KR102353391B1 - Surplus fabric sharing system and method for designer - Google Patents

Abstract

According to the present invention, when franchise sewing factories produce clothing and register information on the remaining surplus fabric in the material bank DB through the management server, designers who design clothing-related products can order and share the necessary surplus fabric from the material bank DB. A system and method for sharing surplus fabrics are disclosed.
The disclosed surplus fabric sharing system includes: a franchise sewing factory management terminal that produces clothing and provides information on the remaining surplus fabric; A management server that operates a surplus fabric sharing site, classifies the surplus fabric provided from the franchise sewing factory management terminal by category, classifies by size, determines a price, and posts it as a surplus fabric product on the surplus fabric sharing site; a material bank database (DB) for storing surplus fabric products posted by the management server and information thereon; and a consumer terminal accessing the sharing site to order and pay for the surplus fabric product.

Description

Surplus fabric sharing system and method for designer

The present invention relates to a surplus fabric sharing system and method, and more particularly, when franchise sewing factories produce clothing and register information on surplus fabric remaining in the material bank DB through a management server, designers who design clothing-related products It relates to a surplus fabric sharing system and method for ordering and sharing necessary surplus fabric from a material bank DB.

In general, in the clothing production process, designers create their own unique clothing based on specific content, and deliver work orders that reflect this to a sewing factory.

Sewing factories produce specific garments requested by designers through sewing work using fabrics.

However, in a sewing factory, surplus fabric is often generated after a specific garment requested by a designer is produced using fabric.

On the other hand, designers need a small amount of fabric to produce sample clothes according to the specific content they have created, but fabric vendors sell them only in a certain unit for apparel production.

Accordingly, there is a problem in that designers have no choice but to purchase a certain unit of fabric more than necessary for the production of sample clothes.

Korean Patent Publication No. 10-0609062 (Registration Date: July 27, 2006)

It is an object of the present invention to solve the above problems, when franchise sewing factories produce clothing and register information on surplus fabric in the material bank DB through the management server, designers who design clothing-related products can use the material bank DB It is to provide a surplus fabric sharing system and method so that the necessary surplus fabric can be ordered and shared.

Surplus fabric sharing system according to an aspect of the present invention for achieving the above object, a franchise sewing factory management terminal that provides information on the surplus fabric remaining after producing clothing; A management server that operates a surplus fabric sharing site, classifies the surplus fabric provided from the franchise sewing factory management terminal by category, classifies by size, determines a price, and posts it as a surplus fabric product on the surplus fabric sharing site; a material bank database (DB) for storing surplus fabric products posted by the management server and information thereon; and a consumer terminal accessing the sharing site to order and pay for the surplus fabric product.

The management server includes a member information DB that stores company information created based on identification information of the franchise sewing factories that have joined, a content information DB that stores content information so that a designer can design their own clothing, and the franchise sewing It may include a fabric information DB that stores information about the surplus fabric uploaded by the factory management terminal.

The management server may include: a communication unit that interworks with the franchise sewing factory management terminal and the consumer terminal through a wired network or a wireless network; a database for storing communication order information received from the outside through the communication unit, or storing the stock amount and inventory amount of the surplus fabric, classification data, and product information; And based on the sales data according to the product order information, using the cost and sales price for each product, calculate the margin and operating profit ratio for a certain period and match the product name. It may include a microprocessor that receives and learns major factors, models the learned data to create a sales model, and inputs new surplus fabric information into the sales model to predict and calculate margin and operating profit rates.

The microprocessor calculates a margin rate and an operating profit rate for a certain period using the cost and sales price for each product based on the sales data, matches the product name to the product name, stores it in the database as training data, and models the training data to create a model Estimation function formula (E(x)) that shows the relationship between margin rate and operating profit rate by classifying the modeling data group for ) can be calculated.

The microprocessor calculates distance values between each operating profit rate data for each product name and estimated data corresponding to the graph of the estimation function formula, sums up all the calculated distance values, and divides it by the number of data according to the number of product names, the calculated distance The slope (a) value and the intercept (b) value of the function formula having the margin ratio and operating profit ratio that are the smallest among the values and are closest to the graph of the estimated function formula are calculated, and the calculated slope (a) value and intercept (b) value by substituting into the estimation function formula to determine the sales function formula (y=ax+b), creating a sales model for calculating the operating profit ratio according to the margin ratio, and substituting each margin ratio (x) calculated for each product name into the sales model. It is possible to calculate the operating profit rate (y) for each product name, compare the operating profit rate (y) for each product name and the commission data, and list them in descending order.

