AI-ENABLED RECOMMENDATION SYSTEM WITH MACHINE LEARNING AND LONG-RANGE RF COMMUNICATION FOR INDUSTRIAL CHEMICAL VOLUMETRIC FILLING MACHINES

Abstract

An ai-enabled recommendation system with machine learning and long-range rf communication for industrial chemical volumetric filling machines comprises LRAITx Node (100) provides monitoring of the current demand and operational parameters of the machine in real time and even brings the machine to rest in critical cases on its own, for the increased safety and reliability in industry applications, Tte following are elements included in this node: Arduino - Tiny ML Kit (101), XBee WPAN Module (102), Accelerometer (104), Current Sensor (103), Actuator (106), and Power Supply (105) the LRAIRx Node a Jetson Nano Board, XBee WPAN Module, GPRS Modem, Display, and Power Supply helps transfer data towards a user’s cloud for Machine Learning developed analytics and AI based suggestion while the visual aspect in respect to the operators appears to be inside the physical entity.

Specification

Description:FIELD OF THE INVENTION
This invention relates to ai-enabled recommendation system with machine learning and long-range rf communication for industrial chemical volumetric filling machines.
BACKGROUND OF THE INVENTION
The development of this AI-based recommendation system has as its uniqueness the industrial chemical volumetric filling machines that are able to monitor the current performance and state of the machine in real time. The ability to turn the machine off automatically in cases of irregulaties is one of the integrated features of the system along with data acquisition modules, anomaly recognition, and automatic safety shut down. The data that was gathered is sent to a specially designed cloud server that is incorporated with machine learning models that assist in predictive analytics and recommendations to promote action. Such data can be viewed by the operators and authorized persons through web panel and local display and therefore it helps in maintenance, safety, and efficiency.
The current work is directed to the important issue of enhancement of reliability and efficiency of the chemical volumetric filling machines which face the problems of the non linear current consumption, breakdowns, low efficiency of the operation. From the on line monitoring systems there is a need for improvement of both the real time analysis and prediction of problems in order to minimize losses caused by downtime, damage to equipment and poor quality of manufacture. This project proposes to combine the three in an integrated model thus solving the time lags in operational performance and reducing operational maintenance and promoting security and optimum utilization of the machines.
CN113404325B: The invention provides an intelligent grouting joint filling machine for single-port wall cracks and a construction method, comprising a bottom plate, wherein lifting mechanisms are symmetrically fixed on the upper surface of the bottom plate, a connecting beam is fixed between the two lifting mechanisms, the middle part of the connecting beam is connected with a horizontal moving device in a sliding manner, a grouting mechanism is fixed on the top of the horizontal moving device, a screeding mechanism is fixed on the top of the grouting mechanism, and self-locking universal wheels are symmetrically fixed on the lower surface of the bottom plate. According to the invention, the single grouting mechanism is arranged, the grouting mechanism is driven to move through the lifting mechanism and the horizontal moving mechanism, grouting is carried out on the cracks, the use cost is low, the grouting mechanism is flexible to use, the grouting mechanism is suitable for most grouting occasions, the rotating rod is driven to rotate through the fourth servo motor, the second T-shaped block is driven to slide through the first shifting column, further reciprocating sliding of the screeding head is realized, the screeding head screeds the slurry on the cracks, and the attractiveness is improved.
RESEARCH GAP: AI-driven monitoring and recommendation system with long-range RF communication for autonomous safety and predictive maintenance of industrial volumetric filling machines is the novelty of the system.
ES2974526T3: A method for filling a gas canister with pressurized or liquefied gas from a canister filling machine may comprise inserting a valve of a gas canister into an interior space of an adapter, through an opening of the adapter having a shape to allow insertion of the valve. The adapter allowing a fluidic connection of the valve of the gas container to a filling port of the filling machine, and comprising at least one channel that is configured, when the valve is inserted into the opening, to conduct pressurized or liquefied gas from the filling port to the valve, the valve comprising: a container port facing the interior of the gas container and at least one exterior port opening laterally to a longitudinal axis of the valve to facilitate entry of the gas into and exit of the gas from the container when the valve is in an open position and to prevent entry or exit when the valve is in a closed position; and filling the gas canister with the pressurized or liquefied gas while maintaining the valve in the open position. (Automatic translation with Google Translate, no legal value).
RESEARCH GAP: AI-driven monitoring and recommendation system with long-range RF communication for autonomous safety and predictive maintenance of industrial volumetric filling 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.
The innovation is working as an interconnected system that tracks, investigates, and manages the general technical condition of volumetric filling machines used in chemical industries. The key work module installed close to the machine captures current and vibration signals in real-time. This information is processed at the site in order to monitor certain abnormalities or variations from the standard operating features. If such an event occurs, the device automatically activates an emergency stopping mechanism so as to avoid any further abuse of the machines and any operational risks. The data is first wirelessly transmitted through a second module known as the communication bridge which then passes this information to a custom cloud server. This server integrates machine learning capabilities that review the received data for patterns, outliers, and possible predictive features. These predictive features are later used to create suggestions that involve maintenance, change of operations, or other measures as required.
