Fabric Roll Research Articles

Numerical simulation of fabric cold pad-batch winding and quality assessment of fabric in roll

Proper fabric winding quality is crucial for achieving desired finishing effects in cold pad-batch dyeing. In this work, a detailed 3D finite element model and assessment criteria were established to analyze the influences of winding pattern, pick-up, and tension function on fabric winding quality, revealed the complex relationship between winding process and fabric roll shape. Material viscoelasticity’s time-dependent effects on stress distribution were considered. Results show that employing a following roller effectively suppresses tangential creases and axial streaks but increases seam imprints and reduces fabric roundness. Increasing pick-up improves winding quality by reducing creases, streaks, and compression deformations. However, it also elevates internal radial stress, hindering control over seam imprints. Winding with variable tension, conicity coefficient α and power index i have significant impacts on coiling quality. In addition, increasing α or decreasing i effectively enhances winding quality, with the power function performing better in tension adjustment and overall winding quality.

Design of image classification system for fabric inspection process using Raspberry Pi

This research is designed as a prototype of defect inspection system on fabric production using machine learning-based image processing technology using the open source Google teachable machine application integrated with Raspberry Pi-3B. The prototype of fabric defect inspection system is built by utilizing two rollers that function as a fabric roll house before and after the inspection process. On both rollers, a fabric is stretched to be inspected, so that from a roll of fabric with a certain length, it can be seen how many defects occur on the fabric. The inspection system is carried out using a web camera with a certain level of lighting connected to a raspberry pi as a control device. Raspberry Pi functions as an image processing device and fabric rolling motor controller. In addition to the category of fabric in good condition, this system classifies into two categories of defects, namely slap defects and sparse defects. The test results show that this system has an average frame per second (FPS) of 4.85, an average inference time of 181.1 ms, with an accuracy of image classification results of 98.4 %.

Proposal for Prevention of Occupational Disease Risk Using the Hiradc Method at PT X in the Dyeing Department

People in this era have various needs in carrying out life. The needs that need to be used by the community have multiple kinds of things, such as clothing. Clothes used by the community go through various processes before becoming finished goods. Before becoming ready-to-wear, clothes came from raw materials such as fabric rolls. There are multiple production processes, such as yarn, fabric, chemical dyeing, etc. One of the places where fabrics are produced is textile factories. A textile factory is a company that produces products in the form of fabrics. The manufacture of fabrics that occur in textile factories must involve mixing chemicals so that the fabric has good quality. The process of mixing these chemical substances involves workers, and the chemical substances used are classified as Hazardous and Toxic Materials (B3), so these chemicals can have a bad impact on their workers if there is physical contact with the worker's body. Exposure to chemicals in the worker's body will cause a risk of developing Occupational Diseases (PAK). Therefore, in this study, data will be processed to prevent workers' risk of Occupational Diseases (PAK) using the HIRADC (Hazard Identification, Risk Assessment, and Determining Control) method. The proposal given in this study is a proposal for the use of Personal Protective Equipment (PPE) and Standard Operating Procedure (SOP) for preventive measures against Occupational Diseases (PAK) for workers

Web-Based Measuring Instrument Calibration Scheduling Information System

The production method has prioritized guaranteeing excellent manufacturing quality in response to the increasing competitiveness in the clothing industry. Utilizing a fabric roll meter measuring instrument dramatically enhances the overall quality of the product by guaranteeing precise measurements. Roll meter fabric measuring equipment in the garment industry evaluates product accuracy based on customer specifications, ensuring exceptional quality. Effective regulation is essential for the management and upkeep of cloth roll meter measuring instruments. Therefore, it is necessary to develop a system that can evaluate the level of urgency for calibrating various equipment and identify those that need recalibration despite having already been calibrated. This project created a web-based system for scheduling the calibration of fabric roll meters. The system was designed using the PHP programming language and MySQL for database management. Use cases delineate how the user interacts with the system, whereas an activity diagram represents the sequence of user activities. Furthermore, a sequence diagram illustrates the user's participation in chronological order. The information system implements maintenance schedules, oversees the calibration of fabric roll meter measuring instruments, stores calibration certificates, and effectively handles calibration data to guarantee precision and efficiency.

