Capacity planning data processing method and apparatus, medium, and electronic device
By calculating the balance, smoothness, and historical proportion deviation of capacity planning, and combining it with an operations research model to optimize supplier capacity planning, the problem of accuracy in evaluating the rationality of supplier capacity planning in garment production is solved, and the rational allocation of capacity and production stability are achieved.
Patent Information
- Authority / Receiving Office
- CN · China
- Patent Type
- Patents(China)
- Current Assignee / Owner
- SHANSHU TECH (BEIJING) CO LTD
- Filing Date
- 2022-12-01
- Publication Date
- 2026-06-12
AI Technical Summary
In garment production, existing technologies cannot accurately evaluate the rationality of suppliers' capacity planning, resulting in a lack of effectiveness in judging the rationality of suppliers' capacity planning.
By calculating the balance deviation, smoothness deviation, and historical proportion deviation of capacity planning, a capacity planning rationality deviation index is constructed. Combined with the operations research model, the supplier capacity planning is optimized to achieve rationality evaluation.
Accurately evaluate the rationality of supplier capacity planning, avoid capacity peaks and troughs, ensure production stability and consistency with historical ratios, and optimize the capacity planning process.
Smart Images
Figure CN116307444B_ABST
Abstract
Description
Technical Field
[0001] This application relates to the field of computer and data processing technology, and more specifically, to a method, apparatus, medium, and electronic device for processing capacity planning data. Background Technology
[0002] In a production setting, such as apparel manufacturing, the lifecycle of a garment typically includes stages like product planning, design, evaluation, supplier allocation, manufacturing, transportation, and market launch. Apparel brands are primarily responsible for the product planning, design, and supplier allocation stages. To ensure effective utilization of supplier capacity during the allocation stage, brands often begin supplier capacity planning immediately after the product planning phase. Currently, capacity planning often relies on manual, subjective assessment using Excel charts, lacking an effective estimation of its rationality. Furthermore, the subjective nature of capacity planning assessment leads to inaccurate evaluation of supplier capacity planning rationality. Therefore, accurately evaluating the rationality of supplier capacity planning is a pressing technical problem that needs to be solved. Summary of the Invention
[0003] The embodiments of this application provide a capacity planning data processing method, apparatus, computer program product or computer program, computer-readable medium and electronic device, which can at least to some extent accurately evaluate the rationality of the supplier's capacity planning.
[0004] Other features and advantages of this application will become apparent from the following detailed description, or may be learned in part from practice of this application.
[0005] According to one aspect of the embodiments of this application, a capacity planning data processing method is provided. The method includes: obtaining the initial capacity planning quantity for each product segment of a target supplier in each month of a planning period; calculating, based on the initial capacity planning quantity and a balance target for the target supplier, a capacity planning balance offset for all product segments of the target supplier within the planning period, wherein the capacity planning balance offset is used to characterize the capacity planning balance of the target supplier; and calculating, based on the initial capacity planning quantity, a capacity planning smoothness offset for all product segments of the target supplier within the planning period, wherein the capacity planning smoothness offset is used to characterize the balance of the target supplier's capacity planning. The following steps are taken: First, the smoothness of the target supplier's capacity planning is assessed. Second, based on the initial capacity planning amount and the historical proportions of the target supplier in each product segment, the historical proportion offset of the target supplier's capacity planning for all product segments within the planning period is calculated. This historical proportion offset characterizes the historical proportion fit of the target supplier. Third, based on the capacity planning balance offset, the capacity planning smoothness offset, and the historical proportion offset, the capacity planning rationality offset is calculated according to preset weights for different offsets. This rationality offset characterizes the rationality of the target supplier's capacity planning.
[0006] In some embodiments of this application, based on the foregoing scheme, the capacity planning balance offset is calculated using the following formula:
[0007]
[0008] EO I,j,m =max[PQ I,j,m -(2-γ)×PQ I,j,average ,γ×PQ I,j,average -PQ I,j,m ]
[0009]
[0010] Among them, EO I,j,M EO represents the offset of capacity planning balance across all product segments of the j-th supplier, i.e., the target supplier, within the planning period; I,j,m PQ represents the capacity planning balance offset of all product segments of the j-th supplier in month m within the planning period; I,j,m γ represents the planned production capacity for all product segments of the j-th supplier in month m of the planning period; γ represents the balance target for the j-th supplier, rounded from 0 to 100%; PQ I,j,average This represents the average monthly planned production capacity for all product segments of the j-th supplier during the planning period; Number MI represents the number of months; M represents the set of all product segments; and M represents the set of months in the planning period.
