Textile yarn production monitoring, regulating and controlling method

Abstract

The invention relates to the technical field of textile yarn production, and discloses a textile yarn production monitoring, regulating and controlling method which comprises the following steps: step 1, inspecting raw materials through comprehensive inspection equipment, and performing preliminary inspection and screening on the raw materials; the intelligent management system is arranged, the whole yarn production process is monitored, data of each link are collected in real time and transmitted to the system center, when the system detects unqualified product values, an analysis program can be immediately started through a built-in intelligent algorithm, the problem is judged, and corresponding countermeasures are triggered, so that the production efficiency is improved, and the production cost is reduced. And if the problem is derived from the raw materials, the system can immediately mark the batch of raw materials as unavailable, and if the problem occurs in the subsequent production process, such as improper fiber treatment and substandard spun yarn quality, the system can quickly send a work stopping instruction to the production line, so that the effect of reducing the use consumption of the production line is achieved.

Description

Technical Field

[0001] The invention relates to the technical field of textile yarn production, in particular to a textile yarn production monitoring and control method. Background Art

[0002] Textile yarn production is the process of processing various textile fibers into products of a certain fineness for weaving, rope making, thread making, knitting and embroidery. Yarn can be divided into types such as short-staple yarn and continuous filament, and its fineness can be expressed in a variety of ways, such as number, metric count, imperial count, denier, etc. The yarn production process includes two main stages: spinning and weaving. Spinning is the stage of processing fibers into yarn, while weaving is the stage of weaving yarn into cloth. During the spinning process, yarn can be divided into natural fiber yarn and chemical fiber yarn according to the source of the fiber. Natural fiber yarn includes cotton, linen, silk, etc., while chemical fiber yarn includes regenerated fiber and synthetic fiber. After spinning, these fibers are formed into yarn and become the basic material for textile production.

[0003] The classification of yarn includes pure spun yarn, blended yarn and ply yarn. Pure spun yarn is composed of the same fiber, such as pure cotton yarn, wool yarn, etc. Blended yarn is composed of two or more fibers, while ply yarn is formed by combining and twisting two or more single yarns. In addition, the production of yarn also involves different spinning systems, such as worsted yarn and coarse yarn, and is classified according to different spinning methods. Worsted yarn is spun through the combing process, with high parallel straightness of fibers and uniform yarn, but the cost is relatively high. It is mainly used as raw materials for high-grade fabrics and knitwear. Coarse yarn does not go through the combing process, has poor parallel straightness of fibers, and a loose structure. It is mostly used as raw materials for general fabrics and knitwear.

[0004] At present, in the actual application of textile yarn production monitoring and control methods, the yarn textile production line is monitored in real time, and the detection data is identified through a logic system. According to the qualification of the detection data, the quality of the yarn finally produced is judged. However, when one of the data is unqualified, if the subsequent process continues to operate, it will cause waste of raw materials for yarn production, thereby resulting in waste of costs. Summary of the invention

[0005] The object of the present invention is to provide a method for monitoring and controlling textile yarn production to solve the problems raised in the above-mentioned background technology.

[0006] To achieve the above object, the present invention provides the following technical solution: a method for monitoring and controlling textile yarn production, comprising the following steps: Step 1: Inspect the raw materials through comprehensive inspection equipment and conduct preliminary inspection and screening of the raw materials; Step 2: Open the compacted raw material package into small pieces or small fiber bundles, remove impurities such as dust, grass clippings, oil stains, etc., mix fibers of different types or properties evenly to meet the specific requirements of yarn products, and analyze the image of the mixed raw materials using image processing technology; Step 3: Send the processed fibers to a carding machine, arrange the fibers into a line through the carding action, remove short fibers and impurities between the fibers, combine multiple carded fiber strips together, and improve the straightening parallelism and uniformity of the fibers through the drafting and mixing action of the drawing frame to make fiber strips of specified length and weight, and perform real-time detection of the parallelism and uniformity of the fibers; Step 4: The drawn fiber strips are fed into a roving frame, and after drafting and twisting, the fiber strips are thinned and twisted to form roving. The roving is fed into a spinning frame, and after further drafting, twisting and winding, spun yarn is formed. The thickness, strength and twist of the spun yarn can be adjusted according to actual production needs. Step 5: Wind the spun yarn into a package with large capacity, good shape and certain density. Singe the yarn as needed, combine two or more single yarns together, and add a certain twist to make a high-strength and well-structured strand. Step 6. An intelligent management system is set up throughout the production line to integrate the MES quality management system, ERP system, etc. to achieve real-time collection, analysis and push of production data. These data are identified through the logic system. When the data does not meet the standards, the operating parameters of each device will be adjusted accordingly.

