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This study establishes the principles and process steps of a new basic trousers pattern using measurements obtained according to the rules of the anthropometric measurement system. The newly developed pattern-making system in this study will be called the “Anthropometric Measurements Based Pattern Making System” (AnMePa). It is aimed at producing trousers that are more fitting to the body, thanks to this pattern-making system.

In this research, four pattern-making systems used in many parts of the world were compared with the “Anthropometric Measurements Based Pattern Making System” (AnMePa) with regard to the overall appearance and body fit of trousers prepared according to these systems. 10 virtual mannequins (VM) with different adult female body measurements were created, and trousers patterns were prepared for these mannequins. The trousers’ patterns were made and dressed on the mannequins in a 3D virtual dressing system. The body fit of the virtual garments was evaluated by five experts. The scores given by the experts were evaluated using the fuzzy logic method.

According to the results, it is seen that the new basic trousers pattern developed by utilizing the anthropometric measurement system, AnMePa, provides the best body fit among the basic trousers patterns created according to the other examined pattern-making systems. The combination of 3D virtual dressing and fuzzy logic in the evaluation of garment body fit is considered an innovative method for the future of fashion design and production.

In the developed AnMePa, unlike the existing pattern-making systems, values that can be associated with the body measurements of individuals in a way that could be suitable for each community were used instead of constant values in the pattern-making process. Furthermore, the integration of 3D virtual fitting and fuzzy logic in assessing garment fit is considered a pioneering approach with significant implications for the future landscape of fashion design and production.

Designing of clothes using the historical prototypes is very popular in contemporary practice. The purpose of this paper is to apply 2D and 3D computer-aided design (CAD) systems to reconstruct the historical pattern block and get the virtual image in accordance with the prototypes. New algorithm has been proved for men trousers taken from the nineteenth century.

Our approach is to develop a method of CAD to reconstruct historical trousers through analyzing and rebuilding of historical algorithms used to pattern blocks making, old anthropometrical database, and the pattern blocks shaping. Trousers construction, methods of trousers shaping by hands, body sizes schedule, manuals of 36 pattern cutting systems, and its sketches from nineteenth century have been analyzed. Then, by means of parameterization of historical pattern blocks, we have developed the universal trousers pattern cutting algorithm. The final step of the research has been devoted to virtual fitting technology that helps to determine the differences between historical trousers chosen as prototype and virtual image reconstructed by 3D CAD.

The authors have developed the parametrical module of 2D CAD and expanded the application of 3D CAD to re-designing of completely new object such as nineteenth century trousers pattern blocks in accordance with the historical method of shaping by hands. The conformity between the style of historical trousers and the virtual images reconstructed from two resources – pattern block and sketch silhouette – has been achieved.

This study demonstrated the contemporary approach to historical garments reconstruction by means of CAD. This study should help researchers of historical costume and practical specialists in apparel industry to apply historical heritage in a contemporary way.

The study in this article aims to focus on a novel design concept of virtual 3D garment which is realized with the help of traditional patternmaking methodology and the CAD softwares in order to directly conceive the virtual clothing on a mannequin morphotype in cyberspace in consideration of the ease allowance between the body shape and the garment.

The method of acquisition of 3D human body was explained at first. Then the process of creation of garment 3D model associated with the draping technique was presented. The superposition of patterns from the 3D modeling and the traditional method used in industries was done in order to visualize the right results. At last, the dynamic validation of the garment was carried out in order to analyze the fitting results of try‐on simulation.

The 3D modeling technique method based on the draping technique shows that the garment fits perfectly to the body shape of the wearer.

For the ready‐to‐wear manufacture, this method can be also involved on the parametric mannequin in order to reduce the lifetime of development by eliminating the process of pattern grading in the future.

The originality of this article comes from the combination of the traditional draping technique with the advanced CAD softwares in consideration of the fitting and draping of the garment. This concept is used not only in the context of mass customized product but also in mass production for the ready‐to‐wear apparel industries. The patterns are directly adjusted in 3D and can immediately be tried on in 3D simulation. As a result, the process in 2D patternmaking design can be eliminated.

The purpose of this paper is to present recent work for optimizing the estimation of ease allowance of a garment using fuzzy logic and sensory evaluation.

The current method first generates a number of fuzzy models each corresponding to one specific key body part and one specific wearer's movement and then aggregates all the values of ease allowance generated from these fuzzy models using the ordered weighted averaging (OWA) operator. The aggregated ease allowance takes into account geometric measures on all representative human bodies, comfort sensations of wearers related to all movements or actions and different styles of trousers (tight, normal and loose). The weights of the OWA operator can be used to adjust the compromise between the style of garments and the comfort sensation of wearers. The related weights of the OWA operator are automatically determined according to designer's linguistic criteria characterizing the relationship between wearer's movements and the features of the garment to be designed.

Based on the optimized values of ease allowance generated from fuzzy models related to different key body positions and different wearer's movements, the authors obtain a personalized ease allowance, permitting to further improve the wearer's fitting perception of a garment. The effectiveness of the method has been validated in the design of trousers of jean type. It can also be applied for designing other types of garment.

Integration of wearer's body shapes and human comfort in the design of personalized garments.

