AI BASED PREDICTIVE AND RECOMMENDATION SOLUTION FOR CONDITION MONITORING OF PRESSURE FILLING MACHINE IN THE CARBONATED BEVERAGE PACKAGING INDUSTRY

Abstract

AI based predictive and recommendation system for condition monitoring of pressure filling machine in the carbonated beverage packaging industry comprises Raspberry Pi processor (22), GSM modem (11), neural stick (12), liquid pressure sensor (18), temperature sensor (17), accelerometer (16), RTC module (13), SD card module (14), and TFT display (21) are all included in the PRSCMTNode (10), various sensors, a potent processor, and communication modules are seamlessly integrated with the help of a speaker, led indicator, and power supply to facilitate real-time data collection, AI-driven analysis, and predictive maintenance for improved condition monitoring of pressure filling machines in the carbonated beverage packaging sector. The Raspberry Pi processor, which is a computational powerhouse in this innovation, is used to analyze data from multiple sensors in real-time to provide predictions and insights for the condition monitoring of pressure filling machines in the carbonated beverage packaging industry. It does this by utilizing its AI processing capabilities with the Neural Stick.

Specification

Description:FIELD OF THE INVENTION
This invention relates to ai based predictive and recommendation solution for condition monitoring of pressure filling machine in the carbonated beverage packaging industry.
BACKGROUND OF THE INVENTION
This cutting-edge invention, which introduces a thorough condition monitoring system specifically made for pressure filling machines, is important in completely changing the carbonated beverage packaging industry. A strong processing unit that uses AI algorithms is used to handle and analyze operational data that is collected in real-time by means of the smooth integration of sensors. The system's capacity to foresee possible problems and offer practical recommendations helps to increase operational effectiveness and decrease downtime. Access to an intuitive web dashboard providing useful information about the machine's health and performance is provided to operators.
The industry that packages carbonated beverages has trouble keeping an eye on and maintaining pressure filling equipment. Existing systems often do not provide comprehensive, real-time insights on the operational health of these devices, which can lead to unplanned downtime and potential production delays. Operators are unable to proactively address problems before they become more serious due to the lack of predictive capabilities and practical recommendations.
US7270158B2: An apparatus is provided for needle filling and thermally resealing containers having stoppers that are needle penetrable for filling the containers with a substance, and are thermally resealable for thermally sealing a needle hole in the stopper upon withdrawal of a needle therefrom. A container support of the apparatus supports at least one container having a resealable stopper in a substantially fixed position during needle filling and thermally resealing a needle hole in the stopper upon withdrawal of a needle therefrom. A manifold is drivingly mounted over the container support and comprises (1) a needle cartridge including a needle for penetrating the resealable stopper and introducing a substance through the needle and into the container, a needle mount for mounting the needle cartridge on the manifold, and a needle cover releasably coupled to the needle mount for covering the needle during transportation, installation and/or removal of the needle cartridge from the manifold, and that is removable from the needle cartridge upon mounting the needle cartridge to the manifold. The manifold further includes a thermal source for heating a needle penetrated region of the stopper and, in turn, sealing a needle hole in the stopper.
RESEARCH GAP: AI based predictive maintenance and health monitoring for Pressure Filling Machine in the Carbonated Beverage Packaging Industry is the novelty of the system.
US10144540B2: Apparatus for filling devices that are penetrable for filling the devices with a substance, and resealable for sealing the resulting hole. A device support supports at least one such device in a substantially fixed position relative to the support during filling and/or resealing. A manifold drivingly mounted over the device support can include a cartridge including a filling needle for penetrating a resealable stopper and introducing a substance therethrough into the device, a mount for mounting the cartridge on the manifold, and a removable cover releasably coupled to the mount for covering the filling needle during transportation, installation and/or removal of the cartridge from the manifold. The manifold can include a thermal source for heating a penetrated region of the stopper and, sealing the hole.
