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This paper aims to describe the control software of a novel manufacturing system called plasma-assisted bio-extrusion system (PABS), designed to produce complex multi-material and functionally graded scaffolds for tissue engineering applications. This fabrication system combines multiple pressure-assisted and screw-assisted printing heads and plasma jets. Control software allows the users to create single or multi-material constructs with uniform pore size or pore size gradients by changing the operation parameters, such as geometric parameters, lay-down pattern, filament distance, feed rate and layer thickness, and to produce functional graded scaffolds with different layer-by-layer coating/surface modification strategies by using the plasma modification system.

MATLAB GUI is used to develop the software, including the design of the user interface and the implementation of all mathematical programing for both multi-extrusion and plasma modification systems.

Based on the user definition, G programing codes are generated, enabling full integration and synchronization with the hardware of PABS. Single, multi-material and functionally graded scaffolds can be obtained by manipulating different materials, scaffold designs and processing parameters. The software is easy to use, allowing the efficient control of the PABS even for the fabrication of complex scaffolds.

This paper introduces a novel additive manufacturing system for tissue engineering applications describing in detail the software developed to control the system. This new fabrication system represents a step forward regarding the current state-of-the-art technology in the field of biomanufacturing, enabling the design and fabrication of more effective scaffolds matching the mechanical and surface characteristics of the surrounding tissue and enabling the incorporation of high number of cells uniformly distributed and the introduction of multiple cell types with positional specificity.

The purpose of this paper is to quickly acquire a cheongsam pattern using the fit quantification method to meet individual fit requirement.

Based on the cheongsam pattern database including basic patterns and graded patterns, we defined the main control parts of the cheongsam pattern by analyzing the pattern modification. Combining human body shape characteristics, this paper utilized the fuzzy membership function to quantify the cheongsam fit, and defined the modified model of the cheongsam control part.

The fitness quantification method can provide suitable primary body characteristics for custom-pattern and helps to produce customized cheongsam quickly.

This paper proposed a method of generating customized cheongsam pattern based on fitness quantification by using fuzzy membership function. The method combined the industry pattern design experience and mathematic knowledge to generate the individual fit pattern rapidly. It can be applied in cheongsam customization.

The comfort and fit of clothes are affected by fabric properties, dressed ease and environmental conditions, in which dressed ease is influenced by the interaction among complex shapes of human body, style design and fabric mechanical properties.

In this study, the dressed ease distribution at waist section, which is related to body surface convex angle, was investigated using 3D scanning. A series of surface convex angles on bust and back were formed after adjusting the mannequin. The mannequin was scanned by TC2 separately in garments with eight different ease allowances. Then the dressed ease distributions at waist under different convex angles of body surface have been acquired by calculating the distance between waist points and dressed surfaces along normal directions.

The results showed that the body surface convex angle was weakly related to the dressed ease when the garments’ bust ease allowance was below 4 cm. When the garments’ bust ease allowance was within 6–12 cm, the body convex angle had a great impact on the dressed waist ease distribution in the condition of 26º–33º bust convex angle and 13.96º–17.96º back slope angle. For slack garments with more than 16 cm ease allowance, the dressed waist ease distribution did not relate to the bust convex angle, while it strongly related to the bust convex angle between 13.96º and 17.96º. The regression model was statistically significant between the dressed ease value and the body surface convex angle.

According to the dressed waist ease distribution of different body surface convex angles, this paper gives an application of pattern modification in order to optimize the waist fit. The results can provide guidance for the optimization of different body shapes. At the same time, the application of gap data to 3D virtual fitting can greatly improve the authenticity of virtual simulation effect.

This paper aims to focus on studying the addition of nano-tungsten disulfide (WS₂) on fretting wear performance of ultra-high-molecular-weight-polyethylene (UHMWPE).

In this study, the effect of WS₂ content on fretting wear performance of UHMWPE was investigated. The fretting wear performance of the UHMWPE and WS₂/UHMWPE nanocomposites were evaluated on oscillating reciprocating friction and wear tester. The data of the friction coefficient and the specific wear rate were obtained. The worn surfaces of composites were observed. The transfer film and its component were analyzed.

With the addition of 0.5% WS₂, the friction coefficient and specific wear rate increased. With the content increased to 1% and 1.5%, the friction coefficient and specific wear rate decreased. The lowest friction coefficient and specific wear rate were obtained with the addition of 1.5% nano-WS₂. Continuingly increasing content, the friction coefficient and wear rate increased but lower than that of pure UHMWPE.

The research indicated the fretting wear performance related to the content of nano-WS₂ with the incorporation of WS₂ into UHMWPE.

The result may help to choose the appropriate content.

The main originality of the research is to reveal the fretting behavior of UHMWPE and WS₂/UHMWPE nanocomposites. It makes us realize the nano-WS₂ had an effect on the fretting wear performance of UHMWPE.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-04-2020-0151/

This paper aims to study the influence of load and environment medium on the fretting behavior of SAF 2507 SDSS.