Reducing heat gain from sheet metal‐clad walls by utilizing industrially wasted materials (experimental study)

AbstractBuildings' walls are covered to reduce environmental impact and esthetics, and cladding materials vary based on public preference and financial capacity. Metal sheets with glossy surfaces are commonly used, but researchers propose using aluminum sheets and filling gaps with commercial waste materials, like, fabric roll sticks or circular plastic hollow parts. A test room with internal dimensions of 1 × 1 × 2 m used in Baghdad (latitude 33.2° N) was used to study thermal behavior, with a window‐type air conditioner providing standard thermal conditions. The air gap attached to the top of the test wall was either left open or closed during the day. Results showed that double‐layer bamboo packing preserved 52.1% with a closed‐air gap and 49.5% with an open‐air gap, but no discernible difference was observed between the two situations.

Toward a sustainable transition in automated production: enabling the vision-based approach and synchronous control for textile surface inspection systems

The textile and apparel industry is one of the largest industries in the world, with significant environmental and social impacts, such as manual labor in poor working conditions and resource depletion and environmental degradation due to ineffective production. As a result, there is an increasing need for sustainable practices and a transition toward a more circular and responsible industry. In this paper, we introduce the proposed approach in the context of a sustainable transition for the industrial textiles. Instead of human labor, the automated solution to detect defects is proposed for the 4.0 revolution in general and the textile industry in particular. Specifically, the mechanical design of a three-dimensional model for small- and medium-sized fabric rolls is portrayed. Some computational mechanics are created to ensure a stable mechanism and proper actuators. For acquiring accurate data and measuring the machine state, several installations, that is, a digital camera, load cell, and positioning sensor, and the layout of the light source are improved to intensify the image quality. The control theme, such as the cross-coupling controller, offers superior performance in synchronization and vibration-less motion. Lastly, the excellent detection method is provided by the convolutional neural network scheme for offline training to distinguish defects on products. Instead of a manual check or low rate of defect detection on products, the contributions of this research are as follows: (a) analyzing the mechanical design of the textile machining system in terms of dynamic characteristics; (b) implementing a smooth scheme based on motion control synchronization; and (c) integrating various strategies, including vision-based computation and control topology, to demonstrate superior performance. These results highlight that our approach can be widely adapted to address sustainability challenges not only in the textile field but also in global manufacturing practices.

PALEORADIOLOGICAL STUDY ON TWO INFANTS DATED TO THE 17th AND 18th CENTURIES

During an excavation campaign in the Church of the Conversion of Saint Paul in Roccapelago (North Italy), a hidden crypt was discovered, which yielded the remains of more than 400 individuals. The crypt was used as a cemetery by the inhabitants of the village of Roccapelago between the 16th and 18th centuries. Along the north side of the crypt, an area apparently separated from the rest of the burials was found, bordered by stones, where several burials of newborns and infants were concentrated. From here, five fabric rolls containing bones were recovered, and it was decided not to carry out destructive analyses, allocating the two best examples to a thorough radiological investigation to try to define the type of burial and the complete biological profile of the infant. The two rolls, subjects of this study, can be dated archaeologically between the 17th and 18th centuries. CT analysis shows a varied group of bones with a fairly good state of conservation. The paleoradiological study carried out had the primary objective of avoiding the destruction of the two rolls, ensuring their conservation; but at the same time, providing essential data to understand their nature, defining the biological profile and the type of deposition.