RESEARCH GAP: AI based predictive maintenance and health monitoring for Pressure Filling Machine in the Carbonated Beverage Packaging Industry 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 innovative system's brains, the PRSCMTNode, are outfitted with a variety of sensors, including an accelerometer, temperature sensor, liquid pressure sensor, and RTC module. In the carbonated beverage packaging sector, these sensors continuously collect data from the pressure filling machine, covering vital factors including temperature, vibrations of the machine, and pressure. This extensive dataset provides a detailed picture of the machine's current state of operation. Serving as the central processing unit, the Raspberry Pi CPU is enhanced by the Neural Stick to enable effective real-time analysis of the sensor data that has been gathered. Using established machine learning methods designed to forecast the pressure filling machine's performance and health, this processing unit acts as the PRSCMTNode's central decision-making hub.
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 innovative system's brains, the PRSCMTNode, are outfitted with a variety of sensors, including an accelerometer, temperature sensor, liquid pressure sensor, and RTC module. In the carbonated beverage packaging sector, these sensors continuously collect data from the pressure filling machine, covering vital factors including temperature, vibrations of the machine, and pressure. This extensive dataset provides a detailed picture of the machine's current state of operation. Serving as the central processing unit, the Raspberry Pi CPU is enhanced by the Neural Stick to enable effective real-time analysis of the sensor data that has been gathered. Using established machine learning methods designed to forecast the pressure filling machine's performance and health, this processing unit acts as the PRSCMTNode's central decision-making hub.
A dedicated cloud server built for Internet of Things applications receives processed data transmitted via a GSM modem, which facilitates communication. The incoming data is then analyzed by this cloud server using AI algorithms, which produce recommendations and forecast insights regarding the pressure filling machine's condition. The complex user interface includes a TFT display on the device that shows recommendations, AI-driven forecasts, and real-time health information. In addition, a personalized web dashboard that can be accessed via the cloud provides operators with a thorough overview that includes historical data, specific insights into the machine's performance, and practical suggestions for maintenance and optimization. Operators may stay informed and take proactive action based on the AI-driven insights supplied by the system, which guarantees they receive email notifications in a timely manner.
BEST METHOD OF WORKING
The Raspberry Pi processor, GSM modem, neural stick, liquid pressure sensor, temperature sensor, accelerometer, RTC module, SD card module, and TFT display are all included in the PRSCMTNode. Various sensors, a potent processor, and communication modules are seamlessly integrated with the help of a speaker, led indicator, and power supply to facilitate real-time data collection, AI-driven analysis, and predictive maintenance for improved condition monitoring of pressure filling machines in the carbonated beverage packaging sector.
The Raspberry Pi processor, which is a computational powerhouse in this innovation, is used to analyze data from multiple sensors in real-time to provide predictions and insights for the condition monitoring of pressure filling machines in the carbonated beverage packaging industry. It does this by utilizing its AI processing capabilities with the Neural Stick.
The PRSCMTNode's built-in GSM modem allows processed data to be transmitted from the device to a customized cloud server, enabling real-time monitoring and analysis of pressure filling machine conditions in the carbonated beverage packaging sector. This feature promotes seamless communication.
The PRSCMTNode's integrated Neural Stick boosts the Raspberry Pi Processor's computational power, enabling sophisticated AI-driven data analysis from a variety of sensors to deliver real-time insights and forecasts for the condition monitoring of pressure filling machines in the carbonated beverage packaging sector.
The temperature, accelerometer, and liquid pressure sensors-all of which are connected to the PRSCMTNode-combine to allow for thorough monitoring and analysis of pressure filling machines in the carbonated beverage packaging sector, enabling real-time insights and predictive maintenance.
The user-friendly interface of the pressure filling machine is made possible by the TFT Display, which is interfaced on PRSCMTNode. It presents real-time AI-driven predictions and recommendations, giving operators prompt access to vital information that enhances monitoring and decision-making in the carbonated beverage packaging sector.
