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The textile industry holds immense significance in the economy of any nation, particularly in the production of synthetic yarn and fabrics. Consequently, the pursuit of acquiring high-quality products at a reduced cost has become a significant concern for countries. The primary objective of this research is to leverage data mining and data intelligence techniques to enhance and refine the production process of texturized yarn by developing an intelligent operating guide that enables the adjustment of production process parameters in the texturized yarn manufacturing process, based on the specifications of raw materials.

This research undertook a systematic literature review to explore the various factors that influence yarn quality. Data mining techniques, including deep learning, K-nearest neighbor (KNN), decision tree, Naïve Bayes, support vector machine and VOTE, were employed to identify the most crucial factors. Subsequently, an executive and dynamic guide was developed utilizing data intelligence tools such as Power BI (Business Intelligence). The proposed model was then applied to the production process of a textile company in Iran 2020 to 2021.

The results of this research highlight that the production process parameters exert a more significant influence on texturized yarn quality than the characteristics of raw materials. The executive production guide was designed by selecting the optimal combination of production process parameters, namely draw ratio, D/Y and primary temperature, with the incorporation of limiting indexes derived from the raw material characteristics to predict tenacity and elongation.

This paper contributes by introducing a novel method for creating a dynamic guide. An intelligent and dynamic guide for tenacity and elongation in texturized yarn production was proposed, boasting an approximate accuracy rate of 80%. This developed guide is dynamic and seamlessly integrated with the production database. It undergoes regular updates every three months, incorporating the selected features of the process and raw materials, their respective thresholds, and the predicted levels of elongation and tenacity.

One of the major reasons of layout-related difficulties faced by manufacturing industries is non-value-adding and redundant work. Plant layout study aims at economic production with larger volumes and variety as well. Method studies focus on the effectiveness with efficiency by a systematic critical scrutiny of work being done. The intention is to identify logical sequence of activities highlighting and eliminating the unnecessary mudas. Time and motion study is a combination of time study and motion study analysing and eliminating any unnecessary movement for productivity optimization of that job or process. Thus, through the elimination of unnecessary motions, times for performing the processes may be reduced and productivity increased. The intention is to subdivide the different operations of a job or process into measurable elements. Hence this case has been developed based on the primary data. The primary data was collected using Industrial Engineering Studies like layout study, method study and time and motion study. This case has been classroom tested with MBA students in their Lean Management Course.

Arin Synthetics Ltd. (ASL) though had installed modern machinery in its facility, process efficiency and optimization were a concern. Top Brass at ASL believed that ASL was overstaffed and its processes had creep as far as efficiency is concerned. This case focuses on ways to improve the process efficiency to rationalize the manpower at ASL. Presence in large growing global markets put cost pressure on ASL, thus mandating improvement in the efficiency of its processes through manpower rationalization. This case, therefore, discusses one of the highly staffed process of waste collection. Could ASL achieve reduction in the manpower in waste reduction without affecting the overall process? Was there a strategic mistake in the thought process of disposing of the waste generated by the manufacturing complex?

Operations management, Productivity and performance, Quality management, Lean management.

Discusses the 6th ITCRR, its breadth of textile and clothing research activity, plus the encouragement given to workers in this field and its related areas. States that, within the newer research areas under the microscope of the community involved, technical textiles focuses on new, ‘smart’ garments and the initiatives in this field in both the UK and the international community at large. Covers this subject at length.

To investigate the performance of linings in clothing.

A total of 24 lining fabrics were produced in different constructions. 150 denier 350 twist/cm filament polyester warp yarn was used for all of the fabrics. Two different weft yarns (textured, filament) were used to produce lining fabrics in three different densities.

In the garment sector, lining performance is highly important for the manufacture of proper quality garments. The main problem of linings during usage is seam slippage for some constructions.

Fabric constructions were chosen as warp rips, weft rips, ripstop (rips both in warp and weft direction) and plain weave. Seam slippage, bending behaviour, crease recovery angle and comfort properties of the linings were measured and the results evaluated.

The paper contributes to understanding the performance of linings.

This paper aims to extracted sericin from the cocoons of Bombyx mori silkworms, and sericin powder was applied onto drawn textured polyethylene terephthalate (PET) yarns as a spin finish. The reactivity on the surface of PET yarns was analyzed through Fourier transform infrared spectrophotometry–attenuated total reflectance (FTIR-ATR) and dyeing with methylene blue as a reactive dye. Also, investigations were conducted on the effects of sericin, citrc acid (CA) (as a crosslinking agent), and sodium hypophosphite (as a catalyst) concentrations on some properties of false-twist textured PET yarns.

A false-twist texturing machine (Scragg-Shirley minibulk, England) was used with the draw ratio of 1.05, heating temperature of 120°C, texturing speed of 100 m min⁻¹ and applied twist of 3,000 TPM. The aqueous extraction of sericin was carried out by the boiling of the raw silk in distilled water with L:R: 40:1 for 120 min. The aqueous solution was filtered with a filter paper to remove the impurities and insoluble fibroin. Finally, the sericin solution was freeze-dried to obtain the sericin powder. The sericin solution was applied on the drawn textured PET yarns using the “pad-dry-cure” method.