WASTE MANAGEMENT COGNIZANCE IN KNITWEAR UNITS OF LUDHIANA

The increasing pace of industrial development has created concerns for the environmental issues. Knitting industry has been characterized as one of the highly polluting industries generating a huge amount of waste that creates various environmental problems and hazards. The present study was effectuated to study the different types of waste generation and waste utilization practices followed by the knitting units of Ludhiana. An exploratory survey of ten knitting units was conducted using a self structured interview schedule. It was noted that majority of the units were established during 1999 to 2009 with an initial investment of 90-95 lakhs and were having an annual turnover upto 15 crores. Total 2305 employees were employed in the selected knitting units, out of which 1233 were skilled workers, 751 were semi-skilled workers, 271 were unskilled workers, 30 were supervisors and 20 were managers. The waste hosiery fabrics were generated in the form of surplus fabric after order completion, fabric roll end waste and fabric with cuts or torn fabric (50%). In cutting and stitching sections, waste was mainly generated due to cutting left overs and thread waste (50% each). All the ten selected units sell the waste fabrics to rag collectors, five units to retailers and three units to shoddy industries. It was also reported that four units either dispose off or burn the waste to get rid of it. The major problem faced for proper utilization of waste fabrics was lack of designing knowledge (80%) followed by shortage of time (70%) and inadequate skills (60%).

Mathematical models for the two-dimensional variable-sized cutting stock problem in the home textile industry

In this paper, we consider the two-dimensional Variable-Sized Cutting Stock Problem (2D-VSCSP) with guillotine constraint, applied to the home textile industry. This is a challenging class of real-world problems where, given a set of predefined widths of fabric rolls and a set of piece types, the goal is to decide the widths and lengths of the fabric rolls to be produced, and to generate the cutting patterns to cut all demanded pieces. Each piece type considered has a rectangular shape with a specific width and length and a fixed demand to be respected. The main objective function is to minimize the total amount of the textile materials produced/cut to satisfy the demand. According to Wäscher, Haußner, & Schumann (2007), the addressed problem is a Cutting Stock Problem (CSP), as the demand for each item is greater than one. However, in the real-world application at stake, the demand for each item type is not very high (below ten for all item types). Therefore, addressing the problem as a Bin-Packing Problem (BPP), in which all items are considered to be different and have a unitary demand, was a possibility. For this reason, two approaches to solve the problems were devised, implemented, and tested: (1) a CSP model, based on the well-known Lodi and Monaci (2003) model (3 variants), and (2) an original BPP-based model. Our research shows that, for this level of demand, the new BPP model is more competitive than CSP models. We analyzed these different models and described their characteristics, namely the size and the quality of the linear programming relaxation bound for solving the basic mono-objective variant of the problem. We also propose an ϵ−constraint approach to deal with a bi-objective extension of the problem, in which the number of cutting patterns used must also be minimized. The quality of the models was evaluated through computational experiments on randomly generated instances, yielding promising results.

Using deep learning to detect the presence/absence of defects on leather: on the way to build an industry-driven approach

In textile/leather manufacturing environments, as in many other industrial contexts, quality inspection is an essential activity that is commonly performed by human operators. Error, fatigue, ergonomic issues, and related costs associated to this fashion of carrying out fabric validation are aspects concerning companies’ strategists, whose mission includes to watch over the physical integrity of their employees, while aiming at enhanced quality control methods implementation towards profit maximization. Considering these challenges from a technical/scientific perspective, machine/deep learning approaches have been showing great skills in adapting a wide range of contexts and, in particular, industrial environments, complementing traditional computer vision methods with characteristics such as increased accuracy while dealing with image classification and segmentation problems, capacity for continuous learning from experts input and feedback, flexibility to easily scale training for new contextualization classes – unknown types of occurrences relevant to characterize a given problem –, among other advantages. The goal of crossing deep learning strategies with fabric inspection processes is pursued in this paper. After providing a brief but representative characterization of the targeted industrial context, in which, typically, fabric rolls of raw-material mats must be processed at a relatively low latency, an Automatic Optical Inspection (AOI) system architecture designed for such environments is revisited [1], for contextualization purposes. Afterwards, a set of deep learning-oriented training methods/processes is proposed in combination with neural networks built based on Xception architecture, towards the implementation of one of the components that integrate the aforementioned system, from which is expected the identification of presence/absence of defective textile/leather raw material at a low-latency. Several models powered by Xception were trained with different tunning parameters, resorting to datasets variations that were set up from raw images of leather, following different annotation strategies (meticulous and rough). The model that performed better reached 96% of accuracy.