The Speaker that is connected to the PRSCMTNode is used to communicate vital information to operators in charge of the condition monitoring of pressure filling machines in the carbonated beverage packaging sector in a timely manner, improve the user interface, and provide auditory alerts and notifications.
ADVANTAGES OF THE INVENTION
1. This cutting-edge system's PRSCMTNode serves as its focal point, seamlessly combining a number of sensors, a powerful processing unit, and communication modules to enable real-time data collection, AI-driven analysis, and predictive maintenance for improved pressure filling machine condition monitoring in the carbonated beverage packaging sector.
2. The GSM Modem ensures real-time monitoring and analysis of pressure filling machine conditions in the carbonated beverage packaging business by facilitating the transmission of processed data from the PRSCMTNode to a customized cloud server. This allows for seamless communication.
3. The PRSCMTNode receives vital operating data from the Liquid Pressure sensor, Temperature sensor, and Accelerometer together, which allows for thorough monitoring and analysis of pressure filling machines in the carbonated beverage packaging sector. Predictive maintenance and real-time insights are made possible by this.
4. The pressure filling machine's TFT Display serves as an intuitive user interface, displaying real-time AI-driven forecasts and suggestions. In the carbonated beverage packaging business, this guarantees operators instant access to vital information for better monitoring and decision-making.
5. The Speaker in this cutting-edge system works to deliver audio alerts and notifications, improving the user interface and guaranteeing prompt delivery of critical information to operators supervising pressure filling machine condition monitoring in the carbonated beverage packaging sector.
, Claims:1. Ai based predictive and recommendation system for condition monitoring of pressure filling machine in the carbonated beverage packaging industry comprises Raspberry Pi processor (22), GSM modem (11), neural stick (12), liquid pressure sensor (18), temperature sensor (17), accelerometer (16), RTC module (13), SD card module (14), and TFT display (21) are all included in the PRSCMTNode (10), various sensors, a potent processor, and communication modules are seamlessly integrated with the help of a speaker, LED indicator, and power supply to facilitate real-time data collection, AI-driven analysis, and predictive maintenance for improved condition monitoring of pressure filling machines in the carbonated beverage packaging sector.
2. The system as claimed in claim 1, wherein the Raspberry Pi processor, which is a computational powerhouse in this innovation, is used to analyze data from multiple sensors in real-time to provide predictions and insights for the condition monitoring of pressure filling machines in the carbonated beverage packaging industry, it does this by utilizing its AI processing capabilities with the Neural Stick.
3. The system as claimed in claim 1, wherein the PRSCMTNode's built-in GSM modem allows processed data to be transmitted from the device to a customized cloud server, enabling real-time monitoring and analysis of pressure filling machine conditions in the carbonated beverage packaging sector. This feature promotes seamless communication.
4. The system as claimed in claim 1, wherein the PRSCMTNode's integrated Neural Stick boosts the Raspberry Pi Processor's computational power, enabling sophisticated AI-driven data analysis from a variety of sensors to deliver real-time insights and forecasts for the condition monitoring of pressure filling machines in the carbonated beverage packaging sector.
5. The system as claimed in claim 1, wherein the temperature, accelerometer, and liquid pressure sensors all of which are connected to the PRSCMTNode combine to allow for thorough monitoring and analysis of pressure filling machines in the carbonated beverage packaging sector, enabling real-time insights and predictive maintenance.
6. The system as claimed in claim 1, wherein the user-friendly interface of the pressure filling machine is made possible by the TFT Display, which is interfaced on PRSCMTNode, it presents real-time AI-driven predictions and recommendations, giving operators prompt access to vital information that enhances monitoring and decision-making in the carbonated beverage packaging sector.
7. The system as claimed in claim 1, wherein the Speaker that is connected to the PRSCMTNode is used to communicate vital information to operators in charge of the condition monitoring of pressure filling machines in the carbonated beverage packaging sector in a timely manner, improve the user interface, and provide auditory alerts and notifications.

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