Fabrication Quality Research Articles

Comprehensive Assessment of the Quality of Knitted Fabrics for Children's Underwear after Washings

Comprehensive Assessment of the Quality of Knitted Fabrics for Children's Underwear after Washings

Kompresijska svojstva pletenina štampanih tehnikom sublimacione transfer štampe

Compression properties of textile materials are useful for determining fullness, softness, smoothness, and stiffness. In addition, compression parameters have significant influence on fabric hand value and quality of textile materials. The present paper reports a study of the sublimation printing process influence on the change in compression properties of knitted fabrics (polyester, cotton, and cotton/ polyester) intended for sportswear manufacturing. For that purpose, the KES-FB3-A Compression Tester was used for measuring compression parameters of knitted fabrics. The parameters, which contributed to the smallest reduction percentage in compression properties of polyester knitted fabrics were yarn linear density and weight. For cotton-rich knitted fabrics sublimation coating powder was used for paper modification to bond disperse dyes to cotton fibres. The analysis of the results showed that the printing process had a smaller influence on the change of compression parameters of polyesters in relation to cotton and cotton/polyester knitted fabrics. It was noted that the printing process had the effect of thickness reduction for all knitted fabrics to varying degrees. Printing process contributed to small decrease in compressibility and specific volume values for polyester knitted fabrics. The modification process contributed to the significant reduction of the compressibility for cotton (from 34.46% to 47.89%) and cotton/polyester (from 38.81% to 50.75%) knitted fabrics. In addition, reduction in specific volume values range from 41.86% to 44.19% for cotton and from 42.37% to 45.75% for cotton/ polyester knitted fabrics was notted.

Potential of AA7075 as a Tribological Material for Industrial Applications -A Review

Lightweight materials in general and alumunium alloys in particular are increasingly becoming important engineering materials in order to improve the sustainability aspects of engineering products. Amongst the alumunium alloys, AA7075, due to its strength to weight ratio along with other technical benefits has become a prominent material. The literature suggests that AA7075 is structurally good, however its poor tribological properties can be enhanced by introducing different reinforcements. Further, the mechanical and tribological behaviour of AA7075 relies on variety of factors such as fabrication route, quality and quantity of reinforcement, etc. In this work we summarize the work carried out in studying the various mechanical and tribological properties of AA7075. The paper will focus on the ceramic and solid lubricant reinforced AA7075 hybrid composites. A section also summarizes the applications of the alumunium alloys and composites in various engineering applications.

High-speed synchrotron X-ray imaging of directed energy deposition of titanium: effects of processing parameters on the formation of entrapped-gas pores

Laser based directed energy deposition (DED) is a competitive method for repairing and remanufacturing metallic parts used in numerous industries including aerospace and biomedical. However, the numerous dynamic phenomena associated with the DED process often result in defects such as entrapped-gas pores, lack of fusion, and undesirable anisotropic properties. The entrapped-gas pore, being one of the most common issues, not only influences melt-pool dynamics but also reduces the fabrication quality and mechanical properties of parts fabricated by the DED process. To reduce and further understand this issue, the real-time observation of the pore formation process needs to be studied first. To directly observe the phenomena in the melt pool, high-speed techniques are needed because rapid solidification leads to rapid pore formation and movement. In-situ high-speed X-ray has been proven to be an effective method in investigating the melt pool dynamics and pore formation mechanisms in the laser powder bed fusion process, in which the fabrication process is quite different from that in DED. Here, the high-speed X-ray method is extended to study the formation of entrapped-gas pores. The real-time formation and quantitative analysis of pores under each set of processing parameters (particle velocity, laser power, and spot welding dwelling time of stationary laser) in the DED process are investigated. We found that the DED with a higher particle velocity (3.19 m/s) produced a smaller average pore size of 27.8 µm and a lower pore area fraction of 0.52%. The DED under lower laser power (156 W) generated a smaller average pore size of 20.3 µm and a lower pore area fraction of 1.94%. The shorter dwelling time (10 ms) benefited the decrease of both average pore size and pore area fraction.

