A clothing production quality evaluation method based on big data analysis

Abstract

The invention relates to the field of clothing production, and in particular to a clothing production quality evaluation method based on big data analysis, comprising the following steps: S1. cutting quality detection; S2. cutting quality analysis; S3. sewing quality detection; S4. sewing quality analysis; S5. assembly quality detection; S6. assembly quality analysis; S7. comprehensive quality evaluation. The invention obtains a cutting evaluation coefficient of each clothing piece according to the cutting quality data of the clothing fabric, and then screens out each sewable piece, obtains a sewing quality evaluation coefficient of the clothing according to the sewing quality data of the clothing piece, obtains an assembly quality evaluation coefficient of the clothing according to the process detail data of the clothing, and then comprehensively analyzes to obtain a production quality evaluation index of the clothing, and provides feedback thereon, so as to more accurately and comprehensively reflect the overall production quality status of the clothing, help ensure the consistency and stability of clothing production, and reduce quality fluctuations.

Description

Technical Field

[0001] The present invention relates to the field of clothing production, and in particular to a clothing production quality evaluation method based on big data analysis. Background Art

[0002] As people's living standards continue to improve, the demand for clothing is becoming increasingly diversified and personalized. While the clothing industry is booming, the quality of clothing production has become a vital concern. Consumers have higher and higher requirements for the quality of clothing. They not only pay attention to style design, but also pay more attention to wearing comfort, durability and safety. This has prompted clothing manufacturers to pay attention to quality to meet consumer expectations. High-quality clothing can not only meet consumers' pursuit of wearing experience, but also enhance brand image and market competitiveness. Continuous research and improvement on clothing production quality will drive the entire clothing industry in a healthier and more sustainable direction and provide people with better quality clothing products.

[0003] The patent name is a technical solution published in a Chinese patent entitled "A clothing production quality inspection device and its inspection method" (patent number is 202111036529.5). The solution is to place the clothing between two fixed plates, slide the sliding block through a motor and a threaded rod, flatten the clothing with a roller and cut it, and then salt-immerse the I-shaped buttons, rivets and zippers of the clothing and observe the rust. Then, by pulling the limit rod and other operations, the clothing pieces with stitches are limited and clamped, and finally the hydraulic cylinder is started to slide the sliding table to tear the clothing pieces, and the spring dynamometer readings are observed and recorded to understand the maximum strength of the stitches. At the same time, It can comprehensively evaluate the production quality of garments and ensure the accuracy of the test results, but there are still some shortcomings, which are specifically manifested in the following aspects: First, the scheme records the maximum strength of the seams by sliding and tearing the garment pieces, but does not involve the analysis of the stitch length of the seams. It may not be able to accurately judge the tightness and uniformity of the seams, and cannot fully reflect the quality of the sewing process. In some cases, although the seam strength meets the requirements, the stitch length is unreasonable, which will still affect the overall quality and durability of the garment. Problems such as thread unravelling may also occur during subsequent use, and are difficult to detect and prevent in advance.

[0004] Second, the plan does not involve cutting analysis of garment pieces, which may result in some cutting defects not being detected in time, such as inconsistent sizes, irregular shapes, etc., resulting in mismatches or inconsistencies in the splicing and stitching of the final garments, thereby affecting the overall shape and wearing effect of the garments. Summary of the invention

[0005] In order to overcome the shortcomings of the background technology, an embodiment of the present invention provides a clothing production quality evaluation method based on big data analysis, which can effectively solve the problems involved in the above-mentioned background technology.

[0006] The purpose of the present invention can be achieved through the following technical solutions: a method for evaluating clothing production quality based on big data analysis, the method comprising the following steps: S1. Cutting quality detection: used to obtain clothing fabric cutting quality data, the fabric cutting quality data including the size accuracy and contour conformity of each clothing piece.

[0007] S2. Cutting quality analysis: According to the cutting quality data of the clothing fabric, the cutting evaluation coefficient of each clothing piece is obtained, and then the sewing pieces are screened out.

[0008] S3. Sewing quality inspection: used to obtain sewing quality data of garment pieces, including the firmness of seams and uniformity of stitch length.

[0009] S4. Sewing quality analysis: used to obtain the sewing quality evaluation coefficient of clothing based on the sewing quality data of clothing pieces.

[0010] S5. Assembly quality inspection: used to obtain detailed process data of clothing, including button tightness and zipper quality.

[0011] S6. Assembly quality analysis: used to obtain the assembly quality evaluation coefficient of clothing based on the detailed process data of the clothing.

