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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.

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.

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 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 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.

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.

The concept of developing clothing sizes has taken importance in recent years due to increasing expectations of consumers for branded clothing and its value in terms of fit and durability. The kids’ ready-to-wear brands are expected to pose the least fit issues, thereby covering a wider population of a particular size. This necessitates the standardization of measurements. The lack of standardized approaches has caused fit issues like mismatching of sizes and alterations, in a heterogenous consumer market, like India. The performance of branded apparel depends on the quality of the measurements considered in developing sizes and the approach for standardization. There is a lacuna in the measurements used by the kids’ apparel domestic brands. This study aims to propose an anthropometric approach for deriving quality measurements that can be used effectively in developing kids’ sizes to fit a wider population of kids, thereby reducing the need for alterations.

The measurement data was gathered through the quantitative method. An anthropometric survey was conducted by measuring school kids. A total of 544 kids (girls and boys) of age group 6–8 years were measured to obtain prime anthropometric measurements required for ready-to-wear apparel production. WHO manual and ISO 8559, 1998 meant for anthropometry survey for garment industry was referred for accurate measuring following the landmarks for measuring.

The findings revealed differences in the anthropometric measurements based on gender and age. The anthropometric measurements showed variations within the same body mass index (BMI) range. S, M and L sizes were identified within an age group. The apparel manufacturers and designers need to focus on the discrepancies occurring in the body measurements of an age group to address and control fit issues in kids ready to wear apparel.

The anthropometric approach can be significantly used to control undesired fit and comfort issues in kids’ ready-to-wear apparel.

This study helped to understand the importance of scientific measuring practices to arrive at standardized measurements to develop sizes in ready-to-wear apparel manufacturing.

The purpose of this paper is to develop a new suit sizing system based on up‐dated data, using data mining techniques, to improve the final quality and reduce the waste of fabric. This paper aims to investigate the effect of data reduction on the final fitness of the sizing chart.

Principal component analysis is applied to reduce the sizing variables, non‐hierarchical clustering approach is used to segment the heterogeneous population to more homogeneous one, and the aggregate loss of fitness is used to evaluate the resulted sizing chart.

The results show that, when principal component analysis reduces the ten sizing variables to two main components, the final fitness for the resulted sizing chart is the best. These two main components are height and circumference. The hierarchical clustering approach could effectively group all body type to seven clusters. The resulted sizing chart could be used as a reference for suit manufacturers.

Due to wide differences in race, nutrition and climate, people who live in different countries have their own body size; also, most of current sizing systems are out‐dated, so there is an urgent need to develop a new sizing system. Due to the growing rate of globalization, the final results will be useful for those companies wanting to connect to global business chains.

This work introduces the first suit sizing systems, based on data mining, for Iranian males, that has more fitness in comparison to the current sizing chart. The effect of the number of principal components on the final fitness of a sizing system is introduced as an innovative way, to avoid losing useful data during data reduction process with principal component analysis.

The purpose of this study was to categorize the whole body shapes of overweight and obese females in the US and examine apparel fit based on the current ASTM sizing standards related to the body shapes categorized.

Body scan data from 2,672 subjects were used. To categorize their whole body shapes using 97 body measurements, principal component analysis with varimax rotation, a hierarchical cluster analysis and K-means cluster analysis were used. To compare the ASTM sizing standards for plus sizes (curvy and straight) and missy sizes (curvy and straight), five body parts (bust, under bust, waist, top hip, hip) using the formula for fit tolerance (measurement plus half of the interval) were compared with the ASTM sizing standards to determine the size appropriate for each body part.

Five whole body shapes among overweight and obese females in the US were categorized: Rectangle-curvy; parallelogram-moderately curvy; parallelogram-hip tilt; inverted trapezoid-moderately curvy and inverted trapezoid-hip tilt. When the body measurements in each body shape were compared with the current ASTM sizing systems for both misses and plus sizes, four-fifths or more of overweight and obese female adults in the US would find it difficult to obtain a perfect fit for both tops and bottoms.

Identifying whole body shapes among overweight and obese women in the US contributes significantly, as it will help apparel companies that target the markets of larger women develop a new sizing system. This study is the first attempt to analyze fit by comparing the ASTM sizing charts with body measurements in each body shape group. Further, the study contributes to the body-related literature by filling gaps in missing whole BS categories among overweight and obese females.

The purpose of this paper was to develop the first standard apparel sizing system for Saudi adult female population originating from anthropometric study using three-dimensional (3D) body scanner.

An anthropometric survey was conducted in four regions of the country where 1,074 participants between the ages of 18 and 63 were scanned using white light 3D body scanner. K-means cluster analysis using stature and hip girth as control variables produced the proposed sizing system, whereas regression equations were used to determine the parameters between measurements of different sizes.

Three sizing groups with 12 size designations in each totalling 36 size designations were identified. The sizing charts developed in this study show that key girth measurement ranges of chest, waist and hips are comparable to that of ISO standard and (ASTM D5585-11), while the Saudi female population falls into shorter height brackets than ISO and ASTM standards.

In this study, the first anthropometric database for Saudi female population was established using 3D body scanning technology, and a sizing system for this target population was developed.