Physicochemical Assessment of the Biodegradability of Agricultural Nonwovens Made of PLA

Compostable biodegradable plastics are an ecological alternative to traditional products based on petroleum derivatives, whose post-use waste may pollute the natural environment. Modern polymer materials show the functional properties of plastics obtained by conventional methods, but they also may be degraded as a result of biochemical transformations in composting. This allows such materials to be included in the scheme of the currently implemented circular economy, which does not generate post-consumer waste. This paper presents methods for the assessment of the biodegradation process of selected agricultural nonwovens produced from commercial PLA 6252D polylactide, supplied by Nature Works® LLC, USA. The agricultural nonwovens tested, obtained by the spun-bond technique, were characterised by different degrees of crystallinity in the range from 11.1% to 31.4%. Biodegradation tests were carried out as simulated aerobic composting while maintaining constant environmental conditions in accordance with test procedures based on PN-EN/ISO standards using the method of sample mass loss determination. Gel chromatography (GPC/SEC) and FTIR spectroscopy were also applied to assess the degree of biodegradation. The aim of this study was to evaluate the effect of the crystallinity of nonwoven made of PLA 6252 D on its degradation in a compost environment.

Optimisation of the Sublimation Textile Printing Process Using the Taguchi Method

In this paper, printing parameters for the sublimation printing of polyester fabrics like the number of strokes, the sublimation paper weight in grams per square metre, the fusing temperature and time were optimised using the Tauguchi experimental design technique. In the evaluations the signal-to-noise ratio was used. Sixteen experiments were performed with respect to the L 16 Orthogonal array design for the Tauguchi approach. The results show a considerable improvement in the signal-to-noise ratio as compared to the initial conditions. Through this study, not only can optimum printing conditions for sublimation printed polyester fabrics be obtained but also the significant factors that affect water vapour resistance.

Detection of Remote Sensing Warp Tension during Weaving on Plain Twill and Satin Fabric

Warp tensions were measured while a machine was operating on a woven cotton fabric with three different woven patterns. This study was carried out with image analysis methods using a high speed camera. Three weave pattern types: plain, twill and satin were woven on the same weaving machine, and thus it could be understood how weave pattern differences affect warp tension. Each of these three weaves was woven in three weft densities: 20, 28 and 45 wefts per cm. These fabrics were able to be made on a weaving machine with an automatic dobby. It was aimed to investigate warp tension differences for three basic weave patterns while keeping all machine settings constant. The weave settings of the dobby were changed for plain, twill and satin weaves. Warp tension calculation was based on the warp elasticity theory. Warp elasticises were measured by image processing methods in MATLAB using a high-speed camera. It was aimed to improve upon the new method of warp extension measurement of fabric when the loom is in operation. It was observed that the warp tension in plain fabric was higher than for twill and satin under the same conditions.

Barrier Properties of Footwear Packages against Water Vapour Transport and Thermal Resistance

In this paper the authors focused on the analysis of relations between the material (such as knitted fabrics with a two and three dimensional structure) configurations and hygienic parameters of packages. In order to measure hygienic properties, the water vapour permeability and absorption were both used with the thermal resistance capacity. The connector role in the packages measured was played by air (in the case of two – layered package), polyurethane foam and three – dimensional knitted fabric with similar characteristics to polyurethane foam in respect of the mass per square metre and thickness. On the basis of the results obtained, a statistical model of the barrier was created and the changes in water vapour transport process described.

New Design of a Boost Drive Circuit with an Energy Recovery Function for the Piezoelectric Jacquard Needle

Aiming at the technical bottlenecks existing in the current warp knitting machine control system such as jacquard drive circuit, the design method of self-boosting power supply circuit integrated with jacquard driver is proposed for the embedded warp knitting machine jacquard control system for miniaturization design. The voltage boost circuit designed can boost the low voltage from the input of the working power supply to the high voltage for the output to drive the oscillation of the piezoelectric ceramic jacquard needles. Since the circuit adopts energy storage inductance instead of current-limiting resistor to optimize the driving circuit, it not only limits the forward charging current of the piezoelectric ceramic, but also effectively realize the energy recovery function. The effectiveness of the design method is verified by simulation.

