spacing distances for subsequent analysis.

[0041] Step S202: randomly selecting a layout planning area to arrange the regional feature points on the original plate area, and defining a do-not-disturb area according to the regional feature points and the reference spacing distance.

[0042] By arranging the regional feature points on the original plate area, the layout simulation of the layout planning area can be realized. At this time, the do not disturb area delineated with the regional feature point as the center and the reference distance as the radius is the area where the regional feature points of the remaining layout planning areas cannot be placed. Because when the remaining regional feature points are in the do not disturb area, there will definitely be area overlap. At this time, the solution obtained is definitely not a valid layout solution.

[0043] Step S203: Update the area on the original plate area except the do not disturb area to a new original plate area, and select the layout planning area again for layout according to the new original plate area, until all layout planning areas are arranged to output the type layout plan.

[0044] By continuously updating the original plate area, effective layout of each layout planning area can be achieved, thereby reducing the number of layout planning areas as much as possible, reducing the amount of data processing and improving overall work efficiency.

[0045] The steps of randomly selecting a layout planning area to arrange the regional feature points on the original plate area include: Step S300: randomly generate a virtual position point on the original plate area, and determine the virtual spacing distance according to the virtual position point and the contour points of the contour line of the original plate area.

[0046] The virtual position point is a position point on the original plate area, and the virtual interval distance is a distance value between the virtual position point and a contour point of the contour line of the original plate area.

[0047] Step S301: defining a virtual position point whose virtual spacing distance is not less than the reference spacing distance of the current layout planning area as a valid position point.

[0048] When the virtual spacing distance is not less than the baseline spacing distance of the current layout planning area, it means that when the layout planning area is placed under the virtual position point, the two layout planning areas will not overlap. At this time, it is defined as a valid position point for identification to facilitate subsequent analysis.

[0049] Step S302: construct a valid position set based on all valid position points, and arrange the regional feature points of the layout planning area only within the valid position set.

[0050] The valid position set is a set consisting of all the determined valid position points. By arranging the regional feature points only within the valid position set, the number of arrangement times of the layout planning area can be reduced, thereby improving the overall work efficiency.

[0051] After the effective layout plan is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: Step S400: In each valid layout scheme, valid layout schemes having the same required production type and the same number of corresponding simulation types are defined as similar layout schemes.

[0052] Define similar layout schemes to determine effective layout schemes that can produce the same effect, which is convenient for subsequent analysis.

[0053] Step S401: determining the regional gap distance according to each layout planning area in a similar layout scheme, and performing an average calculation based on all regional gap distances to determine the regional mean distance.

[0054] The regional gap distance is the distance value between a single typesetting planning area and the other typesetting planning areas. In the current situation, the regional gap distance of a single typesetting planning area can be determined by averaging all distance values ​​between a single typesetting planning area and the other typesetting planning areas; the regional mean distance is the average value of all regional gap distances.

[0055] Step S402: Determine the area mean distance with the largest value according to the sorting rule, and delete the other similar layout schemes except the valid layout scheme corresponding to the area mean distance.

[0056] The sorting rules can be used to determine the mean distance of the area with the largest value. That is, at this time, the gaps between the layout planning areas are larger, which is convenient for subsequent cutting. Therefore, only the effective layout plan needs to be retained to reduce the occurrence of repeated processing of data that can achieve the same effect in the future.

[0057] After the original demand quantity is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: Step S500: Determine whether there are at least two reasonable cutting combinations with the same and smallest original demand quantities.

[0058] The purpose of the judgment is to find out whether there are multiple reasonable cutting combinations that meet the requirements, so as to determine the only cutting combination to be used.

[0059] Step S5001: If there are not at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as the used cutting combination.

[0060] When there are not at least two reasonable cutting combinations with the same and smallest original demand quantities, it means that there is only one reasonable cutting combination that meets the requirements, and it can be determined as the cutting combination to be used.

[0061] Step S5002: If there are at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as an alternative cutting combination.

[0062] When there are at least two reasonable cutting combinations with the same and smallest original demand quantity, it means that there are multiple reasonable cutting combinations that meet the requirements. At this time, they are defined as alternative cutting combinations to distinguish different reasonable cutting combinations for subsequent analysis.

[0063] Step S501: performing difference calculation based on the simulated production quantity of each required production type in the candidate cutting combination and the corresponding required production quantity to determine the excess production quantity.