[0012] S7. Comprehensive quality evaluation: It is used to obtain the production quality evaluation index of clothing according to the sewing quality evaluation coefficient and assembly quality evaluation coefficient of clothing, and provide feedback.

[0013] Preferably, the specific analysis method of the cutting quality detection is as follows: in the first step, a number of key points are determined on each garment piece according to the set position and marked, recorded as key points of each garment piece, the key points of each garment piece are matched one by one according to the set garment structure, recorded as key point groups of each garment piece, and the distance between the key point groups of each garment piece is measured, recorded as d mi , m represents the number of the mth garment piece, m = 1, 2, ..., q, i represents the number of the key points of the i-th group of garment pieces, i = 1, 2, ..., n, and at the same time, the preset design distance of each key point group of each garment piece is read from the management database, recorded as Substituting this into the formula Get the size accuracy of each garment piece α m .

[0014] In the second step, images of each garment piece are acquired, and design drawings of each garment piece are read from the management database. The edge contours of each garment piece are extracted from the images of each garment piece and the design drawings of each garment piece through edge detection technology, which are recorded as the edge contour of each garment piece and the design edge contour of each garment piece. The overlapping length of the edge contour of each garment piece and the corresponding design edge contour is obtained by superimposing the edge contours of each garment piece and the design edge contour of each garment piece, which is recorded as l. m , and extract the length of the design edge contour of each garment piece, recorded as Substituting this into the formula Get the contour conformity β of each garment piece m .

[0015] Preferably, the specific analysis method of the cutting quality analysis is: respectively reading the size accuracy α of each garment cutting piece m , Contour conformity β m , substituting it into the formula γ m =α m *η1+β m *η2 obtains the cutting evaluation coefficient γ of each garment piece m , η1 and η2 represent the weight factors of the set size accuracy and contour conformity respectively, and compare the cutting evaluation coefficient of each garment piece with the preset qualified threshold value of the cutting evaluation coefficient of the garment piece and the usable threshold value of the cutting evaluation coefficient of the garment piece. If the cutting evaluation coefficient of a garment piece is greater than or equal to the preset qualified threshold value of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece is qualified and recorded as a qualified piece. If the cutting evaluation coefficient of a garment piece is less than the preset qualified threshold value of the cutting evaluation coefficient of the garment piece, and is greater than or equal to the preset usable threshold value of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece needs to be improved and is recorded as a usable piece. Secondary processing is performed on each usable piece. If the cutting evaluation coefficient of a garment piece is less than the preset usable threshold value of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece is unqualified. All qualified pieces and usable pieces after secondary processing are counted and combined as each sewable piece.

[0016] Preferably, the specific analysis method of the sewing quality detection is as follows: in the first step, a number of test samples are randomly selected from the sewing pieces that have been sewn as test samples, which are recorded as test pieces. The sutures on the test pieces are fixed on the tensile testing equipment, and the tension is gradually applied according to the set tension level until the sutures become loose, and the value of the tension level at this time is recorded as the maximum tension λ of each test piece. j , j represents the number of the jth sampled piece, j = 1, 2, ..., k, through the formula The stitch firmness σ of the garment pieces is obtained, k represents the number of sampled pieces, and λ0 represents the set reference tension.

[0017] In the second step, two adjacent stitches are grouped together, and the distance between each group of stitches of each sampled piece is measured along the stitches by a measuring tool, which is recorded as the stitch distance d' of each group of stitches of each sampled piece. jf , f represents the number of the fth group of stitches, f = 1, 2, ..., g, and the average stitch length of each sampled piece is obtained by taking the average stitch length of each group of stitches on each sampled piece, which is recorded as Substituting this into the formula Uniformity of stitch length of garment pieces g represents the number of seam groups. At the same time, the stitch length of each group of seam threads of each sampled piece is compared with the preset maximum allowable stitch length. If the stitch length of a group of seam threads of a sampled piece is greater than or equal to the preset maximum allowable stitch length, the seam thread of the sampled piece is judged to be skipped. The number of skipped seams of each sampled piece is counted, and the number of skipped seams of the garment piece is obtained by taking the average value, which is recorded as τ.

[0018] Preferably, the specific analysis method of the sewing quality analysis is: respectively reading the stitching firmness σ and stitch uniformity of the garment pieces The number of jumps τ, substituting it into the formula Get the sewing quality evaluation coefficient of clothing φ1, φ2, and φ3 represent the weight factors of suture firmness, stitch uniformity, and number of skipped stitches, respectively, and τ0 represents the maximum allowable number of skipped stitches.

