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MULTINETWORK CONTROL AND FEEDBACK SOLUTION WITH NRF, XBEE, IOT, AND PREDICTIVE SYSTEM FOR INDUSTRIAL DIE MAKING HYDRAULIC EXTRUSION

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MULTINETWORK CONTROL AND FEEDBACK SOLUTION WITH NRF, XBEE, IOT, AND PREDICTIVE SYSTEM FOR INDUSTRIAL DIE MAKING HYDRAULIC EXTRUSION

ORDINARY APPLICATION

Published

date

Filed on 22 November 2024

Abstract

A multinetwork control and feedback system with nrf, xbee, iot, and predictive system for industrial die making hydraulic extrusion comprises MNCTN Node that consists of a Raspberry Pi, an nRF Module, an actuator, a GPRS modem, current and temperature sensors, and a power supply, enables accurate mechanical activities and allows the gathering of real-time data which is sent to the cloud for further analytical and operational improvement of industrial hydraulic extrusion systems the MNCRN Node comprising a Raspberry Pi, nRF Module, XBee Module, an LED indicators, and a power unit acts as a reliable communication device with confirmed wireless connection and stable data transfer between the machine control unit and the cloud platform.

Patent Information

Application ID202411090832
Invention FieldBIOTECHNOLOGY
Date of Application22/11/2024
Publication Number49/2024

Inventors

NameAddressCountryNationality
MONICA GULATILOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. ALOK JAINLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. SOURABH KUMARLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
TARA SINGLALOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. CHANDRA MOHANLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia
DR. DEEPAK PRASHARLOVELY PROFESSIONAL UNIVERSITY, JALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia

Applicants

NameAddressCountryNationality
LOVELY PROFESSIONAL UNIVERSITYJALANDHAR-DELHI G.T. ROAD, PHAGWARA, PUNJAB-144 411, INDIA.IndiaIndia