Reconstruction of the Costume Elements of the Shilikty “Golden Man”

The article contains the reconstruction of the Shilikty “Golden Man” clothing based on multidisciplinary studies of the archeological material from the royal kurgan “Baigetobe” in the Tarbagatai foothills. The authors describe in detail the reconstruction of the anthropological appearance and the results of studying organic samples from the burial complex, as well as explain the final shape of royal attire and justify the details and components of the reconstructed costume. The methodological basis of the study is the systemic approach that allows one to view the categories of the Saka royal clothing as profound systems. Within the approach, the methodology and the recreation of ancient royal clothing rely on a wide range of analogies from Eurasian Saka-Scythian monuments and ethnographic materials. Based on these monuments and materials, the authors have established that certain elements in the clothing of early nomads of Kazakhstan have more in common with the clothing of neighboring tribes of Asian steppes in the early Iron Age. This is evident in the cut, detailing and the décor of clothing recovered from such monuments as Pazyryk, Katanda, Tuyekta and Akalakha. The methodological challenge to study clothing based on archeological data is primarily related to the condition of the source. The authors briefly characterize the organic probes from the kurgan burial chamber that have been studied using regular and digital microscopes and conclude that the clothing of the Shilikty Man was colorful. Within the framework of multidisciplinary research, the authors have conducted an anthropological study of the skeletal remains and the sculptural reconstruction of the person from the Baigetobe kurgan. Anthropologically, this person belongs to the mixed Caucasoid and Mongoloid type with prevalent Caucasoid elements, which agrees with the anthropological features of the ancient population of Central Asia in the early Iron Age. Therefore, gold jewelry, the quality of fabrics and the multilevel burial structure confirm the high profile of the Shilikty Golden Man. The conclusions and results can be used for the reconstruction of the composite image of the nomadic nobility in Central Asia in the early Saka period.

EDDs: A series of Efficient Defect Detectors for fabric quality inspection

Deep Convolutional Neural Network (DCNN) has recently advanced state-of-the-art performance on vision-related tasks and its application is further extended to industrial fields. The paper focuses on the problem of fabric defect detection to which an efficient DCNN architecture is developed. In contrast to previous methods that directly apply existing DCNN models demonstrated on natural images to industrial images, the proposed Efficient Defect Detectors (EDDs) are sufficiently optimized with consideration of the characteristics of fabric surface images, i.e., resolution, defect appearance, etc. Firstly, lightweight backbone is suggested in EDD to improve computational efficiency without reduction in image resolution. Secondly, a new feature fusion strategy named L-shaped feature pyramid network (L-FPN) is proposed and utilized to make full use of low-level texture features which are demonstrated to be more important than high-level semantic features in defect recognition. Based on the configurations of lightweight backbone and L-FPN, we use only one hyper-parameter to jointly adjust the proportion of resources occupied by width, depth and input resolution so that a family of defect detectors under different resource constraints can be developed. Experiments are conducted on a large fabric dataset to demonstrated the effectiveness of EDDs. Compared with the recent state-of-the-art detector, EfficientDet-d3, EDD-d3 achieves higher mean Average Precision (mAP) (20.9 vs 19.9) but with fewer parameters. EDD-d3 has 8.59M parameters and 31.78B FLOPs (floating point operation per second), which respectively are 39.8% and 49.0% lower than EfficientDet-d3. The proposed EDDs achieve better trade-off between accuracy and speed than previous methods. EDDs could be applied to fabric production sits with different resource restrictions, which demonstrates that EDDs have important application value.

