Pengpeng Cheng and Daoling Chen
The purpose of this paper is to analyze the fit and thermal and moisture comfort factors to provide some reference value for the functional design of underwear.
Abstract
Purpose
The purpose of this paper is to analyze the fit and thermal and moisture comfort factors to provide some reference value for the functional design of underwear.
Design/methodology/approach
The body size data of 100 male youths are measured to analyze the body shape of the lower body. Based on the complete body size, the authors selected the matching underwear, and obtained the relevant data for the mathematical model of thermal and moisture using Grey correlation analysis method.
Findings
In allusion to the defect of fit comfort and thermal-moisture comfort of the crotch, this paper presented a mathematical model, and experimental results showed that breathable fabric and breathable volume are the key factors.
Originality/value
It was clarified that which is the key to the thermal and moisture comfort. At the same time, male lower body characteristics index is clear.
Details
Keywords
In order to study the static and dynamic comfort of tight sportswear in winter, the subjective comfort was aimed to be evaluated by collecting sensory data such as humidity…
Abstract
Purpose
In order to study the static and dynamic comfort of tight sportswear in winter, the subjective comfort was aimed to be evaluated by collecting sensory data such as humidity feeling, cold feeling and other perceptions. In this paper, the experiment was divided into standing, squatting, jumping, jogging, walking and so on.
Design/methodology/approach
Through particle swarm optimization-cuckoo search model, the sensory factors that affect the overall comfort were optimized, and it was found that there were great differences in the overall comfort factors under different motions. Then, analytic hierarchy process was used to sort the optimized sensory indicators in each experimental stage, and the influence degree of sensory indicators was studied. Finally, by the long short-term memory (LSTM) model, taking comfort senses of standing, squatting, jumping and jogging as input parameters, and regarding comfort senses of walking, lifting legs and resting as output parameters, the prediction model was founded.
Findings
The results showed that there were certain differences between the prediction value and the real subjective evaluation value, but most of the predicted values were consistent with the real values on the sensory level, and the overall prediction level was good, which meant that the LSTM model had more accurate prediction ability for subjective evaluation and could be extended to other sports.
Originality/value
The research results could provide scientific methods for the design of tight-fitting sportswear in winter.
Details
Keywords
Daoling Chen and Pengpeng Cheng
In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this…
Abstract
Purpose
In order to help companies better grasp the perceptual needs of consumers for patterns, so as to carry out more accurate product pattern development and recommendation, this research develops a product pattern design system based on computer-aided design.
Design/methodology/approach
First, use the Kansei engineering theory and method to obtain the user's perceptual image, and deconstruct and encode the pattern based on the morphological analysis method, then through the BP neural network to construct the mapping relationship between the user's perceptual image and the pattern design elements, and finally calculate and find the corresponding design code combination according to the design goal to guide the pattern design.
Findings
Taking costume paper-cut patterns as an example, the feasibility of this system is verified, the design system can well reflect the user's perceptual image in the pattern design and improve the efficiency of pattern customization service.
Originality/value
Compared with the traditional method that relies on the designer's personal experience to propose a design plan, this research provides scientific and intelligent design methods for product pattern design.
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Pengpeng Cheng, Daoling Chen and Jianping Wang
For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural…
Abstract
Purpose
For comfort evaluation of underwear pressure, this paper proposes an improved GA algorithm to optimize the weight and threshold of BP neural network, namely PSO-GA-BP neural network prediction model.
Design/methodology/approach
The objective parameters of underwear, body shape data, skin deformation and other data are selected for simulation experiments to predict the objective pressure and subjective evaluation in dynamic and static state. Compared with the prediction results of BP neural network prediction model, GA-BP neural network prediction model and PSO-BP neural network prediction model, the performance of each prediction model is verified.
Findings
The results show that the BP neural network model optimized by PSO-GA algorithm can accelerate the convergence speed of the neural network and improve the prediction accuracy of underwear pressure.
Originality/value
PSO-GA-BP model provides data support for underwear design, production and processing and has guiding significance for consumers to choose underwear.
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Keywords
Pengpeng Cheng, Daoling Chen and Jianping Wang
The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.
Abstract
Purpose
The purpose of this paper is to improve the prediction accuracy of the body shape prediction model and provide some reference value for the design of underwear.