The microprocessor calculates each margin rate (x) for each product name for the verification data group, substitutes each calculated margin rate (x) into the sales model to calculate the operating profit rate (y), respectively, calculated for each product name Calculate the distance values from the graph of the estimated function formula for the margin ratio (x) and operating profit ratio (y) of The sales model can be verified according to whether the difference between the calculated average distance value and the minimum distance value is within an error range by comparing with the minimum distance value in the relationship between (y).

On the other hand, the surplus fabric sharing method according to another aspect of the present invention for achieving the above object comprises the steps of: (a) uploading information about the surplus fabric remaining after the franchise sewing factory management terminal produces clothes to the management server; (b) categorizing, by the management server, the surplus fabric uploaded from the franchise sewing factory management terminal by category, classifying by size, determining a price, and posting the surplus fabric product as a surplus fabric product on a sharing site; (c) storing, by the management server, the surplus fabric product and its information in a location bank database (DB); and (d) accessing the sharing site by the consumer terminal to order and pay for the surplus fabric product.

In step (d), the management server calculates the margin rate and operating profit rate for a certain period using the cost and sale price for each product based on the sales data according to the order information of the surplus fabric product, and matches the product name with the product name, and the period It learns by inputting key factors for a period that differs by more than a certain amount compared to other values, creates a sales model by modeling the learned data, and predicts margin and operating profit rates by entering new surplus fabric information into the sales model can be calculated.

In step (d), the management server calculates the margin rate and operating profit rate for a certain period using the cost and sales price for each product based on the sales data, matches the product name with the product name, stores it in the database as learning data, and stores it in the learning data. It is classified into a modeling data group for modeling and generating a model, and a verification data group for verifying the created model. In the modeling data group, the margin rate and operating profit rate are learned by product name to indicate the relationship between the margin rate and the operating profit rate. Calculate the function formula (E(x)), calculate the distance values between each operating profit rate data for each product name and the estimated data corresponding to the graph of the estimated function formula, respectively, and add all the calculated distance values to the number of data according to the number of product names By dividing by , the slope (a) value and intercept (b) value of the function formula that is the smallest among the calculated distance values and has the margin and operating profit ratio closest to the graph of the estimated function formula are calculated, and the calculated slope (a) value and intercept (b) values are substituted into the estimation function formula to determine the sales function formula (y=ax+b), a sales model is created to calculate the operating profit ratio according to the margin ratio, and each margin ratio (x) calculated for each product name is By substituting each into the sales model, the operating profit rate (y) for each product name can be calculated, and the operating profit rate (y) and commission data can be compared for each product name and listed in descending order.

In step (d), the management server calculates each margin rate (x) for each product name for the verification data group, and substitutes each calculated margin rate (x) into the sales model to calculate the operating profit rate (y), , calculates distance values from the graph of the estimated function formula for each margin rate (x) and operating profit rate (y) calculated for each product name, calculates the average distance value for the calculated distance values, and uses the calculated distance average value as the margin rate The sales model can be verified according to whether the difference between the calculated average distance value and the minimum distance value is within an error range by comparing with the minimum distance value in the relationship between (x) and the operating profit margin (y).

According to the present invention, designers who design clothing-related products can order and utilize as much surplus fabric as necessary for sample clothing production from the material bank DB.

In addition, the sewing factory can save the cost of using the vehicle by collecting the surplus fabric at regular intervals, and on the contrary, it is possible to obtain ancillary revenue by selling the surplus fabric.

And, the sharing system according to the present invention can be applied to other industries such as leather, bags, shoes, and wigs.

1 is a configuration diagram schematically showing the main configuration of the surplus fabric sharing system according to an embodiment of the present invention.
2 is a configuration diagram schematically illustrating an internal configuration of a management server according to an embodiment of the present invention.
3 is a diagram illustrating an operation flowchart for explaining a method for sharing a surplus fabric according to an embodiment of the present invention.
4 is a flowchart illustrating a process of predicting and calculating a sales margin ratio and an operating profit ratio for a surplus fabric in the management server according to an embodiment of the present invention.
5 is a diagram illustrating an example of calculating a function expression having a margin rate and an operating profit rate closest to the graph of the estimation function expression according to an embodiment of the present invention.