[0007] Preferably, the comprehensive testing equipment in step one includes a single fiber strength meter, a fiber fineness tester, etc., which can complete the testing of multiple indicators at one time. The single fiber strength meter measures the tensile strength of the fiber to evaluate its ability to resist breakage during use, and the fiber fineness tester measures the diameter or linear density of the fiber to understand its fineness distribution and uniformity.

[0008] Preferably, the data detected by the comprehensive inspection equipment will be detected and recorded by the intelligent management system. If the data does not reach the standard value, the raw materials will be screened and will not be used in the weaving of the yarn. If the data reaches the standard, the equipment will operate and load the materials normally.

[0009] Preferably, the image processing technology in step 2 evaluates the mixing uniformity by calculating the density, distribution and other parameters of the fibers in the image. If the mixing uniformity of the raw materials does not meet the standard, the raw materials will be screened. If the mixing is uniform, the raw materials will continue to participate in the weaving of the yarn.

[0010] Preferably, the detection of fiber parallelism and uniformity in step three specifically adopts image processing method, uses image processing technology to analyze the microscopic image of the fiber, and evaluates the straightening parallelism by calculating parameters such as the straightening length and arrangement angle of the fiber. The specific steps are to take a microscopic image of the fiber, and use image processing software to analyze and calculate. If the data does not meet the standards, it is necessary to make corresponding adjustments to the operating parameters of the drawing frame.

[0011] Preferably, the drafting multiple of the spun yarn produced in the step 4 should be controlled within a reasonable range (usually 10-50 times) to ensure that the coarse yarn can be evenly stretched and thinned and reach the special number (count) required by the subsequent process. When twisting, the appropriate twist range should be selected according to the yarn specifications and uses, and the twisting should be uniform and stable. When the stretched and twisted yarn is wound on the bobbin according to the forming requirements to form a tube-shaped spun yarn, it should be ensured that the winding is tight, the layers are clear, the formation is good, and the unwinding is convenient.

[0012] Preferably, the spun yarn in step 4 will be monitored in real time by the production process monitoring in the intelligent management system, and the spun yarn produced at this time node will be recorded. If the quality of the spun yarn is unqualified in the subsequent finished product quality inspection, data dependence can be provided based on this time node to prepare for subsequent equipment adjustments.

[0013] Preferably, in the step five, during the spinning, doubling and weaving processes, many short and loose fibers will be left on the surface of the yarn, and these fibers will form a layer of short fluff on the surface of the fabric. This layer of fluff not only affects the appearance and finish of the fabric, but is also easily contaminated with dust during the production process, increasing the difficulty of cleaning the fabric. The singeing treatment can remove these fluffs, making the surface of the yarn and fabric smooth and flat, thereby improving the overall quality of the fabric.

[0014] Preferably, the intelligent management system in step six collects data in real time during the yarn production process. For unqualified product values, if it is raw materials, the raw materials will not be selected. If it is fibers, spun yarn, etc. in subsequent production processes, the production equipment will stop working to reduce consumption costs.

[0015] The present invention provides a method for monitoring and controlling textile yarn production, which has the following beneficial effects: (1) The present invention monitors the entire yarn production process by setting up an intelligent management system. The data of each link are collected in real time and transmitted to the system center. When the system detects unqualified product values, its built-in intelligent algorithm will immediately start the analysis program, determine the problem and trigger corresponding countermeasures. If the problem originates from the raw materials, the system will immediately mark the batch of raw materials as unusable. If the problem occurs in the subsequent production process, such as improper fiber processing, substandard yarn quality, etc., the system will quickly issue a stop operation instruction to the production line, thereby achieving the effect of reducing the use and consumption of the production line.

