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As a first step towards objective evaluation of garment appearance, the present work considered seams on three‐dimensional surfaces which simulate actual garment surfaces. The geometric profiles of the 3‐D seams were scanned using a laser scanner. 1‐D and 2‐D digital filters were applied to obtain pucker signals from the geometric profiles by removing “high frequency” components due to fabric surface texture and “low frequency” components due to garment silhouette and drape. The advantages and disadvantages of the 1‐D and 2‐D digital filters are compared. Four physical parameters are examined to see their relevance to the subjective pucker grade. It was found that log(σ²), i.e. the logarithm of the variance of the heights of pucker signals, is the best set of physical parameters for the objective evaluation of seam pucker. In addition, latest attempts at capturing and analyzing 3D garment image using a Cyberware laser scanner and Surfacer software are reported.

In e-commerce, consumers have begun to rely on the opinions of fellow consumers who posted through online consumer reviews to a reputation management system. An ethical concern has arisen in the use and abuse of these new systems. We examine the underlying ethical issues that entrepreneurs are confronting in this time of surging e-commerce. Using 32 vignettes, one for each cross-section of our research construct framework, followed by two Likert scales for respondents to indicate their agreement with the action described from both the perspective of ethicality and professional acceptability, we received responses for 1,252 vignettes, which generated a dataset of 2,504 data points. The results of our pilot study suggest that the ethical considerations for business professionals conducting business online are more nuanced and complex than conventional wisdom on the subject might suggest. While 60 research subjects are small, the use of paired vignettes in our survey allowed us to measure at least 1,000 paired responses for each research construct. The results have the potential of revealing how young professionals have been conditioned by the prevalence of web-based interactions and the anonymity they afford participants, as well as the degree to which they rationalize the misrepresentation of information by business professionals for the purpose of manipulating consumers’ purchasing decisions in order to drive sales. If consumers’ trust in reputation management systems erodes, the result could be a collapse of the entire system as a meaningful source of information. We also demonstrate the tolerance of what is deemed ethical versus professionally acceptable with online business practices.

The purpose of this paper is to model the relationship between manufacturing parameters, especially finishing treatments and instrumental tactile properties measured by Kawabata evaluation system.

Two soft computing approaches, namely artificial neural network (ANN) and fuzzy inference system (FIS), have been applied to predict the compression and surface properties of knitted fabrics from finishing process. The prediction accuracy of these models was evaluated using both the root mean square error and mean relative percent error.

The results revealed the model's ability to predict instrumental tactile parameters based on the finishing treatments. The comparison of the prediction performances of both techniques showed that fuzzy models are slightly more powerful than neural models.

This study provides contribution in industrial products engineering, with minimal number of experiments and short cycles of product design. In fact, models based on intelligent techniques, namely FIS and ANNs, were developed for predicting instrumental tactile characteristics in reference to finishing treatments.

The conversion of fabric into a garment involves many interactions such as the selection of suitable sewing thread, optimization of sewing parameters, ease of conversion of fabric into the garment and actual performance of the sewn fabric during wear of the garment. The adjustment of all sewing parameters is necessary to ensure quality. The purpose of this paper is to define the parameters that affect seam quality comprehensively.

This study primarily focuses on the studies dealing with the effect of various parameters on-seam quality in detail. A systematic literature review was conducted.

The interactions between parameters may lead to different results than the effect of a single parameter. In addition, changing some parameters may have a positive effect on one element of seam quality while having a negative effect on another. For this reason, it is very important to properly select the parameters according to the specific end use of the garment products and also to consider the interactions.

The knowledge of various factors that affect seam quality will be helpful for manufacturers to improve production performance and to be able to produce high-quality seam.

This study systematically explores the literature on global niche market strategies within the fashion industry to allow the mapping of niche practices and examine the benefits, success factors and characteristics of a niche strategy. Additionally, it identifies data gaps and necessitates a detailed examination to uncover areas with inadequate information.

This study utilized the Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA 2020) method for systematic review and included 70 studies to analyze their findings.

This systematic literature review pinpoints niche strategies shaping the future of the fashion industry while developing sectors of the textile and apparel industry, fashion technology, fashion retail business, fashion media and communication, luxury fashion, sustainable fashion, adaptive clothing and transgender fashion within the fashion supply chain. A niche market strategy utilizes both pull and push marketing in the fashion industry. Scholarly literature commonly underscores the understanding of the consumer as a pivotal factor in the success of fashion niche market strategy.

This review offers a comprehensive overview of fashion niche strategy practices, aiming to inspire fashion industry professionals. It also serves as a guide for fashion industry professionals, summarizing best practices across various fashion industry sectors to help develop effective niche strategy competencies for firms.