[0019] Preferably, the specific analysis method of the assembly quality inspection is as follows: in the first step, a number of pieces are randomly selected from the finished garments as quality inspection garments, which are recorded as each quality inspection garment, and tension is gradually applied to each button of each quality inspection garment according to the set tension level until the button becomes loose, and the value of the tension level borne by each button of each quality inspection garment is recorded as the tension λ' of each button of each quality inspection garment ax , a represents the number of the a-th quality inspection garment, a=1,2,...,b, x represents the number of the x-th button, x=1,2,...,y, through the formula The button tightness of the clothing is obtained, υ, y represents the number of buttons, b represents the number of pieces of clothing inspected, and λ'0 represents the set reference value of button tension.

[0020] In the second step, the zipper images of each quality inspection garment are acquired, and the edge contours of the zippers of each quality inspection garment are extracted by edge detection technology, which are recorded as the edge contours of each quality inspection garment zipper. The standard edge contours of the garment zippers are read from the management database, and the overlap length of the edge contours of each quality inspection garment zipper is obtained by overlapping the zippers of each quality inspection garment with the standard edge contours of the garment zippers. At the same time, the length of the standard edge contours of the garment zippers is extracted, and the appearance quality of the zippers of each garment is obtained by dividing the overlap length of the edge contours of each quality inspection garment zipper by the length of the standard edge contour of the garment zipper, which is recorded as ξ a At the same time, the force required to close the zipper of each quality inspection garment is tested multiple times using a dynamometer, recorded as P ar , r represents the number of the r-th zipping, r = 1, 2, ..., o, and in each repeated zipping process, the number of times the zipper of each quality inspection garment is stuck is counted, recorded as θ ar , substituting it into the formula Get the zipper mass ρ of the clothing, They respectively represent the weight factors of the set zipper appearance quality, the pulling force required for the zipper to be closed, and the number of times the zipper of the quality inspection clothing is stuck, and ο represents the number of times the zipper is closed.

[0021] Preferably, the specific analysis method of the assembly quality analysis is: respectively read the button fastening degree υ and the zipper quality ρ of the clothing, and substitute them into the formula ψ=υ*κ1+ρ*κ2 to obtain the assembly quality evaluation coefficient ψ of the clothing, where κ1 and κ2 respectively represent the weight factors of the set button fastening degree and zipper quality.

[0022] Preferably, the specific analysis method for comprehensive quality evaluation is: reading the sewing quality evaluation coefficient of the garment respectively The assembly quality evaluation coefficient ψ is substituted into the formula The production quality evaluation index χ of the clothing is obtained, where w1 and w2 represent the weight factors of the set sewing quality evaluation coefficient and the assembly quality evaluation coefficient respectively, and e represents a natural constant. The production quality evaluation index of the clothing is compared with the preset production quality evaluation index threshold. If the production quality evaluation index of the clothing is greater than or equal to the preset production quality evaluation index threshold, it means that the production quality of this batch of clothing is qualified. If the production quality evaluation index of the clothing is less than the preset production quality evaluation index threshold, it means that the production quality of this batch of clothing is unqualified, and feedback is given.

[0023] Compared with the prior art, the embodiments of the present invention have at least the following advantages or beneficial effects: 1. The present invention obtains the cutting evaluation coefficient of each garment piece based on the fabric cutting quality data of the garment, and then screens out each sewable piece, which can avoid using pieces of poor quality for sewing, thereby ensuring the quality of the final garment product.

[0024] 2. The present invention obtains the sewing quality evaluation coefficient of clothing according to the sewing quality data analysis of clothing pieces, which can intuitively reflect the level of sewing quality, help to find problems in time and make improvements, so that the sewing quality of different batches of clothing remains relatively stable and consistent.

[0025] 3. The present invention obtains the clothing assembly quality evaluation coefficient based on the clothing process detail data analysis, which can better control the production process, realize the refined management of clothing quality, and improve the overall clothing assembly quality.

[0026] 4. The present invention obtains the production quality evaluation index of clothing based on the sewing quality evaluation coefficient and assembly quality evaluation coefficient of clothing, and provides feedback, which can more accurately and comprehensively reflect the overall production quality status of clothing, help ensure the consistency and stability of clothing production, and reduce quality fluctuations. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] The present invention is further described using the accompanying drawings, but the embodiments in the accompanying drawings do not constitute any limitation to the present invention. A person skilled in the art can obtain other drawings based on the following drawings without creative work.

[0028] Figure 1 It is a schematic diagram of the method flow of the present invention. DETAILED DESCRIPTION

[0029] 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.

[0030] See also Figure 1 As shown, the present invention provides a clothing production quality evaluation method based on big data analysis, the method comprising the following steps: S1. Cutting quality detection: used to obtain clothing fabric cutting quality data, the fabric cutting quality data including the size accuracy and contour conformity of each clothing piece.