Pelatihan Bahasa Inggris Pada Pedagang Kain Tenun Di Desa Pringgasela Melalui Direct Selling

Pringgasela is one of the tourism places in Lombok island which is located at Pringgasela Sub-district, East Lombok Regency. Pringgasela has been announced as a Fabric Industry Centre in Lombok island, the best quality of fabrics is produced by the fabric craftsmen and craftswomen in that place, this fabric industry is important to support the local economic system of Pringgasela’s society. Foreign tourists are the target market of the fabric sellers in global scale; however, this opportunity was not supported by the English communication skill of the sellers. This program is aimed to train and facilitate the fabric craftsmen, craftswomen and the fabric sellers of English communication skill by using Direct Selling gradually and continuously, so they could improve their skill in English communication, especially in promoting their products. Technically, the objectives of this program were; 1). to train the the fabric craftsmen, craftswomen and the fabric sellers of English communication skill, so they could promote their products to the foreign tourists effectively and efficiently; 2). as the alternative solution for the fabric sellers, in which they would not rely their target profit to the local guide or travel agency anymore. The method of this program has been done through four steps; 1). Planning; 2). Action; 3). Guiding; and 4). Reflection and Evaluation. During the process of the program, the trainers team monitor the participants by interviewing them related with the material, the method used and the tutors of this program. Generally, the participants gave a positive response, they stated that this program was a good training program and the materials given were appropriate for them that clearly explained by the professional tutors. Based on the calculation data, the responses of the participants were; 1) 83% (very good category); 2). 8% (good category); 3). 8% (enough category); and 4) 0% (less category).

Pelatihan Bahasa Inggris Pada Pedagang Kain Tenun Di Desa Pringgasela Melalui Direct Selling

Pringgasela is one of the tourism places in Lombok island which is located at Pringgasela Sub-district, East Lombok Regency. Pringgasela has been announced as a Fabric Industry Centre in Lombok island, the best quality of fabrics is produced by the fabric craftsmen and craftswomen in that place, this fabric industry is important to support the local economic system of Pringgasela’s society. Foreign tourists are the target market of the fabric sellers in global scale; however, this opportunity was not supported by the English communication skill of the sellers. This program is aimed to train and facilitate the fabric craftsmen, craftswomen and the fabric sellers of English communication skill by using Direct Selling gradually and continuously, so they could improve their skill in English communication, especially in promoting their products. Technically, the objectives of this program were; 1). to train the the fabric craftsmen, craftswomen and the fabric sellers of English communication skill, so they could promote their products to the foreign tourists effectively and efficiently; 2). as the alternative solution for the fabric sellers, in which they would not rely their target profit to the local guide or travel agency anymore. The method of this program has been done through four steps; 1). Planning; 2). Action; 3). Guiding; and 4). Reflection and Evaluation. During the process of the program, the trainers team monitor the participants by interviewing them related with the material, the method used and the tutors of this program. Generally, the participants gave a positive response, they stated that this program was a good training program and the materials given were appropriate for them that clearly explained by the professional tutors. Based on the calculation data, the responses of the participants were; 1) 83% (very good category); 2). 8% (good category); 3). 8% (enough category); and 4) 0% (less category).

ATLAS17LS – A large-format prototype silicon strip sensor for long-strip barrel section of ATLAS ITk strip detector

The ATLAS experiment is going to replace the current Inner Detector with an all new inner tracker (ITk) in the ATLAS detector for HL-LHC at CERN. Silicon strip detectors cover the outer layers of the barrel and the endcap sections. We have designed and fabricated a prototype single-sided n+-in-p AC-coupled silicon strip sensor for the outer barrel layer with long strips (LS), ATLAS17LS. It is of the maximum allowable size to fit in a 6-in. silicon wafer, with an outer dimension of 9.80(width)×9.76(length)cm2. The sensor features two rows of LS strip segments, 4.83 cm strip length per segment, a strip pitch of 75.5 μm, and a slim edge design. We have implemented technology for high voltage operation of up to 1000V, with a good signal collection after irradiation fluence of 5.6 × 1014neq∕cm2at the end of HL-LHC operation.We had two objectives for the ATLAS17LS fabrication: qualification of the sensor design and fabrication quality, and providing an adequate number of the sensors for prototyping the building blocks of the strip detector. The sensors were fabricated in 3 batches by HPK with standard wafers from the foundry (320 μm physical thickness). Additional 10 sensors were fabricated with a thinner active thickness of 240 μm to investigate the influence of active thickness on charge collection. Another additional 5 sensors, with special passivation to investigate the influence of passivation on humidity sensitivity. The visual inspection of fabricated sensors revealed an inadequacy that the designed metal width of 10 μm was too narrow. The initial measurements by the vendor showed that the sensors fulfilled the specifications: onset voltages of Microdischarge VMD above the operation voltage VOP (700V for the 1st and 2nd batches; 500V for the 3rd batch, which has improved the yield), leakage currents of < 0.1μA/cm2 at VOP, full depletion voltages VFD< 330V, and rates of bad strips <<1%.

