VISION-BASED PRODUCT COUNTER, PARAMETER MONITORING, AND PREDICTIVE ANALYSIS SYSTEM WITH MACHINE LEARNING FOR TEXTILE THREADER MACHINES

Abstract

A vision-based product counter, parameter monitoring, and predictive analysis system with machine learning for textile threader machines comprises PredictiveEdge Mote (100) who is equipped with Jetson Nano (101), camera (102), temperature sensor (104), accelerometer (105), current sensor (107), HMI Display (103) and power supply (106), one can do not only real-time counting of any of their products but quite a number of machine features such as temperature and voltage thus maintaining good production management of a sewing thread-tying machine with PredictiveEdge Mote's structure level camera module, it makes accurate view of the quantities of sewn product clasped, thus improving the control of the production barbeques of the sewing beckoning machines.

Specification

Description:FIELD OF THE INVENTION
This invention relates to vision-based product counter, parameter monitoring, and predictive analysis system with machine learning for textile threader machines.
BACKGROUND OF THE INVENTION
This advanced innovation enables the implementation of an improved vision-based counting and maintenance system to textile threader machines in form of inpatient model based advancement. The system records comprehensive operational parameters of machinery including but not limited to temperature, acceleration, current, add visual parameters in an effort to monitor product output quantity as well as the working condition of the machinery very well. This information is first sent to a central cloud computer integrated with learning algorithms that interprets the information and generates insights and recommendations for efficient operations and predictive maintenance of the machine. Feedback is instantaneous for the operator on the ground through visual dispensation, the management team also has access to target areas that they can monitor through a web dashboard viewing the time operational and operational data in real time.
The present innovation meets the necessity for accurate product identification, synthetic parameters in real time, and maintenance prediction in textile threader machines, which is pivotal for production efficiency as well as machine dependability. A lot of past monitoring systems were poorly designed, often neglecting the submission of relevant real-time information concerning the volume of goods produced and the state of the machine, which led to production delays, unanticipated machine breakdowns, and expensive maintenance. Working conditions in textile threader machines are harsh and further warrant constant monitoring of the machine in order to enhance performance and prevent production-inhibiting defects. This technology combines a vision-based product counter with parameter sensing and machine learning analytics, facilitating early actions, improving maintenance optimization, and improving efficiency and durability of the machines.
US20180016721A1: A sewing machine includes at least one needle bar, a threading motor, a threading mechanism, a processor, and a memory. The threading mechanism is configured to pass an upper thread through an eye of a sewing needle. The memory is configured to store computer-readable instructions that, when executed by the processor, instruct the processor to perform processes. The processes include making one of a setting that prohibits operation of the threading mechanism and a setting that does not prohibit the operation of the threading mechanism. The processes include switching the operation of the threading mechanism by prohibiting the operation of the threading mechanism in a case where the setting that prohibits the operation of the threading mechanism is made, and permitting the operation of the threading mechanism in a case where the setting that does not prohibit the operation of the threading mechanism is made.
RESEARCH GAP: Vision-based product counting and predictive parameter monitoring with machine learning for textile threader machines is the novelty of the system.
JP2024145808A: To provide a sewing device capable of determining whether a thread holding mechanism that grips and holds a thread is holding the thread. [Solution] The sewing device includes a thread holding mechanism that grips and holds the thread, a detection unit, and a determination unit. The thread holding mechanism has a first holding unit that is displaceable between a holding position where the thread is held and a release position where the thread is released, a second holding unit that clamps and holds the thread together with the first holding unit in the holding position, and a movement unit that moves the first holding unit between the holding position and the release position. The detection unit detects a physical quantity corresponding to the displacement of the second holding unit (S21). The determination unit determines whether the thread is held between the first holding unit and the second holding unit based on the detection result of the detection unit (S22).
RESEARCH GAP: Vision-based product counting and predictive parameter monitoring with machine learning for textile threader machines is the novelty of the system.
SUMMARY OF THE INVENTION
This summary is provided to introduce a selection of concepts, in a simplified format, that are further described in the detailed description of the invention.
This summary is neither intended to identify key or essential inventive concepts of the invention and nor is it intended for determining the scope of the invention.