Optical fiber-based sensors as an experimental tool to assess the weft and warp yarn tension beam-to-roll in rapier weaving machines

High cycle rates are important in commercial weaving machines to maximize productivity. Faster operation, however, can lead to higher tension on the yarns, which in turn increases the occurrence of yarn breakage and thus machine interruptions. Significant work has therefore been conducted to improve the many weaving machine components with the goal to attain higher production rates without increasing the yarn loads. Quantifying the impact of such improvements is not always possible using conventional, indirect measurement techniques. In addition, these techniques are limited to locations with sufficient access to the yarn to mount a sensor, typically between the warp beam and the first harness. In this paper, we show that the use of optical fiber-based sensors allows directly measuring the yarn tension in both the warp and weft directions in the region from the warp beam to the fabric rolls in rapier-type weaving machines. To do so, we replaced one warp and one weft yarn with an optical fiber equipped with strain sensors and measured strain throughout the subsequent weaving process. The small diameter of the optical fiber allowed minimizing our intrusion on the weaving operation. Our main observations are four-fold. Firstly, we demonstrated how the strain on the warp yarns evolves during the weaving cycle and we used this to focus on the beat-up phase for a low weaving resistance situation. Secondly, we monitored the warp yarn tension between the warp beam and the fabric rolls. Thirdly, we exploited the multiplexing capability of the optical fiber sensors to obtain a tension distribution along the width of the fabric in the weft direction between the reed to the fabric roll. Fourthly, we observed and identified the different phases of a yarn insertion (weft-wise) in a double rigid rapier machine.

DEVELOPING AN INTELLIGENT AUTOMATION AND REPORTING SYSTEM FOR FABRIC INSPECTION MACHINES

In textile companies, the detection of flaws and unacceptable areas of fabrics at the quality control stage has great importance for apparel production, although it is also a post-manufacturing operation for weaving and knitting mills, today it is still mostly being carried out on the guidance of human perception and sensory abilities. Such quality control operations are based on the attendant employee’s detection of the flaws and the unacceptable areas by visual inspection and scanning the overall fabric structure which is being transported on a brightly illuminated straight plane. The detected flaws during the scanning operation are recorded on the flaw charts and these outcomes subsequently are subjected to the quality control supervisor’s evaluation and thereafter, it is decided whether the related inspection reports would exemplify an appropriate fabric to be used in production or not. In this study, it is aimed to develop a new system which enables to integrate the empirical paperwork-based reports that are still being commonly utilized by the majority of the textile companies in to the contemporary technology and also allows to compare such reports with the previous ones when it is necessary. The proposed system development consists of a fabric inspection machine which is equipped with a PLC-controlled digital display or in other words an intelligent control, and a web based software that enables the controller to analyze the reports comprehensively and simultaneously those of produced by this system, The system, which renders paperwork reports obsolete, allows the reports to be viewed on computer screens as soon as the inspection was completed, and all of the fabric rolls within the same order, multiple batches or bundles to be displayed on a single screen. Thus, it permits to determine the usability of the fabric for the production via employing the 4-points system which is one of the prevailing methods for quality control procedures in the industry. Consequently, it is aimed to achieve significant time and labor savings in textile companies via utilizing this new developed system.

Development of a water purifier for radioactive cesium removal from contaminated natural water by radiation-induced graft polymerization