[0031] The specific analysis method of cutting quality detection is as follows: in the first step, a number of key points are determined on each garment piece according to the set position and marked, recorded as key points of each garment piece, each key point of each garment piece is matched one by one according to the set garment structure, recorded as key point groups of each garment piece, and the distance between each key point group of each garment piece is measured, recorded as d mi, m represents the number of the mth garment piece, m = 1, 2, ..., q, i represents the number of the key points of the i-th group of garment pieces, i = 1, 2, ..., n, and at the same time, the preset design distance of each key point group of each garment piece is read from the management database, recorded as Substituting this into the formula Get the size accuracy of each garment piece α m ; Making the key points of each cutting piece correspond to the structure of the garment helps to ensure that the overall pattern and structure of the garment meet the design requirements, improve the accuracy of the cutting pieces, and reduce errors.

[0032] It should be noted that the clothing structure refers to the composition and relationship of various parts of the clothing, and the distance between each key point group refers to the distance between points in different key point groups. In a specific embodiment, the top can be divided into structural parts such as collar, shoulder, chest, waist, cuffs, etc. according to the clothing structure. The key points are determined at the two structural parts of the collar and shoulder of the clothing piece according to the set position, and the collar key points and the shoulder key points are recorded as a key point group. The one-to-one correspondence means that the collar key points in each clothing piece correspond to the shoulder key points, and the distance between the key point groups is the distance from the collar key point to the shoulder key point.

[0033] In the second step, images of each garment piece are acquired, and design drawings of each garment piece are read from the management database. The edge contours of each garment piece are extracted from the images of each garment piece and the design drawings of each garment piece through edge detection technology, which are recorded as the edge contour of each garment piece and the design edge contour of each garment piece. The overlapping length of the edge contour of each garment piece and the corresponding design edge contour is obtained by superimposing the edge contours of each garment piece and the design edge contour of each garment piece, which is recorded as l. m , and extract the length of the design edge contour of each garment piece, recorded as Substituting this into the formula Get the contour conformity β of each garment piece m ; It can timely discover the deformation or deviation that may occur in the cutting piece during the production process, so as to facilitate timely adjustment and improvement.

[0034] S2. Cutting quality analysis: According to the cutting quality data of the clothing fabric, the cutting evaluation coefficient of each clothing piece is obtained, and then the sewing pieces are screened out.

[0035] The specific analysis method of the cutting quality analysis is: respectively read the size accuracy of each garment piece α m , Contour conformity β m , substituting it into the formula

[0036] γ m =α m *η1+β m*η2 obtains the cutting evaluation coefficient γ of each garment piece m , η1, η2 represent the weight factors of the set size accuracy and contour conformity respectively, compare the cutting evaluation coefficient of each garment piece with the preset qualified threshold of the cutting evaluation coefficient of the garment piece and the threshold of the cutting evaluation coefficient of the garment piece. If the cutting evaluation coefficient of a garment piece is greater than or equal to the preset qualified threshold of the cutting evaluation coefficient of the garment piece, it means that the garment piece is qualified and recorded as a qualified piece. If the cutting evaluation coefficient of a garment piece is less than the preset qualified threshold of the cutting evaluation coefficient of the garment piece and is greater than or equal to the preset qualified threshold of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece is qualified and recorded as a qualified piece. If the cutting evaluation coefficient can be used at a threshold, it means that the cutting of the garment piece needs to be improved and is recorded as a usable piece. Each usable piece is subjected to secondary processing. If the cutting evaluation coefficient of a garment piece is less than the preset threshold of the cutting evaluation coefficient of the preset garment piece, it means that the cutting of the garment piece is unqualified. All qualified pieces and the usable pieces after secondary processing are counted and combined as sewable pieces. Pieces of different quality grades are clearly distinguished to facilitate subsequent targeted processing, improve production efficiency, ensure that only qualified pieces are used for sewing, and help improve the overall quality of clothing.

[0037] It should be noted that the specific analysis method for performing secondary processing on each usable piece is: reading the distance d between each key point group of each garment piece mi , the design distance of each key point group of each garment piece The distances between the key point groups of each usable piece and the design distances of each key point group are obtained by screening and are recorded as d si , s represents the number of the sth available piece, s=1,2,...,p, through the formula Get the difference Δd between the distance between each key point group of each usable piece and the designed distance si If the difference between the distance between a certain key point group of a usable cutting piece and the design distance is positive, the fabric at the key point group of the usable cutting piece is cut accordingly; if the difference between the distance between a certain key point group of a usable cutting piece and the design distance is negative, the fabric at the key point group of the usable cutting piece is not processed; if the difference between the distance between each key point group of a usable cutting piece and the design distance is negative, it is directly recorded as a qualified cutting piece, thereby completing the secondary processing of each usable cutting piece.