[0011] In some embodiments of this application, based on the foregoing scheme, the capacity planning smoothness offset is calculated using the following formula:
[0012]
[0013] SO I,j,m =|PQ I,j,m -PQ I,j,n |
[0014] Among them, SO I,j,M SO represents the capacity planning smoothness offset of the j-th supplier, i.e., all product segments of the target supplier, within the planning period; I,j,m PQ represents the capacity planning smoothness offset for all product segments of the j-th supplier in month m of the planning period; I,j,m PQ represents the planned production capacity of all product segments of the j-th supplier in month m within the planning period; I,j,n This represents the planned production capacity of all product segments of the j-th supplier in month n of the planning period, where month n is the month preceding month m, and when m = 1, month n is the last month of the planning period.
[0015] In some embodiments of this application, based on the foregoing scheme, the historical proportion offset of capacity planning is calculated using the following formula:
[0016]
[0017]
[0018] Among them, HO I,j,M This represents the historical proportion offset of capacity planning for all product segments of the j-th supplier within the planning period; HO i,j,M PQ represents the historical proportion offset of product segment i of supplier j within the planning period; i,j,m This represents the planned production capacity of product segment i from supplier j in month m within the planning period; HP i,j PQ represents the historical percentage of the j-th supplier in product segment i, where the sum of the historical percentages of all product segments of the j-th supplier is 100%. I,j,m This represents the planned production capacity for all product segments of the j-th supplier in month m within the planning period.
[0019] In some embodiments of this application, based on the foregoing scheme, the deviation in the rationality of the capacity planning is calculated using the following formula:
[0020] RO I,j,M =a×EO I,j,M +b×SO I,j,M +c×HO I,j,M
[0021] Among them, RO I,j,M This represents the deviation in the reasonableness of the capacity planning of the j-th supplier, i.e., the target supplier; EO I,j,M SO represents the offset of capacity planning equilibrium for all product segments of the j-th supplier within the planning period; I,j,M This represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; HO I,j,M denoted as , where represents the historical proportion offset of capacity planning for all product segments of supplier j within the planning period; 'a' represents the preset weighting of capacity planning balance offset; 'b' represents the preset weighting of capacity planning smoothness offset; 'c' represents the preset weighting of historical proportion offset of capacity planning; and 'J' represents the set of suppliers.
[0022] In some embodiments of this application, based on the foregoing scheme, the method further includes:
[0023] Suppliers whose capacity planning rationality deviation exceeds a preset threshold are identified, and a supplier set is obtained;
[0024] Based on the constraints and objective function of capacity planning, the capacity planning amount of each supplier in the supplier set for each month within the planning period is used as the decision variable. The capacity of each supplier in the supplier set is replanned through an operations research model to optimize the rationality deviation of the capacity planning.
[0025] In some embodiments of this application, based on the foregoing scheme, the capacity planning objective function includes the following formula:
[0026]
[0027] Among them, EO I,j,M SO represents the offset of capacity planning equilibrium for all product segments of the j-th supplier within the planning period; I,j,M This represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; HO I,j,M denoted as the historical proportion offset of capacity planning for all product segments of the j-th supplier within the planning period; a represents the balance weight proportion; b represents the smoothness weight proportion; c represents the historical proportion weight proportion; J represents the set of suppliers.
[0028] According to one aspect of the embodiments of this application, a capacity planning data processing apparatus is provided. The apparatus includes: an acquisition unit, configured to acquire the initial capacity planning quantity of each product segment of a target supplier for each month within a planning period; a first calculation unit, configured to calculate, based on the initial capacity planning quantity and a balance target for the target supplier, a capacity planning balance deviation of all product segments of the target supplier within the planning period, wherein the capacity planning balance deviation is used to characterize the capacity planning balance of the target supplier; and a second calculation unit, configured to calculate, based on the initial capacity planning quantity, a capacity planning smoothness deviation of all product segments of the target supplier within the planning period, wherein the capacity planning smoothness deviation is used to characterize the capacity planning balance of the target supplier. The system comprises four calculation units: a third calculation unit, a fourth calculation unit, and a fifth calculation unit. The third calculation unit is used to characterize the smoothness of the target supplier's capacity planning; the fourth calculation unit is used to characterize the historical proportion fit of the target supplier's historical proportions within the planning period, based on the initial capacity planning amount and the historical proportions of the target supplier in each product segment; the fourth calculation unit is used to characterize the reasonableness of the target supplier's capacity planning, based on the capacity planning balance deviation, the capacity planning smoothness deviation, and the capacity planning historical proportion deviation, according to preset weights for different deviations.
[0029] According to one aspect of the embodiments of this application, a computer program product or computer program is provided, which includes computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods described in the above embodiments.
[0030] According to one aspect of the embodiments of this application, a computer-readable medium is provided having a computer program stored thereon, which, when executed by a processor, implements the method described in the above embodiments.