Six years after the Fukushima-nuclear accident, the dissolved radioactive cesium (Cs) is now hardly detected in environmental natural waters. These natural waters are directly used as source of drinking and domestic waters in disaster-stricken areas in Fukushima. However, the possibility that some radioactive Cs adsorbed on soil or leaves will contaminate these natural waters during heavy rains or typhoon is always present. In order for the returning residents to live with peace of mind, it is important to demonstrate the safety of the domestic waters that they will use for their daily life. For this purpose, we have synthesized a material for selective removal of radioactive Cs by introducing ammonium 12-molybdophosphate (AMP) onto polyethylene nonwoven fabric through radiation-induced emulsion graft polymerization technique. Water purifiers filled with the grafted Cs adsorbent were installed in selected houses in Fukushima. The capability of the grafted adsorbent to remove Cs from domestic waters was evaluated for a whole year. The results showed that the tap water filtered through the developed water purifier contained no radioactive Cs, signifying the very effective adsorption performance of the developed grafted adsorbent. From several demonstrations, we have commercialized the water purifier named “KranCsair®”.Furthermore, we have also developed a method for the mass production of the grafted nonwoven fabric. Using a 30L grafting reactor, it was possible to produce the grafted nonwoven fabric with a suitable range of degree of grafting. When an irradiated roll of nonwoven trunk fabric with a length of 10m and a width of 30cm was set in the reactor filled with glycidyl methacrylate (GMA), AMP, Tween 80 monomer emulsion solution at 40°C for 1h, the difference of Dgs in the length and the width on roll of fabrics was negligible.

全方向移動型マテリアルハンドリングロボットの機構と制御

This paper describes mechanism and control of a semi-automated material handling robot that combines flexibility of operation by a person and convenience of automation technology, to automate process of positioning when catching a raw fabric roll in material handling cart. This robot has omnidirectional drive mechanism, kinematics based control system, automatic delivery mechanism, and system for detect and approach a positioning target. As a result, the robot performed automatic positioning using the machine vision system, and performed the automatic delivery of the goods.

Colour stripping of reactive‐dyed cotton by ozone treatment

Trials have been carried out to investigate the efficiency of ozone treatment in the colour stripping of reactive‐dyed cotton fabrics. The trials were performed on a specially designed apparatus to inject ozone gas into the liquor passing through a perforated beam with fabric rolls on it, just like a beam dyeing machine with ozone venturi injection. Conventional reductive colour stripping was applied as the control treatment, and ozone treatment was applied for three different application times (15, 30, and 45 min). Trials were performed with seven selected reactive dyes having various chromophores and reactive groups. The results indicate that 45 min ozone treatment yielded the best colour stripping results among the three application times. Furthermore, the colour stripping percentages of the 45 min ozone treatment were higher for four of the tested dyes, the same for one of the tested dyes, and lower for two of the tested dyes compared with the control treatment, which consisted of conventional reductive colour stripping. Colour stripping of 90% and above was achieved for all samples of the 45 min ozone treatment. The chemical oxygen demand values of the colour stripping baths were compared: the average value of the 45 min ozone application baths was 105 mg l−1, and it was 1993 mg l−1 for the conventional reductive treatment baths. Consequently, a reduction in chemical oxygen demand of almost 94% was achieved by ozone treatment compared with conventional reductive treatment. The strength values of the fabrics after the respective treatments were similar, with a difference of only 3%.

Automatic Detection and Classification of Defects in Knitted Fabrics

High technological equipments are currently used in the knitted fabric production process. However, repetitive tasks are still being performed by human operators in steps of this process, thus reducing productivity and product quality. The inspection of fabric rolls which occurs after the knitting process corresponds to an example. As this activity is still performed by a human inspector, mistakes are common because of human inability to maintain attention during long working hours. In this work, the development of an automated inspection system for knitted fabric in raw and flat state is presented. In order to automatically inspect the fabric, new methods of detection and classification using computer vision are proposed. The system was evaluated in a series of tests using a large image database created from rolls supplied by the industry. Excellent rates on defect detection and classification were achieved, demonstrating the effectiveness of the proposed approach.

全方向移動マテリアルハンドリングロボットの試作

This paper describes prototyping of a semi-automated material handling robot that combines flexibility of operation by an operator and convenience of automation technology, to automate process of positioning when catching a raw fabric roll as a target in material handling cart. This robot has omnidirectional drive mechanism, kinematics based control system, and machine vision system for detect and approach the target. Its omnidirectional motion can be estimated through odometry calculation by analyzing forward kinematics. Machine vision system is also available to detect target position and posture using AR marker. At this stage, the robot can be controlled through a basic operation to approach a raw fabric roll by using above machine vision system.

