Human–robot collaboration is a new trend in modern manufacturing. Safety, or human protection, is of great significance due to humans and robots sharing the same workshop space. To achieve effective protection, in this paper, a contact force sensor based on an 8-shaped wound polymer optical fiber is proposed. The 8-shaped wound structure can convert the normal contact force to the shrinkage of the 8-shaped optical fiber ring. The macro-bending loss of the optical fiber is used to detect the contact force. Compared with conventional sensors, the proposed scheme has the advantage of high flexibility, low cost, fast response, and high repeatability, which shows great promise in actively alerting users to potential collisions and passively reducing the harm caused to humans.
Chemicals: Manufacture, use, etc., Textile bleaching, dyeing, printing, etc.
Ritik Batra, Narjes Pourjafarian, Samantha Chang
et al.
Recently, there has been a surge of interest in sustainable energy sources, particularly for wearable computing. Triboelectric nanogenerators (TENGs) have shown promise in converting human motion into electric power. Textile-based TENGs, valued for their flexibility and breathability, offer an ideal form factor for wearables. However, uptake in maker communities has been slow due to commercially unavailable materials, complex fabrication processes, and structures incompatible with human motion. This paper introduces texTENG, a textile-based framework simplifying the fabrication of power harvesting and self-powered sensing applications. By leveraging accessible materials and familiar tools, texTENG bridges the gap between advanced TENG research and wearable applications. We explore a design menu for creating multidimensional TENG structures using braiding, weaving, and knitting. Technical evaluations and example applications highlight the performance and feasibility of these designs, offering DIY-friendly pathways for fabricating textile-based TENGs and promoting sustainable prototyping practices within the HCI and maker communities.
Jackson K. Wilt, Natalie M. Larson, Jennifer A. Lewis
The rapid design and fabrication of soft robotic matter is of growing interest for shape morphing, actuation, and wearable devices. Here, we report a facile fabrication method for creating soft robotic materials with embedded pneumatics that exhibit programmable shape morphing behavior. Using rotational multi-material 3D printing, asymmetrical core-shell filaments composed of elastomeric shells and fugitive cores are patterned in 1D and 2D motifs. By precisely controlling the nozzle design, rotation rate, and print path, one can control the local orientation, shape, and cross-sectional area of the patterned fugitive core along each printed filament. Once the elastomeric matrix is cured, the fugitive cores are removed, leaving behind embedded conduits that facilitate pneumatic actuation. Using a connected Fermat spirals pathing approach, one can automatically generate desired print paths required for more complex soft robots, such as hand-inspired grippers. Our integrated design and printing approach enables one to rapidly build soft robotic matter that exhibits myriad shape morphing transitions on demand.
This research investigates the feasibility of producing affordable, functional acoustic guitars using 3D printing, with a focus on producing structural designs with proper tonal performance. Conducted in collaboration with William Schiesser, the study uses a classical guitar model, chosen for its lower string tension, to evaluate the tonal characteristics of a 3D-printed prototype made from polylactic acid (PLA). Due to the build plate size constraints of the Prusa Mark 4 printer, the guitar body was divided into multiple sections joined with press-fit tolerances and minimal cyanoacrylate adhesive. CAD modeling in Fusion 360 ensured dimensional accuracy in press-fit connections and the overall assembly. Following assembly, the guitar was strung with nylon strings and tested using Audacity software to compare recorded frequencies and notes with standard reference values. Results showed large deviations in lower string frequencies, likely caused by the material choice utilized in printing. Accurate pitches were reached with all strings despite frequency differences through tuning, demonstrating that PLA and modern manufacturing methods can produce affordable, playable acoustic guitars despite inevitable challenges. Further research may investigate alternative plastics for superior frequency matching. This approach holds significant potential for expanding access to quality instruments while reducing reliance on endangered tonewoods, thereby encouraging both sustainable instrument production and increased musical participation. This also creates opportunities for disadvantaged communities where access to musical instruments remains a challenge. Keywords: Luthiery, Stereolithography, 3D-Print, Guitar Making
Nick Willemstein, Mohammad Ebrahim Imanian, Herman van der Kooij
et al.
Additive Manufacturing (AM) is a promising solution for handling the complexity of fabricating soft robots. However, the AM of hyperelastic materials is still challenging with a limited material range. Within this work, pellet-based 3D printing of very soft thermoplastic elastomers (TPEs) was explored (down to Shore Hardness 00-30). Our results show that TPEs can have similar engineering stress and maximum elongation as Ecoflex OO-10. In addition, we 3D-printed airtight thin membranes (0.2-1.2 mm), which could inflate up to a stretch of 1320%. Combining the membrane's large expansion and softness with the 3D printing of hollow structures simplified the design of a bending actuator that can bend 180 degrees and reach a blocked force of 238 times its weight. In addition, by 3D printing TPE pellets and rigid filaments, the soft membrane could grasp objects by enveloping an object or as a sensorized sucker, which relied on the TPE's softness to conform to the object or act as a seal. In addition, the membrane of the sucker acted as a tactile sensor to detect an object before adhesion. These results suggest the feasibility of AM of soft robots using soft TPEs and membranes as a promising class of materials and sensorized actuators, respectively.