[0031] According to one aspect of the embodiments of this application, an electronic device is provided, including: one or more processors; and a storage device for storing one or more programs, which, when executed by the one or more processors, cause the one or more processors to perform the method described in the above embodiments.
[0032] In some embodiments of this application, the capacity planning balance offset can be used to guide suppliers to avoid peaks and troughs in capacity planning during allocation, which is beneficial for enterprises to use capacity when allocating it to suppliers. The capacity planning smoothness offset can be used to guide suppliers to keep their planned quantities in each month consistent with the planned quantities of the previous and next months, which is beneficial for suppliers to rationally arrange production. The capacity planning historical proportion offset can be used to guide suppliers to maintain consistency between the current planned product segmentation and the historically planned product segmentation. Furthermore, by creating three new indicators related to the rationality of capacity planning—namely, "capacity planning balance offset," "capacity planning smoothness offset," and "capacity planning historical proportion offset"—and then constructing the "capacity planning rationality offset" indicator based on these three indicators, the rationality of supplier capacity planning can be intuitively displayed and evaluated through the "capacity planning rationality offset" indicator.
[0033] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and do not limit this application. Attached Figure Description
[0034] The accompanying drawings, which are incorporated in and form part of this specification, illustrate embodiments consistent with this application and, together with the description, serve to explain the principles of this application. It is obvious that the drawings described below are merely some embodiments of this application, and those skilled in the art can obtain other drawings based on these drawings without any inventive effort. In the drawings:
[0035] Figure 1 A flowchart of a capacity planning data processing method according to an embodiment of this application is shown;
[0036] Figure 2 Another flowchart of a capacity planning data processing method according to an embodiment of this application is shown;
[0037] Figure 3 A block diagram of a capacity planning data processing apparatus according to an embodiment of this application is shown;
[0038] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown. Detailed Implementation
[0039] Exemplary embodiments will now be described more fully with reference to the accompanying drawings. However, these exemplary embodiments can be implemented in many forms and should not be construed as limited to the examples set forth herein; rather, these embodiments are provided to make this application more comprehensive and complete, and to fully convey the concept of the exemplary embodiments to those skilled in the art.
[0040] Furthermore, the described features, structures, or characteristics can be combined in any suitable manner in one or more embodiments. Numerous specific details are provided in the following description to give a thorough understanding of embodiments of this application. However, those skilled in the art will recognize that the technical solutions of this application can be practiced without one or more of the specific details, or other methods, components, apparatuses, steps, etc., can be employed. In other instances, well-known methods, apparatuses, implementations, or operations are not shown or described in detail to avoid obscuring various aspects of this application.
[0041] The block diagrams shown in the accompanying drawings are merely functional entities and do not necessarily correspond to physically independent entities. That is, these functional entities can be implemented in software, in one or more hardware modules or integrated circuits, or in different network and / or processor devices and / or microcontroller devices.
[0042] The flowcharts shown in the accompanying drawings are merely illustrative and do not necessarily include all content and operations / steps, nor do they necessarily have to be performed in the described order. For example, some operations / steps can be broken down, while others can be combined or partially combined; therefore, the actual execution order may change depending on the specific circumstances.
[0043] It should be noted that "multiple" in this article refers to two or more. "And / or" describes the relationship between related objects, indicating that three relationships can exist. For example, A and / or B can represent: A alone, A and B simultaneously, or B alone. The character " / " generally indicates that the preceding and following related objects have an "or" relationship.
[0044] It should be noted that the terms "first," "second," etc., in the specification, claims, and accompanying drawings of this application are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that such uses of these terms can be interchanged where appropriate so that the embodiments of this application described herein can be implemented in orders other than those illustrated or described.
[0045] The proposed capacity planning data processing solution in this application can be applied to supplier capacity planning scenarios. For example, in the apparel production scenario, the lifecycle of a garment typically includes stages such as product planning, design, evaluation, supplier allocation, manufacturing, transportation, and market launch. Apparel brands are primarily responsible for the three stages of product planning, design, evaluation, and supplier allocation. Generally, it takes 7 to 9 months from product planning to supplier allocation. To ensure effective use of supplier capacity during the supplier allocation stage, apparel brands often begin supplier capacity planning immediately after the product planning stage. Therefore, accurately evaluating the rationality of capacity planning is crucial for determining whether to implement supplier capacity planning.
[0046] The implementation details of the technical solutions in the embodiments of this application are described in detail below:
[0047] Figure 1 A flowchart of a capacity planning data processing method according to an embodiment of this application is shown. This capacity planning data processing method can be executed by a device with computing processing capabilities. (Refer to...) Figure 1 As shown, this capacity planning data processing method includes at least steps 110 to 150, which are detailed below:
[0048] In step 110, the initial planned capacity for each product segment of the target supplier for each month within the planning period is obtained.
