Garment sample preparation labor cost accounting method, system, equipment and medium

Abstract

The invention provides a clothing sample preparation labor cost accounting method, system and device, and a medium. The method comprises the following steps: constructing a comprehensive coefficient library; comprising a basic style coefficient library, a component coefficient library, a brand difficulty coefficient library, a technical center difficulty coefficient library and a proofing piece number influence coefficient library; matching various coefficients under each style of different work types through a fuzzy matching algorithm in combination with style information specified by a client; comprising a basic style coefficient, a component coefficient, a brand difficulty coefficient, a technical center difficulty coefficient and a proofing piece number influence coefficient; performing comprehensive calculation on each coefficient under each style of different work types through a clothing sample preparation coefficient accounting model to obtain a comprehensive coefficient; and calculating the performance salaries of all employees in the garment sample preparation process, and obtaining a corresponding labor cost accounting result. According to the method, an enterprise can be helped to realize more accurate, flexible and real-time clothing sample preparation labor cost accounting, so that resource allocation is optimized, and the market response speed is increased.

Description

Technical Field

[0001] The present invention relates to the field of cost accounting in the garment manufacturing industry, and more specifically to a method, system, equipment and medium for calculating the labor cost of garment sample making. Background Art

[0002] Cost accounting for clothing sample making is at the core of the clothing manufacturing industry. It is not only related to the cost control and profit management of enterprises, but also an important yardstick for measuring production efficiency and market competitiveness. However, the current accounting methods and technologies have encountered many challenges in actual operation.

[0003] First, the existing accounting methods often only consider limited factors such as working hours and wage standards, but ignore key factors such as the complexity of clothing styles, the difficulty of component processing, and differences in brand requirements. This simplified processing leads to a large deviation between the accounting results and the actual costs, which makes it difficult to meet the urgent needs of enterprises for refined management.

[0004] Secondly, the lack of flexibility and adaptability is also a major weakness of the existing accounting methods. With the rapid changes in the clothing market and the increasing diversification of consumer demand, new styles, new processes and new materials are constantly emerging in the clothing sample making process. However, the current accounting methods often fail to quickly capture the impact of these changes on costs, making it difficult for companies to flexibly adjust their cost accounting strategies when facing market fluctuations. This lag not only limits the decision-making efficiency of companies, but may also put them at a disadvantage in the fierce market competition.

[0005] In addition, in terms of capacity accounting, the existing method mainly relies on subjective scoring by experienced team leaders. Although this method can reflect the work performance of employees to a certain extent, it has significant limitations. Human scoring is easily mixed with emotional factors and other non-professional considerations, resulting in a lack of objectivity and consistency in scoring. The evaluation criteria of different team leaders may vary greatly, which not only affects the fairness of the scoring, but also makes it difficult for the evaluation results to be used as a reliable basis for decision-making. At the same time, this subjective scoring method lacks transparency and standardized processes, making it difficult to establish a fair and transparent evaluation environment.

[0006] More importantly, the traditional manual scoring method fails to fully utilize the advantages of modern information technology. With the intensification of industry competition and the advancement of technology, companies increasingly need to rely on data analysis to optimize production processes and reduce costs. However, the existing subjective scoring method is difficult to provide sufficient data support, which limits the management's ability to make fact-based decisions. This lack of data support not only affects the cost control efficiency of enterprises, but may also hinder the digital transformation process of enterprises.

[0007] Therefore, how to design a labor cost accounting method for clothing sample making to improve the accuracy, flexibility and adaptability of labor cost accounting, while reducing the impact of human factors and realizing data-driven precise management is an urgent problem that technical personnel in this field need to solve. Summary of the invention

[0008] In view of this, the present invention provides a method for calculating labor costs for clothing sample making. By comprehensively considering multiple dimensions such as the complexity of clothing styles, the difficulty of component processing, and differences in brand requirements, combined with modern information technology means, the cost accounting can be made precise, dynamic, and automated, thereby effectively supporting the company's refined management decisions, enhancing market competitiveness, and promoting the sustainable and healthy development of the clothing manufacturing industry.

