HYBRID EDGE DEVICE WITH NRF AND LORA RF NETWORK FOR BEHAVIOR ANALYSIS AND AI-ENABLED HEALTH RECOMMENDATIONS IN STEEL MANUFACTURING FIXED GANTRY MILLING MACHINES

Abstract

A hybrid edge device with nrf and lora rf network for behavior analysis and ai-enabled health recommendations in steel manufacturing fixed gantry milling machines comprises Edgenrf Mote mounted with a Jetson Nano Board, LoRa Module, GPS Module, Accelerometer, Current sensor and power supply allows complex real-time monitoring of machine function, location, and power to be executed with optimal data capture and effective transmission to the Industrial cloud for further analysis the Datanrflra Mote, combines a Jetson Nanoboard, nRF Module, LoRa Module, Capacitive Touch Display, and Power Supply, enhanced functionality by allowing data visualization locally at the mote and communication to the wider area enabling killers to see and be able to act on critical insight and recommendations often needed for managing equipment actively.

Specification

Description:FIELD OF THE INVENTION
This invention relates to hybrid edge device with nrf and lora rf network for behavior analysis and ai-enabled health recommendations in steel manufacturing fixed gantry milling machines.
BACKGROUND OF THE INVENTION
This innovation offers a hybrid edge device configuration containing advanced communication technologies and intelligent monitoring, capable of analyzing machine behavior and providing AI-enabled health recommendations for various manufacturing processes. The system includes separate modules that have sensors for environmental and operational data, real-time processing units, and communication modules for effective data transfer. It employs a strong network, and the devices push the data collected to a bespoke cloud for processing along clouds in order to afford machine-learning analytics for the prediction processes. The outcomes may be viewed by the operators and other authorized personnel through a web interface complied with a touch display, enabling fast and efficient management of all manufacturing equipment.
The present invention focuses on the self-monitoring, maintenance and performance improvement of the industrial equipment, mainly the fixed gantry milling machines concerning steel manufacturing. Typical approaches do not provide the required functionalities of real-time data acquisition and foresight, as well as recommendations for actions which often results to breakdowns, inefficient work processes and high cost of maintenance. The lack of integrated monitoring systems prevents the operators from effective early alarm systems used for mechanical wear, misalignment or inefficient processes. This project provides a hybrid edge device system that allows for real time monitoring, behavioral functions, and health monitoring systems using artificial intelligence, and improves reliability of the industrial equipment, reduces the downtime, and optimizes operation efficiency in industrial environments.
CN209379971U: The utility model discloses a kind of for processing the numerical control gantry Finish Milling Machine of straight-bar machines pedestal, comprising: lathe bed, table mechanism, two mainshaft mechanisms and control device, table mechanism are slidably arranged on lathe bed, and straight-bar machines pedestal to be processed is driven to move along lathe bed;Two mainshaft mechanisms are symmetricly set on lathe bed two sides, mainshaft mechanism includes heel post, oblique column, main shaft, spindle box, spindle motor, heel post is connected to lathe bed side, oblique column is slidably arranged on heel post, spindle box is slidably arranged on the installation inclined-plane of oblique column, the feed motion of main shaft may be implemented by horizontal and inclination both direction adjusting, after main spindle's are fixed, spindle motor drives main shaft to rotate in spindle box;Control device, control device are mounted in the control cabinet of the lathe bed.The utility model can carry out Automatic Control, high-efficient, precision is high, at low cost, and may be implemented to carry out simultaneous processing to straight-bar machines pedestal different angle, different sides.
RESEARCH GAP: The novelty of this system lies in its hybrid edge device network integrating nRF and LoRa RF technologies for AI-driven behavior analysis and health recommendations in steel manufacturing fixed gantry milling machines.
CN113927318A: The invention provides a gantry type double-rotary-table numerically-controlled milling machine which comprises a machine body, wherein the lower end of the machine body is fixedly connected with a plurality of supporting feet, and the left side and the right side of the upper end of the machine body are respectively and fixedly connected with a first fixing frame and a second fixing frame. Through the axial slewing mechanism who sets up can drive the cutting motor respectively through first brake motor and second brake motor and do the Z axle, the rotation of X axle and Y axle direction, and treat the part clamping of processing back on the clamping board, can adjust the Z axle angle of spare part through the step motor who sets up, thereby can make the cutting motor can accomplish the cutting of a plurality of angles, thereby accomplish the curved surface processing of multidimension degree, and this device all is provided with the cutting motor in the both sides of upper and lower displacement mechanism, thereby once can carry the cutter, can reduce the number of times of tool changing, and can load two the same cutters simultaneously, man-hour, alternate processing, the solution cutter is man-hour for a long time, the high temperature, the great problem of wearing and tearing.