Tactile evaluation of down jacket fabric by the comprehensive handle evaluation system for fabrics and yarns

Down jacket fabric is greatly important in determining the quality of a down jacket. In order to enrich the research on fabric handle, subjective and objective evaluations were made for down jacket fabrics that were less studied. The comprehensive handle evaluation system for fabrics and yarns (CHES-FY) can be used to evaluate the tactile handle of the fabric by accurately and efficiently measuring the basic mechanical properties of the fabric. Therefore, the CHES-FY was used to link the objective evaluation with the subjective handle, so as to effectively estimate the total handle value of the down jacket fabric. Fifty-two kinds of down jacket fabrics were objectively tested through measuring 17 extracted parameters, and principal component analysis was adopted to establish the five main handle characteristics of fullness, softness, stiffness, smoothness, looseness and tightness to characterize basic style of the down jacket fabrics. The results showed that the subjective and objective results were in good agreement. These characteristics can be used as indicators to characterize fabric performance, and the principal component expression to characterize fabric handle can better predict the handle characteristics of down jacket fabrics. This also proves that the CHES-FY can quickly and accurately obtain the fabric handle value, and can also evaluate the fabric quality level.

Coaxial hole array fabricated by ultrafast femtosecond-laser processing with spatially multiplexed vortex beams for surface enhanced infrared absorption

Here, we combined shaping and multiplexing of the laser beam to achieve ultrafast femtosecond-laser patterning of Au films with coaxial and circular hole arrays at a printing rate of 106 elements per second. Fabrication quality of the developed parallel laser-printing approach was found to be enough to replicate coaxial hole arrays with a resonant transmission over 90% in the mid-IR spectral range resulted from coupling between localized electromagnetic mode supported by coaxial unit cell and the lattice-type SPPs. Coupling of the surface plasmons localized within the coaxial holes to the vibration modes of the deposited analyte, widely used antihistamine drag Diphendramine, was found to provide around 800-fold enhancement of the amplitude of characteristic IR bands allowing reliable SEIRA-based fingerprint identification at trace concentrations. Our findings are consistent with the calculated amplitude of the electromagnetic hot spots suggesting their predominant contribution to the observed SEIRA effect. The ability to tune in a facile way the hole geometry and arrangement in the process of fabrication allows to tailor the spectral position of the resonance spanning practically relevant spectral range from 4 to 10 μm. This makes the coaxial microhole arrays produced with ultrafast direct laser printing promising for IR filtering and sensing.

Automatic Fabric Defect Detection Method Using PRAN-Net

Fabric defect detection is very important in the textile quality process. Current deep learning algorithms are not effective in detecting tiny and extreme aspect ratio fabric defects. In this paper, we proposed a strong detection method, Priori Anchor Convolutional Neural Network (PRAN-Net), for fabric defect detection to improve the detection and location accuracy of fabric defects and decrease the inspection time. First, we used Feature Pyramid Network (FPN) by selected multi-scale feature maps to reserve more detailed information of tiny defects. Secondly, we proposed a trick to generate sparse priori anchors based on fabric defects ground truth boxes instead of fixed anchors to locate extreme defects more accurately and efficiently. Finally, a classification network is used to classify and refine the position of the fabric defects. The method was validated on two self-made fabric datasets. Experimental results indicate that our method significantly improved the accuracy and efficiency of detecting fabric defects and is more suitable to the automatic fabric defect detection.