[0038] It should be noted that, in a specific embodiment, η1 can be set to 0.5, and η2 can be set to 0.5. Accurate size is the key basis for clothing fit. If the size is inaccurate, the clothing may not be wearable at all or the wearing effect may be extremely poor. The contour conformity will affect the overall shape and appearance of the clothing. Therefore, the weights corresponding to the size accuracy and contour conformity are equal.

[0039] S3. Sewing quality inspection: used to obtain sewing quality data of garment pieces, including the firmness of seams and uniformity of stitch length.

[0040] The specific analysis method of the sewing quality detection is as follows: in the first step, a number of test samples are randomly selected from the sewing pieces that have been sewn as test samples, which are recorded as the sampled test pieces. The sutures on the sampled test pieces are fixed on the tensile testing equipment, and the tension is gradually applied according to the set tension level until the sutures become loose. The value of the tension level at this time is recorded as the maximum tension λ of each sampled test piece. j , j represents the number of the jth sampled piece, j = 1, 2, ..., k, through the formula The seam firmness σ of the garment pieces is obtained, where k represents the number of sampled pieces and λ0 represents the set reference tension; ensuring that the seams of the garments have sufficient firmness in actual use, improving the durability of the garments, and helping to ensure the stability and consistency of product quality.

[0041] In the second step, two adjacent stitches are grouped together, and the distance between each group of stitches of each sampled piece is measured along the stitches by a measuring tool, which is recorded as the stitch distance d' of each group of stitches of each sampled piece. jf , f represents the number of the fth group of stitches, f = 1, 2, ..., g, and the average stitch length of each sampled piece is obtained by taking the average stitch length of each group of stitches on each sampled piece, which is recorded as Substituting this into the formula Uniformity of stitch length of garment pieces g represents the number of seam groups. At the same time, the stitch lengths of each group of seam threads on each sampled piece are compared with the preset maximum allowable stitch length. If the stitch length of a group of seam threads on a sampled piece is greater than or equal to the preset maximum allowable stitch length, the seam threads on that sampled piece are judged to be skipped. The number of skipped seams on each sampled piece is counted, and the number of skipped seams on the garment piece is obtained by taking the average value, which is recorded as τ. This method can accurately evaluate the stitch length and skipped seam problems on the seams on the pieces, promptly discover defects in production, and improve the appearance quality of garments.

[0042] S4. Sewing quality analysis: used to obtain the sewing quality evaluation coefficient of clothing based on the sewing quality data of clothing pieces.

[0043] The specific analysis method of the sewing quality analysis is: respectively reading the stitching firmness σ and the stitch uniformity of the garment pieces. The number of jumps τ, substituting it into the formula Get the sewing quality evaluation coefficient of clothing φ1, φ2, and φ3 represent the weight factors of seam firmness, stitch uniformity, and number of skipped stitches, respectively, and τ0 represents the maximum allowable number of skipped stitches. It can more accurately and comprehensively reflect the actual sewing quality level of clothing and help improve the stability of the overall quality of clothing.

[0044] It should be noted that, in a specific embodiment, φ1 can be set to 0.4, φ2 can be set to 0.3, and φ3 can be set to 0.3. The firmness of the seam is directly related to the durability and quality of the clothing. Once the seam is not firm, the clothing is prone to problems such as damage. The uniformity of stitch length affects the appearance and craftsmanship of the clothing. Too many skipped stitches will affect the sewing quality and appearance. Therefore, the weight corresponding to the firmness of the seam is slightly higher, and the weights corresponding to the uniformity of stitch length and the number of skipped stitches are equal.

[0045] S5. Assembly quality inspection: used to obtain detailed process data of clothing, including button tightness and zipper quality.

[0046] The specific analysis method of the assembly quality inspection is as follows: in the first step, a number of pieces are randomly selected from the finished garments as the quality inspection garments, which are recorded as each quality inspection garment, and tension is gradually applied to each button of each quality inspection garment according to the set tension level until the button becomes loose, and the value of the tension level of each button of each quality inspection garment is recorded as the tension λ' of each button of each quality inspection garment ax , a represents the number of the a-th quality inspection garment, a=1,2,...,b, x represents the number of the x-th button, x=1,2,...,y, through the formula The button tightness υ of the clothing is obtained, where y represents the number of buttons, b represents the number of pieces of clothing to be inspected, and λ'0 represents the set reference value of button tension; ensuring that buttons are not easy to loosen and fall off during normal use, improving the durability and practicality of clothing, and helping manufacturers to strictly control the quality of button installation and improve the overall quality level of products.