[0009] In order to achieve the above object, the present invention adopts the following technical solution:

[0010] In a first aspect, the present invention provides a method for calculating labor cost of garment sample making, comprising the following steps:

[0011] S1. Construct a comprehensive coefficient library; the comprehensive coefficient library includes: a basic model coefficient library, a component coefficient library, a brand difficulty coefficient library, a technical center difficulty coefficient library, and a proofing number influence coefficient library;

[0012] S2. Combine the style information specified by the customer and match the various coefficients of each style of different types of work through fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient;

[0013] S3. Through the clothing sample coefficient calculation model, various coefficients under each style of different types of work are comprehensively calculated to obtain a comprehensive coefficient;

[0014] S4. Based on the comprehensive coefficient, the performance wages of all employees in the garment sample making process are calculated to obtain the corresponding labor cost accounting results.

[0015] Furthermore, in said S1,

[0016] The basic style coefficient library is based on the production process, time and material cost of different clothing styles, and assigns coefficients reflecting the basic workload to each clothing style under different types of work;

[0017] The component coefficient library is based on the complexity, processing difficulty, required materials and special process requirements of each garment component, and allocates coefficients reflecting the processing workload and particularity to each component under different types of work;

[0018] The brand difficulty coefficient library sets a coefficient reflecting the difficulty of sample preparation for each brand under different types of work based on the requirements and quality standards of different brands;

[0019] Based on the technical level, equipment advancement, production experience, personnel quality, and project management ability of the technology center, a difficulty coefficient library for the technology center assigns coefficients reflecting its sample preparation ability and efficiency to each technology center under different work types.

[0020] Based on the impact of the number of sample pieces on production efficiency, material utilization rate, labor cost, and time cost, an influence coefficient library for the number of sample pieces assigns coefficients reflecting its scale effect and cost - benefit to each number of sample pieces under different work types.

[0021] Further, the step S2 includes:

[0022] S21. Construct a multi - dimensional feature vector M including clothing style M1, component M2, brand M3, technology center M4, and number of sample pieces M5 for each style under different work types i ; where M i =(M1, M2, M3, M4, M5);

[0023] S22. For each type of coefficient library in the comprehensive coefficient library, respectively construct a corresponding feature vector space V for different work types i =(V1, V2, …, V n-1 , V n );

[0024] S23. Define a similarity function sim=(M i , V i ), and calculate the similarity between the multi - dimensional feature vector M i and the feature vector space V i ; where

[0025]

[0026] S24. Set a threshold T. When sim=(M, V i )≥T, select the coefficient corresponding to this project as the matching result. If there are multiple projects meeting the conditions, select the coefficient corresponding to the project with the largest sim(K, vi) value as the matching result; if sim=(M, V i )<T and no suitable coefficient can be directly matched, use the difference algorithm for coefficient estimation and take the coefficient estimation result as the matching result;

[0027] S25. Output the basic style coefficient, component coefficient, brand difficulty coefficient, technology center difficulty coefficient, and influence coefficient of the number of sample pieces corresponding to each style under different work types.

[0028] Further, in the step S24, using the difference algorithm for coefficient estimation includes:

[0029] Given two close data points X1 and X2, use the difference algorithm to calculate the unknown point X i The coefficient C i :

[0030]

[0031] Among them, C1 and C2 are the coefficients corresponding to data points X1 and X2 respectively.

[0032] Furthermore, in S3, the comprehensive coefficient K is calculated based on the clothing sample coefficient calculation model. ij ,include:

[0033]

[0034] Where A represents the additional adjustment factor composed of multiple factors, and p represents the number of samples.

[0035] Furthermore, the additional adjustment factor A is constructed, including:

[0036] Construct an external factor set Q including seasonal changes Q1, market trends Q2, and raw material price fluctuations Q3; Q = (Q1, Q2, Q3);

[0037] Set an initial weight for each external factor, where the sum of the weights is equal to 1;

[0038] Construct a basic adjustment function for each external factor and combine it with actual data to obtain the specific adjustment value of the factor under the current conditions;

[0039] Combining the initial weights of each factor and its corresponding adjustment value, the additional adjustment factor is calculated using a weighted sum formula.

[0040] Furthermore, in S4, the performance salary S of employees in the garment sample making process is calculated, including:

[0041]

[0042] in, represents the skill wage of job type i, Represents the performance-based basic salary for job type i.