To further clarify advantages and features of the present invention, a more particular description of the invention will be rendered by reference to specific embodiments thereof, which is illustrated in the appended drawings. It is appreciated that these drawings depict only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention will be described and explained with additional specificity and detail with the accompanying drawings.
This innovation is an integrated monitoring and analysis system for the textile threader machines which tracks products in real time while monitoring preset parameters and provides predictive analysis. As the core of the system, the vision module allows to count the number of products that are being processed and activate it for control over production rates. This vision-based counter, in addition to the aim of production flow, also provides the vital information necessary for trend analysis and explanation of the anomalies in the output. In addition to these visual images, the system uses multiple sensors to measure and record the most important parameters of the machine, such as operating temperature, acceleration and current consumption. The information from these sensors helps monitoring the operable condition of the machine and its changes to avoid excessive loading or poor operational conditions.
BRIEF DESCRIPTION OF THE DRAWINGS
The illustrated embodiments of the subject matter will be understood by reference to the drawings, wherein like parts are designated by like numerals throughout. The following description is intended only by way of example, and simply illustrates certain selected embodiments of devices, systems, and methods that are consistent with the subject matter as claimed herein, wherein:
FIGURE 1: SYSTEM ARCHITECTURE
The figures depict embodiments of the present subject matter for the purposes of illustration only. A person skilled in the art will easily recognize from the following description that alternative embodiments of the structures and methods illustrated herein may be employed without departing from the principles of the disclosure described herein.
DETAILED DESCRIPTION OF THE INVENTION
The detailed description of various exemplary embodiments of the disclosure is described herein with reference to the accompanying drawings. It should be noted that the embodiments are described herein in such details as to clearly communicate the disclosure. However, the amount of details provided herein is not intended to limit the anticipated variations of embodiments; on the contrary, the intention is to cover all modifications, equivalents, and alternatives falling within the scope of the present disclosure as defined by the appended claims.
It is also to be understood that various arrangements may be devised that, although not explicitly described or shown herein, embody the principles of the present disclosure. Moreover, all statements herein reciting principles, aspects, and embodiments of the present disclosure, as well as specific examples, are intended to encompass equivalents thereof.
The terminology used herein is for the purpose of describing particular embodiments only and is not intended to be limiting of example embodiments. As used herein, the singular forms "a"," "an" and "the" are intended to include the plural forms as well, unless the context clearly indicates otherwise. It will be further understood that the terms "comprises," "comprising," "includes" and/or "including," when used herein, specify the presence of stated features, integers, steps, operations, elements and/or components, but do not preclude the presence or addition of one or more other features, integers, steps, operations, elements, components and/or groups thereof.
It should also be noted that in some alternative implementations, the functions/acts noted may occur out of the order noted in the figures. For example, two figures shown in succession may, in fact, be executed concurrently or may sometimes be executed in the reverse order, depending upon the functionality/acts involved.
In addition, the descriptions of "first", "second", "third", and the like in the present invention are used for the purpose of description only, and are not to be construed as indicating or implying their relative importance or implicitly indicating the number of technical features indicated. Thus, features defining "first" and "second" may include at least one of the features, either explicitly or implicitly.
Unless otherwise defined, all terms (including technical and scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which example embodiments belong. It will be further understood that terms, e.g., those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
This innovation is an integrated monitoring and analysis system for the textile threader machines which tracks products in real time while monitoring preset parameters and provides predictive analysis. As the core of the system, the vision module allows to count the number of products that are being processed and activate it for control over production rates. This vision-based counter, in addition to the aim of production flow, also provides the vital information necessary for trend analysis and explanation of the anomalies in the output. In addition to these visual images, the system uses multiple sensors to measure and record the most important parameters of the machine, such as operating temperature, acceleration and current consumption. The information from these sensors helps monitoring the operable condition of the machine and its changes to avoid excessive loading or poor operational conditions.