[0047] In the second step, the zipper images of each quality inspection garment are acquired, and the edge contours of the zippers of each quality inspection garment are extracted by edge detection technology, which are recorded as the edge contours of each quality inspection garment zipper. The standard edge contours of the garment zippers are read from the management database, and the overlap length of the edge contours of each quality inspection garment zipper is obtained by overlapping the zippers of each quality inspection garment with the standard edge contours of the garment zippers. At the same time, the length of the standard edge contours of the garment zippers is extracted, and the appearance quality of the zippers of each garment is obtained by dividing the overlap length of the edge contours of each quality inspection garment zipper by the length of the standard edge contour of the garment zipper, which is recorded as ξ a At the same time, the force required to close the zipper of each quality inspection garment is tested multiple times using a dynamometer, recorded as P ar, r represents the number of the r-th zipping, r = 1, 2, ..., o, and in each repeated zipping process, the number of times the zipper of each quality inspection garment is stuck is counted, recorded as θ ar , substituting it into the formula Get the zipper mass ρ of the clothing, They respectively represent the weight factors of the set zipper appearance quality, the pulling force required for the zipper to be closed, and the number of times the zipper is stuck during quality inspection, and ο represents the number of times the zipper is closed. This helps to promptly discover possible manufacturing defects or deviations in the zipper and ensure the consistency of product quality.

[0048] It should be noted that, in a specific embodiment, It can be set to 0.2. It can be set to 0.4. It can be set to 0.4. The pulling force required for the zipper to be closed is related to the convenience and smoothness of use, and the number of times the zipper of the quality inspection clothing is stuck can reflect the reliability and durability of the zipper. Therefore, the pulling force required for the zipper to be closed and the number of times the zipper of the quality inspection clothing is stuck have equal weights.

[0049] S6. Assembly quality analysis: used to obtain the assembly quality evaluation coefficient of clothing based on the detailed process data of the clothing.

[0050] The specific analysis method of the assembly quality analysis is: respectively read the button fastening degree υ and the zipper quality ρ of the clothing, and substitute them into the formula ψ=υ*κ1+ρ*κ2 to obtain the clothing assembly quality evaluation coefficient ψ, κ1 and κ2 respectively represent the weight factors of the set button fastening degree and zipper quality; the influence of the two important components of buttons and zippers on the overall quality of clothing can be comprehensively considered, which is helpful for the manufacturer to accurately grasp the level of clothing assembly quality, find problems in time and make improvements.

[0051] It should be noted that, in a specific embodiment, κ1 can be set to 0.5, and κ2 can be set to 0.5. The tightness of the buttons is related to practical usage issues such as whether the clothing is easy to fall off or open when worn, and has a great impact on the overall function of the clothing. Poor quality of the zipper may cause the clothing to open and close unsmoothly and be easily damaged, affecting the wearing experience and the service life of the clothing. Therefore, the weights corresponding to the tightness of the buttons and the appearance quality of the zipper are equal.

[0052] S7. Comprehensive quality evaluation: It is used to obtain the production quality evaluation index of clothing according to the sewing quality evaluation coefficient and assembly quality evaluation coefficient of clothing, and provide feedback.

[0053] The specific analysis method for comprehensive quality evaluation is: read the sewing quality evaluation coefficient of the garment separately The assembly quality evaluation coefficient ψ is substituted into the formula The production quality evaluation index χ of the clothing is obtained, wherein w1 and w2 represent the weight factors of the set sewing quality evaluation coefficient and the assembly quality evaluation coefficient respectively, and e represents a natural constant. The production quality evaluation index of the clothing is compared with the preset production quality evaluation index threshold. If the production quality evaluation index of the clothing is greater than or equal to the preset production quality evaluation index threshold, it means that the production quality of the batch of clothing is qualified. If the production quality evaluation index of the clothing is less than the preset production quality evaluation index threshold, it means that the production quality of the batch of clothing is unqualified, and feedback is given to it; this helps to improve the quality control level in the production process, ensure the stability of product quality, and facilitate the adoption of targeted improvement measures.

[0054] It should be noted that, in a specific embodiment, w1 can be set to 0.5, and w2 can be set to 0.5. Good sewing quality is directly related to the overall firmness, flatness, and beautiful lines of clothing, and has a great impact on the appearance and durability of clothing. The assembly quality evaluation coefficient covers the installation quality of accessories such as zippers and buttons, which is very important for some clothing that pays attention to details and overall effects. Therefore, the weights corresponding to the sewing quality evaluation coefficient and the assembly quality evaluation coefficient are equal.

