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The purpose of this paper is to use a systematic model for detecting misfit between the garment and the target group.

Using an empirical–analytical methodology, the systematic model was tested. The input data were run through the model to generate the output data, which were analysed, including basic statistics. The purpose of the analysis was to detect misfit and improve the garment measurement chart. This procedure was repeated until a clear result was reached.

The result of this study is an optimised garment measurement chart, which considers the garment’s ease, different sizes/proportions in relation to a target group. The results show that it is possible to use a systematic model to define the shortcomings of a garment´s range of sizes and proportions.

Further studies are needed to verify the results of the theoretical garment fit and their values in relation to real garment fit.

If the systematic model is implemented to improve the theoretical garment fit, this may have effects on the available garment sizes and its proportions, resulting in increased theoretical garment fit for the target group.

The paper presents a systematic model for detecting and eliminating theoretical fitting; the model includes both garment ease allowance and defined points of misfit.

Sizing system is a fundamental topic in garment fitting. The purpose of this study was to assess the fit of existing police uniforms (shirt, jacket, overcoat and trousers) and develop a sizing system for upper and lower body uniforms of Amhara policemen in Ethiopia.

In total, 35 body dimensions of 889 policemen were taken through a manual anthropometric survey following the procedures in ISO 8559:1989 after each subject was interviewed on issues related to garment fit. The anthropometric data were pre-processed, key body dimensions were identified by principal components analysis and body types were clustered by the agglomerative hierarchical clustering algorithm and verified by the XGBoost classifier in a Python programming environment. The developed size charts were validated statistically using aggregate loss and accommodation rate.

About 44% of the subjects encountered fit problems every time they own new readymade uniforms. Lengths and side seams of shirts, and lengths and waist girths of trousers are the most frequently altered garment sites. Analysis of the anthropometric measurements resulted in 13 and 15 sizes for the upper and lower bodies, respectively. Moreover, the comparison of the developed upper garment size chart with the existing size chart for a shirt showed a considerable difference. This indicates that inappropriate size charts create fit problems.

The study considers the analysis of fit problems and sizing system development in a less researched country. Moreover, the proposed data mining procedure and its application for size chart development is unique and workable.

The purpose of this paper is to identify common issues among commercial body size charts, and to propose a sizing improvement methodology without changing the number of sizes in the range. One goal is to equalize the number of people accommodated by each size within the range, and to propose a way to evaluate the effectiveness of the improvement.

The proposed method consists of three phases: (Phase I) identify target population; (Phase II) analysis of existing size charts; and (Phase III) improvement of the initial size chart. Phase III is the key process, which includes repeated manipulation of intersize intervals of the three primary measurements (chest, waist and hip) for improved consistency of overall and interior accommodate rates among the three measurement categories. A program was developed in RStudio® to generate trials and side-by-side bar plots for visualization of the differences in accommodate rates.

The main issue in commercial body size charts observed is the inconsistency of the interior accommodation rates among measurement categories. Some other issues include: lack of important measurements, failure to provide ranges and gaps between measurement ranges of adjacent sizes.

This paper proposed a complete work flow to improve body size charts to fix the common issues. The method integrates historic size information and new anthropometric information extracted from a national-scale sizing database (e.g. SizeUSA). The study also brought association of the secondary body measurements with primary measurements without using linear regression. Hence, information from body size charts can be more efficiently used in acquiring other size information.

Size fit and economic efficiency are two crucial aspects that need to be considered in designing a sizing system. However, there could exist a trade-off between those aspects in order to establish a practical sizing system. The purpose of this paper is to develop a sequential hybrid method of grid and optimization to generate a practical sizing system using anthropometric data.

The proposed sequential hybrid method consisted of two sequential steps, which employs grid method and optimization method. In the initial step, the grid method creates primary grids that accommodate a designated percentage (e.g. 90%) of users with best size fit. In the subsequent step, the optimization method generated additional grids to provide acceptable fit, with minimum fit penalty scores for users unaccommodated by the primary grids. Our method was applied to the development of a sizing system for men's military jackets. The proposed method performances were evaluated in terms of accommodation percentage, size fit and number of sizing categories.

Our proposed method resulted in 26 primary grids during the initial step, which cover 90% of users. Next, we generated six additional grids during the subsequent step that provide minimum fit penalty scores for the rest (10%) users.

The main contributions of this paper are as follows: consider accommodation percentage, size fit and number of sizing categories in the design of sizing system; combine the grid and optimization methods and evaluate a sizing system for men's military jackets. The proposed method is applicable to develop optimal sizing systems for multiple-size products.

A survey of 100 young women's body measurements was undertaken during 1992/93. The findings are the basis of Part 3, which aims to explain how size charts are developed for garments; to evaluate the measuring equipment used and to compare the size chart body measurements with those proportionally derived by traditional formulae. A size chart is the artificial dividing of a range of measurements which are concise and consistent. There are different types of size charts. Some are of body measurement for specific proportion and shape. Others are for garments including ease allowances which vary according to the garment style and type of fabric. Size charts can be developed in three stages commencing with the raw survey data, which is then rounded to the nearest 1.0 cm or 0.5 cm and finally ease allowance is added for the finished garment. During the survey some measurements were repeated using different measuring equipment so that a comparison could be made to select the most suitable for pattern construction. The use of the anthropometer is limited as it can only take linear measurements. However, it is helpful when analysing body proportion, whereas the tape measures attached to the harness and a metal tape measure can record the contour surface of the body, which is more appropriate for clothing. The adjustable square and angle were a little difficult to position correctly but were useful to check the formulae used for pattern construction. A comparison is made between the survey body measurements and traditional formula to derive body measurements which are difficult to take. The dividing of the height by eight heads is useful for length proportions. The derived neck shape and survey measurements were comparable. Head measurements suitable for hoods were similar for all bust and neck sizes. Only the height showed any progression in size. This concludes the three articles which explain the taking of body measurements, methods of analysing the data and applying it to clothing pattern construction. It is hoped that this will aid those in industry and education who wish to undertake research and to develop new technology.