This review thoroughly analyzes niche strategy implementation in the fashion industry, presenting an important resource for individuals new to this sector. It highlights the significance of niche strategies in improving the comprehension of emerging participants in the fashion business.

The purpose of this paper was to find a simple and easy-operated method for filtering eco-friendly corrosion inhibitors.

The molecular structures and atomic electronegativities of the four kinds of natural reagents, iota-Carrageenan, sodium alginate, sodium dodecanesulphonate (SDS) and sodium dodecylbenzene sulfonate were calculated by Gaussian and Natural Bond Orbital, and the corrosion inhibition rates were forecasted by the calculated results. Then, the realistic corrosion inhibition efficiency were confirmed by electrochemical impedance spectroscopy and potentiodynamic polarization tests in 3.5 Wt.% sodium chloride corrosive solutions. At the same time, the function of pefloxacin mesylate (PM) was explored in this paper polarization tests in 3.5 Wt.% sodium chloride corrosive solutions.

Results showed that the order calculated by the chemical software was correct, and the corrosion inhibition of SDS was the best. Optimum addition of PM not only can reduce microbial corrosion but also can improve the corrosion inhibition by spatial cooperation.

This method can be used to filter eco-friendly corrosion inhibitors quickly. PM can be also used to improve the corrosion inhibition rate of corrosion inhibitors.

The present method to filter corrosion inhibitors was time-consuming, which needed lots of experiments to verify the corrosion inhibitive efficiency. The calculated method was simpler than others, which need complicated calculation process.

The purpose of this paper is to present bootstrapping as an alternative statistical methodology to analyze time studies and input data for discrete‐event simulations. Bootstrapping is a non‐parametric technique to estimate the sampling distribution of a statistic by doing repeated sampling (i.e. resampling) with replacement from an original sample. This paper proposes a relatively simple implementation of bootstrap techniques to time study analysis.

Using an inductive approach, this work selects a typical situation to conduct a time study, applies two bootstrap procedures for the statistical analysis, compares bootstrap to traditional parametric approaches, and extrapolates general advantages of bootstrapping over parametric approaches.

Bootstrap produces accurate inferences when compared to those from parametric methods, and it is an alternative when the underlying parametric assumptions are not met.

Research results contribute to work measurement and simulation fields since bootstrap promises an increase in accuracy in cases where the normality assumption is violated or only small samples are available. Furthermore, this paper shows that electronic spreadsheets are appropriate tools to implement the proposed bootstrap procedures.

In previous work, the standard procedure to analyze time studies and input data for simulations is a parametric approach. Bootstrap permits to obtain both point estimates and estimates of time distributions. Engineers and managers involved in process improvement initiatives could use bootstrap to exploit better the information from available samples.

This paper aims to predict the needle penetration force (NPF) in denim fabrics using the artificial neural network (ANN) and multiple linear regression (MLR) models based on the effects of various sewing parameters.

In order to design the ANN and MLR models, four parameters including fabric weight, number of fabric layers, weave pattern, and sewing needle size are taken into account as the input parameters and NPF as the output parameter. According to these parameters, 140 samples of data were resulted. Each sample was tested five times. From these 140 data (input-output data pairs), 112 were used for training the ANN and MLR models and 28 samples were used to test the performance of ANN and MLR. Also, the NPF was measured on the Instron tensile tester to simulate sewing process.

The results indicated that the NPF in denim fabrics can be well predicted in terms of sewing parameters by using ANN and MLR models, in which the ANN model exhibits greater performance than MLR (RANN=0.989> RMLR=0.901).

The NPF measurement method is limited at low speed.

Using the ANN model for forecasting NPF in denim fabrics can help the garment manufactures to produce high-quality denim products and improve the sewing process through reducing seam damage. The NPF could be also measured in the cycle loading conditions similar to sewing machine process by using a special designed tools mounted on the Instron tensile tester.

The purpose of this paper is to develop a dress design knowledge base (DDKB), which is expected to be further applied to a personalized dress recommendation system.

Dress design knowledge can be expressed as the relationship between designer's fashion perceptions of different dress elements. In order to extract dress design knowledge, a dress shape ontology (DSO) is firstly developed, which can be further used to form a dress element matrix (DEM). A perceptual descriptive space of the dress (DPDS) is developed for the description of the designer's fashion perception of dress. Through a standard sensory evaluation procedure performed by experienced experts (designers), the expected relationship can be obtained. This relationship is then mathematically simulated by fuzzy logic tools for the expected DDKB.

In this paper, a DDKB has been developed. The established knowledge base has been validated, and it can be further applied to dress recommendation system for a specific consumer.

This study introduces the concept of knowledge base to the area of dress individualized design. The knowledge-based design process based on sensory evaluation and fuzzy logic can efficiently solve the individualization of dress design in traditional design processes, which can provide a novel way to dress design individualization.