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art to which the present invention pertains can easily implement them. The present invention may be implemented in several different forms and is not limited to the embodiments described herein.

In order to clearly explain the present invention, parts irrelevant to the description are omitted, and the same reference numerals are assigned to the same or similar components throughout the specification.

Throughout the specification, when a part is "connected" with another part, this includes not only the case of being "directly connected" but also the case of being "electrically connected" with another element interposed therebetween. . Also, when a part "includes" a certain component, it means that other components may be further included, rather than excluding other components, unless otherwise stated.

When a part is referred to as being “above” another part, it may be directly on the other part, or the other part may be involved in between. In contrast, when a part refers to being "directly above" another part, no other part is involved in between.

The terms first, second and third etc. are used to describe, but are not limited to, various parts, components, regions, layers and/or sections. These terms are used only to distinguish one part, component, region, layer or section from another part, component, region, layer or section. Accordingly, a first part, component, region, layer or section described below may be referred to as a second part, component, region, layer or section without departing from the scope of the present invention.

The terminology used herein is for the purpose of referring to specific embodiments only, and is not intended to limit the present invention. As used herein, the singular forms also include the plural forms unless the phrases clearly indicate the opposite. The meaning of "comprising," as used herein, specifies a particular characteristic, region, integer, step, operation, element and/or component, and includes the presence or absence of another characteristic, region, integer, step, operation, element and/or component. It does not exclude additions.

Terms indicating a relative space such as “below” and “above” may be used to more easily describe the relationship of one part shown in the drawing to another part. These terms, along with their intended meanings in the drawings, are intended to include other meanings or operations of the device in use. For example, if the device in the drawings is turned over, some parts described as being "below" other parts are described as being "above" other parts. Thus, the exemplary term “down” includes both the up and down directions. The device may be rotated 90 degrees or at other angles, and terms denoting relative space are to be interpreted accordingly.

Although not defined otherwise, all terms including technical and scientific terms used herein have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention belongs. Commonly used terms defined in the dictionary are additionally interpreted as having a meaning consistent with the related technical literature and the presently disclosed content, and unless defined, are not interpreted in an ideal or very formal meaning.

Hereinafter, with reference to the accompanying drawings, the embodiments of the present invention will be described in detail so that those of ordinary skill in the art can easily carry out the present invention. However, the present invention may be implemented in several different forms and is not limited to the embodiments described herein.

1 is a configuration diagram schematically showing the main configuration of the surplus fabric sharing system according to an embodiment of the present invention.

1, the surplus fabric sharing system 100 according to the present invention, the franchise sewing factory management terminal 110, the management server 120, the material bank database (DB) 130 and the consumer terminal (140) include

The franchise sewing factory management terminal 110, the surplus fabric sharing system, provides information on the surplus fabric remaining after the production of clothes. That is, the franchise sewing factory management terminal 110 is a computer terminal of a sewing factory company, and accesses and uploads information on the surplus fabric to the management server 120 .

The management server 120 operates the surplus fabric sharing site, classifies the surplus fabric provided from the franchise sewing factory management terminal by category, classifies by size, determines the price, and posts it as a surplus fabric product on the surplus fabric sharing site. .

The material bank DB 130 stores surplus fabric products posted by the management server and information about them.

The consumer terminal 140 is a smartphone mainly carried by designers or a computer terminal used by designers, and accesses a sharing site to order and pay for surplus fabric products.

In addition, the management server 120 is a member information DB that stores company information created based on identification information of the franchise sewing factories that have joined, and a content information DB that stores content information so that designers can design their own clothing. and a fabric information DB that stores information on surplus fabric uploaded by the franchise sewing factory management terminal.

The member information DB is a database of subscriber information. In particular, based on identification information corresponding to the name, address, ID, password, contact information, etc. of the orderer or each company, the down payment, balance, or down payment and balance are distributed The account information corresponding to the name of the bank, account holder, account number, etc. for fabric, etc.) into a database.

The content information DB stores characters, characters, or logos in a database by category in order to support the ordering designer to design his/her own clothing. In particular, the name of the content provider and description of the content, category items for classification (couples/love/animals/numbers/flowers/movies/food/music/figures, etc.) and basic information on images, etc. It stores the sales amount and contract information.