[0043] In a second aspect, the present invention provides a clothing sample making labor cost accounting system, comprising:

[0044] Comprehensive coefficient library construction module: construct a comprehensive coefficient library; the comprehensive coefficient library includes: basic model coefficient library, component coefficient library, brand difficulty coefficient library, technical center difficulty coefficient library, and proofing number influence coefficient library;

[0045] Coefficient matching module: Combined with the style information specified by the customer, the fuzzy matching algorithm is used to match the various coefficients of each style of different types of work; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient;

[0046] Comprehensive coefficient calculation module: Through the clothing sample coefficient calculation model, the various coefficients of each style of different types of work are comprehensively calculated to obtain the comprehensive coefficient;

[0047] Labor cost accounting module: Based on the comprehensive coefficient, the performance wages of all employees in the clothing sample making process are calculated to obtain the corresponding labor cost accounting results.

[0048] In a third aspect, the present invention provides an electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor implements the above-mentioned method for calculating labor cost of clothing sample making when executing the computer program.

[0049] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned clothing sample making labor cost accounting method is implemented.

[0050] The descriptions of the second to fourth aspects of the present invention can refer to the detailed description of the first aspect; and the beneficial effects of the descriptions of the second to fourth aspects can refer to the analysis of the beneficial effects of the first aspect, which will not be repeated here.

[0051] It can be seen from the above technical solution that compared with the prior art, the present invention has the following beneficial effects:

[0052] 1. By building a comprehensive coefficient library including basic style coefficient library, component coefficient library, brand difficulty coefficient library, technical center difficulty coefficient library and sample number influence coefficient library, a comprehensive consideration of multiple influencing factors in the garment sample making process is achieved. Compared with the existing technology that only calculates costs based on a single or limited factor, it can more accurately reflect the real cost of garment sample making and improve the accuracy and reliability of cost accounting.

[0053] 2. Use fuzzy matching algorithm to match various coefficients under each style information of different types of work, and use difference algorithm to estimate coefficients when the appropriate coefficient cannot be directly matched. This flexible processing method improves the adaptability and flexibility of cost accounting, enabling the method to cope with a variety of complex situations, such as the introduction of new styles, the application of special processes, etc., without the need to frequently update the coefficient library, reducing maintenance costs.

[0054] 3. It also considers the impact of external factors such as seasonal changes, market trends, and raw material price fluctuations on the cost of clothing sample making, and dynamically adjusts the cost accounting results by constructing additional adjustment factors. This dynamic adjustment mechanism makes the cost accounting results closer to the actual situation, and can timely reflect the impact of market changes and raw material price fluctuations on costs, providing a more accurate basis for the company's cost management and decision-making. BRIEF DESCRIPTION OF THE DRAWINGS

[0055] In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings required for use in the embodiments or the description of the prior art will be briefly introduced below. Obviously, the drawings described below are only embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on the provided drawings without paying creative work.

[0056] Figure 1 A flow chart of a method for calculating labor cost of garment sample making provided by an embodiment of the present invention;

[0057] Figure 2 A schematic diagram of the structure of a clothing sample making labor cost accounting system provided by an embodiment of the present invention;

[0058] Figure 3 A schematic diagram of the structure of an electronic device is provided for an embodiment of the present invention. DETAILED DESCRIPTION

[0059] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0060] The accounting method provided in the embodiment of the present application can be applied to an accounting server. The above-mentioned accounting server can be hardware or software. When the accounting server is hardware, it can be implemented as a distributed server cluster that provides accounting services, or it can be implemented as a single server. When the accounting server is software, it can be installed in the servers listed above. It can be implemented as multiple software or software modules, or it can be implemented as a single software or software module, which is not specifically limited here.

[0061] Embodiment 1;

[0062] like Figure 1 As shown, the present invention provides a method for calculating labor cost of clothing sample making, comprising the following steps:

[0063] S1. Construct a comprehensive coefficient library; the comprehensive coefficient library includes: a basic model coefficient library, a component coefficient library, a brand difficulty coefficient library, a technical center difficulty coefficient library, and a proofing number influence coefficient library;

[0064] S2. Combine the style information specified by the customer and match the various coefficients of each style of different types of work through fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient;

[0065] S3. Through the clothing sample coefficient calculation model, various coefficients under each style of different types of work are comprehensively calculated to obtain a comprehensive coefficient;

[0066] S4. Based on the comprehensive coefficient, the performance wages of all employees in the garment sample making process are calculated to obtain the corresponding labor cost accounting results.

[0067] This method accurately estimates costs through a comprehensive coefficient library and fuzzy matching algorithm, uses a difference algorithm to respond to new style challenges, and introduces additional adjustment factors to quantify the impact of external market factors. It can help companies achieve more accurate, flexible and real-time clothing sample making labor cost accounting, thereby optimizing resource allocation and enhancing market response speed.