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 is working as an interconnected system that tracks, investigates, and manages the general technical condition of volumetric filling machines used in chemical industries. The key work module installed close to the machine captures current and vibration signals in real-time. This information is processed at the site in order to monitor certain abnormalities or variations from the standard operating features. If such an event occurs, the device automatically activates an emergency stopping mechanism so as to avoid any further abuse of the machines and any operational risks. The data is first wirelessly transmitted through a second module known as the communication bridge which then passes this information to a custom cloud server. This server integrates machine learning capabilities that review the received data for patterns, outliers, and possible predictive features. These predictive features are later used to create suggestions that involve maintenance, change of operations, or other measures as required.
The system allows two types of users such as the operators and the authorized person to view the data. The second feature is available via a web dashboard that connects to a cloud server enabling off-site access. Using such interfaces, users are able to observe the functioning of the machine in real time, check the machine's operating history and perform the actions suggested by the predictive insights. Integrating real time data collection, data local analysis, and remote machine learning capabilities, this system promotes maintenance activities, decreases unavailability of machines, improves reliability of machines and therefore can be used in industrial automation and to optimize the operating capabilities of the enterprise.
BEST METHOD OF WORKING
The LRAITx Node provides monitoring of the current demand and operational parameters of the machine in real time and even brings the machine to rest in critical cases on its own, for the increased safety and reliability in industry applications. The following are elements included in this node: Arduino - Tiny ML Kit, XBee WPAN Module, Accelerometer, Current Sensor, Actuator, and Power Supply.
The LRAIRx Node a Jetson Nano Board, XBee WPAN Module, GPRS Modem, Display, and Power Supply helps transfer data towards a user's cloud for Machine Learning developed analytics and AI based suggestion while the visual aspect in respect to the operators appears to be inside the physical entity
The LRAITX Node and LRAIRX Node both equipped with the XBee WPAN Module in order to achieve robust and reliable wireless communication for data transfer and as a result gives the possibility of monitoring and predictive analysis all over the system without interruptions.
The actuator included in the LRAITx Node allows automatically stop the machine while an upset condition is present, saves the equipment, and reduces idle time since the machine does not need to be physically shut off.
In the LRAIRx Node, synched with a GPRS Modem, which is another dependable avenue for connecting to the cloud-server allowing for improved analytics and control/review of the processes done within the server.
The Display, which is integrated onboard the LRAIRx Node, provides a simple interface for real time data visualization allowing the operators to gain direct insights into machine status and behavior.
ADVANTAGES OF THE INVENTION
1. To assure that malfunctions are detected at the earliest possible moment, the Accelerometer and Current Sensor present in the LRAITx Node allow for the performance of machines to be performed in real time without fail.
2. Thanks to the incorporation of an Actuator within the LRAITx Node, the machine can be automatically stopped if anomalies are identified to mitigate damage and promote safe operations.
3. The Jetson Nano Board within the LRAIRx Node performs data functions intended for communication purposes and provides information on trends to the operators for improved decision making.
4. The XBee WPAN Module which was previously mentioned is found in both nodes and extends reliable communication over great distances providing uninterrupted data flow between the modules and the cloud server.
5. Thanks to the custom cloud server, machine learning capabilities embedded in the sensors can analyze the data and accurately determine when maintenance is required while also providing AI powered suggestions to minimize unplanned downtimes.
6. Real-time information, alerts and predictive information are available for easy retrieval through the Display of LRAIRx Node and the web dashboard, making surveillance simple and seamless.
7. The GPRS Modem embedded in the LRAIRx Node provides a reasonable alternative for transferring data to the user's specific cloud server for data analysis and out of the box usage scenarios.
, Claims:1. An ai-enabled recommendation system with machine learning and long-range rf communication for industrial chemical volumetric filling machines comprises LRAITx Node (100) provides monitoring of the current demand and operational parameters of the machine in real time and even brings the machine to rest in critical cases on its own, for the increased safety and reliability in industry applications, Tte following are elements included in this node: Arduino - Tiny ML Kit (101), XBee WPAN Module (102), Accelerometer (104), Current Sensor (103), Actuator (106), and Power Supply (105).
2. The system as claimed in claim 1, wherein the LRAIRx Node a Jetson Nano Board, XBee WPAN Module, GPRS Modem, Display, and Power Supply helps transfer data towards a user's cloud for Machine Learning developed analytics and AI based suggestion while the visual aspect in respect to the operators appears to be inside the physical entity.
3. The system as claimed in claim 1, wherein the LRAITX Node and LRAIRX Node both equipped with the XBee WPAN Module in order to achieve robust and reliable wireless communication for data transfer and as a result gives the possibility of monitoring and predictive analysis all over the system without interruptions.
4. The system as claimed in claim 1, wherein the actuator included in the LRAITx Node allows automatically stop the machine while an upset condition is present, saves the equipment, and reduces idle time since the machine does not need to be physically shut off.
5. The system as claimed in claim 1, wherein the LRAIRx Node, synched with a GPRS Modem, which is another dependable avenue for connecting to the cloud-server allowing for improved analytics and control/review of the processes done within the server.
6. The system as claimed in claim 1, wherein the Display, which is integrated onboard the LRAIRx Node, provides a simple interface for real time data visualization allowing the operators to gain direct insights into machine status and behavior.

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