Advancements in fabrication methods have shaped new computing device technologies. Among these methods, depositing electrical contacts to the channel material is fundamental to device characterization. Novel layered and two-dimensional (2D) materials are promising for next-generation computing electronic channel materials. Direct-write printing of conductive inks is introduced as a surprisingly effective, significantly faster, and cleaner method to contact different classes of layered materials, including graphene (semi-metal), MoS2 (semiconductor), Bi-2212 (superconductor), and Fe5GeTe2 (metallic ferromagnet). Based on the electrical response, the quality of the printed contacts is comparable to what is achievable with resist-based lithography techniques. These devices are tested by sweeping gate voltage, temperature, and magnetic field to show that the materials remain pristine post-processing. This work demonstrates that direct-write printing is an agile method for prototyping and characterizing the electrical properties of novel layered materials.
Inks deposited in conventional direct ink writing need to be able to support their own weight and that of the upper layers with minimal deformation to preserve the structural integrity of the three-dimensional (3D) printed parts. This constraint limits the range of usable inks to high-viscosity materials. Embedded printing enables the use of much softer inks by depositing the materials in a bath of another fluid that provides external support, thus diversifying the types of 3D printable structures. The interactions between the ink and bath fluids, however, give rise to a unique type of defect: spreading of the dispensed ink behind the moving nozzle. By printing horizontal threads made of dyed water in baths of Carbopol suspensions, we demonstrate that the spreading can be attributed to the pressure field generated in the viscous bath by the relative motion of the nozzle. As the pressure gradient increases with the viscosity of the bath fluid while the viscosity of the ink resists the flow, a larger bath-to-ink viscosity ratio results in more spreading for low-concentration Carbopol baths. For high-concentration, yield-stress-fluid baths, we find that the steady-state viscosity alone cannot account for the spreading, as the elastic stress becomes comparable to the viscous stress and the bath fluid around the dispensed ink undergoes fluidization and resolidification. By parameterizing the transient rheology of the high-concentration Carbopol suspensions using a simple viscoelastic model, we suggest that the ink spreading is exacerbated by the elasticity but is mitigated by the yield stress as long as the yield stress is low enough to allow steady injection of the ink. These results help illuminate the link between the bath rheology and the printing quality in embedded 3D printing.
Mohammad Toufiqul Hoque, Tian Benrui, Thomas Grethe
et al.
Cellulosic materials like cotton and linen are excellent textile substrates for dyeing with reactive and direct dyes. Due to their cellulosic nature, cotton and linen exhibit good affinity towards direct and reactive dyes. This good affinity is the reason for good washing and rubbing fastness. Chitosan is a bio-based polymer gained by the deacetylation of chitin. In contrast to cellulose, chitosan exhibits also amino functional groups. The purpose of this paper is to evaluate if a chitosan based pretreatment of cotton and linen can lead to different dyeing properties. After different chitosan based pretreatments, the color properties are determined by CIEL*a*b* indices. The rubbing fastness in dry and wet conditions is measured. Even if in the actual study no positive effects were determined by pretreatment of chitosan, the determined results could be utilized in future research to develop other functional treatments of cotton and linen materials with implemented chitosan.
Textile bleaching, dyeing, printing, etc., Engineering machinery, tools, and implements
Abstract 3D body scanning and printing are attracting attention as innovative technologies for producing dress forms. While designing dress forms, the shape of the human body must be accurately reflected in the different postures. This study explored the development of dress forms as a tool to understand changes in body size and shape according to postures and reflect this information to design and fit evaluation in the apparel industry. The holistic development process of dress forms in standing and sitting postures was suggested for representing the body shape of a specific target group. The average shape of middle-aged Korean women was derived by analyzing the 6th Size Korea data. A representative participant whose dimensions were closest to the average size was selected among recruited participants for the dress form development. The body data were acquired with a portable 3D scanner and corresponding dress forms and accessories were modeled using 3D CAD software. The models were inspected and corrected through prototyping. Full-size dress forms in standing and sitting postures were printed using a fused deposition modeling (FDM) 3D printer and post-processed. Completed dress forms were body-scanned and their accuracy was evaluated through morphological similarity comparison, cross-sectional image comparison, surface area and volume comparison, and mesh deviation analysis. Although there were some minor differences caused by the modeling process, the developed dress forms reflected the main characteristics and shapes of the representative body satisfactorily.