[0068] The following is a further detailed description of each step and related technical features of the method:

[0069] In this embodiment S1, a comprehensive coefficient library is constructed;

[0070] Specifically, the comprehensive coefficient library includes: basic model coefficient library, component coefficient library, brand difficulty coefficient library, technical center difficulty coefficient library, and proofing number impact coefficient library;

[0071] The basic style coefficient library is based on the production process, time and material cost of different clothing styles, and assigns coefficients reflecting the basic workload to each clothing style under different types of work;

[0072] As shown in Table 1 below, in the process of garment sample making, the pattern making coefficients corresponding to some pattern makers in the basic style coefficient library and the sample making coefficients corresponding to the sample workers are shown;

[0073] Table 1

[0074]

[0075] The component coefficient library is based on the complexity, processing difficulty, required materials and special process requirements of each garment component, and allocates coefficients reflecting the processing workload and particularity to each component under different types of work;

[0076] As shown in Table 2 below, in the process of garment sample making, the pattern making coefficients corresponding to some pattern makers in the component coefficient library and the sample making coefficients corresponding to sample garment workers are shown;

[0077] Table 2

[0078]

[0079]

[0080] The brand difficulty coefficient library sets a coefficient reflecting the difficulty of sample preparation for each brand under different types of work based on the requirements and quality standards of different brands;

[0081] The technical center difficulty coefficient database is based on the technical level, equipment advancement, production experience, personnel quality and project management ability of the technical center, and allocates coefficients reflecting its sample preparation ability and efficiency to each technical center under different types of work;

[0082] The proofing quantity impact coefficient library is based on the impact of the proofing quantity on production efficiency, material utilization, labor cost and time cost, and allocates coefficients reflecting its scale effect and cost-effectiveness to each proofing quantity under different types of work.

[0083] In this step, by constructing a comprehensive coefficient library with multiple dimensions including basic styles, components, brand difficulty, technical center difficulty and the impact of the number of samples, the labor cost accounting of clothing sample making has been refined and dynamic, which has significantly improved the accuracy and flexibility of cost accounting, and provided strong support for enterprises to optimize resource allocation, improve production efficiency and market competitiveness.

[0084] In this embodiment S2, in combination with the style information specified by the customer, various coefficients under each style of different types of work are matched through a fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient;

[0085] Specifically include:

[0086] S21, construct a multidimensional feature vector M containing clothing style M1, component M2, brand M3, technical center M4 and number of sample pieces M5 for each style of different types of work. i ; Among them, M i =(M1,M2,M3,M4,M5);

[0087] S22. For each type of coefficient library in the comprehensive coefficient library, construct the characteristic vector space V corresponding to different types of work. i =(V1,V2,…,V n-1 ,V n );

[0088] S23. Define the similarity function sim = (M i , V i ) and calculate the similarity between the multi-dimensional feature vector M i and the feature vector space V i ; where

[0089]

[0090] S24. Set the threshold T. When sim = (M, V i ) ≥ T, select the coefficient corresponding to this item as the matching result. If there are multiple items that meet the conditions, select the coefficient corresponding to the item with the largest sim(K, vi) value as the matching result; if sim = (M, V i ) < T and no suitable coefficient can be directly matched, use the difference algorithm to estimate the coefficient and use the coefficient estimation result as the matching result;

[0091] It also includes: Given two adjacent data points X1, X2, use the difference algorithm to calculate the coefficient C i at the unknown point X i :

[0092]

[0093] where C1 and C2 are the coefficients corresponding to the data points X1 and X2 respectively.

[0094] S25. Output the basic style coefficient, part coefficient, brand difficulty coefficient, technology center difficulty coefficient, and sample-making piece number impact coefficient corresponding to each style of different job types.

[0095] This step combines the fuzzy matching algorithm and the difference algorithm to achieve accurate matching and estimation of various coefficients in clothing sample-making under different job types, effectively improving the flexibility and accuracy of cost accounting, and providing a more refined cost control method for the enterprise.

[0096] In this embodiment S3, through the clothing sample-making coefficient accounting model, various coefficients under each style information of different job types are comprehensively calculated to obtain a comprehensive coefficient;

[0097] Specifically including:

[0098] Calculate the comprehensive coefficient K ij ;

[0099]

[0100] where A represents an additional adjustment factor composed of multiple factors, and p represents the number of sample-making pieces.