In this study, the effect of load on the fretting behavior of SAF 2507 SDSS in air and sea water were studied. The fretting wear tests under different loads were conducted with a ball-on-flat contact configuration. The friction coefficient, wear volume, surface morphology and oxidation component were determined.

With the increase of applied load, the friction coefficient decreases both in air and sea water. The fretting mechanism is gradually transformed from partial slip regime to slip regime in air while the fretting counterparts are all in the state of gross slip in sea water. In sea water, the friction coefficient is lower while the wear loss is higher compared with that in air.

This research suggests that the fretting behavior of SAF 2507 SDSS is related to load and environment medium.

The results may help us to choose the appropriate load under different environments.

The main originality of the research is to reveal the fretting behavior of SAF 2507 SDSS under different loads in air and sea water, which would help us to realize fretting behavior of SAF 2507 SDSS is controlled by the combination of applied load and lubricating environment.

The peer review history for this article is available at: http://dx.doi.org/10.1108/ILT-08-2019-0335.

The purpose of this study is to examine the fretting wear property of ultra-high molecular weight polyethylene (UHMWPE)-based composites reinforced by different content of attapulgite.

A series of composites were prepared by a hot-pressing method. Fretting tests were carried out using an SRV-IV oscillating reciprocating friction wear tester with a load of 10 N and a frequency of 100 Hz. The morphology of the fracture structure and the worn surface was observed by field-emission scanning electron microscopy, X-ray diffraction and a non-contact three dimensional surface profiler.

With the addition of attapulgite, the microstructure of the composites become more regular, and their heat resistance improved. Furthermore, the friction coefficient and the specific wear rate of the composites with lower filler content reduced compared with that of neat UHMWPE, and the optimum filler content is 1 per cent.

The study investigated the fretting resistance mechanism of the attapulgite in the UHMWPE matrix. The results could help to provide some experimental evidence for the broader application of silicates on the fretting wear resistance of polymers.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-10-2019-0420/

This paper aims to study the tribological properties of high strength glass fabric/phenolic laminate composites reinforced by carbon fiber (CF) with and without graphene oxide (GO) modified.

In this study, the tribological performance tests of the composites were conducted on a block-on-ring tester (MRH-03). The applied load, linear velocity and duration of time are 200 N, 0.5 m/s and 120 min, respectively. The friction coefficient and specific wear rate were shown.

The optimal content of GO on CFs is 0.2 per cent mass fraction. The optimal content of GO addition means the strongest interfacial adhesion between the CF and the matrix.

The main originality of this paper is to reveal the effect of surface GO on CF on the tribological properties of fabric-reinforced composites.

The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-07-2019-0273/

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 main purpose is to construct the mapping relationship between garment flat and pattern. Particle swarm optimization–least-squares support vector machine (PSO-LSSVM), the data-driven model, is proposed for predicting the pattern design dimensions based on small sample sizes by digitizing the experience of the patternmakers.

For this purpose, the sleeve components were automatically localized and segmented from the garment flat by the Mask R-CNN. The sleeve flat measurements were extracted by the Douglas–Peucker algorithm. Then, the PSO algorithm was used to optimize the LSSVM parameters. PSO-LSSVM was trained by utilizing the experience of patternmakers.

The experimental results demonstrated that the PSO-LSSVM model can effectively improve the generation ability and prediction accuracy in pattern design dimensions, even with small sample sizes. The mean square error could reach 1.057 ± 0.06. The fluctuation range of absolute error was smaller than the others such as pure LSSVM, backpropagation and radial basis function prediction models.

By constructing the mapping relationship between sleeve flat and pattern, the problems of the garment flat objective recognition and pattern design dimensions accurate prediction were solved. Meanwhile, the proposed method overcomes the problem that the parameters are determined by PSO rather than empirically. This framework could be extended to other garment components.

Considering two-dimensional features in the body shape classification system cannot fully reflect the three-dimensional (3D) morphological characteristics of human body. The purpose of this paper is to propose a 3D feature based method to characterize and classify the upper body shape of women, and then obtained the corresponding garment block and improved the fitness of clothing.

In this study, the [TC]² 3D scanner was used to obtain human data, and 15 layers of cross-sections of young females’ upper body were extracted. In total, 240 space vectors were obtained with the center of the bust cross-section as the original point. By using the principal component analysis and K-means clustering analysis, the body shape classification based on the space vectors length was realized. The garment block corresponding to three body types was obtained using the 3D scanning data and the cross-section convex hull, and compared with existing garment block and evaluated fitness of the blocks.

In total, 11 main components used to characterize the 3D morphological features of young women were obtained, which could explain 95.28 percent features of young women’s upper body. By cluster analysis, the body shape of women was divided into three categories. The block of three body types was obtained by the construction of the convex hull model.

This paper investigates a classification method of the body shape based on space vector length, which can effectively reflect the difference of surface shape of human body and further improve the matching degree of human body and clothing.