Textile bleaching, dyeing, printing, etc., Social Sciences
In the past few years, the widespread use of 3D printing technology enables the growth of the market of 3D printed products. On Esty, a website focused on handmade items, hundreds of individual entrepreneurs are selling their 3D printed products. Inspired by the positive effects of machine-readable tags, like barcodes, on daily product marketing, we propose AnisoTag, a novel tagging method to encode data on the 2D surface of 3D printed objects based on reflection anisotropy. AnisoTag has an unobtrusive appearance and much lower extraction computational complexity, contributing to a lightweight low-cost tagging system for individual entrepreneurs. On AnisoTag, data are encoded by the proposed tool as reflective anisotropic microstructures, which would reflect distinct illumination patterns when irradiating by collimated laser. Based on it, we implement a real-time detection prototype with inexpensive hardware to determine the reflected illumination pattern and decode data according to their mapping. We evaluate AnisoTag with various 3D printer brands, filaments, and printing parameters, demonstrating its superior usability, accessibility, and reliability for practical usage.
In this study, we propose a novel motif-based approach for unsupervised textile anomaly detection that combines the benefits of traditional convolutional neural networks with those of an unsupervised learning paradigm. It consists of five main steps: preprocessing, automatic pattern period extraction, patch extraction, features selection and anomaly detection. This proposed approach uses a new dynamic and heuristic method for feature selection which avoids the drawbacks of initialization of the number of filters (neurons) and their weights, and those of the backpropagation mechanism such as the vanishing gradients, which are common practice in the state-of-the-art methods. The design and training of the network are performed in a dynamic and input domain-based manner and, thus, no ad-hoc configurations are required. Before building the model, only the number of layers and the stride are defined. We do not initialize the weights randomly nor do we define the filter size or number of filters as conventionally done in CNN-based approaches. This reduces effort and time spent on hyperparameter initialization and fine-tuning. Only one defect-free sample is required for training and no further labeled data is needed. The trained network is then used to detect anomalies on defective fabric samples. We demonstrate the effectiveness of our approach on the Patterned Fabrics benchmark dataset. Our algorithm yields reliable and competitive results (on recall, precision, accuracy and f1- measure) compared to state-of-the-art unsupervised approaches, in less time, with efficient training in a single epoch and a lower computational cost.
The use of natural dyes on textiles is developing due to the growing of environmental awareness and avoidance in production of some unsafe synthetic dyes. Pretreatment of wool yarn with chitosan-poly (amidoamine) dendrimer (Ch-PAMAM) hybrid for improving the antimicrobial, antioxidant, and dyeing properties of cochineal and madder as the high consumption natural dyes for dyeing of wool yarns was studied. It was found that cochineal and madder dye exhaustion on treated wool yarn as compared with raw wool yarn were increased by 22% and 10%, respectively. Results indicated that the equilibrium concentrations of cochineal and madder on the treated samples were achieved at 20% o.w.f. and 125% o.w.f., respectively. Furthermore, antioxidant and antimicrobial activities of treated samples were excellent (>99%). It can be concluded that Ch-PAMAM hybrid can be applied on wool yarns as the antioxidant, antimicrobial, and bio-mordant agent to achieve higher natural dye absorption, and eliminate the metal mordants and acid from the dyeing of natural dyes on the wool.
Science, Textile bleaching, dyeing, printing, etc.
Cement concrete is used in small structure to big multi-storied buildings. It is noteworthy to concentrate on concrete elements and mix ratio to achieve desirable strength with feasible cost of raw material. In this investigation, fibers reinforced concrete specimens (M50 grade) were prepared. The strength and durability were tested and compared with the properties of plain concrete (PC). The fibers such as coir, kenaf, and Polypropylene (PP) were used as reinforcement and the compressive, split tensile, flexural, and durability analysis were performed. The compressive test resulted that the natural fiber-based PC/Coir & PC/PP-Coir specimens displayed the maximum compressive strength of 64.5 and 66 MPa owing to the small density and slighter water up taking properties of coir and PP fiber. The split tensile test showed that the PC/kenaf specimen exhibited the higher split tensile strength of 7.3 MPa due to the presence of kenaf fiber with high young’s modulus. Flexural test reported that the PC/PP-Coir/Kenaf specimen exhibited the higher flexural strength of 7.6 MPa because of reinforcing effect offered by coir, kenaf, and PP fibers. Durability study showed that the PC/PP and PC/PP-coir specimens displayed the minimum weight loss of 1.05 and 2.1% and the minimum loss in compressive strength of 3.4 and 4.6%, respectively, in alkaline medium. It was concluded from this study that the coir fiber could be a suitable candidate to improve the strength and durability of concrete.
Science, Textile bleaching, dyeing, printing, etc.
Hasan Tahir, Benny Malengier, Carla Hertleer
et al.