[0064] The excess production quantity is the excess material quantity that will be obtained after cutting according to the layout based on the plan, and is determined by subtracting the corresponding demand production quantity from the simulated production quantity.

[0065] Step S502: constructing a historical interval with the current time point as the end point and a width of the preset historical duration on the preset time axis, and determining the historical production quantity in the historical interval according to the current demand production type.

[0066] The time axis is a coordinate axis formed by the combination of various time points. The coordinate axis points from the time points that have passed to the time points that have not yet arrived, where the time points that have passed are the left side of the time axis, and the left side of the time axis is defined as the front; the historical duration is the duration set by the staff to obtain data on the historical order status of stamping parts. This duration is a fixed duration. By constructing a historical interval, it is convenient to obtain and analyze data within the historical duration; the historical production quantity is the total amount of stamping parts of a single demand production type produced in the historical interval.

[0067] Step S503: Calculate according to each historical production quantity to determine the historical production proportion of each required production type.

[0068] The historical production proportion refers to the production ratio of stamping parts of a single demand production type to all demand production types of stamping parts. It is determined by dividing a single historical production quantity by the sum of all historical production quantities. The larger the value, the larger the production quantity of this stamping part in history, which means it is the most popular. At this time, the excess stamping parts are more likely to be used later.

[0069] Step S504: Calculate and determine the single redundant parameter according to the historical production ratio and the current corresponding redundant production quantity, and sum up all the single redundant parameters to determine the combined redundant parameter.

[0070] The single excess parameter is the value of the historical production ratio multiplied by the excess production quantity, and the combined excess parameter is the sum of all single excess parameters.

[0071] Step S505: determining the combined redundant parameter with the largest value according to the sorting rule, and determining the candidate cutting combination corresponding to the combined redundant parameter as the used cutting combination.

[0072] The redundant parameter of the combination with the largest value can be determined through the sorting rules, that is, the possibility that the redundant stamping parts produced at this time will be consumed later is the highest, so the corresponding alternative cutting combination can be determined as the cutting combination to be used.

[0073] After the combination of redundant parameters is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: Step S600: Determine whether there are at least two candidate cropping combinations with the same and largest combination redundant parameters.

[0074] The purpose of the judgment is to find out whether there are multiple candidate cutting combinations that meet the combination redundant parameter requirements, so as to determine the only cutting combination to be used.

[0075] Step S6001: If there are not at least two candidate cropping combinations with the same and largest combined redundant parameters, the candidate cropping combination corresponding to the largest combined redundant parameter is determined as the used cropping combination.

[0076] When there are not at least two candidate cutting combinations with the same and largest redundant parameters, it means that there is only one candidate cutting combination that meets the requirements, and it can be determined as the used cutting combination.

[0077] Step S6002: If there are at least two candidate cutting combinations with the same combined redundant parameters and the largest one, the candidate cutting combination corresponding to the largest combined redundant parameter is defined as the waiting cutting combination.

[0078] When there are at least two candidate cutting combinations with the same and largest combination redundant parameters, it means that there are multiple candidate cutting combinations that meet the requirements. At this time, a waiting cutting combination is defined to distinguish different candidate cutting combinations for subsequent analysis.

[0079] Step S601: determining the number of single board types according to the required production types in each valid layout scheme in the waiting cutting combination.

[0080] The number of single board types is the number of required production types in a single valid layout plan.

[0081] Step S602: performing mean calculation according to the number of all single board types to determine the mean type number, and determining the waiting cutting combination corresponding to the mean type number with the smallest value as the used cutting combination.

[0082] The mean type quantity is the average of all single board type quantities. The smallest mean type quantity indicates that the number of stamping parts required to be cut out from an original plate is the least, which is the most convenient for processing. Therefore, the corresponding waiting cutting combination can be determined as the using cutting combination.