[0055] The present invention obtains the cutting evaluation coefficient of each garment piece according to the cloth cutting quality data of the garment, and then screens out each sewable piece, obtains the sewing quality evaluation coefficient of the garment according to the sewing quality data of the garment pieces, obtains the assembly quality evaluation coefficient of the garment according to the process detail data of the garment, obtains the production quality evaluation index of the garment according to the sewing quality evaluation coefficient and the assembly quality evaluation coefficient of the garment, and provides feedback, which can more accurately and comprehensively reflect the overall production quality status of the garment, help ensure the consistency and stability of garment production, and reduce quality fluctuations.

[0056] Although the embodiments of the present invention have been shown and described above, it is to be understood that the above embodiments are exemplary and are not to be construed as limitations on the present invention. A person skilled in the art may make changes, modifications, substitutions and variations to the above embodiments within the scope of the present invention and they are still covered by the protection scope of the present invention.

Claims

1. A clothing production quality evaluation method based on big data analysis, characterized in that: The steps include: S1. Cutting quality detection: used to obtain the cutting quality data of clothing fabrics, including the size accuracy and contour conformity of each clothing piece; S2. Cutting quality analysis: according to the cutting quality data of the clothing fabric, the cutting evaluation coefficient of each clothing piece is obtained, and then each sewing piece is selected; S3. Sewing quality detection: used to obtain sewing quality data of garment pieces, including the firmness of the seams and the uniformity of the stitch length; S4. Sewing quality analysis: used to obtain the sewing quality evaluation coefficient of clothing according to the sewing quality data of clothing pieces; S5. Assembly quality inspection: used to obtain detailed process data of clothing, including button tightness and zipper quality; S6. Assembly quality analysis: used to obtain the assembly quality evaluation coefficient of the garment according to the garment process detail data analysis; S7. Comprehensive quality evaluation: used to analyze the production quality evaluation index of clothing according to the sewing quality evaluation coefficient and assembly quality evaluation coefficient of clothing, and provide feedback; The specific analysis method for comprehensive quality evaluation is: Read the sewing quality evaluation coefficient of the garments respectively , Assembly quality evaluation coefficient , substituting it into the formula Get the production quality evaluation index of clothing ,in They represent the weight factors of the set sewing quality evaluation coefficient and assembly quality evaluation coefficient respectively. It represents a natural constant. The production quality evaluation index of the clothing is compared with the preset production quality evaluation index threshold. If the production quality evaluation index of the clothing is greater than or equal to the preset production quality evaluation index threshold, it means that the production quality of this batch of clothing is qualified. If the production quality evaluation index of the clothing is less than the preset production quality evaluation index threshold, it means that the production quality of this batch of clothing is unqualified, and feedback is given.

2. The method for evaluating clothing production quality based on big data analysis according to claim 1, characterized in that: The specific analysis method of the cutting quality detection is: In the first step, several key points are determined on each garment piece according to the set position and marked, recorded as key points of each garment piece, and the key points of each garment piece are matched one by one according to the set garment structure, recorded as key point groups of each garment piece, and the distance between the key point groups of each garment piece is measured, recorded as , Indicates The number of the garment piece, , Indicates The key points of the group clothing pieces are numbered. At the same time, the preset design distance of each key point group of each garment piece is read from the management database and recorded as , substituting it into the formula Get the size accuracy of each garment piece ; In the second step, images of each garment piece are acquired, and design drawings of each garment piece are read from the management database. The edge contours of each garment piece are extracted from the images of each garment piece and the design drawings of each garment piece through edge detection technology, which are recorded as the edge contour of each garment piece and the designed edge contour of each garment piece. The overlapping length of the edge contour of each garment piece and the corresponding designed edge contour is obtained by superimposing the edge contours of each garment piece and the designed edge contours of each garment piece, which is recorded as , and extract the length of the design edge contour of each garment piece, recorded as , substituting it into the formula Get the contour conformity of each garment piece .