[0016] (2) The present invention can capture high-definition images of the raw material mixture through image processing technology, such as a high-resolution camera or scanner. These images are then sent to professional image processing software or algorithms for analysis. In the image processing stage, image preprocessing is first performed, including steps such as denoising, contrast enhancement, and edge detection to improve the visibility and recognizability of the fibers in the image. Subsequently, advanced image analysis algorithms can be used to automatically identify and measure multiple key parameters of the fibers in the image, such as diameter, length, color, shape, and their distribution density and arrangement pattern in space, and the raw materials can be screened, thereby achieving the effect of preventing the raw materials from affecting yarn production.

[0017] (3) The present invention collects and analyzes the extracted fiber characteristic parameters and compares them with preset evaluation standards. The evaluation standards may be formulated based on industry experience, product requirements or customer specifications to determine whether the fiber straightening and parallelism meet the standards. If the analysis results show that the data do not meet the standards, that is, the fiber straightening and parallelism do not meet the requirements, then further measures need to be taken to improve it. In order to solve the problem of fiber straightening and parallelism not meeting the standards, textile companies usually adjust the operating parameters of the drawing frame. By adjusting the tension, speed, gap of the combing elements and other parameters of the drawing frame, the fiber straightening and parallelism can be improved, thereby achieving the effect of improving the stability of the subsequent spinning process and the quality of the yarn. DETAILED DESCRIPTION