[0083] Reference Figure 2 Based on the same inventive concept, an embodiment of the present invention provides a washing machine drum stamping parts production optimization system based on big data, comprising: Acquisition module, used to obtain external detailed orders; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the required production type and the corresponding required production quantity according to the external detailed order; The processing module determines the layout planning area corresponding to the required production type according to the preset area matching relationship; The processing module randomly selects any number of demand production types to construct a product type combination, and randomly generates a number of simulation types according to the demand production types in the product type combination; The processing module randomly arranges the simulated types and the corresponding layout planning areas on the preset original plate area to output a type layout plan, and defines a type layout plan in which all the plate planning areas are within the original plate area and the plate planning areas do not overlap as a valid layout plan for the product type combination; The processing module randomly generates a number of scheme selections according to each valid typesetting scheme, and combines the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination; The processing module determines the simulated production quantity of each demand production type according to the number of scheme selections and the number of simulated types of each demand production type in the effective typesetting scheme; The processing module defines the effective cutting combination when the simulated production quantity of each demand production type determined by the determination module is not less than the corresponding demand production quantity as a reasonable cutting combination, and performs sum calculation based on the solution selection quantity in the reasonable cutting combination to determine the original demand quantity; The processing module determines the original demand quantity with the smallest value according to a preset sorting rule, defines a reasonable cutting combination corresponding to the original demand quantity as a use cutting combination, and processes the raw materials according to the use cutting combination; A type layout scheme determination module is used to determine the type layout scheme; The regional feature point arrangement module is used to determine the specific arrangement of the regional feature points; An effective typesetting scheme selection module is used to select and process partially identical effective typesetting schemes; A reasonable cutting combination screening module is used to screen multiple reasonable cutting combinations that meet the requirements; The alternative cutting combination screening module is used to screen multiple alternative cutting combinations that meet the requirements.

[0084] Those skilled in the art can clearly understand that for the convenience and simplicity of description, only the division of the above-mentioned functional modules is used as an example. In actual applications, the above-mentioned functions can be assigned to different functional modules as needed, that is, the internal structure of the device is divided into different functional modules to complete all or part of the functions described above. The specific working process of the system, device and unit described above can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.

[0085] An embodiment of the present invention provides a computer-readable storage medium storing a computer program that can be loaded by a processor and executed by a method for optimizing the production of washing machine drum stamping parts based on big data.

[0086] Computer storage media include, for example, various media that can store program codes, such as USB flash drives, mobile hard disks, read-only memories (ROM), random access memories (RAM), magnetic disks or optical disks.

Claims

1. A method for optimizing the production of washing machine drum stamping parts based on big data, characterized in that: include: Get external detail order; Determine the required production type and corresponding required production quantity based on external detailed orders; Determine the layout planning area corresponding to the required production type based on the preset area matching relationship; Randomly select any number of demand production types to construct a product type combination, and randomly generate the number of simulation types according to the demand production types in the product type combination; According to the number of simulated types and the corresponding layout planning areas, a type layout scheme is randomly arranged on the preset original plate area to output a type layout scheme, and a type layout scheme in which all plate planning areas are within the original plate area and the plate planning areas do not overlap is defined as a valid layout scheme for the product type combination; Randomly generate a number of scheme selections according to each valid typesetting scheme, and combine the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination; Determine the simulated production quantity of each demand production type according to the number of scheme selections and the number of simulated types of each demand production type in the effective typesetting scheme; The effective cutting combination when the simulated production quantity of each demand production type is not less than the corresponding demand production quantity is defined as a reasonable cutting combination, and the original demand quantity is determined by summing up the selected quantities of the solutions in the reasonable cutting combination; The original demand quantity with the smallest value is determined according to a preset sorting rule, and a reasonable cutting combination corresponding to the original demand quantity is defined as a use cutting combination, and the raw materials are processed according to the use cutting combination.

2. The method for optimizing the production of washing machine drum stamping parts based on big data according to claim 1, characterized in that: The steps of randomly arranging the simulated types and the corresponding layout planning areas on the preset original plate area to output the type layout plan include: Determine the regional feature points corresponding to the layout planning area according to the preset feature matching relationship; Determine the point spacing distance according to the regional feature points and the contour points on the contour line of the layout planning area, and define the point spacing distance with the smallest value as the reference spacing distance; A layout planning area is randomly selected to arrange the regional feature points on the original plate area, and a do not disturb area is defined according to the regional feature points and the reference distance; Update the area on the original plate area except the Do Not Disturb area to the new original plate area, and select the layout planning area again for layout according to the new original plate area, until all layout planning areas are arranged to output the type layout plan.

3. The method for optimizing the production of washing machine drum stamping parts based on big data according to claim 2, characterized in that: The steps of randomly selecting a layout planning area to arrange the regional feature points on the original plate area include: A virtual position point is randomly generated on the original plate area, and a virtual spacing distance is determined according to the virtual position point and the contour point of the contour line of the original plate area; A virtual position point whose virtual spacing distance is not less than the reference spacing distance of the current layout planning area is defined as a valid position point; A valid position set is formed according to all valid position points, and the regional feature points of the layout planning area are arranged only within the valid position set.