The fabric information DB stores the image, size, quantity, company name, address, contact information, etc. of surplus fabric.

2 is a configuration diagram schematically illustrating an internal configuration of a management server according to an embodiment of the present invention.

Referring to FIG. 2 , the management server 120 according to the present invention includes a communication unit 210 , a database 220 , a microprocessor 230 , and a memory 240 .

The communication unit 210 transmits and receives data by interworking with the franchise sewing factory management terminal 110 and the consumer terminal 140 through a wired network or a wireless network.

The database 220 stores communication order information received from the outside through the communication unit, or stores the stock amount and inventory amount of surplus fabrics, classification data, and product information.

The microprocessor 230 calculates a margin rate and an operating profit rate for a certain period using the cost and sales price for each product based on the sales data according to the product order information, matches the product name, and differs by more than a certain amount compared to other values during the period. It learns by receiving input of major factors for the period of departure, creates a sales model by modeling the learned data, and inputs new surplus fabric information into the sales model to predict and calculate margin and operating profit rates.

In addition, the microprocessor 230 may calculate a margin rate and an operating profit rate for a certain period using the cost and sale price for each product based on the sales data, match the product name with the product name, and store it in the database 220 as learning data.

In addition, the microprocessor 230 classifies the learning data into a modeling data group for generating a model by modeling the training data, and a verification data group for verifying the generated model, and for the modeling data group, the margin and operating profit rate for each product name. can be learned to calculate an estimated function expression (E(x)) representing the relationship between the margin rate and the operating profit rate.

In addition, the microprocessor 230 calculates the distance values between each operating profit rate data for each product name and the estimated data corresponding to the graph of the estimation function expression, respectively, adds up all the calculated distance values, and divides it by the number of data according to the number of product names. , it is possible to calculate the slope (a) value and the intercept (b) value of the function formula having the margin ratio and operating profit ratio that are the smallest among the calculated distance values and are closest to the graph of the estimated function formula.

In addition, the microprocessor 230 determines the sales function formula (y = ax + b) by substituting the calculated slope (a) value and the intercept (b) value into the estimation function formula to calculate the operating profit rate according to the margin rate. You can create a sales model.

In addition, the microprocessor 230 calculates an operating profit rate (y) for each product name by substituting each margin rate (x) calculated for each product name into the sales model, and compares the operating profit rate (y) with the commission data for each product name in descending order can be listed as .

Here, the fee data means a fee required for one product when an order for a specific surplus fabric is received from a consumer and sales are generated. That is, products with a high operating profit rate and low commission data are ranked on the top list.

At this time, the management server 120 receives a fee at a certain rate for each of the franchise sewing factory management terminal 110 that supplied the surplus fabric and the consumer terminal 140 that ordered the surplus fabric when a specific surplus fabric is traded. .

Meanwhile, the microprocessor 230 may calculate each margin rate (x) for each product name for the verification data group, and substitute each calculated margin rate (x) into the sales model to calculate the operating profit rate (y), respectively. .

In addition, the microprocessor 230 may calculate distance values from the graph of the estimation function expression for each margin rate (x) and operating profit rate (y) calculated for each product name.

In addition, the microprocessor 230 calculates a distance average value for the calculated distance values, compares the calculated distance average value with a minimum distance value in the relationship between the margin rate (x) and the operating profit rate (y), and calculates the calculated distance value. The sales model can be verified according to whether the difference between the average distance value and the minimum distance value is within an error range.

In addition, the microprocessor 230 matches the margin rate and operating profit rate calculated using the cost and sales price for each product to the product name as shown in Table 1 below, and corresponds to the matched product name with the product type, price, market size, etc. (220) can be stored.

product name Product type market size cost price Margin rate operating margin Product 1 plain side medium scale S1 P1 0.4 0.3 Product 2 linen small S2 P2 0.35 0.2 ... ... ... ... ... ... ... product n cottonwood medium scale Sn Pn 0.5 0.35

Here, the market size includes a small market with less than 100,000 users, a medium market with more than 100,000 users and less than 1 million users, and a large market with more than 1 million users. In addition, the microprocessor 230 converts the modeling data group into products. According to the type, reclassified into 6 fields such as general cotton, oxford cotton, canvas cotton, linen, cotton, and daimaru, and for each reclassified modeling data group, the margin ratio (x) and operating profit ratio (y) are calculated by product name. By learning, the estimation function equation (E(x)) representing the relationship between the margin rate (x) and the operating profit rate (y) can be calculated for each of the six categories of product types.