3. The method for evaluating clothing production quality based on big data analysis according to claim 2, characterized in that: The specific analysis method of the cutting quality analysis is: respectively reading the size accuracy of each garment piece , Contour Conformity , substituting it into the formula Get the cutting evaluation coefficient of each garment piece , The weight factors representing the set size accuracy and contour conformity respectively, compare the cutting evaluation coefficient of each garment piece with the preset qualified threshold of the cutting evaluation coefficient of the garment piece and the usable threshold of the cutting evaluation coefficient of the garment piece. If the cutting evaluation coefficient of a garment piece is greater than or equal to the preset qualified threshold of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece is qualified and is recorded as a qualified piece. If the cutting evaluation coefficient of a garment piece is less than the preset qualified threshold of the cutting evaluation coefficient of the garment piece, and is greater than or equal to the preset usable threshold of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece needs to be improved and is recorded as a usable piece. Secondary processing is performed on each usable piece. If the cutting evaluation coefficient of a garment piece is less than the preset usable threshold of the cutting evaluation coefficient of the garment piece, it means that the cutting of the garment piece is unqualified. All qualified pieces and usable pieces after secondary processing are counted and combined as each sewable piece.

4. The method for evaluating clothing production quality based on big data analysis according to claim 1, characterized in that: The specific analysis method of the sewing quality detection is: The first step is to randomly select a number of test samples from each sewing piece that has been sewn as each sample piece, and fix the stitches on each sample piece on the tensile testing device. Gradually apply tension according to the set tension level until the stitches become loose. The value of the tension level at this time is recorded as the maximum tension of each sample piece. , Indicates The number of the sampled pieces, , through the formula Get the seam strength of garment pieces , Indicates the number of sampled pieces. Indicates the set reference tension; The second step is to take two adjacent stitches as a group, and use a measuring tool to measure the distance between each group of stitches of each sampled piece along the stitches, and record it as the stitch distance of each group of stitches of each sampled piece. , Indicates The number of the group sutures, , the average stitch length of each sampled piece is obtained by taking the average stitch length of each group of stitches on each sampled piece, which is recorded as , substituting it into the formula Get the uniformity of stitch length of garment pieces , It indicates the number of stitch groups. At the same time, the stitch length of each stitch group of each sampled piece is compared with the preset maximum allowable stitch length. If the stitch length of a stitch group of a sampled piece is greater than or equal to the preset maximum allowable stitch length, it is determined that the stitches of the sampled piece are skipped. The number of skipped stitches of each sampled piece is counted, and the number of skipped stitches of the garment piece is obtained by taking the average value, which is recorded as .

5. The method for evaluating clothing production quality based on big data analysis according to claim 4, characterized in that: The specific analysis method of the sewing quality analysis is: Read the seam strength of garment pieces separately , needle spacing uniformity , Jumper times , substituting it into the formula Get the sewing quality evaluation coefficient of clothing , They represent the weight factors of suture firmness, stitch uniformity, and number of stitch skipping, respectively. Indicates the maximum allowed number of jumper settings.

6. The method for evaluating clothing production quality based on big data analysis according to claim 5, characterized in that: The specific analysis method of the assembly quality inspection is: In the first step, a number of pieces of finished garments are randomly selected as quality inspection garments, which are recorded as each quality inspection garment, and tension is gradually applied to each button of each quality inspection garment according to the set tension level until the button becomes loose. The value of the tension level of each button of each quality inspection garment is recorded as the tension level of each button of each quality inspection garment. , Indicates The number of the garment to be inspected, , Indicates The number of the buttons, , through the formula Get the button tightness of clothing , Indicates the number of buttons, Indicates the number of garments inspected. Indicates the set reference value of button tension; In the second step, the zipper images of each quality inspection garment are acquired, and the edge contours of the zippers of each quality inspection garment are extracted by edge detection technology, which are recorded as the edge contours of each quality inspection garment. The standard edge contours of the garment zippers are read from the management database, and the overlap length of the edge contours of each quality inspection garment zipper is obtained by overlapping the zippers of each quality inspection garment with the standard edge contours of the garment zippers. At the same time, the length of the standard edge contours of the garment zippers is extracted, and the appearance quality of the zippers of each garment is obtained by dividing the overlap length of the edge contours of each quality inspection garment zipper by the length of the standard edge contour of the garment zipper, which is recorded as At the same time, the force required to close the zipper of each quality inspection garment is tested multiple times using a dynamometer, recorded as , express The number of the pull-close, , and in each repeated zipping process, the number of times the zipper of each quality inspection garment is stuck is counted and recorded as , substituting it into the formula Get the zipper quality of the garment , They represent the weight factors of the set zipper appearance quality, the pulling force required for the zipper to close, and the number of times the zipper of the quality inspection clothing is stuck. Indicates the number of pulls and closes.

7. The method for evaluating clothing production quality based on big data analysis according to claim 6, characterized in that: The specific analysis method of the assembly quality analysis is: Read the button tightness of the garment individually , Zipper quality , substituting it into the formula Get the clothing assembly quality evaluation coefficient , They respectively represent the weight factors of the set button fastening degree and zipper quality.

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