Multi-Response Optimisation for the Development of an Activated Carbon Web as Interlining for Higher Electrical Conductivity and EMI Shielding Using Grey Relational Analysis

This paper presents a simple and novel method of producing an activated carbon (AC) non-woven web from acrylic waste derived from discarded bathmats converted into a nonwoven web by a carding and needle punching machine. After stabilisation at lower temperature, carbonisation of the stabilised web was performed in a muffle furnace. The carbonisation temperature, the holding time of the activated carbon web at the final temperature, the heating rate to reach the final carbonisation temperature and the number of steps adopted for developing the carbon web were optimised using the grey relational analysis (GRA) approach to get optimum responses of the surface area of the web, electrical conductivity and electromagnetic shielding. The results demonstrated a large improvement in electrical conductivity as surface resistivity decreased from 134.21 Ω.mm to 0.28 Ω.mm, and the corresponding electromagnetic shielding increased to 82.63 dB when the temperature of the carbonisation, the holding time and number of steps were increased. The surface area in the AC web was increased from 73 m2g-1 to 210 m2g-1 with an increase in the carbonisation temperature, the holding time and number of steps to reach the final temperature. The optimisation technique used in this work could be successfully used in cost and error reduction while producing an AC web. The optimised AC web was characterised by Brunauer, Emmett and Teller (BET), X-ray diffraction characterisation and elemental analysis (EDX) in order to determine changes in its structure, surface area, degree of crystallinity, inter-layer spacing and proportion of different elements. The AC web developed can be effectively employed as interlining in apparels because of its flexibility and eco-friendly electromagnetic shielding, as it works on the principle of the absorption, reflections and internal reflections of electromagnetic radiations.

Investigation of the Influence of Stretch on the Air Permeability of Knitted Fabric: Effect of Loop Length

Most of the time, a certain degree of stretch prominently and incrementally occurs in intimate wear, leisure wear, sportswear, medical textiles etc., during their action. Variations in the stretch gradient would definitely cause changes in the air permeability of knitted fabrics. The influence of variables such as loop length, the presence of an elastomeric component and fabric structure on the air permeability of cotton single jersey and pique knitted fabrics in a stretched state was critically analysed. In this work, changes in the air permeability of cotton jersey samples with and without elastomer were investigated and reported by keeping the samples in static up to an incremental stretch of 40% at a rate of 10% of the stretch gradient, in a dry relaxed state, wet relaxed state and fully relaxed state.

Is China’s Textile Industry Still a Labour-Intensive Industry?

Is China’s textile industry (CTI) still a laboor-intensive one? To answer this question, this study measures the capital-labour intensity and technology intensity of CTI and its sub-sectors during 2006-2018, then applies factor intensity classification and cluster analysis to identify their industrial attributes. The results show that CTI and its sub-sectors are still the labour- and non-technology-intensive. All the indexes of capital-labour intensity and technology intensity of CTI and its sub-sectors are below 100, lower than the average of industry sectors, indicating that they are not separate from the category of labour-intensive industry and still heavily dependent on labour. And cluster analysis verifies the industrial classification results. So CTI still needs to keep on increasing its capital intensity and technology intensity to achieve the goal of industrial transformation and upgrading in the future.

Intensification of Press Felt Dewatering for Tissue Machines

This article describes a method of dewatering press felts using a blow-through device. The essence of this method is pressing out free water contained in the felt with unheated air at a slight overpressure. The usefulness of this method for various types of felt used in tissue machines was tested. The results showed that the effectiveness of this process depends mainly on the proper selection of the pressure difference on both sides of the dewatering felt and of the blow-through time (dwell time). The increase in the dryness of felts dewatered by means of the air blow-through method is closely related to the structure and contamination of the felt. In the second part of the study, the felts were additionally dewatered using a suction chamber with a vacuum of 20 kPa. Unfortunately, the increase in the dryness of the felts by means of a vacuum was not very high, only up to 2.8%.

Prediction of Garment Production Cycle Time Based on a Neural Network

The process of garment production has always been a black box. The production time of different clothing is different and has great changes, thus managers cannot make a production plan accurately. With the world entering the era of industry 4.0 and the accumulation of big data, machine learning can provide services for the garment manufacturing industry. The production cycle time is the key to control the production process. In order to predict the production cycle time more accurately and master the production process in the garment manufacturing process, a neural network model of production cycle time prediction is established in this paper. Using a trained neural network to predict the production cycle time, the overall error of 6 groups is within 5%, and that of 3 groups is between 5% and 10%. Therefore, this neural network can be used to predict the future production cycle time and predict the overall production time of clothing.