In addition, the microprocessor 230 is a distance value ([E ( x)-y(x)] ² ) are calculated respectively, and the calculated distance values are added up and divided by the number of data (m) according to the number of product names to become the smallest among the calculated distance values and the most in the graph of the estimation function expression. The slope (a) value and the intercept (b) value of the functional formula having the margin ratio (x) and the operating profit ratio (y) that are close to each other can be calculated for each of the six categories of product types.

In addition, the microprocessor 230 substitutes the slope (a) value and the intercept (b) value calculated according to the six fields of the product type into the estimation function formula for each of the six fields of the product type to the sales function formula (y = ax + b). ), a sales model that calculates the operating profit ratio according to the margin ratio can be created for each product type, such as general cotton, oxford cotton, canvas cotton, linen, cotton wood, daimaru, and the like.

In addition, the microprocessor 230 reclassifies the modeling data group into three fields of a small market, a medium market, and a large market according to the market size, and for each reclassified modeling data group, the margin rate (x) for each product name , by learning the operating profit rate (y), it is possible to calculate the estimated function equation (E(x)) representing the relationship between the margin rate (x) and the operating profit rate (y) for each of the three areas of the market size.

In addition, the microprocessor 230 is a distance value ([E(x)) between each operating profit rate (y) data for each product name and the estimated data corresponding to the graph of the estimated function formula (E(x)) for each of the three fields of the market scale. )-y(x)] ² ) are calculated, each calculated distance values are summed up and divided by the number of data (m) according to the number of product names. The slope (a) value and the intercept (b) value of the functional formula having the margin rate (x) and the operating profit rate (y) can be calculated according to the three fields of market size.

In addition, the microprocessor 230 substitutes the slope (a) value and the intercept (b) value calculated according to the three fields of the market size into the estimated function equations for each of the three fields of the market size, respectively, to the sales function formula (y = ax + By determining b), a sales model that calculates the operating profit ratio according to the margin ratio can be created for each of the three fields according to the small market, medium market, and large market size of the market.

In the memory 240, the microprocessor 230 calculates a margin rate and an operating profit rate for a certain period of time using the cost and sales price for each product based on sales data according to product order information, matches the product name to the product name, and learns the learned data. The sales model created by modeling can be temporarily saved.

In addition, the memory 240 may store processing data of the microprocessor 230 or store data received from the franchise sewing factory management terminal 110 and the consumer terminal 140 .

Meanwhile, although not shown in the drawing, the management server 120 according to the present invention may include a data input unit for receiving data from an administrator, a display unit for displaying data or information or processed data, and the like. Here, the data input unit may be a smart phone carried by the administrator.

3 is a diagram illustrating an operation flowchart for explaining a method for sharing a surplus fabric according to an embodiment of the present invention.

Referring to FIG. 3 , in the surplus fabric sharing system 100 according to the present invention, the franchise sewing factory management terminal 110 uploads information on the surplus fabric remaining after producing clothes to the management server 120 (S310) .

Here, the franchise sewing factory management terminal 110 may upload a fabric material and fabric material information. Fabric material means the actual fabric on which the pattern will be printed, such as silk, cotton, nylon, etc. Fabric material information is an image file produced by photographing the fabric material with a digital camera or scanning it with a scanner (eg, JPG, JPEG, BMP file, etc.) means In addition, the fabric material information may include data such as a fabric material number provided by a supplier for each image file, and fabric material characteristics (eg, feel of a material, a degree of material), and the like. The fabric material information may include pattern information. The pattern information means an image file (eg, JEPG, JPG, BMP file, etc.) to be printed on actual fabric materials such as floral and animal patterns.

Then, the management server 120 classifies the surplus fabric uploaded from the franchise sewing factory management terminal by category, classifies by size, determines the price, and posts it on the surplus fabric sharing site as a surplus fabric product (S320).

Here, when determining the price for the surplus fabric, the management server 120 may determine by applying the thickness, width, weight (weight) of the fabric as well as the type and size of the fabric.

Next, the management server 120 stores the surplus fabric product and information thereon in the location bank database (DB) 130 (S330).