Specification

Description:FIELD OF THE INVENTION
This invention relates to multinetwork control and feedback solution with nrf, xbee, iot, and predictive system for industrial die making hydraulic extrusion.
BACKGROUND OF THE INVENTION
This invention provides a market control and feedback management system for industrial hydraulic extrusion machines with real time control and data transmission to the centralized cloud. The system implements a combination of several wireless communication technologies in order to deliver timely and quality connectivity across nodes. It incorporates sensors and actuators for measuring and controlling selected machine indexes and transmitting these para-metric data and performance data to a custom cloud server. Such a platform enables storage and analysis of big data providing the said platform predicturaive capabilities and monitoring recommendations and operations, artificial intelligence. Other prominent features allow authorized personnel to view received information along with relevant insights and control parameters through an integrated display, and web where operational logic is greatly improved.
This innovation provides an effective solution of an automatic and real-time monitoring and control of industrial hydraulic extrusion systems, which tend to be inefficient, periodically idle without planning and don't provide any analytic value. Conventional systems are poorly integrated with the machine process and data analysis requiring overtime to rectify faults, raise the cost of repairs, and operate below optimal levels. The invention fills the void between the operational information and the controlling action for machine control systems by offering a multinetwork solution that combines machine control with predictive feedback signals and analytics. It enables the rapid identification of the occurrence of irregularities, provides high levels of machine dependability, minimizes the period within which a machine is inactive, and provides the operators with information which will enable them to better manage the resources available as well as the operations that will be pursued.
CN103551408B: The invention relates to an extrusion moulding method for parts with inner flanges and outer flanges and an extrusion mould. The extrusion moulding method of the parts comprises the following steps: 1, placing a blank material in a female die, wherein the extrusion mould comprises an internal male die and an external male die sleeved on the periphery of the internal male die, a step shaft structure is arranged at the lower end of the internal male die, an annular moulding gap is formed between the external male die and the internal male die; 2, driving the internal male die to downwards move for extruding the blank material through a first loading mechanism which is in transmission connection with the internal male die, extruding an inner hole, enabling a step surface of a step shaft structure at the lower end of the internal male die to be supported against the blank material to keep stable, driving the external male die to downwards move to extrude the blank material through a second loading mechanism which is in transmission connection with the external male die until extruding a required part; and 3, completing the extrusion, wherein the loading mechanism drives the internal male die and the external male die to return to take the formed part out. According to the extrusion moulding method, the internal male die and the external male die are respectively driven to form the step-shaped inner hole and the outer flange part, the process is simple, the material utilization ratio is high, and the production cost is low.
RESEARCH GAP: Multinetwork integration of nRF, XBee, IoT, and AI-driven predictive analytics for real-time control and feedback in hydraulic extrusion systems is the novelty of the innovation.
CN103551410B: The invention relates to an extrusion moulding method for shaft parts with flanges, and a special extrusion mould. The adopted extrusion moulding method comprises the following steps: 1, placing a blank material in a female die, wherein the extrusion moulding mould comprises an external male die with a center hole extending along the axial direction, an internal male die is arranged in the center hole of the external male die in a penetrating manner, the hole wall of the center hole of the external male die is matched with the peripheral wall of the internal male die in a guiding sliding manner, a corresponding power output shaft of a press drives the external male die to extrude the blank material and downwards moves to reach the thickness of the flange of the required part; 2, ejecting the external male die to be kept stable on the blank material, wherein the press and a power output shaft which is in transmission connection with the corresponding internal male die drive the internal male die to downwards extrude the blank material, and the required part is formed through extrusion; and 3, completing the extrusion, wherein the press drives the external male die and the internal male die to return to eject the formed part. According to the extrusion moulding method, by adopting sequential extrusion moulding, the one-time extrusion area is small, the extrusion force required by one-time extrusion is small, the input of equipment is reduced by adopting the equipment with small tonnage, and the production cost is lowered.
RESEARCH GAP: Multinetwork integration of nRF, XBee, IoT, and AI-driven predictive analytics for real-time control and feedback in hydraulic extrusion systems is the novelty of the innovation.
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.
It is possible to say that this unit performs artificial intelligence work because it acts as an integral member of a multinetwork control subsystem, industrial machine operation management, data collection, and analysis. The architecture of the system is divided into three interconnected nodes, which are used for different purposes and are connected wirelessly. First node is the one that works as the control unit of the machine, directly communicating with it. It supervises the critical parameters of the machine in operation such as current, temperature, etc. and operates actuators to perform the machine operations. This node regularly and automatically obtains vital information and sends it wirelessly to the second node while guaranteeing that the machine is controlled from the node. The second node is known as an independent communication node. It enhances the communication range and reliability of the system by serving as a link between the primary control node and the cloud network. Also, it has a visual indicator system for quick information about the system to clients. This node guarantees that all of the data that has been collected will be securely streamed to the cloud for additional analysis and evaluation.
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.
It is possible to say that this unit performs artificial intelligence work because it acts as an integral member of a multinetwork control subsystem, industrial machine operation management, data collection, and analysis. The architecture of the system is divided into three interconnected nodes, which are used for different purposes and are connected wirelessly. First node is the one that works as the control unit of the machine, directly communicating with it. It supervises the critical parameters of the machine in operation such as current, temperature, etc. and operates actuators to perform the machine operations. This node regularly and automatically obtains vital information and sends it wirelessly to the second node while guaranteeing that the machine is controlled from the node. The second node is known as an independent communication node. It enhances the communication range and reliability of the system by serving as a link between the primary control node and the cloud network. Also, it has a visual indicator system for quick information about the system to clients. This node guarantees that all of the data that has been collected will be securely streamed to the cloud for additional analysis and evaluation.
