A new methodology for the development of sizing systems for the mass customization of garments

Mpampa, Maria L.; Azariadis, Philip; Sapidis, Nickolas S.

doi:10.1108/09556221011008802

Cited by 31 publications

(40 citation statements)

References 18 publications

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“…Therefore, it was concluded that the K-means cluster analysis was not a suitable method for this research. Mpampa et al (2010) distributed sizes evenly along each control variable. This method is more controllable and fits this research.…”

Section: Methodsmentioning

confidence: 99%

“…For a garment sizing system, the value of the interval depends on the absolute value of the control variables, the fabric properties, and the tolerance level of consumers for the control variables (Ashdown & DeLong, 1995; Petrova, 2007). Mpampa, Azariadis, and Sapidis (2010) used the intervals of the drop value between chest girth and waist girth to classify people into seven body types. Gupta and Gangadhar (2004) used the standard deviation as the interval for height.…”

Section: Literature Reviewmentioning

confidence: 99%

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A Method to Create Body Sizing Systems

Xia

Istook

2017

Clothing and Textiles Research Journal

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Literature reviews show that consumers are not satisfied with the fit of garments sold in stores, primarily due to outdated sizing systems used by companies and the limited number of sizes being produced. The purpose of this article is to present a sizing system creation method, which can be applied on body measurement data to improve the overall fit of garments. Data from the SizeUSA study was used. The sizing system creation process included natural log-transformation, principle component analysis, multivariate linear regression, size range determination, and measurements calculation. The created sizing system was then compared with ASTM D5585-11e1. Analysis of the results showed that the method used to create the sizing system was reliable and repeatable. This was an important research effort for apparel manufactures, as it demonstrated a method to create a sizing system that is flexible and can be altered to fit target consumer groups!

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Section: Methodsmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

A Method to Create Body Sizing Systems

Xia

Istook

2017

Clothing and Textiles Research Journal

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“…This paper adopted body shapes already classified in studies by [10; 11; 12]. The methodology modified from [23] utilised three steps, namely: selection of the key dimensions, determining the size range, and the calculation of the body dimensions for the different sizes using least-squares regression analysis. Least-squares regression analysis, in terms of apparel sizing, may be described as a statistical technique in which the values of secondary body dimensions are predicted from known values of the key body dimensions [24].…”

Section: Transformation Of Anthropometric Data Into Size Specificationmentioning

confidence: 99%

Use of 3D Scanning Technologies to Extract Body Measurements for Customised Size Charts for Predominant African and Caucasian Body Shapes in South Africa

Makhanya¹,

Klerk²,

Muthambi³

et al. 2015

Proceedings of the 6th International Conference on 3D Body Scanning Technologies, Lugano, Switzerland, 27-28 October 2015

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The South African sizing system was adapted from an outdated British sizing system. This contributes to the fit problems currently experienced by female apparel consumers in South Africa. To improve ready-to-wear apparel fit, body measurements and body shapes prevalent within a target population need to be identified and subsequently form a basis for a sizing system. The South African apparel industry bases apparel design and manufacturing on standard figures yet research shows that female consumer populations consist of women of different body shapes and body proportions. Diverse ethnic groups within populations further aggravate the variations. Differently shaped consumers experience different fit problems from standard apparel and size charts and therefore require differently shaped apparel. In an attempt to address ready-to-wear apparel fit problems among the ethnically diverse South African female population, this paper sought to compile customised size charts of body shape classes predominant among African and Caucasian women. This paper utilised scan data of 233 African (n1 = 109) and Caucasian (n 2 = 125) women aged 18-25 years that were selected using the purposive and snow-balling techniques. Body shape descriptors from literature guided body shape classification formulae that were computed from circumferential drop values of the samples and mean ± standard deviation. These were used to classify participants' bodies into different body shape categories. A print-out of virtual body images showing participants' front and side view images were subjected to visual analysis by a panel of experts to confirm body shapes assigned from measurements. The body shape defining parameters adopted in this study were. triangle: Mean to Maximum (in cm) i.e. 12.6 ≤ hip-bust ≤ 29.8, hourglass: Mean ≤ bust-waist ≤ Maximum i.e. 18 ≤ bust-waist ≤ 26.6 and rectangle: Mean (18 cm)-3 x SD (12.3 cm) < bust-waist < mean i.e. 5.6 < bust-waist < 18. Findings show that there were 64 African triangle, 42 Caucasian triangle, 30 African hourglass, 51 Caucasian hourglass, 14 African rectangle and 32 Caucasian rectangle. The significant differences between the Caucasian hourglass figure assumed to be similar to the Western hourglass used as a standard figure by ready-to-wear apparel manufacturing, confirmed need for customised size charts for the predominant body shapes among South African women. This paper resulted in the computation of customised size charts for the different predominant African and Caucasian body shapes. While there are a number of Western studies that classify body shape using drop values, there has not been such study in South Africa.

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“…The book "Virtual Humans" clearly demonstrates the scope of their applicability from virtual presenters for Television (TV) and World Wide Web (WEB), to virtual assistants for training in the case of emergency, virtual workers in industrial applications, virtual actors in computer-generated movies to virtual characters for the garment industry [1]. The complexity of today's garment industry has led to unit advanced computer-aided (CAD) technologies and 3D graphic software for assisting designers' creativities, reducing garments' manufacturing costs and more importantly to serve customers' needs and increase their satisfaction percentage [2]. Recently, an obvious trend in garment manufacturing processes has become epitomized by individualized garment production supported by CAD systems for garment pattern construction [3][4][5][6] and their appearances on parametric body models in standing positions, the body dimensions of which could be adjusted to specific customers' body measurements.…”

Section: Introductionmentioning

confidence: 99%

Designing an Adaptive 3D Body Model Suitable for People with Limited Body Abilities

A¹

2014

J Textile Sci Eng

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A new methodology for the development of sizing systems for the mass customization of garments

Cited by 31 publications

References 18 publications

A Method to Create Body Sizing Systems

A Method to Create Body Sizing Systems

Use of 3D Scanning Technologies to Extract Body Measurements for Customised Size Charts for Predominant African and Caucasian Body Shapes in South Africa

Designing an Adaptive 3D Body Model Suitable for People with Limited Body Abilities

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