[0018] The present invention provides a method for monitoring and controlling textile yarn production, comprising the following steps: Step 1: Inspect the raw materials through comprehensive inspection equipment, and conduct preliminary inspection and screening of the raw materials; the comprehensive inspection equipment includes single fiber strength tester, fiber fineness tester, etc., which can complete the detection of multiple indicators at one time. The single fiber strength tester measures the tensile strength of the fiber to evaluate its ability to resist breakage during use. The fiber fineness tester measures the diameter or linear density of the fiber to understand its fineness distribution and uniformity. For raw materials that do not meet the tensile strength and fiber linear density, under the action of the intelligent management system, even if the raw materials have been loaded into the equipment, the equipment will not work, and it needs to replace qualified raw materials to continue working; Step 2: Open the compacted raw material package into small pieces or small fiber bundles, remove impurities such as dust, grass clippings, oil stains, etc., mix fibers of different types or properties evenly to meet the specific requirements of yarn products, and analyze the image of the mixed raw materials using image processing technology; The specific working principle of image processing technology involves multiple links and steps, mainly including image acquisition, image preprocessing, image analysis, image enhancement, image restoration, image coding and compression, image segmentation and image recognition, etc. Image acquisition is to convert optical information into digital images through equipment (such as cameras, scanners), image preprocessing is to denoise, smooth, sharpen, etc. to improve image quality, image analysis is to extract features such as pixels, colors, textures, etc., which may involve segmentation and feature extraction, image enhancement is to adjust contrast and brightness, histogram equalization, improve visual effects, image restoration is to establish a metamorphic model, apply the inverse process to restore the original information, reduce blur and distortion, image coding and compression use JPEG, PNG and other methods to reduce the amount of storage and transmission data, image segmentation divides the image into independent regions, and commonly used algorithms include threshold segmentation, region growing, edge detection, image recognition is to extract feature information, compare with known features, and identify target categories and attributes; Advanced image acquisition equipment, such as high-resolution cameras or scanners, can capture high-definition images of the raw material mixture. These images are then sent to professional image processing software or algorithms for analysis. In the image processing stage, image preprocessing is first performed, including denoising, contrast enhancement, edge detection and other steps to improve the visibility and recognizability of the fibers in the image. Subsequently, advanced image analysis algorithms can automatically identify and measure multiple key parameters of the fibers in the image, such as diameter, length, color, shape, and their distribution density and arrangement pattern in space. The key to evaluating the uniformity of mixing is to analyze the uniformity of fiber distribution. This usually involves calculating the fiber distribution density map in space, and evaluating the uniformity of mixing by comparing the density differences in different areas. At the same time, indicators such as the number of intersections between fibers and the randomness of fiber arrangement are also considered to fully reflect the uniformity of the mixture. If the analysis results show that the mixing uniformity of the raw materials does not meet the preset standards, the batch of raw materials will be automatically or manually sent to the screening system for further processing. The screening system will separate according to the specific properties of the fibers (such as size, density, etc.) to ensure that the fibers that do not meet the requirements are removed, thereby improving the uniformity of the overall mixture; on the contrary, if the mixing uniformity of the raw materials meets or exceeds the expected standards after evaluation, then the batch of raw materials will be considered qualified and continue to participate in the subsequent yarn spinning process; Step 3: Send the processed fibers to a carding machine, arrange the fibers into a line through the carding action, remove short fibers and impurities between the fibers, combine multiple carded fiber strips together, and improve the straightening parallelism and uniformity of the fibers through the drafting and mixing action of the drawing frame to make fiber strips of specified length and weight, and perform real-time detection of the parallelism and uniformity of the fibers; First, use a high-resolution microscope or micro-camera to photograph the fiber sample. These devices can capture the fine structure of the fiber, including its morphology, color, texture, and subtle arrangement. In order to obtain more accurate and comprehensive data, the focus, exposure, white balance and other parameters of the microscope should be properly set when shooting, and the impact of external light and vibration on the image quality should be minimized; Import the captured microscopic images into professional image processing software for preliminary preprocessing. This step aims to improve image quality and the accuracy of subsequent analysis. Preprocessing may include image denoising, contrast enhancement, edge sharpening, color correction and other operations to highlight the outline and detail features of the fibers. Utilizing the powerful functions of image processing software, fiber feature extraction is performed on the pre-processed image. This step is critical, as it involves automatically identifying and measuring multiple key parameters of the fiber, such as straight length, arrangement angle, etc. To achieve this goal, the software usually uses edge detection algorithms to identify the boundaries of the fibers, and evaluates the straightness and parallelism of the fibers by calculating the straightness and inclination of the boundaries. The extracted fiber characteristic parameters are counted and analyzed, and compared with the preset evaluation standards. The evaluation standards may be based on industry experience, product requirements or customer specifications to determine whether the fiber straightening and parallelism meet the standards. If the analysis results show that the data does not meet the standards, that is, the fiber straightening and parallelism do not meet the requirements, then further measures need to be taken to improve them. In order to solve the problem of fiber straightening and parallelism not meeting the standard, textile enterprises usually adjust the operating parameters of the drawing frame. The drawing frame is an important equipment in the textile pre-treatment process. It is used to combine multiple fiber strands into a uniform fiber strand and further straighten and arrange the fibers in the