RESEARCH GAP: The novelty of this system lies in its hybrid edge device network integrating nRF and LoRa RF technologies for AI-driven behavior analysis and health recommendations in steel manufacturing fixed gantry milling machines.
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.
The innovation encompasses a large network of hybrid edge devices that are meant to acquire, process, and send important machine data for streaming analytics. Every module which constitutes the system deploys specific sensors and processing units that provide the capabilities to measure parameters such as machine operations and vibrations as well as power and position of the specified machine in space. These parameters are acquired and computed within the modules in order to avoid the unnecessary delays and bottlenecks in the process of data manipulation. Then, the data were wirelessly transmitted using the abovementioned variety of communication protocols with the aim of achieving industrial grade connectivity and reliability. The gathered information is sent to a dedicated cloud server over an encrypted WiFi connection. The cloud server unifies the processes by acting as the data storage and processing base using the data analysis algorithms. Such algorithms search through the data generated by the monitored equipment and its parameters and determine when certain thresholds are met or exceeded, and provide recommendations on how to maintain the equipment. Generated knowledge is utilized for the purpose of preventive maintenance, improvement of operational processes and general performance of the monitored equipment.
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.
The innovation encompasses a large network of hybrid edge devices that are meant to acquire, process, and send important machine data for streaming analytics. Every module which constitutes the system deploys specific sensors and processing units that provide the capabilities to measure parameters such as machine operations and vibrations as well as power and position of the specified machine in space. These parameters are acquired and computed within the modules in order to avoid the unnecessary delays and bottlenecks in the process of data manipulation. Then, the data were wirelessly transmitted using the abovementioned variety of communication protocols with the aim of achieving industrial grade connectivity and reliability. The gathered information is sent to a dedicated cloud server over an encrypted WiFi connection. The cloud server unifies the processes by acting as the data storage and processing base using the data analysis algorithms. Such algorithms search through the data generated by the monitored equipment and its parameters and determine when certain thresholds are met or exceeded, and provide recommendations on how to maintain the equipment. Generated knowledge is utilized for the purpose of preventive maintenance, improvement of operational processes and general performance of the monitored equipment.
There are two basic interfaces for the use of the data and insights knowledge where authorized personnel are permitted, No operators are authorized and those are a web- based dashboard and a capacitive collar interface screen designed as part of the system. As to the web dashboard, this gives an overview picture of the machine health, parameters of operation and forecast on productivity which helps the users make the necessary decisions live. As to the collar screen, it is a stand-alone screen which allows the user to modify basic indicators and receive notifications which saves time for the user and makes the interface more convenient.
BEST METHOD OF WORKING
The Edgenrf Mote mounted with a Jetson Nano Board, LoRa Module, GPS Module, Accelerometer, Current sensor and power supply allows complex real-time monitoring of machine function, location, and power to be executed with optimal data capture and effective transmission to the Industrial cloud for further analysis.
The Datanrflra Mote, combines a Jetson Nanoboard, nRF Module, LoRa Module, Capacitive Touch Display, and Power Supply, enhanced functionality by allowing data visualization locally at the mote and communication to the wider area enabling killers to see and be able to act on critical insight and recommendations often needed for managing equipment actively.
The LraIoT Mote equipped with a Jetson Nano board, an nRF module, Buzzer and a power supply, provide responsive wireless communication and instant onsite alerts for timely and appropriate reaction to instances of machine abnormalities thereby improving safety within manufacturing environments.