[0101] Further, the construction of the additional adjustment factor A includes:

[0102] Construct an external factor set Q including seasonal changes Q1, market trends Q2, and raw material price fluctuations Q3; Q = (Q1, Q2, Q3);

[0103] Set an initial weight for each external factor, where the sum of the weights is equal to 1;

[0104] Construct a basic adjustment function for each external factor and combine it with actual data to obtain the specific adjustment value of the factor under the current conditions;

[0105] Combining the initial weights of each factor and its corresponding adjustment value, the additional adjustment factor is calculated using a weighted sum formula.

[0106] Specifically, seasonal changes use periodic functions (such as sine or cosine functions) to simulate the impact of clothing demand in different time periods of a year; market trends use time series analysis models to evaluate the impact of market trends on the difficulty and cost of making samples for specific styles of clothing; raw material price fluctuations use regression analysis to establish linear or nonlinear functions related to the market price index to quantify the impact of raw material price changes on costs.

[0107] This step constructs a clothing sample coefficient calculation model and introduces additional adjustment factors, comprehensively considering the impact of various internal and external factors on cost accounting, and realizes the precise calculation of the comprehensive coefficient for each style information of different types of work, further improving the accuracy and practicality of cost accounting, and providing enterprises with a more scientific basis for cost control.

[0108] In this embodiment S4, based on the comprehensive coefficient, the performance wages of all employees in the garment sample making process are calculated to obtain the corresponding labor cost accounting results.

[0109] Furthermore, the calculation of the performance salary S of employees in the clothing sample making process includes:

[0110]

[0111] in, represents the skill wage of job type i, Represents the performance-based basic salary for job type i.

[0112] During the calculation process, the employee's skill salary is first determined based on his or her job type and skill level, and then the skill salary is adjusted based on the comprehensive coefficient to reflect the wage differences under different workloads and difficulty levels.

[0113] Through the clothing sample making labor cost accounting method in this embodiment, the performance wages of all employees in the clothing sample making process can be calculated more accurately, thereby obtaining accurate labor cost accounting results. This not only helps enterprises to allocate resources more reasonably and optimize cost structure, but also improves the overall competitiveness of enterprises.

[0114] Embodiment 2;

[0115] In this embodiment, a clothing manufacturing enterprise introduces a clothing sample labor cost accounting method to achieve more accurate, flexible and transparent cost management, and aims to optimize resource allocation, improve production efficiency, and enhance market response speed.

[0116] The following is the specific implementation process:

[0117] The style information specified by a certain customer includes: clothing style: adult men's woven trousers; parts: waistband, leg openings, pockets, additional parts (darts or pleats); brand: high-end brand; technical center: a technical center with advanced equipment and technical team; number of samples: 10 pieces.

[0118] Furthermore, the fuzzy matching algorithm is used to match the coefficients of each style of different types of work, including:

[0119] The coefficients of the pattern maker for the specific style of "Adult Men's Woven Trousers" are:

[0120] Basic model coefficient 0.6, component coefficient 0.255, brand difficulty coefficient 0.2, technical center difficulty coefficient 0.2, sample number impact coefficient 0.7; Among them, component coefficient includes: waistband 0.1, leg opening 0.01*1.5, pocket 0.05*2, additional parts 0.02*2;

[0121] The coefficients of the sampler for the specific style of "adult men's woven trousers" are:

[0122] Basic style coefficient 0.2, component coefficient 0.385, brand difficulty coefficient 0.2, technical center difficulty coefficient 0.2, sample number impact coefficient 0.7; Among them, component coefficient includes: waistband 0.16, hem 0.03*1.5, pocket 0.05*2, additional parts 0.02*1;

[0123] Furthermore, through the clothing sample coefficient calculation model, the various coefficients under each style of different types of work are comprehensively calculated to obtain the comprehensive coefficient;

[0124]

[0125] Among them, the additional adjustment factor A composed of multiple factors is 0.85;

[0126] The comprehensive coefficient K of the pattern maker for the specific style of "adult men's woven trousers" 11 is 7.46725; K 11 =(0.6+0.255+0.2+0.2)*0.85*10*0.7=7.46725

[0127] The comprehensive coefficient K of the sample maker for the specific style of "adult men's woven trousers" 21 is 5.86075; K 11 =(0.2+0.385+0.2+0.2)*0.85*10*0.7=5.86075

[0128] Furthermore, the performance wages of all employees in the clothing sample making process are calculated to obtain the corresponding labor cost accounting results;

[0129]

[0130] The monthly skill wages of pattern makers and sample makers are 4,000 yuan and 3,000 yuan respectively; the performance-based basic wages of pattern makers and sample makers are 40 yuan and 30 yuan respectively;

[0131] The above 10 samples can be completed in one working day. If there are 20 working days in that month, the monthly comprehensive coefficients of the pattern maker and the sample maker are 149.345 and 117.215 respectively. The monthly performance salary of the pattern maker is 149.345×40+4000=9973.8 yuan; the monthly performance salary of the sample maker is 117.215×30+3000=6516.45 yuan.

