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This study was initiated in order to develop a system for made‐to‐measure (MTM) pattern generation with special reference to computer‐aided design (CAD) applications. Recognition of the relationship between body figuration and pattern construction is essential for the production of MTM clothing with good fit. By linking theory and practice, a methodology has been developed for research in this field from female figure typing through sizing, pattern design construction and grading to pattern alteration. The study is divided into three parts. In the first part, the background to women's sizing systems and categorisation of female figure types is discussed, and a new system of size codes and size charts is proposed.

Prior to implementing computerised pattern alterations for figuration on a commercial CAD system, a large database with reference to the standard graded patterns, the alteration movements and relevant information needs to be generated. There are many difficulties in creating grade rules and alteration movements, especially for the bust suppression and the shaped sleeve. In order to obtain sophisticated patterns with a good fit for MTM (made‐to‐measure) clothing, the authors' pattern alteration technique is a combination of pattern design construction and grading. The procedure is divided into ten stages and the practical verification was carried out in the form of seven case studies. In addition, drafting rules on the MicroFit system for automatic pattern generation are demonstrated by converting the numerical grade rules created on the GGT AccuMark system into body‐related formulae.

Following the investigations of sizing systems and size codes in the first part of this study (published in JFMM 4/1), comparative analysis of three systems of pattern design construction is carried out. The relevant pattern dimensions are then formulated so as to implement computerised made‐to‐measure (MTM) pattern generation for the construction of the bodice and sleeve blocks. Based on these new formulations, the establishment of the proposed size charts is simplified and a construction plan is presented to illustrate the new pattern construction system. This is developed to be both logical and flexible for application to different female figure types. In addition, a grade plan is recommended for advanced pattern grading.

The purpose of this study was to explore participants’ fit perceptions of customized garments and investigate the factors that affected the customized fit.

Because different patternmaking methods generate varied fit results, eight customized dresses were developed for four fit models aged 18–25 using two different made-to-measure (MTM) systems (Gerber AccuMark and Telestia Creator). The authors designed a questionnaire to assess the fit of the final garments on each of the four models. A total of 12 participants (four fit models and eight experts) attended a live evaluation meeting and completed the questionnaire. The quantitative and qualitative data of the participants’ fit perceptions were collected and analyzed.

The authors compared the fit outputs of the two MTM systems and determined the fit issues from the participants’ perceptions. The results showed that the participants evaluated the customized fit mainly according to the ease, seam placement and wrinkle occurrence. The majority of fit models and experts preferred Dress B created using Telestia Creator to Dress A developed using Gerber AccuMark. The participants’ fit perceptions also revealed that many factors, such as the MTM systems, participants’ fit preferences, models’ body characteristics, fabric and ease, impacted the fit results. In addition, the experts perceived more fit issues than the models.

The fit output comparison of the two MTM systems could be valuable for pattern makers to use the systems. The research results would also be useful for apparel companies to conduct a fit evaluation and improve their customization processes.

Describes a PC‐based CAD system for producing made‐to‐measure garment patterns which has been developed and implemented in the commercial environment of a bridalwear manufacturer. The software simulates the hand drafting methods of the company while automating pattern production with the following benefits: first, very rapid production of made‐to measure patterns; second, production of patterns which require minimal alteration at first fitting; third, a user friendly interface with very short training period; fourth, the de‐skilling of the pattern cutting procedure so that problems of staff turnover and training are minimal; and fifth, the elimination of human error in pattern cutting. Initial software development concentrated on bodice patterns. Further enhancements included sleeves and skirts and the mixing and matching of these three components of a dress. Cutting layouts were produced using automatic layout algorithms so that the whole procedure from order and measurements entry through pattern drafting and lay‐planning to the final full scale plotting could be carried out automatically. Furthermore, a queuing system allowed several orders previously entered on the computer to be processed in succession without any intervention by an operator. All the company’s styles are now held by the computer, which is in constant use, to the exclusion of the previously used skilled and lengthy hand drafting methods.

The fast and easy generation of personalized mannequin is the premise for the accurate 3D measurement for the customers in an electronic made to measure (e_MTM) system. The purpose of this paper is to attempt to propose a new virtual human mannequin modeling technique to meet this requirement.

The customized human mannequin is constructed by assemblage of the body parts. The body parts including bust, waist and hip segments are achieved by modification of the standard body section templates, while the silhouette obtained from the front and side photos are used to confine the distortion of the parts.

The main findings are the section template base and assemblage method for mannequin modeling.

The proposed method can free the burden of high cost and inconvenience of 3D scanner in the measurement process of e_MTM system, and in the mean time without loss of measurement accuracy.