process. By adjusting the drawing frame's tension, speed, gap of the combing elements and other parameters, the fiber straightening and parallelism can be improved, and the stability of the subsequent spinning process and the yarn quality can be improved. After adjusting the operating parameters of the draw frame, it is necessary to retake the microscopic image of the fiber, and perform image processing and data analysis again to verify the effectiveness of the improvement measures. If the data still does not meet the standards, it is necessary to continue to adjust the parameters or check other factors that may affect the fiber straightening and parallelism. Through continuous feedback and optimization, the fiber straightening and parallelism can be gradually improved to ensure the quality and stability of textile products. Step 4: The drawn fiber strips are fed into a roving frame, and after drafting and twisting, the fiber strips are thinned and twisted to form roving. The roving is fed into a spinning frame, and after further drafting, twisting and winding, spun yarn is formed. The thickness, strength and twist of the spun yarn can be adjusted according to actual production needs. During the spun yarn production stage, the transformation process of each spun yarn from raw material to finished product is closely monitored by high-definition cameras and various sensors of the intelligent management system. These devices not only record intuitive information such as the appearance and diameter change of the spun yarn, but also monitor key parameters such as the temperature and humidity of the production environment and the operating status of the machine through advanced sensing technology. These data are transmitted to the central processing unit in real time and processed by complex algorithms to form a comprehensive understanding of the spun yarn production process. When the spun yarn is successfully produced at this time point, the system will automatically record key information such as production time, raw material batches used, production equipment number, etc., forming a complete production record chain. The establishment of this record chain provides a traceable data basis for subsequent finished product quality inspection; After the yarn is processed into finished products, it will go through a strict quality inspection process. If the yarn quality is found to be unqualified during the inspection, such as broken ends, uneven yarns, insufficient strength, etc., the intelligent management system will immediately start the quality traceability mechanism. By comparing the information in the finished product and the production record chain, the system can quickly locate the production time node of the problematic yarn, and then trace it back to the specific production equipment, raw material batches and even production operators; This data-dependent mechanism provides a valuable basis for subsequent equipment adjustment and optimization. Enterprises can analyze possible causes based on the production conditions of problematic spinning, such as equipment aging, improper parameter settings, raw material quality problems, etc., and formulate targeted improvement measures accordingly, such as equipment maintenance, adjustment of production process parameters, replacement of high-quality raw materials, etc., to improve the quality stability of subsequent production batches; Based on the data support provided by the intelligent management system, enterprises can not only respond quickly to quality issues, adjust and optimize equipment, but also establish a long-term mechanism for continuous improvement. By analyzing historical production data, enterprises can identify potential risk points in the production process and take preventive measures in advance. At the same time, the system can also provide a scientific basis for the production decision-making of enterprises according to the changing trends of production efficiency and quality indicators, and promote the development of textile production in a more intelligent and efficient direction. Step 5: Wind the spun yarn into a package with large capacity, good shape and certain density. Singe the yarn as needed, combine two or more single yarns together, and add a certain twist to make a high-strength and well-structured strand. Step 6. An intelligent management system is set up throughout the production line to integrate the MES quality management system, ERP system, etc. to achieve real-time collection, analysis and push of production data. These data are identified by the logic system. When the data does not meet the standards, the operating parameters of each device will be adjusted accordingly; The intelligent management system realizes the all-round monitoring of the whole process of yarn production through the sensor network, high-definition cameras and Internet of Things technology throughout the production line. From raw material storage, fiber pretreatment, yarn spinning to finished product packaging, the data of each link is collected in real time and transmitted to the system center. These data include but are not limited to the batch information of raw materials, the straightness and parallelism of fibers, the diameter and strength of yarn, the temperature and humidity of the production environment, and the operating status of the equipment. When the system detects unqualified product values, its built-in intelligent algorithm will immediately start the analysis program, determine the problem and trigger the corresponding response measures. If the problem is caused by raw materials, the system will immediately mark the batch of raw materials as unusable and notify the procurement department to change suppliers or adjust procurement standards to ensure that subsequent production is not affected. If the problem occurs in the subsequent production process, such as improper fiber processing, substandard yarn quality, etc., the system will quickly issue a stop order to the production line; After receiving feedback on the numerical value of unqualified products, the intelligent management system will immediately communicate with the production equipment and control it to enter a shutdown state. This immediate shutdown mechanism not only avoids the further production of unqualified products, reduces the waste of raw materials and energy consumption, but also protects the production equipment from potential damage. At the same time, the system will also send early warning information to the maintenance team, prompting them to check and repair equipment failures in time to ensure the rapid recovery of the production line; Through real-time data collection and intelligent analysis, the intelligent management system can also provide enterprises with more refined cost control strategies. The system can analyze the cost structure and changing trends of different production links, identify the key points of cost control, and formulate targeted improvement measures for enterprises. For example, by optimizing the ratio of raw materials, adjusting production process parameters, and improving equipment utilization, enterprises can effectively reduce production costs and enhance market competitiveness while ensuring product quality.