[0132] The company not only received monthly performance wages of 9,973.8 yuan and 6,516.45 yuan for pattern makers and sample workers respectively, but was also able to more accurately assess labor costs. Combined with other production costs, the company was able to optimize resource allocation, rationally arrange production plans, improve production efficiency, and quickly respond to market changes, thereby enhancing the company's competitiveness and market response speed.

[0133] Embodiment 3;

[0134] like Figure 2 As shown, this embodiment provides a clothing sample making labor cost accounting system, including:

[0135] Comprehensive coefficient library construction module: used to construct a comprehensive coefficient library; the comprehensive coefficient library includes: basic model coefficient library, component coefficient library, brand difficulty coefficient library, technical center difficulty coefficient library, and proofing number influence coefficient library;

[0136] Coefficient matching module: used to match various coefficients under each style information of different types of work through fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient;

[0137] Comprehensive coefficient calculation module: used to comprehensively calculate various coefficients under each style information of different types of work through the clothing sample coefficient calculation model to obtain the comprehensive coefficient;

[0138] Labor cost accounting module: Based on the comprehensive coefficient, the performance wages of all employees in the clothing sample making process are calculated to obtain the corresponding labor cost accounting results.

[0139] The clothing sample making labor cost accounting system provided in this embodiment builds a comprehensive comprehensive coefficient library, uses a fuzzy matching algorithm to accurately match various coefficients, and then obtains the comprehensive coefficient through comprehensive calculation, so as to efficiently and accurately calculate the performance wages of all employees in the clothing sample making process, thereby realizing the scientific accounting and refined management of labor costs, and significantly improving the accuracy and efficiency of cost control.

[0140] Embodiment 4;

[0141] like Figure 3 As shown, this embodiment provides an electronic device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, and the processor implements the above-mentioned clothing sample making labor cost accounting method when executing the computer program.

[0142] Embodiment 5;

[0143] This embodiment provides a computer-readable storage medium, which stores a computer program. When the computer program is executed by a processor, the above-mentioned clothing sample making labor cost accounting method is implemented.

[0144] In the above embodiments provided in the present application, it should be understood that the disclosed methods, systems, devices and media can be implemented in other ways. The above described methods, systems, devices and media embodiments are only schematic. For example, the division of modules or units is only a logical function division, and there may be other division methods in actual implementation. Each functional unit can be integrated into a processing unit, or each unit can exist physically separately, or two or more units can be integrated into one unit.

[0145] The units and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0146] The computer program includes computer program code, which may be in source code form, object code form, executable file or some intermediate form, etc. Computer readable media may include: any entity or device capable of carrying computer program code, recording medium, USB flash drive, mobile hard disk, magnetic disk, optical disk, computer memory, read-only memory, random access memory, electric carrier signal, telecommunication signal and software distribution medium, etc.

[0147] The above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. These modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application, and should all be included in the protection scope of the present application.

Claims

1. A method for calculating labor cost of clothing sample making, characterized in that: The following steps are involved: S1. Construct a comprehensive coefficient library; the comprehensive coefficient library includes: a basic model coefficient library, a component coefficient library, a brand difficulty coefficient library, a technical center difficulty coefficient library, and a proofing number influence coefficient library; S2. Combine the style information specified by the customer and match the various coefficients of each style of different types of work through fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient; S3. Through the clothing sample coefficient calculation model, various coefficients under each style of different types of work are comprehensively calculated to obtain a comprehensive coefficient; S4. Based on the comprehensive coefficient, the performance wages of all employees in the garment sample making process are calculated to obtain the corresponding labor cost accounting results.