[0049] In this application, an upstream enterprise can typically have multiple suppliers. For the target supplier, product segmentation can refer to specific product specifications. In the field of apparel production, this could be the dimension of fabric type, fabric type-major category, fabric type-major category-minor category, etc. Obtaining the initial planned production capacity of each product segment for each month within the planning period can refer to obtaining the initial planned production volume of T-shirts and shirts for each month within 6 months.
[0050] Continue to refer to Figure 1 In step 120, based on the initial capacity planning amount and the balance target for the target supplier, the capacity planning balance offset of all product segments of the target supplier within the planning period is calculated. The capacity planning balance offset is used to characterize the capacity planning balance of the target supplier.
[0051] In this application, the balance target refers to the balance requirement of the supplier's own capacity planning, which can be set between 0% and 100%.
[0052] In one embodiment of this application, the capacity planning balance offset can be calculated using the following formula:
[0053]
[0054] EO I,j,m =max[PQ I,j,m -(2-γ)×PQ I,j,average ,γ×PQ I,j,average -PQ I,j,m ]
[0055]
[0056] Among them, EO I,j,M EO represents the offset of capacity planning balance across all product segments of the j-th supplier, i.e., the target supplier, within the planning period; I,j,m PQ represents the capacity planning balance offset of all product segments of the j-th supplier in month m within the planning period; I,j,m γ represents the planned production capacity for all product segments of the j-th supplier in month m of the planning period; γ represents the balance target for the j-th supplier, rounded from 0 to 100%; PQ I,j,average This represents the average monthly planned production capacity for all product segments of the j-th supplier during the planning period; Number M I represents the number of months; M represents the set of all product segments; and M represents the set of months in the planning period.
[0057] In this application, the capacity planning balance offset can be used to guide suppliers to plan their capacity in each month of the current allocation as close as possible to the upper and lower limits calculated from the average of each month, so as to avoid peaks and troughs in capacity planning. This helps companies use capacity when allocating to suppliers and also helps suppliers to arrange production reasonably.
[0058] Continue to refer to Figure 1 In step 130, based on the initial capacity planning amount, the capacity planning smoothness offset of all product segments of the target supplier within the planning period is calculated, and the capacity planning smoothness offset is used to characterize the capacity planning smoothness of the target supplier.
[0059] In one embodiment of this application, the capacity planning smoothness offset can be calculated using the following formula:
[0060]
[0061] SO I,j,m =|PQ I,j,m -PQ I,j,n |
[0062] Among them, SO I,j,MSO represents the capacity planning smoothness offset of the j-th supplier, i.e., all product segments of the target supplier, within the planning period; I,j,m PQ represents the capacity planning smoothness offset for all product segments of the j-th supplier in month m of the planning period; I,j,m PQ represents the planned production capacity of all product segments of the j-th supplier in month m within the planning period; I,j,n This represents the planned production capacity of all product segments of the j-th supplier in month n of the planning period, where month n is the month preceding month m, and when m = 1, month n is the last month of the planning period.
[0063] In this application, the capacity planning smoothness offset can be used to guide suppliers to keep their planned quantities in each month of the current allocation as consistent as possible with the planned quantities of the previous month and the next month. In capacity planning that meets the capacity planning balance, there may be slight fluctuations. Eliminating such fluctuations helps companies use capacity when allocating it to suppliers and also helps suppliers to arrange production reasonably.
[0064] Continue to refer to Figure 1 In step 140, based on the initial capacity planning amount and the historical proportions of the target supplier in each product segment, the historical proportion offset of the capacity planning for all product segments of the target supplier within the planning period is calculated. The historical proportion offset of the capacity planning is used to characterize the historical proportion fit of the target supplier.
[0065] In this application, the historical ratio can be the percentage of a supplier's historical planned production capacity for a particular product in the total historical planned production capacity.
[0066] In one embodiment of this application, the historical proportion offset of the capacity planning can be calculated using the following formula:
[0067]
[0068]
[0069] Among them, HO I,j,M This represents the historical proportion offset of capacity planning for all product segments of the j-th supplier within the planning period; HO i,j,M PQ represents the historical proportion offset of product segment i of supplier j within the planning period; i,j,m This represents the planned production capacity of product segment i from supplier j in month m within the planning period; HP i,j PQ represents the historical percentage of the j-th supplier in product segment i, where the sum of the historical percentages of all product segments of the j-th supplier is 100%. I,j,mThis represents the planned production capacity for all product segments of the j-th supplier in month m within the planning period.
[0070] In this application, the historical proportion offset of the capacity planning can be used to characterize the degree of consistency between the supplier's current planned product segment and the product segment planned in the past, and in turn, can be used to guide the consistency between the supplier's current planned product segment and the product segment planned in the past. For example, a supplier may have frequently undertaken orders for a certain type of fabric or a certain category of clothing from a company in the past, and the equipment and personnel used to produce these fabrics or categories of clothing are often different. Excessive changes to this structure may bring uncertainty to the capacity utilization during the supplier allocation stage.