When gathered, the vision module data and the sensor data are sent to some central cloud server. The machine learning algorithms are then used here to search for patterns in the available history and real-time data that would more than likely relate to the system temperature being too high or an unexpected acceleration occurring. This analysis is then employed by the system in order to provide predictive assistance, so that the operator can eliminate problems before they cause any downtime or damage to the system. As the models are trained on more data, the ML models also get better in alerting and advising quick actions requiring maintenance, therefore increasing the effectiveness of the machines in the course of time.
In terms of convenience, the processed information and forecasts are located on an interface on the site and can be accessed at any time, thus allowing operators to respond and take action when alerted. In this manner, problems are quickly solved at the manufacturing site. In addition, there is cloud connectivity in the system that allows personnel to login to a web dashboard and access comprehensive historical data, performance trends over time, and change directions for running the machine depending on its condition. This disadvantage also extends the access feature to enhance oversight functions allowing management to oversee the status and productivity of the machines from anywhere making it very ideal for large scale production systems.
BEST METHOD OF WORKING
With the PredictiveEdge Mote who is equipped with Jetson Nano, camera, temperature sensor, accelerometer, current sensor, HMI Display and power supply, one can do not only real-time counting of any of their products but quite a number of machine features such as temperature and voltage thus maintaining good production management of a sewing thread-tying machine.
With PredictiveEdge Mote's structure level camera module, it makes accurate view of the quantities of sewn product clasped, thus improving the control of the production barbeques of the sewing beckoning machines.
The inclusion of HMI Display Interface with PredictiveEdge Mote allows operators to visualize on-site changing conditions of the machine and respond to alerts which helps them to improve the situation awareness and the safety of operations.
PredictiveEdge Mote also incorporates Jetson Nano which allows real time processing of sensor data on site and sending it to custom cloud server for machine learning based predictive analytics and AI recommendation for maintenance.
Utilization of the Temperature Sensor, Accelerometer, and Current Sensor placed onto PredictiveEdge Mote can help a machine operate in a healthy state with the reporting of machine parameters in real time and avoid downtimes, consequently improving the reliability of threader machines in a textile factory.
ADVANTAGES OF THE INVENTION
1. Limiting environmental damage is achieved by monitoring productivity, which can be effective using the camera embedded in the PredictiveEdge Mote. With this feature in place, production output can be tracked reliably in real time. Where machine downtime may be expensive and inefficient, temperature, accelerometer, and current sensors are always active in surveillance of machine performance to detect any deviance from the norm.
2. The PredictiveEdge Mote is adapted with an HMI Display that allows on-site managers to view crucial operational metrics eliminating unnecessary delays in decision making and correcting situations that may disrupt production flow.
3. The PredictiveEdge Mote integrates with a Jetson Nano that captures images which are then subject to analytics and deep learning with a cloud server providing the drive. Enabling predictive information allows one to predict when actions should be taken thus planning when scheduled maintenance is likely to minimize potential breakdowns.
4. Utilizing a cloud interface, personnel authorized to access information through a browser interface are able to view real time and archival datasets which enhances remote surveillance, metabolism, and planning that aims at reducing downtime.
5. By providing predictive maintenance through incorporation of several sensors with ML analytics, the texture threaders machines inside the predictive edge mote remain functional with minimum unplanned shut downs.
, Claims:1. A vision-based product counter, parameter monitoring, and predictive analysis system with machine learning for textile threader machines comprises PredictiveEdge Mote (100) who is equipped with Jetson Nano (101), camera (102), temperature sensor (104), accelerometer (105), current sensor (107), HMI Display (103) and power supply (106), one can do not only real-time counting of any of their products but quite a number of machine features such as temperature and voltage thus maintaining good production management of a sewing thread-tying machine.
2. The system as claimed in claim 1, wherein with PredictiveEdge Mote's structure level camera module, it makes accurate view of the quantities of sewn product clasped, thus improving the control of the production barbeques of the sewing beckoning machines.
3. The system as claimed in claim 1, wherein the inclusion of HMI Display Interface with PredictiveEdge Mote allows operators to visualize on-site changing conditions of the machine and respond to alerts which helps them to improve the situation awareness and the safety of operations.
4. The system as claimed in claim 1, wherein PredictiveEdge Mote also incorporates Jetson Nano which allows real time processing of sensor data on site and sending it to custom cloud server for machine learning based predictive analytics and AI recommendation for maintenance.
5. The system as claimed in claim 1, wherein utilization of the Temperature Sensor, Accelerometer, and Current Sensor placed onto PredictiveEdge Mote can help a machine operate in a healthy state with the reporting of machine parameters in real time and avoid downtimes, consequently improving the reliability of threader machines in a textile factory.

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