The third node is capable of machine learning and data visualization tasks. It communicates with the cloud platform to which all gathered information is sent after applying analytic and artificial intelligence mechanisms. This allows for machine performance predictive analytics for possible machine faults to be diagnosed ahead of time. The analyzed information is stored in a computer and made visible to operators and other authorized personnel through a web interface and a local display. Users of the system are provided with insights, directives, and control during operations, all of which result in increased efficiency and shorter downtimes. Additionally, the novel solution, through its distributed architecture and effective wireless communication, provides control and feedback in real-time facts of complex industrial tasks.
BEST METHOD OF WORKING
The MNCTN Node that consists of a Raspberry Pi, an nRF Module, an actuator, a GPRS modem, current and temperature sensors, and a power supply, enables accurate mechanical activities and allows the gathering of real-time data which is sent to the cloud for further analytical and operational improvement of industrial hydraulic extrusion systems.
The MNCRN Node comprising a Raspberry Pi, nRF Module, XBee Module, an LED indicators, and a power unit acts as a reliable communication device with confirmed wireless connection and stable data transfer between the machine control unit and the cloud platform.
The MNCRcN Node, which has an Arduino Tiny M.L. Kit, Xbee Module, GPRS module, HMI display, and a power supply allows the onboard data representation and online data predictive analytics to be done so as to achieve better decision making and prompt maintenance for the system.
The nRF Module, present in the MNCTN and MNCRN Nodes, provides robust, low latency wireless connections for transport and control of all systems so as to ensure synchronization between control and monitored units.
With long-range sockets, the XBee Module within the MNCRN and MNCRcN Nodes ensures that there are no gaps in connectivity between distributed nodes in the field. It facilitates wireless data transmission over long distances swiftly, thus making sure efficient communication is seamless in industrial areas.
Apart from the antenna, the MNCRcN Node also contains a number of components designed to ensure real-time data for the device, and such alerts are simple for operators to view so the situation can be addressed in an organized manner.
The MNCTN and MNCRcN Nodes have been mounted with GPRS Modems which allow continuous cloud data delivery, even from remote sites, allowing the system to be continuously monitored and improve its reliability and efficiency.
ADVANTAGES OF THE INVENTION
1. The system of integrated sensors and actuators, control and monitoring of machine activities are more effective. For instance, the accuracy of real-time data transmission and control of actuators to change machine states for the course of the work is achieved via MNCTN Node's Raspberry Pi.
2. Robust wireless communication between nodes is achieved through the nRF and XBee modules, thereby guaranteeing that data is relayed from one area of the system to another regardless of the application's complexity and industrial noise.
3. The MNCRcN Node's Arduino tiny machine learning kit, allows these predictive insights to be generated at the cloud level through deep learning algorithms, aiding in early fault detection and minimizing the chances of unexpected downtime.
4. While the HMI display for MNCRcN Node and the web dashboard are designed for operators and authorized people's use, they are able to view real time data and valuable information, which will facilitate effective insight and timely decisions.
5. The modular design using hardware such as Raspberry Pi, Arduino, and GPRS Modems gives the system the flexibility to grow and customize for different industrial setups allowing it to be quite versatile and ready for the future.
6. With the integration of sensors within the system, monitoring of current and temperature attributes further assists in the prevention of damages which maximizes maintenance and repairs while prolonging the usage of the equipment.
, Claims:1. A multinetwork control and feedback system with nrf, xbee, iot, and predictive system for industrial die making hydraulic extrusion comprises MNCTN Node that consists of a Raspberry Pi, an nRF Module, an actuator, a GPRS modem, current and temperature sensors, and a power supply, enables accurate mechanical activities and allows the gathering of real-time data which is sent to the cloud for further analytical and operational improvement of industrial hydraulic extrusion systems.
2. The system as claimed in claim 1, wherein the MNCRN Node comprising a Raspberry Pi, nRF Module, XBee Module, an LED indicators, and a power unit acts as a reliable communication device with confirmed wireless connection and stable data transfer between the machine control unit and the cloud platform.
3. The system as claimed in claim 1, wherein the MNCRcN Node, which has an Arduino Tiny M.L. Kit, Xbee Module, GPRS module, HMI display, and a power supply allows the onboard data representation and online data predictive analytics to be done so as to achieve better decision making and prompt maintenance for the system.
4. The system as claimed in claim 1, wherein the nRF Module, present in the MNCTN and MNCRN Nodes, provides robust, low latency wireless connections for transport and control of all systems so as to ensure synchronization between control and monitored units.
5. The system as claimed in claim 1, wherein with long-range sockets, the XBee Module within the MNCRN and MNCRcN Nodes ensures that there are no gaps in connectivity between distributed nodes in the field, it facilitates wireless data transmission over long distances swiftly, thus making sure efficient communication is seamless in industrial areas.
6. The system as claimed in claim 1, wherein apart from the antenna, the MNCRcN Node also contains a number of components designed to ensure real-time data for the device, and such alerts are simple for operators to view so the situation can be addressed in an organized manner.
7. The system as claimed in claim 1, wherein the MNCTN and MNCRcN Nodes have been mounted with GPRS Modems which allow continuous cloud data delivery, even from remote sites, allowing the system to be continuously monitored and improve its reliability and efficiency.

Documents

NameDate
202411090832-COMPLETE SPECIFICATION [22-11-2024(online)].pdf22/11/2024
202411090832-DECLARATION OF INVENTORSHIP (FORM 5) [22-11-2024(online)].pdf22/11/2024
202411090832-DRAWINGS [22-11-2024(online)].pdf22/11/2024
202411090832-EDUCATIONAL INSTITUTION(S) [22-11-2024(online)].pdf22/11/2024
202411090832-EVIDENCE FOR REGISTRATION UNDER SSI [22-11-2024(online)].pdf22/11/2024
202411090832-EVIDENCE FOR REGISTRATION UNDER SSI(FORM-28) [22-11-2024(online)].pdf22/11/2024
202411090832-FORM 1 [22-11-2024(online)].pdf22/11/2024
202411090832-FORM FOR SMALL ENTITY(FORM-28) [22-11-2024(online)].pdf22/11/2024
202411090832-FORM-9 [22-11-2024(online)].pdf22/11/2024
202411090832-POWER OF AUTHORITY [22-11-2024(online)].pdf22/11/2024
202411090832-REQUEST FOR EARLY PUBLICATION(FORM-9) [22-11-2024(online)].pdf22/11/2024

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