[0019] It should be noted that, in this article, relational terms such as first and second, etc. are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Moreover, the terms "include", "comprise" or any other variants thereof are intended to cover non-exclusive inclusion, so that a process, method, article or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, article or device.

[0020] Finally, it should be noted that the above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Although the present invention has been described in detail with reference to the aforementioned embodiments, those skilled in the art can still modify the technical solutions described in the aforementioned embodiments or replace some of the technical features therein by equivalents. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention shall be included in the protection scope of the present invention.

Claims

1. A method for monitoring and controlling textile yarn production, characterized in that: The following steps are involved: Step 1: Inspect the raw materials through comprehensive inspection equipment and conduct preliminary inspection and screening of the raw materials; Step 2: Open the compacted raw material package into small pieces or small fiber bundles, remove impurities such as dust, grass clippings, oil stains, etc., mix fibers of different types or properties evenly to meet the specific requirements of yarn products, and analyze the image of the mixed raw materials using image processing technology; Step 3: Send the processed fibers to a carding machine, arrange the fibers into a line through the carding action, remove short fibers and impurities between the fibers, combine multiple carded fiber strips together, and improve the straightening parallelism and uniformity of the fibers through the drafting and mixing action of the drawing frame to make fiber strips of specified length and weight, and perform real-time detection of the parallelism and uniformity of the fibers; Step 4: The drawn fiber strips are fed into a roving frame, and after drafting and twisting, the fiber strips are thinned and twisted to form roving. The roving is fed into a spinning frame, and after further drafting, twisting and winding, spun yarn is formed. The thickness, strength and twist of the spun yarn can be adjusted according to actual production needs. Step 5: Wind the spun yarn into a package with large capacity, good shape and certain density. Singe the yarn as needed, combine two or more single yarns together, and add a certain twist to make a high-strength and well-structured strand. Step 6. An intelligent management system is set up throughout the production line to integrate the MES quality management system, ERP system, etc. to achieve real-time collection, analysis and push of production data. These data are identified through the logic system. When the data does not meet the standards, the operating parameters of each device will be adjusted accordingly.

2. A textile yarn production monitoring and control method according to claim 1, characterized in that: The comprehensive testing equipment in step 1, including a single fiber strength meter, a fiber fineness tester, etc., can complete the testing of multiple indicators at one time. The single fiber strength meter measures the tensile strength of the fiber to evaluate its ability to resist breakage during use, and the fiber fineness tester measures the diameter or linear density of the fiber to understand its fineness distribution and uniformity.

3. A textile yarn production monitoring and control method according to claim 1, characterized in that: The data detected by the comprehensive inspection equipment will be detected and recorded by the intelligent management system. If the data does not meet the standard value, the raw materials will be screened and will not be used in the weaving of yarns. If the data meets the standard, the equipment will operate and load materials normally.

4. A textile yarn production monitoring and control method according to claim 1, characterized in that: The image processing technology in step 2 evaluates the mixing uniformity by calculating the density, distribution and other parameters of the fibers in the image. If the mixing uniformity of the raw materials does not meet the standard, the raw materials will be screened. If the mixing is uniform, the raw materials will continue to participate in the weaving of the yarn.

5. A textile yarn production monitoring and control method according to claim 1, characterized in that: The detection of fiber parallelism and uniformity in step three specifically adopts image processing method, uses image processing technology to analyze the microscopic image of the fiber, and evaluates the straightening parallelism by calculating parameters such as the straightening length and arrangement angle of the fiber. The specific steps are to take a microscopic image of the fiber, and use image processing software to analyze and calculate. If the data does not meet the standards, it is necessary to adjust the operating parameters of the drawing frame accordingly.

6. A textile yarn production monitoring and control method according to claim 1, characterized in that: The drafting multiple of the spun yarn produced in the step 4 should be controlled within a reasonable range (usually 10-50 times) to ensure that the coarse yarn can be evenly stretched and thinned to reach the special number (count) required by the subsequent process. When twisting, the appropriate twist range should be selected according to the yarn specifications and uses, and the twisting should be uniform and stable. When the stretched and twisted yarn is wound on the bobbin to form a tube-shaped spun yarn according to the forming requirements, it should be ensured that the winding is tight, the layers are clear, the formation is good, and the unwinding is convenient.

7. A textile yarn production monitoring and control method according to claim 1, characterized in that: The spun yarn in step 4 will be monitored in real time by the production process monitoring in the intelligent management system. The spun yarn produced at this time node will be recorded. If the quality of the spun yarn is unqualified in the subsequent finished product quality inspection, data dependency can be provided based on this time node to prepare for subsequent equipment adjustments.

8. A textile yarn production monitoring and control method according to claim 1, characterized in that: In the step 5, during the spinning, doubling and weaving processes, many short and loose fibers will be left on the surface of the yarn, and these fibers will form a layer of short fluff on the surface of the fabric. This layer of fluff not only affects the appearance of the fabric, but is also easily contaminated with dust during the production process, increasing the difficulty of cleaning the fabric. The singeing treatment can remove these fluffs, making the surface of the yarn and fabric smooth and flat, thereby improving the overall quality of the fabric.

9. A textile yarn production monitoring and control method according to claim 1, characterized in that: The intelligent management system in step six collects data from the yarn production process in real time. For unqualified product values, if it is raw materials, the raw materials will not be selected. If it is fibers, spun yarn, etc. in the subsequent production process, the production equipment will stop working to reduce consumption costs.