Design/methodology/approach
The body size data of 250 male youths is measured to analyze the body shape of the lower body. And there is a total of 56 measurement items, which are clustered by GA-BP-K-means, K-means, optimal segmentation method for ordered samples, wavelet coefficient analysis, regression analysis and Naive Bayes Algorithm. Finally, a test male sample of an unknown body shape was clustered to verify the superiority of the GA-BP-K-means.
Findings
This paper presented the key factors for body shape clustering, and experimental results have shown that the GA-BP neural network model is higher in speed and precision than other algorithm prediction models.
Originality/value
It was clarified which is the key to body shape clustering. At the same time, the GA-BP-K-means algorithm can promote the popularization and application of the prediction model in body shape clustering.
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Keywords
Daoling Chen and Pengpeng Cheng
The purpose of this paper is to study the style design methods of professional female vests that meet the emotional needs of consumers.
Abstract
Purpose
The purpose of this paper is to study the style design methods of professional female vests that meet the emotional needs of consumers.
Design/methodology/approach
Using the theory of kansei engineering as a guide to screen representative samples of female professional vests and relevant emotional vocabularies of styles, through morphological analysis, style design elements of female professional vests are extracted, the fifth-order semantic difference questionnaire was used to establish the perceptual assessment matrix for design elements, the correlation analysis method and multiple linear regression analysis were used to analyze the results of the perceptual evaluation of the sample, find out the relationship between the perceptual vocabulary and design elements of professional female vest styles, and establish a regression model, finally, it is verified by random samples of the market, so as to guide the development of new products.
Findings
The seven design elements extracted from professional female vest styles have an impact on consumer perception, by using a linear analysis method, the correspondence between perceptual perception of consumers and style design elements can be quantified and a model can be established to accurately predict consumers’ perceptual intentions.
Originality/value
The application of perceptual engineering in the style design of professional female vests provides a new idea for the design of clothing styles. It helps garment companies and designers to determine the development direction of professional woman’s vest styles, while the research results provide design reference for other products.
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Pengpeng Cheng and Daoling Chen
The purpose of this paper is to analyze the influence of underwear on the microenvironment of human clothing.
Abstract
Purpose
The purpose of this paper is to analyze the influence of underwear on the microenvironment of human clothing.
Design/methodology/approach
Based on the basic laws of energy and mass conservation, the paper combined the theory of heat and mass transfer to establish the simulation of the influence of underwear on human thermal reaction in microclimate and prediction model of human thermal reaction law.
Findings
The impact on the microenvironment affected by tighter underwear is less than the effect of loose underwear and computational flow dynamics (CFD) can accurately predict the thermal reaction parameters’ values of the human body.
Originality/value
It can be effectively used for the prediction of heat exchange between human body and environment in high-temperature environment and human thermophysiological parameters, and overcomes the individual differences of human experiments and the danger and repeatability of high-temperature environmental experiments.
Details
Keywords
Luo Yue, Yan Meng, Eunji Lee, Pengpeng Bai, Yingzhuo Pan, Peng Wei, Jie Cheng, Yonggang Meng and Yu Tian
The incorporation of phosphide additives is regarded as a highly effective strategy for enhancing the lubricative qualities of base oils. This study aims to assess the lubrication…
Abstract
Purpose
The incorporation of phosphide additives is regarded as a highly effective strategy for enhancing the lubricative qualities of base oils. This study aims to assess the lubrication behavior and efficacy of various phosphide additives in polyethylsiloxane (PES) through the employment of the Schwingum Reibung Verschleiss test methodology, across a temperature range from ambient to 300°C.
Design/methodology/approach
PES demonstrated commendable lubrication capabilities within the Si3N4/M50 system, primarily attributable to the Si-O frictional reaction film at the interface. This film undergoes disintegration as the temperature escalates, leading to heightened wear. Moreover, the phosphide additives were found to ameliorate the issues encountered by PES in the Si3N4/M50 system, characterized by numerous boundary lubrication failure instances. A chemical film comprising P-Fe-O was observed to form at the interface; however, at elevated temperatures, disintegration of some phosphide films precipitated lubrication failures, as evidenced by a precipitous rise in the coefficient of friction.