A textile-based triboelectric nanogenerator (TENG) is an energy harvesting flexible and lightweight device that converts mechanical energy to electrical energy. This work presents characterization of a novel hybrid 3D printed embroidery TENG for energy harvesting. The digital embroidery part is done on Brother Embroidery Machine PR670E with polyester multifilament conductive hybrid thread (CleverTex) with a linear thread resistance of 280 Ω/m. This embroidery thread is fully compatible with the standard textile embroidery process. The thread is highly suitable for embroidery due to its very good mechanical properties and no loop formation during embroidery. These features make the thread especially suitable for high production quality. It could be used as needle thread or bobbin thread. For the preparation of the embroidery part, the polyester multifilament conductive hybrid thread is used as needle thread with 100% polyester Madeira thread as bobbin thread. These threads have non-toxic, non-skin irritation properties, which makes them suitable for smart wearable energy harvesting applications. Furthermore, these threads are coated with silicone-paraffin emulsions that improve their running during the embroidery process. Among the possible stitch types (satin, fill, prog. fill, piping, motif, cross, concentric circle, radial, spiral, flexible spiral, stippling, net fill, zigzag net fill, and decorative fill), fill stitch with medium stitch density and 4.5 lines per mm has been used to develop this energy harvesting sample. The 3D printed textile fabric is prepared with extremely flexible filament with a tensile elongation at break of 1400%. The output voltage is 200 V and 103 V for tapping and friction characterization, respectively
Textile bleaching, dyeing, printing, etc., Engineering machinery, tools, and implements
Identification of wool and cashmere fibers is one of the most important topics in the textile industry. In order to recognize these similar fibers, a novel identification method based on the convolution neural network and deep learning was proposed in this paper. As we all know, training a new identification network commonly requires lots of sample images and needs an amount of time, so the transfer learning was adopted for the fiber identification. The four pre-trained convolution neural networks, which consist of AlexNet, VGG-16, VGG-19, GoogLeNet, were used for the transfer learning to identify these similar fibers. Then, 65 fiber images of four kinds of fiber samples including goat hair, yellow wool, sheep wool, and cashmere fibers, were collected, respectively, and processed by the methods including random interception and rotation to obtain a total of 390 fiber images, respectively, for the experiment analysis. After comparing different network models, the results showed that the highest identification accuracy was 99.15%, obtained by the VGG-16 transfer learning model and the proportion of training set to testing set was 7:3. In addition, compared with the traditional machine learning algorithmics, this method also had a great improvement in the model performance and identification accuracy.
Science, Textile bleaching, dyeing, printing, etc.
To improve the detection for different fabric types and defect kinds, an approach based on K-Singular Value Decomposition (K-SVD) dictionary learning method is designed to detect fabric defects, which remains important and challenging in the field of textile engineering. The proposed method has two main parts, namely the training and detection. The 32 defect-free fabric samples were used to train the dictionary by K-SVD. The detection process mainly consists of image segmentation, reconstruction by the trained dictionary, and detection. To improve the detection speed, the patch size was applied for detecting the defects, and the learned dictionaries were trained offline. For selecting general patch size, three patch sizes of 16 $$ \times $$ 16 26 $$ \times $$ 26, and 36 $$ \times $$ 36 were used in the experiment. A comparative study found that the 26 $$ \times $$ 26 has a comprehensive performance. The size and location of the defects were denoted by the black rectangle. Experimental results on 55 fabric samples demonstrated that the proposed method can efficiently detect different kinds of fabric defects and fabric types based on false detection rate and the correct detection rate.
Science, Textile bleaching, dyeing, printing, etc.
Yuri Pereira Chuves, Midori Pitanga, Inga Grether
et al.
The growth of the aeronautical sector leads to the growth of polymer composites application, creating new demand for components applications in complex dimensions and shapes. Regarding different methods of draping 2D fabric into a 3D format, the concern is to keep the fabric properties and characteristics, since fiber orientation is modified after draping. For that purpose, this study aims to evaluate the drapability capacity of 2D dry fibrous fabrics (plain, twill, satin, non-crimp-fabric 0/90, and ±45) into a complex geometry, i.e., spherical indent. The energy required to drape fabric is composed of fabric deformation mechanisms (shear and bending), which were used together with microscopic deformation analysis to determine the appropriate fabric architectures with the highest malleability. Both NCF fabrics presented high energy and roughness on the fabric surface due to the folding effect of stitching. On the other hand, plain and twill weave fabrics required lower energy to drape but demonstrated higher fiber misalignment and deformation. The satin warp/weft relation favored shear and bending mechanisms, presenting better uniformity in load distribution, symmetry on drape capability, lower deformation degree, and lower fiber misalignment. Despite the intermediate load and energy required for drape, ANOVA and optimization methods confirmed that satin fabric showed better malleability behavior for complex geometries applications.