CN102929965A - Generating method of clothes shell fabric sewing process - Google Patents
Generating method of clothes shell fabric sewing process Download PDFInfo
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- CN102929965A CN102929965A CN2012103854781A CN201210385478A CN102929965A CN 102929965 A CN102929965 A CN 102929965A CN 2012103854781 A CN2012103854781 A CN 2012103854781A CN 201210385478 A CN201210385478 A CN 201210385478A CN 102929965 A CN102929965 A CN 102929965A
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Abstract
The invention discloses a generating method of a clothes shell fabric sewing process. A shell fabric is classified according to the analysis on the shell fabric performance; and the corresponding optimal sewing process combination is obtained according to the type of the shell fabric. A shell fabric classifying method comprises the following steps of: on the basis of a shell fabric performance analysis, carrying out factor analysis on obtained performance parameters; then classifying the shell fabric by utilizing a clustering analysis method; in a process of determining the best clustering number, selecting a mixed F counting amount to calculate that the obtained best clustering number is 7; after the clustering is finished, analyzing the common property of each type of the shell fabric to be the evidence of a subsequently-configured sewing machining process, wherein the optimal sewing process combination adopts the orthogonal test method; designing an orthogonal test under different sewing process conditions aiming at different types of typical shell fabrics; and then, judging the sewing flatness grade of a sewing sample, and analyzing a test result to obtain the significance of each sewing machining process parameter on a result, so as to obtain the optimal sewing process combination of seven types of the shell fabrics.
Description
Technical field
The invention belongs to the Garment Technology field, particularly a kind of generation method of garment material sewing technology.
Background technology
In Apparel Manufacturing, sewing processing is the important procedure that affects the ready-made clothes quality, is subject to being permitted multifactorial impact, must fully understand fabric performance, choose reasonable equipment is distributed sewing technology rationally and just can be reached optimum sewing quality, thereby enhance productivity, reduce cost.In clothes processing, that makes processing technology determines it mainly is the experience that relies on the processing personnel, determines to have very large ambiguity by the feel range estimation at present.
Summary of the invention
The purpose of this invention is to provide a kind of garment material sewing technology generation method, mainly be with reference in the at present clothes processing, configure the real work custom of sewing technology according to the fabric of different characteristics empirically, expect over there that namely performance carries out on the basis of discriminant classification the sewing technology of each class shell fabric of Auto-matching.This method is processed automatically based on computing machine, lessly is subject to human factor impact, solves present this area and relies on artificial experience, and the result is fuzzy, problem that can't quantitative automatic generation.
1, a kind of generation method of garment material sewing technology is classified to fabric according to the analysis to fabric performance, obtains the optimum sewing technology combination of correspondence according to the classification of this fabric, it is characterized in that,
Described analysis to fabric performance, it is the style instrument with fabric, fabric is recorded 18 performance index, and these indexs are: comprise T2, T100 and ST thickness, comprise E5-warp, E5-latitude, E latitude 0-warp, E latitude 0-latitude, E through 00-through, E through bending property, the cutting performance G of 00-latitude and EB5, comprise C-warp, C-latitude, B-warp and the tensile property of B-latitude, the formability that comprises F-warp and F-latitude and the weight W of fabric;
Described fabric sorting technique is on the basis that fabric performance is analyzed, and the performance parameter that obtains is carried out factorial analysis, then uses clustering method that fabric is classified, wherein,
Described factorial analysis, that 18 performance index values are carried out dimension-reduction treatment, eliminated simultaneously correlativity mutual between former variable, it comprehensively is 4 common factors the most at last, is designated as C1, C2, C3, C4 observes the load of each common factor on each performance index, with the bending of 4 common factors difference called afters, shear factor, the thick and heavy factor, broadwise elongation factors and warp-wise elongation factors
When definite optimal classification is counted, selecting mixing F normalized set to obtain the optimal classification number is 7 classes, after cluster is finished, observe fabric and characteristic of property thereof, analyze the denominator of fabric of all categories, as the foundation of subsequent configuration sewing processing technology, when in the situation that sample constantly expand, dynamically adjust aforesaid cluster process, so that classification is more reasonable;
Orthogonal experimental method is adopted in described optimum sewing technology combination, for different classes of typical fabric, under different sewing technology conditions, design orthogonal test, then pass judgment on the sewing wrinkle grade of sewing sample, on the test result analysis conspicuousness of working process parameter on result impact of respectively being sewed, obtain the optimum sewing technology combination of 7 types of fabrics being represented by following table
For the fabric of UNKNOWN TYPE, judge that in described 7 types of fabrics which kind of it belongs to, and then mates such best sewing technology to it.
The invention has the beneficial effects as follows, according to fabric performance fabric is classified, and the fabric classification is carried out the coupling of sewing technology accordingly, meet the work habit that the clothes processing industry is manually determined the sewing processing technology.Adopt simultaneously computer system to realize the automatic dynamic classification of fabric, the differentiation of fabric classification and the Auto-matching of sewing technology have solved the difficult point aspect garment material sewing technology designing technique.
Description of drawings
Fig. 1 is the implementation procedure process flow diagram that garment material sewing technology of the present invention generates
Embodiment
As shown in Figure 1, the garment material sewing technology generation method of the present invention's exploitation mainly is according to physical properties of fabric it to be carried out on the basis of category division, realizes in conjunction with the Rapid matching of the optimum sewing technology combination of fabric of all categories.
For the test of fabric performance, mainly refer to the physical and mechanical property of fabric, and the index such as thickness, weight.The fabric performance that the present invention adopts mainly is by FAST Fabric Style instrument, 18 performance index that Measurement and Computation obtains under the standard climate condition, comprise thickness (T2, T100, ST), bending property (E5-warp, E5-latitude, E latitude 0-warp, E latitude 0-latitude, E through 00-through, E through 00-latitude, EB5), cutting performance (G), tensile property (C-warp, C-latitude, B-through, B-latitude), the weight (W) of formability (F-warp, F-latitude) and fabric etc.