Thermal Simulation and Warping Deformation Experimental Study of PEEK in Material Extrusion

AbstractPolyether‐ether‐ketone (PEEK) is a high‐performance biomaterial, which can be used to fabricate dentures, mandible, and other human implants. However, when the material extrusion (MEX) method is employed to print parts using PEEK material, the parts are prone to warpage deformation, which affects the fabrication quality of PEEK parts. Moreover, the uneven temperature field adversely affects the crystallization of PEEK, causing the printed objects with hazel appearance which affects the beauty of the denture. In this paper, finite element analysis is initially performed to study the temperature and stress fields of PEEK under different printing parameters in MEX. Second, the response surface method is used to evaluate the accuracy of the simulation results. Furthermore, a mathematical model of the relationship between warping deformation and the affecting factors during MEX is obtained. The simulation and experimental results show that the temperature field, stress field, and final warping deformation are positively correlated with the extruded filament width, printing speed, and molding chamber temperature, while they are negatively correlated with the nozzle temperature. The impact of each parameter in a descending order is: extruded filament width, printing speed, molding chamber temperature, and nozzle temperature.

Improvement in the absorbency of ozone bleached cotton fabric by the addition of surfactant

The combined effect of surfactants with ozone bleaching process on the quality of cotton fabric was examined in this paper. The concentration of surfactants was varied between 0.01- 0.5 g/l in order to evaluate its effect on CIE whiteness, absorbency and strength of cotton fabric bleached by ozone. The maximum improvement in absorbency (1.07 s) and whiteness (WCIE 66.53) was achieved in the presence of anionic surfactant (0.01 g/l) at optimized experimental conditions. The strength properties of cotton fabric bleached by ozone in the presence of surfactant were also improved. Pollution load of ozone bleaching effluent even after adding surfactant was far less than conventional bleaching effluent. Statistically it was confirmed that surfactant addition significantly improved the whiteness and absorbency of ozone bleached cotton fabric.

Data-Driven Adaptive Control for Laser-Based Additive Manufacturing with Automatic Controller Tuning

Closed-loop control is desirable in direct energy deposition (DED) to stabilize the process and improve the fabrication quality. Most existing DED controllers require system identifications by experiments to obtain plant models or layer-dependent adaptive control rules, and such processes are cumbersome and time-consuming. This paper proposes a novel data-driven adaptive control strategy to adjust laser voltage with the melt pool size feedback. A multitasking controller architecture is developed to incorporate an autotuning unit that optimizes controller parameters based on the DED process data automatically. Experimental validations show improvements in the geometric accuracy and melt pool consistency of controlled samples. The main advantage of the proposed controller is that it can adapt to DED processes with different part shapes, materials, tool paths, and process parameters without tweaking. System identification is not required even when process conditions are changed, which reduces the controller implementation time and cost for end-users.

Effects of balance electrode in deep micro-holes drilling in “nickel plate” through µECM process using H2SO4 electrolyte

Abstract Drilling of high aspect ratio taper-less micro-holes in hard to machine and exotic materials is very challenging field. Electrochemical micro-machining (μECM) is one of the cost-effective process and a better alternative for drilling of deep micro-holes in difficult to cut materials with precise dimension and good surface finish. Quality of deep micro-holes fabrication through µECM is highly influenced by electrolyte material and its concentration as well as balance electrode. In this study, H2SO4 electrolyte (aqueous) is used for the analysis of deep micro-holes drilling in “nickel plate” through µECM process using circular balance electrode. Taguchi technique is used to optimize the machining parameters and ANOVA is applied to investigate the effects of these parameters on the response outputs such as average diameter, overcut and diameter difference. The dominant machining parameters for the responses have been found out and the regression models have been developed. In last, all the experimental results obtained using balanced electrode have been compared with results obtained without using balance electrode at same machining conditions.