This paper presents an introduction to the modelling of virtual garment design process in 3D… Our global project of virtual clothing design, along with the conception of a virtual adaptive mannequin, is devoted to creating and modelling garments in 3D. Starting from ideas of mass customization, e-commerce and the need of numerical innovations in the garment industry, this article presents a model of virtual garment and methodology enabling virtual clothing to be conceived directly on an adaptive mannequin morphotype in 3D. A short description of the overall garment model under constraints is presented. To explain the overall methodology, the basic pattern of trousers is given. The global model of garment creation in 3D is composed of three parts - a human body model, an ease model and a garment model. The most essential part is the ease model, which is necessary for the proposed process of garment modelling. After describing each garment modelling element influencing this process, a detailed presentation of the ease model in relation to the garment model is proposed. The combination of the previously mentioned models may be considered as 2 interconnected sub-models. The first sub-model is linked with the front pattern position on the body and the second with the back pattern position on the trousers with appropriate ease values. In order to execute the identification procedure of the correct ease values and consequently their right positions on the human body, an algorithm of identification is proposed. The two sub-models are strongly connected as in the feedback effect caused by the interactions of the trouser front and back patterns. The aforementioned connection phenomenon appears during modelling and it depends on the structure of the proposed ease model. The relatively significant number of parameters requires the use of the identification technique. Finally, the superposition of virtual and real patterns was done in order to visualise the results.

The human body has the same basic size data but has different surface morphology, resulting in the unfitness even under the same size specification. The purpose of this study was to solve the local fitness problems by representing and quantifying the human surface morphological difference.

Firstly, the 3D point cloud for 323 female students was scanned, and the cross-section layers of the “waist-to-thigh” zone were determined. Secondly, the space vector based on the space Euclidean distance was extracted to represent and quantify the surface morphological difference. And the Principal Component Analysis and K-means were adopted to subdivide the target zone. Thirdly, the pattern based on the subdivision results and surface flattening was generated. Additionally, the fitness was evaluated by the subjective and objective assessments, separately.

The space vector could represent and quantify the shape morphology of the “waist-to-thigh” zone. It had successfully achieved the human body subdivision and corresponding pattern generation for the “waist-to-thigh” zone. And the pattern based on the shape subdivision and surface flattening of the space vector could effectively improve the wearing fitness. Particularly in the waist and crotch area of trousers, the obvious wrinkles had been solved because the space vector is more in line with the shape morphology characteristics.

The proposed method could represent and quantify the difference in human surface morphology in a 3D manner. It solved the unfitness problem caused by the same body size but different shape surface morphology. And it will contribute to the fitness improvement of the trousers.

The purpose of this study is to explore fit problems, satisfaction and preferences of Ethiopian male consumers of ready-made garments (shirt, polo shirt, sweater and khaki and jeans trousers) and highlight the need for a domestic standard garment size chart.

Using a structured questionnaire, 405 usable responses were collected from consumers in four cities (Bahir Dar, Kombolcha, Dessie and Addis Ababa) based on convenience sampling. Moreover, the pattern-making methods of 12 domestic garment manufacturing companies were investigated. One-way analysis of variance and multivariate analysis of variance were used to examine differences in fit satisfaction with age, body size and shape. Multiple regression was used to test hypotheses.

The participants were mostly neither satisfied nor dissatisfied with the fit of the garments irrespective of their age, body size and shape. While age was found to be insignificant, apparel sizes worn and body shape were found to be significant predictors of fit type in most garments. It was also found that most of the domestic garment manufacturing companies use the knock-off method for pattern making, which results in a bad fit as the basic garment for the knock-off is constructed based on other countries’ standards.

This study investigates the fit problems and preferences of ready-made garments in the context of consumers in a developing country. Moreover, it has a contribution in considering men’s body shape in the analysis of fit preferences. The results have implications for developing domestic standard garment size charts to improve fit satisfaction.

The purpose of this study was to assess the body characteristics (body size, garment sizes worn, shape and body satisfaction) of Ethiopian young adult female consumers and their effects on garment fit satisfaction and fit preferences of ready-to-wear garments such as T-shirts, blouses/shirts, skirts and jeans trousers.

Through a structured questionnaire, 418 usable responses were collected from young female university students. One-way analysis of variance (ANOVA) and multivariate ANOVA (MANOVA) were used to examine differences in garment fit satisfaction with the body characteristics of the respondents. Moreover, a multiple regression analysis was used to determine the effect of body characteristics and fit satisfaction on fit preferences in four of the ready-to-wear garments.

The body shapes of above half of the respondents were either bottom hourglass or spoon. The respondents were somewhat dissatisfied with the fit of the ready-to-wear garments, and above 70 per cent of them faced fit problems on average. BMI showed significant fit satisfaction differences in four of the garments, while garment sizes worn were significant only in skirts. However, no statistically significant difference was obtained with body shape. The effect of body characteristics and fit satisfaction on fit preferences was found significant in T-shirts and jeans trousers. The respondents preferred looser shirts and skirts irrespective of their body characteristics.

The paper is unique in comprehensively examining the relationship between body characteristics and garment fit satisfaction and their effects on fit preferences in selected garments in the context of female consumers in a developing country.

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 the present study was to improve the fit of women’s bifurcated garments by developing an equation that can predict the crotch length accurately by using a few basic body measurements. This equation could provide a simple mass-customization approach to the design of bifurcated garments.

Demographic characteristics and easy-to-record body measurements available in the size USA database were used to predict the crotch length. Different methodologies including best subset regression, lasso regression and principal components regression were experimented with to identify the most important predictor variables and establish a relationship between the significant predictors and crotch length.

The lasso regression model provided the highest accuracy, required only five body dimensions and dealt with multicollinearity. The preliminary pattern preparation and garment fit tests indicated that by utilizing the proposed equation, patterns of customized garments could be successfully altered to match the crotch length of the customer, thereby, improving the precision and efficiency of the pattern making process.

Crotch length is a crucial measurement as it determines bifurcated garment comfort as well as aesthetic fit. The crotch length is usually estimated arbitrarily based on non-scientific methods while drafting patterns, and this increases the likelihood of dissatisfaction with the fit of the lower-body garments. The present study suggested an algorithm that could predict crotch length with 90.53% accuracy using the body dimensions height, hips, waist height, knee height and arm length.