4. The method for optimizing the production of washing machine drum stamping parts based on big data according to claim 1, characterized in that: After the effective layout plan is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: In each valid layout plan, valid layout plans with the same required production type and the same number of corresponding simulation types are defined as similar layout plans; In similar layout schemes, the regional gap distance is determined according to each layout planning area, and the average of all regional gap distances is calculated to determine the regional mean distance; The regional mean distance with the largest value is determined according to the sorting rules, and the other similar layout schemes other than the effective layout scheme corresponding to the regional mean distance are deleted.

5. The method for optimizing the production of washing machine drum stamping parts based on big data according to claim 1, characterized in that: After the original demand quantity is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: Determine whether there are at least two reasonable cutting combinations with the same and minimum original demand quantity; If there are not at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as the used cutting combination; If there are at least two reasonable cutting combinations with the same and smallest original demand quantity, the reasonable cutting combination corresponding to the smallest original demand quantity is defined as the alternative cutting combination; The excess production quantity is determined by performing difference calculation based on the simulated production quantity of each required production type in the alternative cutting combination and the corresponding required production quantity; Construct a historical interval with the current time point as the end point and a width of the preset historical length on the preset time axis, and determine the historical production quantity in the historical interval according to the current demand production type; Calculate based on each historical production quantity to determine the historical production proportion of each demand production type; The single excess parameter is determined by calculating the historical production ratio and the corresponding current excess production quantity, and the combined excess parameter is determined by summing up all the single excess parameters; The combined redundant parameter with the largest value is determined according to the sorting rule, and the candidate cutting combination corresponding to the combined redundant parameter is determined as the used cutting combination.

6. The method for optimizing the production of washing machine drum stamping parts based on big data according to claim 5, characterized in that: After the combination of redundant parameters is determined, the production optimization method of washing machine drum stamping parts based on big data also includes: Determine whether there are at least two candidate cutting combinations with the same and largest combination redundant parameters; If there are not at least two candidate cutting combinations with the same and largest combined redundant parameters, the candidate cutting combination corresponding to the largest combined redundant parameter is determined as the used cutting combination; If there are at least two candidate cutting combinations with the same combined redundant parameters and the largest, the candidate cutting combination corresponding to the largest combined redundant parameter is defined as the waiting cutting combination; Determine the number of single board types in the combination waiting for cutting according to the required production types in each valid layout plan; The mean type quantity is determined by performing mean calculation according to the number of all single board types, and the waiting cutting combination corresponding to the mean type quantity with the smallest value is determined as the used cutting combination.

7. A washing machine drum stamping parts production optimization system based on big data, characterized in that: include: Acquisition module, used to obtain external detailed orders; A processing module, connected to the acquisition module and the judgment module, for storing and processing information; A judgment module, connected with the acquisition module and the processing module, for judging the information; The processing module determines the required production type and the corresponding required production quantity according to the external detailed order; The processing module determines the layout planning area corresponding to the required production type according to the preset area matching relationship; The processing module randomly selects any number of demand production types to construct a product type combination, and randomly generates a number of simulation types according to the demand production types in the product type combination; The processing module randomly arranges the simulated types and the corresponding layout planning areas on the preset original plate area to output a type layout plan, and defines a type layout plan in which all the plate planning areas are within the original plate area and the plate planning areas do not overlap as a valid layout plan for the product type combination; The processing module randomly generates a number of scheme selections according to each valid typesetting scheme, and combines the valid typesetting schemes and the corresponding number of scheme selections to generate a valid cutting combination; The processing module determines the simulated production quantity of each demand production type according to the number of scheme selections and the number of simulated types of each demand production type in the effective typesetting scheme; The processing module defines the effective cutting combination when the simulated production quantity of each demand production type determined by the determination module is not less than the corresponding demand production quantity as a reasonable cutting combination, and performs sum calculation based on the solution selection quantity in the reasonable cutting combination to determine the original demand quantity; The processing module determines the original demand quantity with the smallest value according to a preset sorting rule, defines a reasonable cutting combination corresponding to the original demand quantity as a use cutting combination, and processes the raw materials according to the use cutting combination.

8. A computer-readable storage medium, characterized in that: A computer program is stored which can be loaded by a processor and execute the method for optimizing the production of washing machine drum stamping parts based on big data as claimed in any one of claims 1 to 6.

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