Sericin fixation onto the PET yarns was confirmed by FTIR-ATR. The results showed that there were no significant changes in the tensile strength, linear density, crimp contraction and crimp modulus, elongation at break and shrinkage. In contrast, a substantial increase was observed in moisture regain, vertical wicking, dye uptake and ultraviolet protection. There was also a reduction just in the electrical resistivity, in the presence of sericin.

Although sericin has been known to have numerous beneficial properties, its application in textile industry as a spin finish has not been reported yet.

Jacquard woven fabrics are widely used in various sections of upholstery industry, where mattress cover is one of them. Strength of jacquard woven mattress fabric depends on several factors. The objective of this study is to model the multi‐linear relationship between fibre, yarn and fabric parameters on the strength of fabric using artificial neural network (ANN) and Taguchi design of experiment (TDOE) methodologies.

TDOE was applied to determine the optimum design values and the contribution of each parameter. Robustness (performance) of models is measured by root mean squared error (RMSE). These tools will enable the user to predict the fabric strength from number of given inputs. It also provides the knowledge related to the contribution of fibre, yarn and fabric parameters on fabric strength. Fabrics tested in this study made from different fibre types and max/min level for several fabric and yarn‐related parameters. The models generated with TDOE and ANN methodologies were compared with the actual experimental data.

It was found that ANN model gives better approximation with the minimum RMSE.

The data taken from factory are related with jacquard woven fabric.

This study has many practical implications that brings up a general approach for textile industry. During manufacturing, waste or scrap ratio can be reduced and production planning become more efficient.

Firstly, before starting manufacturing in factory, we can easily predict the strength of woven fabric using the defined factors. This makes the model usable at the planning stage of the fabric. Secondly, the contribution of factors affecting fabric strength was determined. The ANN model generated in this study helps the engineers of planning department at the company easy to plan the manufacturing of fabric with a good estimation of fabric strength before the production order.

Sectional warping is the most widely used warp preparation process in weaving. Winding all warp sections with the same length and same tension is a key factor for a good quality warp preparation. It is required that winding thickness (increase in radius due to warp winding) remains the same within and between warp sections. The purpose of this paper is to investigate winding thickness variations within and between warp sections, which can lead to quality problems in woven fabrics.

A measurement system is developed and then an experimental investigation into winding thickness variations is carried out. Winding thickness is measured with respect to number of drum revolutions using a laser sensor with 20 microns resolution. The number of drum revolutions and drum angular position are measured by an incremental encoder. Both sensors are mounted on an industrial sectional warping machine. A real-time software written in C programming language collects and records the data for all sections of warp with respect to drum number of revolutions and then results are evaluated to determine winding thickness variations.

Results show that warp sheet thickness starts with a higher value and it decreases up to around 30 drum revolutions and then it remains constant or decreases very slightly which can be considered as insignificant from practical point of view. Warp sheet thickness (i.e. thickness of one warp layer) fluctuates within each section up to 10 percent CV with five drum revolutions average warp sheet thickness. There are also warp sheet thickness variations between warp sections up to 3 mm.

Considering the short of practical research results on winding thickness variations in the literature, results of this study will be an original contribution to understanding winding thickness variation level. Also, results presented in this paper can be used to develop control algorithms for thickness control in sectional warping machines.

Gale‐force winds and generally inclement weather conditions, especially for those who travelled from north of the Border, fortunately did not affect attendance at, or mar the success of, the fourth Multilayer Workshop held on 8–9 February at the modern production facility of New England Laminates (UK) at West Pimbo Industrial Estate, Skelmersdale, Lancashire. This was Circuit World's second visit to Nelco, and, whereas the earlier visit provided interesting and informative insight into the company's activities (featured together with Nelco SA, Dijon, France, as a Company Profile in Circuit World, Vol. 12, No. 3), the opportunity to attend the Workshop was a special bonus in that it proved extremely instructive and practical, providing a ‘feel’ for the basic ingredients of multilayer materials and how best to utilise them for successful bonding.

This month British industry returns to Argentina at B.A.70. Hugh Grey and Richard Brooks view the prospects.

Perspiration and heat are produced by the body and must be eliminated to maintain a stable body temperature. Sweat, heat and air must pass through the fabric to be comfortable. The cloth absorbs sweat and then releases it, allowing the body to chill down. By capillary action, moisture is driven away from fabric pores or sucked out of yarns. Convectional air movement improves sweat drainage, which may aid in body temperature reduction. Clothing reduces the skin's ability to transport heat and moisture to the outside. Excessive moisture makes clothing stick to the skin, whereas excessive heat induces heat stress, making the user uncomfortable. Wet heat loss is significantly more difficult to understand than dry heat loss. The purpose of this study is to provided a good compilation of complete information on wet thermal comfort of textile and technological elements to be consider while constructing protective apparel.

This paper aims to critically review studies on the thermal comfort of textiles in wet conditions and assess the results to guide future research.

Several recent studies focused on wet textiles' impact on comfort. Moisture reduces the fabric's thermal insulation value while also altering its moisture characteristics. Moisture and heat conductivity were linked. Sweat and other factors impact fabric comfort. So, while evaluating a fabric's comfort, consider both external and inside moisture.

The systematic literature review in this research focuses on wet thermal comfort and technological elements to consider while constructing protective apparel.