Findings
The results show that a phosphide reactive film can be formed and a reduction in wear rate is achieved, which is reduced by 64.7% from 2.98 (for pure PES at 300°C) to 1.05 × 10–9 μm3/N m (for triphenyl phosphite at 300°C).
Originality/value
The data derived from this investigation offer critical insights for the selection and deployment of phosphide additives within high-temperature lubrication environments pertinent to PES.
Peer review
The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2024-0139/
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Keywords
Haona Yao, Hongwei Fu, Yongqiang Lu, Pengpeng Xu and Liang Wang
As project managers are in the central position of sustainable project management (SPM), their competencies become an important factor that affects the outcome of SPM. However…
Abstract
Purpose
As project managers are in the central position of sustainable project management (SPM), their competencies become an important factor that affects the outcome of SPM. However, literature lacks a clear description of the project manager competence system required by SPM. The purpose of this study is to explore what competencies are required by sustainable project management and analyze the hierarchy and attributes of these competencies.
Design/methodology/approach
Aiming to address the problem, several methods were applied in this study. First, with a literature review, semi-structured interviews and Delphi technology, 23 project manager competencies required by SPM are identified. Second, the fuzzy interpretive structural modeling–matrix impact cross-reference multiplication applied to classification (FISM–MICMAC) method is used to analyze the data from 21 experienced project managers in the construction industry, revealing the hierarchy and attributes of the project manager competency system required by SPM.
Findings
The results indicate that the project manager competency system required by SPM includes nine micro levels. According to the nature of the competencies, these nine levels can be summarized into five macro levels. Furthermore, all competencies can be divided into three categories: independent, autonomous and dependent.
Originality/value
This study not only provides project managers and scholars with a further understanding of project manager competencies but also helps contractors make informed and objective judgments in the selection and/or appointments of project managers who have the appropriate competencies for SPM.
Details
Keywords
Zhao Dong, Ziqiang Sheng, Yadong Zhao and Pengpeng Zhi
Mechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic…
Abstract
Purpose
Mechanical products usually require deterministic finite element analysis in the design phase to determine whether their structures meet the requirements. However, deterministic design ignores the influence of uncertainties in the design and manufacturing process of mechanical products, leading to the problem of a lack of design safety or excessive redundancy in the design. In order to improve the accuracy and rationality of the design results, a robust design method for structural reliability based on an active-learning marine predator algorithm (MPA)–backpropagation (BP) neural network is proposed.
Design/methodology/approach
The MPA was used to obtain the optimal weights and thresholds of a BP neural network, and an active-learning function applicable to neural networks was proposed to efficiently improve the prediction performance of the BP neural network. On this basis, a robust optimization design method for mechanical product reliability based on the active-learning MPA-BP model was proposed. Random moving quadrilateral sampling was used to obtain the sample points required for training and testing of the neural network, and the reliability sensitivity corresponding to each sample point was calculated by subset simulated significant sampling (SSIS). The total mass of the mechanical product and the structural reliability sensitivity of the trained active-learning MPA-BP model output were taken as the optimization objectives, and a multi-objective reliability-robust optimization design model was constructed, which was solved by the second-generation non-dominated ranking genetic algorithm (NSGA-II). Then, the dominance function was used in the obtained Pareto solution set to make a dominance-seeking decision to obtain the final reliability-robust optimization design solution. The feasibility of the proposed method was verified by a reliability-robust optimization design example of the bogie frame.
Findings
The prediction error of the active-learning MPA-BP neural network was smaller than those of the particle swarm optimization (PSO)-BP, marine predator algorithm (MPA)-BP and genetic algorithm (GA)-BP neural networks under the same basic parameter settings of the algorithm, which indicated that the improvement strategy proposed in this paper improved the prediction accuracy of the BP neural network. To ensure the reliability of the bogie frame, the reliability sensitivity and total mass of the bogie frame were reduced, which not only realized the lightweight design of the bogie frame, but also improved the reliability and robustness of the bogie.
Originality/value
The MPA algorithm with a higher optimization efficiency was introduced to find the weights and thresholds of the BP neural network. A new active-learning function was proposed to improve the prediction accuracy of the MPA-BP neural network.