Here, the location bank DB 130 can be configured inside the management server 120, and can also be implemented as a separate independent device so that it can be accessed from a remote location.

Next, the consumer terminal 140 accesses the sharing site to order and pay for surplus fabric products (S340).

Here, the consumer terminal 140 may be a smart phone carried by a clothing designer or a desktop computer used by the designer in an office environment.

In addition, the order and payment for the product may be performed in a generally known and conventional method.

Thereafter, the management server 120 may calculate the margin ratio and the operating profit ratio for the surplus fabric sales through the process shown in FIG. 4 .

4 is a flowchart illustrating a process of predicting and calculating a sales margin ratio and an operating profit ratio for a surplus fabric in the management server according to an embodiment of the present invention.

4, the management server 120 according to the present invention, when the communication unit 210 receives the product order information or communication order information (S410), based on the sales data according to the order information of the surplus far-end product, each Using the cost and sales price for each product, a margin ratio and an operating profit ratio for a certain period are calculated (S420).

That is, the management server 120, based on the sales data, using the cost (s) and the sales price (p) for each product according to the following Equation 1, the margin rate (x) and the operating profit rate (y) for one year or three years ) is calculated for each product name.

The management server 120 matches the calculated margin rate and operating profit rate to the product name, and stores the matched product name in the database 220 by matching the product type, price, and market size as shown in Table 1.

In addition, in the management server 120 , the microprocessor 230 calculates the margin and operating profit rate for a certain period using the cost and sale price for each product based on the sales data, matches the product name to the product name, and stores it in the database 220 as learning data. can be saved

Next, the microprocessor 230 learns by matching the margin rate and operating profit rate calculated using the cost and sales price for each product to the product name (S430), and the margin rate and operating profit rate differ by more than a certain amount compared to other values during a certain period of time. I learn by inputting the main factors from the data input part for the period.

Here, the microprocessor 230 may be classified into a modeling data group for generating a model by modeling the training data, and a verification data group for verifying the generated model. For example, the microprocessor 230 sets the learning data corresponding to 800 pieces as the modeling data group (80%) as the modeling data group (80%), and corresponds to 200 pieces, since the number of training data is 1,000 when 1,000 products are sold. The training data to be used can be set as the verification data group (20%).

In addition, the microprocessor 230 learns the margin rate and the operating profit rate for each product name for the modeling data group, and as shown in FIG. 5 , the estimation function expression E(x) of the following Equation 2 representing the relationship between the margin rate and the operating profit rate ) can be calculated.

^{The microprocessor 230 calculates the distance values ([d=H(x)-y(x)] 2} ) between each operating profit rate data for each product name and the estimated data corresponding to the graph of the estimation function expression, respectively, and calculates each calculated angle The cost function of Equation 3 is calculated by adding all distance values d and dividing (average) by the number of data m according to the number of product names.

As shown in FIG. 5 , the microprocessor 230 becomes the minimum according to the cost function expression among the calculated distance values, and the function expression (b) having the margin rate (x) and the operating profit rate (y) closest to the graph of the estimated function expression ), the slope (a) value and the intercept (b) value are calculated. 5 is a diagram illustrating an example of calculating a function expression having a margin rate and an operating profit rate closest to the graph of the estimation function expression according to an embodiment of the present invention. As shown in FIG. 5 , the microprocessor 230 calculates each margin rate (x) and Using the operating profit margin (y) value, the slope (a) value and the intercept (b) value of the function formula (B) can be calculated.

The microprocessor 230 creates a sales model by modeling the learned data (S440).

That is, the microprocessor 230 determines the sales function expression (y = ax + b) by substituting the calculated slope (a) value and the intercept (b) value into the estimation function expression, and sales for calculating the operating profit rate according to the margin rate. create a model

The microprocessor 230 substitutes the slope (a) value and the intercept (b) value corresponding to the graph in FIG. A sales function formula is determined, and a sales model is created according to the determined sales function formula.

The microprocessor 230 may receive new surplus fabric information from a smart phone or an input unit and apply it to a sales model to predict and calculate a margin rate and an operating profit rate (S450).

That is, the microprocessor 230 calculates an operating profit rate (y) for each product name by substituting each margin rate (x) calculated for each product name into the sales model, and compares the operating profit rate (y) with the commission data for each product name in descending order You can list.