Defect Detection of Velvet Bathrobe Fabrics and Grading with Demerit Point Systems

Fabric defects that may occur at different stages of woven terry fabric production requires quality control and classification of fabrics as first or second grade before sending to customer. In this study, before shipping of two different terry fabric orders, defects were detected by inspection of fabric rolls on a lighted control board by experienced experts. Number of the defects and dimensions of the defects seen during the inspection were noted on quality control charts. Detected defects were defined and scored according to different demerit point systems. In this way, the fabric rolls were classified according to the demerit point systems before being shipped to garment enterprises. Disputes can be avoided with classification made by a demerit point system on which manufacturer and the customer have agreed.

Design and application of position pad for cervical surgery via anterior approach

Objective To discuss the clinical effect of new position pad for cervical surgery via anterior approach.Methods A total of 100 patients who had cervical surgery via anterior approach from January to December 2011 were chosen and divided into the observation group (n =52) and the control group (n =48).The observation group adopted the new position pad composed by gel shoulder pad,head wear,cylindric cotton fabric roll,while the control group used conventional position pad composed by gel shoulder pad,head wear,sandbag and assistant cushion.Positioning time,operative time,surgical exposure degree,neck skin integrity and position firmness was compared between two groups.Results Positioning and operative time was respectively (3.63 ± 0.67) min and (1.35 ± 0.23) h in the observation group,both shorter than (8.23 ± 0.81) min and (1.56 ± 0.47) h in the control group,and the differences were statistically significant (t =26.78,4.59,respectively; P ＜0.01).The score of surgical exposure degree was (95.41 ±5.48) in the observation group and (70.24 ± 6.46) in the control group,and the difference was statistically significant (t =32.81,P ＜0.01).The rate of position firmness and neck skin integrity was 92.31％ and 88.46％ in the observation group,and 33.33％,33.33％ in the control group,and the differences were statistically significant (x2 =37.68,32.20,respectively; P ＜ 0.05).Conclusions The new position pad for cervical surgery via anterior approach,which can shorten surgical time,improve position firmness and surgical exposure degree,is practical,effective,convenient and therefore has favorable clinical value. Key words: Cervical spine; Anterior approach surgery; Position pad

Special issue on “Cutting and Packing”

Cutting and packing (C&P) problems are hard combinatorial problems, which arise in the context of many real-world applications, both in industry and in services. In general, they require that “large objects” be divided into “small items” in such a way that waste is minimized. Problems of this kind may involve the cutting of paper rolls into narrower rolls in the paper industry, the cutting of large wooden boards into smaller rectangular panels in the furniture industry, the cutting of irregularly shaped components of garment from fabric rolls in the fashion industry, but also the packing of boxes into containers or the loading of boxes on pallets in logistics applications. The aim of this special issue of the International Transactions in Operational Research (ITOR) is devoted to publish high-quality, state-of-the-art papers that contribute to the methodology and practice of cutting and packing problems resolution, either presenting new insights for understanding problem structure, new algorithmic approaches, or innovative resolution of real-life problems and practical applications. This special issue is also linked to the EURO Summer Institute on Cutting and Packing (ESI-CP), which was held in Porto, Portugal, July 16–29, 2012. Each paper will be peer-reviewed according to the editorial policy of ITOR (http://www3.interscience.wiley.com/journal/118505725/home), published by the International Federation of Operational Research Societies (IFORS). Papers should be original, unpublished, and not currently under consideration for publication elsewhere. They should be prepared according to the instructions to authors that can be found in the journal homepage. Authors should upload their contributions using the submission site http://mc.manuscriptcentral.com/itor, indicating in their cover letter that the paper is intended for this special issue. Other inquiries should be sent directly to any of the Guest Editors in charge of this issue: A. Miguel Gomes ([email protected]), José Fernando Gonçalves ([email protected]), Ramón Alvarez-Valdés ([email protected]), and Valério de Carvalho ([email protected]).