[0071] Continue to refer to Figure 1 In step 150, based on the capacity planning balance offset, the capacity planning smoothness offset, and the capacity planning historical proportion offset, the capacity planning rationality offset of the target supplier is calculated according to the preset allocation weight of different offsets. The capacity planning rationality offset is used to characterize the rationality of the target supplier's capacity planning.
[0072] In this application, it should be noted that the sum of the weights of different offsets can be 1. For example, in the field of garment production, the weight of the capacity planning balance offset can be 50%, the weight of the capacity planning smoothness offset can be 25%, and the weight of the capacity planning historical proportion offset can be 25%.
[0073] In one embodiment of this application, the deviation in the rationality of the capacity planning is calculated using the following formula:
[0074] RO I,j,M =a×EO I,j,M +b×SO I,j,M +c×HO I,j,M
[0075] Among them, RO I,j,M This represents the deviation in the reasonableness of the capacity planning of the j-th supplier, i.e., the target supplier; EO I,j,M SO represents the offset of capacity planning equilibrium for all product segments of the j-th supplier within the planning period; I,j,M This represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; HO I,j,M denoted as , where represents the historical proportion offset of capacity planning for all product segments of supplier j within the planning period; 'a' represents the preset weighting of capacity planning balance offset; 'b' represents the preset weighting of capacity planning smoothness offset; 'c' represents the preset weighting of historical proportion offset of capacity planning; and 'J' represents the set of suppliers.
[0076] In this application, three new indicators related to the rationality of capacity planning are created: “capacity planning balance deviation”, “capacity planning smoothness deviation”, and “capacity planning historical proportion deviation”. Then, based on these three indicators, the “capacity planning rationality deviation” indicator is constructed. The “capacity planning rationality deviation” indicator can be used to intuitively and accurately display and evaluate the rationality of the supplier’s capacity planning.
[0077] This application also makes the following: Figure 2 The steps shown illustrate the data processing scheme for capacity planning.
[0078] See Figure 2 This illustrates another flowchart of a capacity planning data processing method according to an embodiment of this application. Specifically, it includes steps 160 to 170:
[0079] Step 160: Identify suppliers whose capacity planning rationality deviation exceeds a preset threshold, and obtain a supplier set;
[0080] Step 170: Based on the constraints and objective function of capacity planning, the capacity planning amount of each supplier in the supplier set for each month within the planning period is used as the decision variable. The capacity of each supplier in the supplier set is re-planned through the operations research model to optimize the reasonableness deviation of the capacity planning.
[0081] In this application, the constraints for capacity planning may include the following formula:
[0082] EO I,j,m ≥max[PQ I,j,m -(2-γ)×PQ I,j,average ,γ×PQ I,j,average -PQ I,j,m ]
[0083] SO I，j，m ≥|PQ I，j，m -PQ I，j，n
[0084]
[0085] In one embodiment of this application, the capacity planning objective function comprises the following formula:
[0086]
[0087] Among them, EO I,j,M SO represents the offset of capacity planning equilibrium for all product segments of the j-th supplier within the planning period; I,j,MThis represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; HO I,j,M denoted as the historical proportion offset of capacity planning for all product segments of the j-th supplier within the planning period; a represents the balance weight proportion; b represents the smoothness weight proportion; c represents the historical proportion weight proportion; J represents the set of suppliers.
[0088] In this application, the rationality of capacity planning in the apparel industry is described by using a "capacity planning rationality offset," achieving a linear estimation of capacity planning rationality. This indicator can be conveniently used to optimize the rationality of capacity planning during the process of optimizing capacity planning using operations research theory. This ensures that the goal of capacity planning rationality can be effectively considered, while also guaranteeing fast solution speed for the operations research model and ensuring the attainment of the optimal solution in linear programming.
[0089] To help those skilled in the art better understand this application, the following detailed explanation will be provided using a garment production scenario as an example.
[0090] In the results of capacity planning, for a certain supplier, the following data is available, as shown in Table 1.
[0091] Capacity breakdown by month March April May June July Woven 900 2700 8100 4500 1800 knitting 100 300 900 500 200
[0092] Table 1
[0093] Assuming the supplier's balance target is 80%, and the company's priority requirements for balance, smoothness, and historical proportion fit are 2:1:1, and the supplier's historical proportions are 50% woven and 50% knitted.
[0094] The reasonableness deviation of the supplier can be calculated using the formula above.
[0095] The monthly average of the supplier's planned production capacity is 20000 / 5 = 4000.