To demonstrate that the current weaknesses in women's ready‐to‐wear size standardization charts originate not only in the obsolescence of the base data but also in the non‐adherence of order initiators to the suggested standard sizes.

Trouser manufacturers were selected in such a way as to cover the full price‐range spectrum. They provided their waist standard measurements and confirmed that they use the same measurements for all product lines. In‐store measurements were done. Garments were chosen at random from the selection offered in store and measured systematically. The specifications provided by the order initiators, the standard measurements prescribed, and the garment measures were all measured.

Results clearly indicate that order initiators do not adhere to the standard sizes charts and garment manufacturers are incapable or unwilling to produce garments that meet the order initiators’ specifications.

Product selection and limited sample do not allow generalization yet clearly confirm this hypothesis.

Questions the pertinence of investing heavily in the modernization of standard sizes charts if the industry and the governments are not ready to impose adherence by order initiators.

Fills an important void in the existing literature as, although a number of authors have stated that garment manufacturers do not respect the standard sizes proposed by different national organizations or governmental agencies, the authors could not identify one research demonstrating this fact.

The purpose of this paper is to present a model of researching clothing anthropometrics at the Manchester Metropolitan University in the UK (MMU model), to demonstrate steps in devising size charts by analysing raw data, to relate key aspects of size charts to raw data, and to generate debate on such methods that impinge on the disseminated knowledge in this specialised area. Although sizing is important to consumers, retailers and manufacturers, this area has received scarce attention in the literature.

The MMU model presents step‐by‐step processes in generating size charts. Data from 150 women generated descriptive statistics (mean, standard deviation, percentiles); these were utilised to devise seven sizes of a body measurements table. Correlations were used to determine relationships, resulting in size charts with a defined size range and grading increments that are relatable to utilisation by consumers, retailers and manufacturers.

A step‐by ‐step model of analysing raw data is presented. A verifiable size chart, codes, grading increments and size limits relatable to data are generated. The usefulness of size charts is therefore contextualised.

This paper discusses only one model of researching clothing anthropometrics and provides a related conceptual framework; this could be the basis for future research and debate in this area.

For competitiveness, efficient sizing is useful for marketing, especially in creating niches, targeting customers and facilitating consumer satisfaction.

The MMU model provides an initial conceptual framework at one institution, a benchmark for similar practice in academia and industry and subsequent debate in literature.

A computer system for made‐to‐measure pattern production should have the capability of determining default measurements for sets of customer measurements input to the system where one or more of these measurements are missing. This paper recommends the use of default formulae rather than mathematical interpolation of size charts. These default formulae, when applied to a given size chart set, enable measurements to be determined efficiently over wide ranging customer sizes in both stature and girth. The specific default formulae for the German DOB charts are derived for Regular and Outsize charts and also for the full range of Height categories and Bust to Hip relationships, so that all sizes and shapes of customers are catered for. Default formulae have been applied in the MicroFit made‐to‐measure system from Garment Micro Systems and also implemented on this system for checking the validity of measurements entered into the system for each individual customer.

To obtain sizing systems a specialist knowledge is required to analyse statistically body measurements from surveys. Control measurements, size ranges, body proportions and size intervals have to be calculated. A survey of 100 young women was undertaken in 1993/93 at Manchester Metropolitan University and 10 body measurements were taken. This is used to illustrate the statistical analysis of body measurements, the formulation of sizing systems and body measurement tables. A review of previous surveys and their methods of analysis was undertaken. The main control measurements of height, bust, waist and hips denoting the size of the wearer were obtained by correlation. Size ranges and intervals were obtained by normalising the data and comparing the sizes young women bought and previous size charts. Sizing systems for five sizes 8 to 16 were suggested for three heights, short, medium and tall and bust fittings medium, small and very small. This retained the same proportion for the five sizes within each of the nine systems. A further system of changing proportion in girth measurements was developed from the survey of young women based on percentiles and bust fittings. The neck girth which did not correlate strongly with any measurement was analysed separately. Two examples of body measurement tables covering 30 measurements were formulated to illustrate the procedure. Analysing body measurements statistically is problematic especially in small surveys. It is hoped the suggested guidelines will clarify this area. The coding of sizes is still not uniform. A comparison was made with previous tables. It was concluded that the body proportion had changed and the young women were taller and broader in the waist and hips. Part 3 of this study will cover comparing the problems of taking accurate body measurements with different equipment, formulating size charts for different garments and fabrics and relating these to different systems of pattern construction, and finally, testing prototype garments for size and fit.

A simple easy to follow statistical approach has been proposed for developing body size charts from anthropometric data. It has been possible to cover 95 percent of the population using 11 size charts. Multivariate analysis was carried out to detect relationships between variables. Principal component analysis was carried out to identify the key body measurements which can form the basis for classifying the population. Bust for the upper body and hip for the lower body were identified as the critical dimensions affecting garment fit. Body shapes and their distribution within the population have been identified. Validation of size charts was done by calculating the aggregate loss of fit.