The microprocessor 230 may calculate each margin rate (x) for each product name for the verification data group, and substitute each calculated margin rate (x) into the sales model to calculate the operating profit rate (y), respectively.

The microprocessor 230 calculates distance values from the graph of the estimated function expression for each margin rate (x) and operating profit rate (y) calculated for each product name, and may calculate an average distance value for the calculated distance values. .

The microprocessor 230 compares the calculated average distance value with the minimum distance value in the relationship between the margin rate (x) and the operating profit rate (y) to determine whether the difference between the calculated average distance value and the minimum distance value is within the error range. Depending on whether or not the sales model can be verified.

The microprocessor 230 reclassifies the modeling data group into three fields of a small market, a medium market, and a large market according to the market size, and for each reclassified modeling data group, the margin rate (x), sales By learning the profit rate (y), the estimated function equation (E(x)) representing the relationship between the margin rate (x) and the operating profit rate (y) can be calculated for each of the three areas of the market size.

The microprocessor 230 is a distance value ([E(x)- y(x)] ² ) are calculated, each calculated distance values are added up, and divided by the number of data (m) according to the number of product names. The slope (a) value and the intercept (b) value of the functional formula having (x) and the operating profit rate (y) can be calculated according to the three areas of the market size, respectively.

The microprocessor 230 substitutes the slope (a) value and the intercept (b) value calculated according to the three fields of the market size into the estimated function expressions for each of the three fields of the market size, respectively, to obtain a sales function formula (y = ax + b) By determining , a sales model that calculates the operating profit ratio according to the margin ratio can be created for each of the three fields according to the small market, medium market, and large market size of the market.

As described above, according to the present invention, when franchise sewing factories produce clothing and register information on surplus fabric remaining in the material bank DB through the management server, designers who design clothing-related products need surplus fabric in the material bank DB. It is possible to realize a surplus fabric sharing system and method for ordering and sharing.

Those skilled in the art to which the present invention pertains should understand that the present invention can be embodied in other specific forms without changing the technical spirit or essential characteristics thereof, so the embodiments described above are illustrative in all respects and not restrictive. only do The scope of the present invention is indicated by the following claims rather than the detailed description, and all changes or modifications derived from the meaning and scope of the claims and their equivalent concepts should be construed as being included in the scope of the present invention. .

100: surplus fabric sharing system
110: franchise sewing factory management terminal
120: management server
130: material bank DB
140: consumer (designer) terminal
210: communication department
220: database
230: microprocessor
240: memory

Claims (10)