The present invention has adopted clustering method for the division of fabric classification.Owing to having correlativity between 18 parameters that obtain, and number of parameters is many, in order to simplify subsequent treatment, and reduces the error that causes owing to the multicollinearity that exists between variable, adopt factor-analysis approach, 18 performance index values are carried out dimension-reduction treatment, eliminated simultaneously correlativity mutual between former variable, it comprehensively is 4 common factors the most at last, be designated as C1, C2, C3, C4.Observe the load of each common factor on each performance index, with the bending of 4 common factors difference called afters, shear factor, the thick and heavy factor, broadwise elongation factors and warp-wise elongation factors.
The present invention uses the K-means clustering procedure to carry out the division of fabric classification on the basis of above factorial analysis.The K-means clustering procedure needs to determine in advance the optimal classification number, adopts among the present invention and mixes the optimal classification number that F statistic (Mixed-F) is calculated cluster analysis.The concentrated expression of Mixed-F statistic the statistic of degree of scatter between tightness degree and class in the class of all variablees, its value is larger, illustrates that contact is tightr in the class of all variablees, falls apart and contact is overstepping the bounds of propriety between class.It is 7 classes that calculating Mixed-F statistic obtains the optimal classification number.After cluster is finished, observe fabric and characteristic of property thereof, analyze the denominator of all types of fabrics, as the foundation of subsequent configuration sewing processing technology.In the situation that sample constantly expands, can dynamically adjust aforesaid cluster process, so that classification is more reasonable.
The present invention adopts orthogonal test to obtain for the configuration of the optimum sewing technology of fabric of all categories.Selection is carried out orthogonal experiment to the most obvious several technological parameters of sewing quality influence, obtains the optimal sewing technology parameter of fabric of all categories as shown in table 1.
Table 1
The present invention is after the best sewing technology combination that obtains all kinds of fabrics, fabric sample for the unknown, judge by discriminant analysis method in the above 7 class fabrics which kind of it belongs to, and then it is mated such best sewing technology, thereby the realization fabric is made the quick generation of processing technology.
Claims (1)
1. the generation method of a garment material sewing technology is classified to fabric according to the analysis to fabric performance, obtains the optimum sewing technology combination of correspondence according to the classification of this fabric, it is characterized in that,
Described analysis to fabric performance, it is the style instrument with fabric, fabric is recorded 18 performance index, and these indexs are: comprise T2, T100 and ST thickness, comprise E5-warp, E5-latitude, E latitude 0-warp, E latitude 0-latitude, E through 00-through, E through bending property, the cutting performance G of 00-latitude and EB5, comprise C-warp, C-latitude, B-warp and the tensile property of B-latitude, the formability that comprises F-warp and F-latitude and the weight W of fabric;
Described fabric sorting technique is on the basis that fabric performance is analyzed, and the performance parameter that obtains is carried out factorial analysis, then uses clustering method that fabric is classified, wherein,
Described factorial analysis, that 18 performance index values are carried out dimension-reduction treatment, eliminated simultaneously correlativity mutual between former variable, it comprehensively is 4 common factors the most at last, is designated as C1, C2, C3, C4 observes the load of each common factor on each performance index, with the bending of 4 common factors difference called afters, shear factor, the thick and heavy factor, broadwise elongation factors and warp-wise elongation factors
When definite optimal classification is counted, selecting mixing F normalized set to obtain the optimal classification number is 7 classes, after cluster is finished, observe fabric and characteristic of property thereof, analyze the denominator of fabric of all categories, as the foundation of subsequent configuration sewing processing technology, when in the situation that sample constantly expand, dynamically adjust aforesaid cluster process, so that classification is more reasonable;
Orthogonal experimental method is adopted in described optimum sewing technology combination, for different classes of typical fabric, under different sewing technology conditions, design orthogonal test, then pass judgment on the sewing wrinkle grade of sewing sample, on the test result analysis conspicuousness of working process parameter on result impact of respectively being sewed, obtain the optimum sewing technology combination of 7 types of fabrics being represented by following table
For the fabric of UNKNOWN TYPE, judge that in described 7 types of fabrics which kind of it belongs to, and then mates such best sewing technology to it.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111058273A (en) * | 2020-01-04 | 2020-04-24 | 浙江日升服装有限公司 | Method for generating sewing process of garment material |
CN111258253A (en) * | 2020-02-03 | 2020-06-09 | 浙江杰克智能缝制科技有限公司 | Sewing equipment process parameter adjusting system and method |
Citations (1)
Publication number | Priority date | Publication date | Assignee | Title |
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CN102567920A (en) * | 2012-01-18 | 2012-07-11 | 湖南省忘不了服饰有限公司 | Method for generating sewing smoothness based on structural parameters of fabric |
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CN102567920A (en) * | 2012-01-18 | 2012-07-11 | 湖南省忘不了服饰有限公司 | Method for generating sewing smoothness based on structural parameters of fabric |
Non-Patent Citations (1)
Title |
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李艳梅: "服装面料缝纫外观质量客观评价及其缝制加工工艺生成系统的研究", 《东华大学博士学位论文》 * |
Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN111058273A (en) * | 2020-01-04 | 2020-04-24 | 浙江日升服装有限公司 | Method for generating sewing process of garment material |
CN111258253A (en) * | 2020-02-03 | 2020-06-09 | 浙江杰克智能缝制科技有限公司 | Sewing equipment process parameter adjusting system and method |
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Application publication date: 20130213 |