Quality of screen printing in knit fabric for different mesh count on semi solid design

In semi solid design, the parameters of the quality of the printed fabric were color fastness, level of print detail, color difference, print coverage, saw-tooth effect, line sharpness etc. Actually, printed fabric quality was evaluated by these parameters. Again, print coverage, saw-tooth effect, line sharpness, etc. were examined by estimating different distances, angles etc. in printed fabric and these factors were compared with image positives. Mesh opening effect on the quality of screen printed fabric was investigated after printing the semi solid design on knit fabric using different mesh count screens and different types of the link. To print semi solid design on knit fabric different types of ink as well as non-identical mesh count was used. Then mesh screen out come on the design and form of printed fabric in screen printing was examined. For the evaluation of semi solid design effect there remains two different methods.The first one is visual assessment and another way is microscope observation. Here, to determine the probability of the amount of ink flowing by the screen, mesh opening area of every screen was considered and it was done from respective digital microscope images.

Objective Evaluation of Fabric Flatness Grade Based on Convolutional Neural Network

As an important indicator for the appearance and intrinsic quality of textiles, fabric flatness is the immediate cause affecting the aesthetic appearance and performance of textiles. In this paper, the objective evaluation system of fabric flatness based on 3D scanner and convolutional neural network (CNN) is constructed by using the height data of AATCC flatness template. The 3D scanner is responsible for the collection of the height value data of the sample. The effect of different sub-sample cutting sizes, cutting offsets, and network model depths on the objective evaluation coincidence rate of multiple flatness level was studied. The experimental results show that the coincidence rate of the system reaches 98.9% when the collected sample data are cut into subsamples of 20 pixel × 20 pixel with 12 pixel cutting offsets and the 11-layer network model is selected. Finally, this scheme is used to evaluate the flatness of four real fabrics with different colors and textures. The result shows that all of the samples can achieve a higher coincidence rate, which further verifies the adaptability and stability of the objective evaluation system constructed in this paper for fabric flatness evaluation.

Semi-supervised fabric defect detection based on image reconstruction and density estimation

Defective products are a major contributor toward a decline in profits in textile industries. Hence, there are compelling needs for an automated inspection system to identify and locate defects on the fabric surface. Although much effort has been made by researchers worldwide, there are still challenges with computation and accuracy in the location of defects. In this paper, we propose a hybrid semi-supervised method for fabric defect detection based on variational autoencoder (VAE) and Gaussian mixture model (GMM). The VAE model is trained for feature extraction and image reconstruction while the GMM is used to perform density estimation. By synthesizing the detection results from both image content and latent space, the method can construct defect region boundaries more accurately, which are useful in fabric quality evaluation. The proposed method is validated on AITEX and DAGM 2007 public database. Results demonstrate that the method is qualified for automated detection and outperforms other selected methods in terms of overall performance.

Towards a Qualitative-Quantitative Decision-Making Aid for Fatigue Life Evaluation of Naval High Speed Light Craft

The Life of Type (LOT) of a naval High Speed Light Craft (HSLC) can be limited by its structural fatigue life. The fatigue life of a ship is influenced by many factors, such as geometry, fabrication quality, the long-term load distribution, and analytical techniques. The complex dependencies between these factors and the fatigue life cause uncertainty in predictions. A lack of understanding of uncertainty can adversely affect the management of LOT risks, resulting in the reduction of availability of the ship and costly repairs. Therefore, improved understanding of the benefits and limitations of different fatigue life evaluation approaches informs the management of risks relating to the ship’s LOT. This paper presents the first phase of work in a comparative analysis of different fatigue life evaluation approaches for naval HSLC. The present work involves a holistic data review, codification of the data to reveal key themes, and individual expert comparative analysis of the different approaches. The next phase of the study is also described.