2. A method for calculating labor cost of clothing sample making according to claim 1, characterized in that: In S1, The basic style coefficient library is based on the production process, time and material cost of different clothing styles, and assigns coefficients reflecting the basic workload to each clothing style under different types of work; The component coefficient library is based on the complexity, processing difficulty, required materials and special process requirements of each garment component, and allocates coefficients reflecting the processing workload and particularity to each component under different types of work; The brand difficulty coefficient library sets a coefficient reflecting the difficulty of sample preparation for each brand under different types of work based on the requirements and quality standards of different brands; The technical center difficulty coefficient database is based on the technical level, equipment advancement, production experience, personnel quality and project management ability of the technical center, and allocates coefficients reflecting its sample preparation ability and efficiency to each technical center under different types of work; The proofing quantity impact coefficient library is based on the impact of the proofing quantity on production efficiency, material utilization, labor cost and time cost, and allocates coefficients reflecting its scale effect and cost-effectiveness to each proofing quantity under different types of work.

3. A method for calculating labor cost of garment sample making according to claim 1, characterized in that: The S2 comprises: S21, construct a multidimensional feature vector M containing clothing style M1, component M2, brand M3, technical center M4 and number of sample pieces M5 for each style of different types of work. i ; Among them, M i =(M1,M2,M3,M4,M5); S22. For each type of coefficient library in the comprehensive coefficient library, construct the characteristic vector space V corresponding to different types of work. i =(V1,V2,…,V n-1 ,V n ); S23, define similarity function sim=(M i ,V i ), calculate the multidimensional feature vector M i With the eigenvector space V i The similarity between S24. Set a threshold T. When sim=(M, V i )≥T, select the coefficient corresponding to this item as the matching result. If there are multiple items that meet the conditions, select the coefficient corresponding to the item with the largest sim(K, vi) value as the matching result; if sim=(M, V i )<T and no appropriate coefficient can be directly matched, use the difference algorithm to estimate the coefficient and use the coefficient estimation result as the matching result; S25. Output the basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing quantity influence coefficient corresponding to each style of different types of work.

4. A method for calculating labor cost of garment sample making according to claim 3, characterized in that: In S24, the coefficient estimation is performed using a difference algorithm, including: Given two close data points X1 and X2, use the difference algorithm to calculate the unknown point X i The coefficient C i : Among them, C1 and C2 are the coefficients corresponding to data points X1 and X2 respectively.

5. A method for calculating labor cost of garment sample making according to claim 1, characterized in that: In S3, the comprehensive coefficient K is calculated based on the clothing sample coefficient calculation model. ij ,include: Where A represents the additional adjustment factor composed of multiple factors, and p represents the number of samples.

6. A method for calculating labor cost of garment sample making according to claim 5, characterized in that: The additional adjustment factor A is constructed, including: Construct an external factor set Q including seasonal changes Q1, market trends Q2, and raw material price fluctuations Q3; Q = (Q1, Q2, Q3); Set an initial weight for each external factor, where the sum of the weights is equal to 1; Construct a basic adjustment function for each external factor and combine it with actual data to obtain the specific adjustment value of the factor under the current conditions; Combining the initial weights of each factor and its corresponding adjustment value, the additional adjustment factor is calculated using a weighted sum formula.

7. A method for calculating labor cost of garment sample making according to claim 1, characterized in that: In S4, the performance salary S of employees in the garment sample making process is calculated, including: in, represents the skill wage of job type i, Represents the performance-based basic salary for job type i.

8. A clothing sample making labor cost accounting system, characterized in that: include: Comprehensive coefficient library construction module: used to construct a comprehensive coefficient library; The comprehensive coefficient library includes: basic model coefficient library, component coefficient library, brand difficulty coefficient library, technical center difficulty coefficient library, and proofing number influence coefficient library; Coefficient matching module: used to match various coefficients under each style information of different types of work through fuzzy matching algorithm; the various coefficients include: basic model coefficient, component coefficient, brand difficulty coefficient, technical center difficulty coefficient and proofing number influence coefficient; Comprehensive coefficient calculation module: used to comprehensively calculate various coefficients under each style information of different types of work through the clothing sample coefficient calculation model to obtain the comprehensive coefficient; Labor cost accounting module: Based on the comprehensive coefficient, the performance wages of all employees in the clothing sample making process are calculated to obtain the corresponding labor cost accounting results.

9. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, the method for calculating the labor cost of garment sample making according to any one of claims 1 to 7 is implemented.

10. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by a processor, a method for calculating labor cost of garment sample making according to any one of claims 1 to 7 is implemented.

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