[0096] The balance offset in March is max(4000×80%-1000,1000–4000×120%)=2200. Similarly, the balance offsets in April, May, June and July are 200, 4200, 200 and 1200 respectively.
[0097] The supplier's capacity planning balance offset = 2200 + 200 + 4200 + 200 + 1200 = 8000.
[0098] The smoothness offset for March is |1000–2000| = 1000. Similarly, the smoothness offsets for April, May, June, and July are 2000, 6000, 4000, and 3000, respectively.
[0099] The supplier's capacity planning smoothness offset = 1000 + 2000 + 6000 + 4000 + 3000 = 16000.
[0100] The historical percentage offset of the supplier's woven production capacity breakdown is calculated as follows: |(900+2700+8100+4500+1800)-20000*50%| = 8000. Similarly, the historical percentage offset of the supplier's knitted production capacity breakdown is 8000.
[0101] The supplier's historical capacity planning offset is 16,000.
[0102] The supplier's capacity planning rationality deviation is (8000×2+16000×1+16000×1) / (2+1+1)=12000, which shows that the supplier's rationality in this capacity planning is poor.
[0103] If we use the constraints and objective function in the above operations research model, we can obtain the solution in Table 2.
[0104] Capacity breakdown by month March April May June July Woven 2000 2000 2000 2000 2000 knitting 2000 2000 2000 2000 2000
[0105] Table 2
[0106] At this point, the supplier's capacity planning rationality deviation can be calculated as 0.
[0107] The following describes an embodiment of the apparatus described in this application, which can be used to execute the capacity planning data processing method in the above embodiments of this application. For details not disclosed in the apparatus embodiments of this application, please refer to the embodiments of the capacity planning data processing method described above in this application.
[0108] Figure 3 A block diagram of a capacity planning data processing apparatus according to an embodiment of this application is shown.
[0109] Reference Figure 3 As shown, a capacity planning data processing device 300 according to an embodiment of this application includes: an acquisition unit 301, a first calculation unit 302, a second calculation unit 303, a third calculation unit 304, and a fourth calculation unit 305.
[0110] The system includes: an acquisition unit 301, used to acquire the initial capacity planning amount for each product segment of the target supplier in each month of the planning period; a first calculation unit 302, used to calculate the capacity planning balance deviation of all product segments of the target supplier within the planning period based on the initial capacity planning amount and the balance target of the target supplier, wherein the capacity planning balance deviation is used to characterize the capacity planning balance of the target supplier; and a second calculation unit 303, used to calculate the capacity planning smoothness deviation of all product segments of the target supplier within the planning period based on the initial capacity planning amount, wherein the capacity planning smoothness deviation is used to characterize the capacity planning smoothness of the target supplier. Slippage; the third calculation unit 304 is used to calculate the historical proportion offset of the target supplier's production capacity planning for all product segments within the planning period based on the initial production capacity planning amount and the historical proportion of the target supplier in each product segment. The historical proportion offset of production capacity planning is used to characterize the historical proportion fit of the target supplier; the fourth calculation unit 305 is used to calculate the reasonableness offset of the target supplier's production capacity planning based on the production capacity planning balance offset, the production capacity planning smoothness offset, and the historical proportion offset of production capacity planning, according to the preset weights of different offsets. The reasonableness offset of production capacity planning is used to characterize the reasonableness of the target supplier's production capacity planning.
[0111] Figure 4 A schematic diagram of the structure of a computer system suitable for implementing the electronic device of the present application is shown.
[0112] It should be noted that, Figure 4 The computer system 400 of the electronic device shown is merely an example and should not impose any limitation on the functionality and scope of use of the embodiments of this application.
[0113] like Figure 4 As shown, the computer system 400 includes a Central Processing Unit (CPU) 401, which can perform various appropriate actions and processes based on programs stored in Read-Only Memory (ROM) 402 or programs loaded from Storage Unit 408 into Random Access Memory (RAM) 403, such as performing the methods described in the above embodiments. The RAM 403 also stores various programs and data required for system operation. The CPU 401, ROM 402, and RAM 403 are interconnected via a bus 404. An Input / Output (I / O) interface 405 is also connected to the bus 404.
[0114] The following components are connected to I / O interface 405: an input section 406 including a keyboard, mouse, etc.; an output section 407 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and speakers, etc.; a storage section 408 including a hard disk, etc.; and a communication section 409 including a network interface card such as a LAN (Local Area Network) card, modem, etc. The communication section 409 performs communication processing via a network such as the Internet. A drive 410 is also connected to I / O interface 405 as needed. A removable medium 411, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 410 as needed so that computer programs read from it can be installed into storage section 408 as needed.