Detailed body sizes are prerequisite for made to measure or customized manufacture. Nowadays, detailed body sizes can be precisely obtained by using 3D scanners, however, the high prices of the scanners block the population for such approaches. The purpose of this paper is to provide an economical and accurate data-driven method which can predict detailed body sizes with a small number of feature sizes.

First, the representative body sizes are extracted from dozens of detail body sizes by using factor analysis and garment knowledge. Among the representative body sizes, those that are easy to be measured are selected as the feature parameters (FPs). Second, by mining the database of the body sizes, mapping from the FPs to the detailed body sizes is expressed by a combination of radial basis function and multiply linear regression. Thus, for an individual human body, his/her detailed body sizes can be predicted by a small number of FPs.

First, FPs which are easily measured and represent the main shape information of a human body are extracted. Second, detailed body sizes can be functionally predicted by the FPs.

Traditionally, measuring dozens of body sizes for each human body is tiresome and the accuracy of the sizes depends on the experience of the gaugers. In this paper, a small number of body sizes are selected as the FPs which are easy to be measured and can functionally express the other body sizes. Thus, by only measuring the FPs, the detailed body sizes can be intelligently and automatically predicted. This approach is meaningful to improve the intelligence and accuracy of the measurement, so that even an inexperienced gauger is competent to obtain accurate detailed body sizes.

New techniques are required to link 3D whole body scans to manufacturing techniques to allow for the mass‐customization of clothes. This study aims to compare two methods of producing skirts based on 3D whole body scans.

Three females participated in the study. They were scanned with an accurate 3D whole body scanner. A set of relevant 1D measures was automatically derived from the 3D scan. The measures were incorporated in a skirt pattern and the skirt was made from jeans material. The second method was based on triangulation of the scanned waist‐to‐hip part. The points in the 3D scan were first converted to triangles and these triangles were thereafter merged with neighboring triangles of similar orientation until about 40 triangles remained. These triangles were sewn together to form a “patchwork”‐skirt. All females performed fit tests afterwards.

The fit of the 3D‐generated patchwork skirt was much better than the fit of the skirt generated by the 1D scan‐derived measures. In the latter case, two of the three skirts were too wide because the scan‐derived hip circumference exceeded the manually derived values. For the 3D generated skirt, it was necessary to enlarge the triangles with a factor of 1.025 to achieve optimal fit.

As far as is known, this is the first study that reports a direct conversion of a 3D scan to clothing without interference of clothing patterns. The study shows that it is possible to generate a fitting patchwork skirt based on 3D scans; the intermediate step of using 1D measures derived from 3D scans is shown to be error‐prone.

The paper aims to provide an overview of the area of digital pattern developing for customized apparel.

The paper outlines several methods of digital pattern developing for customized apparel, and discusses the principles, characters and applications. Digital pattern developing process has two paths. One path develops apparel according to traditional 2D pattern‐making technology. There are three methods: parametric design, traditional grading technique, and pattern generating based on artificial intelligence (AI). Another path develops pattern through surface flattening directly from individual 3D apparel model.

For parametric method, it can improve greatly the efficiency of pattern design or pattern alteration. However, the development and application of parametric Computer‐Aided‐Design (CAD) systems in apparel industry are difficult, because apparel pattern has fewer laws in graphical structure. For grading technique, it is the most practical method because of its simple theory, with which pattern masters are familiar. But these methods require users with higher experience. Creating expert pattern system based on AI can reduce the experience requirements. Meanwhile, a great deal of experiments should be conducted for each garment with different style to create their knowledge databases. For 3D CAD technology, two methods of surface flattening have been outlined, namely geometry flattening and physical flattening. But many improvements should be done if the 3D CAD systems are applied in apparel mass customization.

The paper provides information of value to the future research on developing a practical made‐to‐measure apparel pattern system.

The purpose of this paper is to concentrate on the development of individualized prototype of apparel patterns for young females from 3D body scanning data.

The authors presented a new pattern-making approach that is composed of three major steps: to establish the relationships between body features and corresponding elements in a prototype (e.g. curve or a point); to classify the relationship into grades that provide alternatives to fit a variety of bodies; and to assemble each individual element into a personalized prototype.

The experiment demonstrated that this method could be used for customized prototype development from 3D body scanning in a relatively easy way.

Currently, the subjects of this study included only Chinese young females, and the regression models were just suitable for the similar body types though, the research method could be extended to other somatotypes and age groups.

This approach can be used in the field of made-to-measure, mass customization, and the quick response for apparel pattern making. The technology in this paper facilitates to generate an individualized pattern prototype from 3D body scanning data.

Originated from the relationship between the features of a human body and the elements of a pattern prototype, the authors presented a new approach to develop an individualized pattern prototype by classifying the features into grades.