LoRa module, which is common for Edgenrf Mote and Datanrflra Mote, ensures efficient data transfer over long distances even in industrial settings and this ease of connectivity enhances real time observation as well as the over analysis of data.
Through the use of the Mote Datanrflra, in the opinion of the on-site operators, it is possible to obtain health indicators of the machine and prognosis, thus improving situational awareness and decision-making processes.
In all three modules, the Nano board Jetson is the one that enables edge computing that involves the processing of critical data at the device level to reduce latencies and improve the accuracy of monitoring industrial assets in real-time.
The nRF Module embedded in both the Datanrflra Mote and LraIoT Mote, provide effective short-range wireless connections allowing for integration of the modules and improved data transmission to the cloud server.
On the other hand, the GPS Module provided within the Edgenrf Mote allows accurate geo-location tracking of the equipment making it possible to carry out spatial analysis and boost the general performance of the system in constantly changing industrial settings.
ADVANTAGES OF THE INVENTION
1. Substantial understanding of equipment performance is attained as it is possible to monitor machine behavior, location, and position in relation to other machines and equipment in real-time owing to the use of accelerometers, GPS modules, and current sensors.
2. Each module uses Jetson Nano boards, which grant sufficient border processing, which cuts down on latency and fully enables real-time analytics without cloud dependence.
3. The combination of these two communication modules also adds to the data transmission efficiency and network scalability since range is long and reliable communication is maintained even in harsh industrial environments.
4. Cloud-based data allows machine learning algorithms to track patterns and forecast failures, allowing machine downtime to be reduced, as well as maintenance necessities.
5. The Datanrflra Mote's capacitive touch display allows operators to interact with the device directly, while the web dashboard allows users to view the device from a distance thereby making the data visible and easy to operate on.
6. Any company that wants to utilize these systems would appreciate the modularity of the system as it would be able to customize it and scale it accordingly to suit different industrial applications.
, Claims:1. A hybrid edge device with nrf and lora rf network for behavior analysis and ai-enabled health recommendations in steel manufacturing fixed gantry milling machines comprises Edgenrf Mote mounted with a Jetson Nano Board, LoRa Module, GPS Module, Accelerometer, Current sensor and power supply allows complex real-time monitoring of machine function, location, and power to be executed with optimal data capture and effective transmission to the Industrial cloud for further analysis.
2. The device as claimed in claim 1, wherein the Datanrflra Mote, combines a Jetson Nanoboard, nRF Module, LoRa Module, Capacitive Touch Display, and Power Supply, enhanced functionality by allowing data visualization locally at the mote and communication to the wider area enabling killers to see and be able to act on critical insight and recommendations often needed for managing equipment actively.
3. The device as claimed in claim 1, wherein the LraIoT Mote equipped with a Jetson Nano board, an nRF module, Buzzer and a power supply, provide responsive wireless communication and instant onsite alerts for timely and appropriate reaction to instances of machine abnormalities thereby improving safety within manufacturing environments.
4. The device as claimed in claim 1, wherein LoRa module, which is common for Edgenrf Mote and Datanrflra Mote, ensures efficient data transfer over long distances even in industrial settings and this ease of connectivity enhances real time observation as well as the over analysis of data.
5. The device as claimed in claim 1, wherein through the use of the Mote Datanrflra, in the opinion of the on-site operators, it is possible to obtain health indicators of the machine and prognosis, thus improving situational awareness and decision-making processes.
6. The device as claimed in claim 1, wherein all three modules, the Nano board Jetson is the one that enables edge computing that involves the processing of critical data at the device level to reduce latencies and improve the accuracy of monitoring industrial assets in real-time.
7. The device as claimed in claim 1, wherein the nRF Module embedded in both the Datanrflra Mote and LraIoT Mote, provide effective short-range wireless connections allowing for integration of the modules and improved data transmission to the cloud server.
8. The device as claimed in claim 1, wherein on the other hand, the GPS Module provided within the Edgenrf Mote allows accurate geo-location tracking of the equipment making it possible to carry out spatial analysis and boost the general performance of the system in constantly changing industrial settings.

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