[0115] Specifically, according to embodiments of this application, the processes described above with reference to the flowcharts can be implemented as computer software programs. For example, embodiments of this application include a computer program product comprising a computer program carried on a computer-readable medium, the computer program containing program code for performing the methods shown in the flowcharts. In such embodiments, the computer program can be downloaded and installed from a network via communication section 409, and / or installed from removable medium 411. When the computer program is executed by central processing unit (CPU) 401, it performs various functions defined in the system of this application.
[0116] It should be noted that the computer-readable medium shown in the embodiments of this application can be a computer-readable signal medium or a computer-readable storage medium, or any combination of the two. A computer-readable storage medium can be, for example,—but not limited to—an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination thereof. More specific examples of a computer-readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer disk, a hard disk, random access memory (RAM), read-only memory (ROM), erasable programmable read-only memory (EPROM), flash memory, optical fiber, portable compact disc read-only memory (CD-ROM), optical storage device, magnetic storage device, or any suitable combination thereof. In this application, a computer-readable storage medium can be any tangible medium containing or storing a program that can be used by or in conjunction with an instruction execution system, apparatus, or device. In this application, a computer-readable signal medium can include a data signal propagated in baseband or as part of a carrier wave, carrying computer-readable program code. Such transmitted data signals can take various forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination thereof. The computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium, which can send, propagate, or transmit a program for use by or in connection with an instruction execution system, apparatus, or device. The program code contained on the computer-readable medium can be transmitted using any suitable medium, including but not limited to wireless, wired, etc., or any suitable combination thereof.
[0117] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this application. Each block in a flowchart or block diagram may represent a module, segment, or portion of code, which contains one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in a block diagram or flowchart, and combinations of blocks in a block diagram or flowchart, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.
[0118] The units described in the embodiments of this application can be implemented in software or hardware, and the described units can also be located in a processor. The names of these units do not necessarily limit the specific unit itself.
[0119] In another aspect, this application also provides a computer program product or computer program including computer instructions stored in a computer-readable storage medium. A processor of a computer device reads the computer instructions from the computer-readable storage medium and executes the computer instructions, causing the computer device to perform the methods described in the above embodiments.
[0120] In another aspect, this application also provides a computer-readable medium, which may be included in the electronic device described in the above embodiments; or it may exist independently and not assembled into the electronic device. The computer-readable medium carries one or more programs, which, when executed by the electronic device, cause the electronic device to perform the methods described in the above embodiments.
[0121] It should be noted that although several modules or units for the device used to perform actions have been mentioned in the detailed description above, this division is not mandatory. In fact, according to the embodiments of this application, the features and functions of two or more modules or units described above can be embodied in one module or unit. Conversely, the features and functions of one module or unit described above can be further divided and embodied by multiple modules or units.
[0122] Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein can be implemented by software or by combining software with necessary hardware. Therefore, the technical solutions according to the embodiments of this application can be embodied in the form of a software product, which can be stored in a non-volatile storage medium (such as a CD-ROM, USB flash drive, external hard drive, etc.) or on a network, including several instructions to cause a computing device (such as a personal computer, server, touch terminal, or network device, etc.) to execute the method according to the embodiments of this application.
[0123] Other embodiments of this application will readily occur to those skilled in the art upon consideration of the specification and practice of the embodiments disclosed herein. This application is intended to cover any variations, uses, or adaptations of this application that follow the general principles of this application and include common knowledge or customary techniques in the art not disclosed herein.
[0124] It should be understood that this application is not limited to the precise structure described above and shown in the accompanying drawings, and various modifications and changes can be made without departing from its scope. The scope of this application is limited only by the appended claims.