a franchise sewing factory management terminal that provides information on surplus fabric remaining after production of clothing;
A management server that operates a surplus fabric sharing site, classifies the surplus fabric provided from the franchise sewing factory management terminal by category, classifies by size, determines a price, and posts it as a surplus fabric product on the surplus fabric sharing site;
a material bank database (DB) for storing surplus fabric products posted by the management server and information thereon; and
a consumer terminal accessing the sharing site to order and pay for the surplus fabric product;
including,
The management server,
a communication unit that interworks with the franchise sewing factory management terminal and the consumer terminal through a wired network or a wireless network;
a database for storing communication order information received from the outside through the communication unit, or storing the stock amount and inventory amount of the surplus fabric, classification data, and product information; and
Based on the sales data according to the communication order information and product order information, using the cost and sales price for each product, calculate the margin and operating profit rate for a certain period and match the product name, a microprocessor for receiving and learning key factors for the period, modeling the learned data to generate a sales model, and inputting new surplus fabric information into the sales model to predict and calculate margin and operating profit rates;
including,
The microprocessor is
Based on the sales data, using the cost and sales price for each product, the margin rate and operating profit rate for a certain period are calculated, matched with the product name, stored in the database as learning data, and modeling data group to create a model by modeling the learning data and the verification data group to verify the created model, and the modeling data group is reclassified into 6 fields including general cotton, Oxford cotton, canvas cotton, linen, cotton, and daimaru according to product types, For each classified modeling data group, the margin rate and operating profit rate are learned for each product name, and an estimated function expression (E(x)) representing the relationship between the margin rate and the operating profit rate is calculated for each of the six fields of the product type,
For each of the six categories of the product type, the distance values between each operating profit rate data for each product name and the estimated data corresponding to the graph of the estimation function formula are respectively calculated, the calculated distance values are all summed up and divided by the number of data according to the number of product names, Calculate the slope (a) value and the intercept (b) value of the functional formula having the margin ratio and operating profit ratio that are the smallest among the calculated distance values and are closest to the graph of the estimated function formula, respectively, according to the six fields of the product type, Sales for calculating the operating profit ratio according to the margin ratio by substituting the calculated slope (a) value and the intercept (b) value into the estimation function formula for each of the six categories of the product type to determine the sales function formula (y=ax+b) A model is created according to the six fields of the above product type, and each margin rate (x) calculated for each product name is substituted in the sales model to calculate the operating profit rate (y) for each product name, and the operating profit rate (y) and commission for each product name Surplus fabric sharing system that compares data and lists them in descending order.
The method of claim 1,
The management server,
The member information DB that stores company information created based on the identification information of the franchised sewing factories, the contents information DB that stores contents information so that designers can design their own clothes, and the franchise sewing factory management terminal upload A surplus fabric sharing system, including a fabric information DB that stores information on one surplus fabric.
delete delete delete The method of claim 1,
The microprocessor calculates each margin rate (x) for each product name for the verification data group, substitutes each calculated margin rate (x) into the sales model to calculate the operating profit rate (y), respectively, calculated for each product name Calculate the distance values from the graph of the estimated function formula for the margin ratio (x) and operating profit ratio (y) of (y) A surplus far-end sharing system that verifies the sales model according to whether the difference between the calculated average distance value and the minimum distance value is within an error range by comparing it with the minimum distance value in the relationship between (y).
(a) uploading, by the franchise sewing factory management terminal, information on the surplus fabric remaining after the production of clothing to the management server;
(b) categorizing, by the management server, the surplus fabric uploaded from the franchise sewing factory management terminal by category, classifying by size, determining the price, and posting the surplus fabric product as a surplus fabric product on a sharing site;
(c) storing, by the management server, the surplus fabric product and its information in a location bank database (DB); and
(d) the consumer terminal accessing the sharing site to order and pay for the surplus fabric product;
including,
In step (d), the management server,
Based on the sales data according to the order information of the surplus fabric products, the margin rate and operating profit rate for a certain period are calculated using the cost and sales price for each product and matched with the product name, It learns by inputting key factors for the period, creates a sales model by modeling the learned data, and inputs new surplus fabric information into the sales model to predict and calculate margin and operating profit rates,
Based on the sales data, using the cost and sales price for each product, the margin rate and operating profit ratio for a certain period are calculated, matched with the product name, and stored in the database as learning data. Modeling data group to create a model by modeling the training data and the verification data group to verify the created model, and the modeling data group is reclassified into 6 fields including general cotton, Oxford cotton, canvas cotton, linen, cotton, and daimaru according to product type, For each classified modeling data group, the margin rate and operating profit rate are learned for each product name, and an estimated function expression (E(x)) representing the relationship between the margin rate and the operating profit rate is calculated for each of the six categories of the product type, and the product type For each of the six fields, the distance values between each operating profit rate data by product name and the estimated data corresponding to the graph of the estimation function formula are calculated, and the calculated distance values are added up and divided by the number of data according to the number of product names. The slope (a) value and the intercept (b) value of the function formula having the margin ratio and operating profit ratio that are the smallest among them and closest to the graph of the estimated function formula are calculated according to the six fields of the product type, respectively, and the calculated slope ( A) By substituting the value and the intercept (b) value into the estimation function formula, the sales function formula (y=ax+b) is determined, and a sales model for calculating the operating profit ratio according to the margin ratio is generated according to the six categories of the above product types. And, by substituting each margin rate (x) calculated for each product name into the sales model, calculating the operating profit rate (y) for each product name, comparing the operating profit rate (y) with the commission data for each product name and listing them in descending order .
delete delete 8. The method of claim 7,
In step (d), the management server,
For the verification data group, each margin rate (x) is calculated for each product name, and operating profit rate (y) is calculated by substituting each calculated margin rate (x) into the sales model, and each calculated margin rate (x) for each product name and calculating the distance values from the graph of the estimated function expression for the operating profit rate (y), calculating the average distance value for the calculated distance values, and using the calculated distance average value as the relationship between the margin rate (x) and the operating profit rate (y) A method of sharing a surplus fabric, in which the sales model is verified according to whether the difference between the calculated average distance value and the minimum distance value is within an error range by comparing it with the minimum distance value in .

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