Claims
1. A method for processing capacity planning data, characterized in that, The method includes: Obtain the initial capacity planning volume for each product segment of the target supplier for each month within the planning period; Based on the initial capacity planning amount and the balance target for the target supplier, calculate the capacity planning balance offset of all product segments of the target supplier within the planning period. The capacity planning balance offset is used to characterize the capacity planning balance of the target supplier. Based on the initial capacity planning amount, calculate the capacity planning smoothness offset of all product segments of the target supplier within the planning period. The capacity planning smoothness offset is used to characterize the capacity planning smoothness of the target supplier. Based on the initial capacity planning amount and the historical proportions of the target supplier in each product segment, the historical proportion offset of the capacity planning for all product segments of the target supplier within the planning period is calculated. The historical proportion offset of the capacity planning is used to characterize the historical proportion fit of the target supplier. Based on the capacity planning balance deviation, the capacity planning smoothness deviation, and the capacity planning historical proportion deviation, the capacity planning rationality deviation of the target supplier is calculated according to the preset allocation weight of different deviations. The capacity planning rationality deviation is used to characterize the rationality of the target supplier's capacity planning. The offset of the capacity planning balance is calculated using the following formula: in, This represents the offset of the capacity planning balance of all product segments of the j-th supplier, i.e., the target supplier, within the planning period; This represents the offset of capacity planning balance for all product segments of the j-th supplier in month m within the planning period; γ represents the planned production capacity of all product segments of the j-th supplier in the m-th month of the planning period; γ represents the balance target for the j-th supplier, with the value ranging from 0 to 100%. This represents the average monthly planned production capacity of all product segments of the j-th supplier during the planning period; I represents the number of months; M represents the set of all product segments; and M represents the set of months in the planning period. The capacity planning smoothness offset is calculated using the following formula: in, This represents the capacity planning smoothness offset of the j-th supplier, i.e., all product segments of the target supplier, within the planning period; This represents the capacity planning smoothness offset of all product segments of the j-th supplier in month m within the planning period; This represents the planned production capacity for all product segments of the j-th supplier in month m within the planning period. This represents the planned production capacity of all product segments of the j-th supplier in month n of the planning period, where month n is the month preceding month m, and when m = 1, month n is the last month of the planning period; The historical proportion offset of the capacity planning is calculated using the following formula: in, This represents the historical proportion offset of capacity planning for all product segments of the target supplier during the planning period for the j-th supplier. This represents the historical proportion offset of the capacity planning for product segment i of supplier j within the planning period; This represents the planned production capacity of product segment i of supplier j in month m within the planning period; This represents the historical percentage of the j-th supplier in product segment i, and the sum of the historical percentages of all product segments of the j-th supplier is 100%. This represents the planned production capacity for all product segments of the j-th supplier in month m within the planning period; The deviation in the rationality of the capacity planning is calculated using the following formula: in, This represents the deviation in the reasonableness of the capacity planning of the j-th supplier, i.e., the target supplier. This represents the offset of the capacity planning balance of all product segments of the j-th supplier within the planning period; This represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; denoted as , where represents the historical proportion offset of capacity planning for all product segments of supplier j within the planning period; 'a' represents the preset weighting of capacity planning balance offset; 'b' represents the preset weighting of capacity planning smoothness offset; 'c' represents the preset weighting of historical proportion offset of capacity planning; and 'J' represents the set of suppliers.
2. The method according to claim 1, characterized in that, The method further includes: Suppliers whose capacity planning rationality deviation exceeds a preset threshold are identified, and a supplier set is obtained; Based on the constraints and objective function of capacity planning, the capacity planning amount of each supplier in the supplier set for each month within the planning period is used as the decision variable. The capacity of each supplier in the supplier set is replanned through an operations research model to optimize the rationality deviation of the capacity planning.
3. The method according to claim 2, characterized in that, The objective function for capacity planning includes the following formula: in, This represents the offset of the capacity planning balance of all product segments of the j-th supplier within the planning period; This represents the capacity planning smoothness offset of all product segments of the j-th supplier within the planning period; denoted as the historical proportion offset of capacity planning for all product segments of the j-th supplier within the planning period; a represents the balance weight proportion; b represents the smoothness weight proportion; c represents the historical proportion weight proportion; J represents the set of suppliers.
4. An apparatus for implementing the capacity planning data processing method as described in any one of claims 1-3, characterized in that, The device includes: The acquisition unit is used to acquire the initial capacity planning volume of each product segment of the target supplier for each month within the planning period; The first calculation unit is used to calculate the capacity planning balance deviation of all product segments of the target supplier within the planning period based on the initial capacity planning amount and the balance target for the target supplier. The capacity planning balance deviation is used to characterize the capacity planning balance of the target supplier. The second calculation unit is used to calculate the capacity planning smoothness offset of all product segments of the target supplier within the planning period based on the initial capacity planning amount. The capacity planning smoothness offset is used to characterize the capacity planning smoothness of the target supplier. The third calculation unit is used to calculate the historical proportion offset of the capacity planning of all product segments of the target supplier within the planning period based on the initial capacity planning amount and the historical proportion of the target supplier in each product segment. The historical proportion offset of capacity planning is used to characterize the historical proportion fitting degree of the target supplier. The fourth calculation unit is used to calculate the capacity planning rationality offset of the target supplier based on the capacity planning balance offset, the capacity planning smoothness offset, and the capacity planning historical proportion offset, according to the preset weights of different offsets. The capacity planning rationality offset is used to characterize the rationality of the target supplier's capacity planning.
5. A computer-readable storage medium, characterized in that, The computer-readable storage medium stores at least one piece of program code, which is loaded and executed by a processor to perform the operations performed by the method as described in any one of claims 1 to 3.
6. An electronic device, characterized in that, The electronic device includes one or more processors and one or more memories, wherein at least one piece of program code is stored in the one or more memories, and the at least one piece of program code is loaded and executed by the one or more processors to perform the operation performed by the method as described in any one of claims 1 to 3.