A SYSTEM FOR REAL-TIME CONDITION MONITORING OF A MANUAL SHRINK WRAPPER MACHINE

Abstract

The present invention provides an Online Condition Monitoring Device for Manual Shrink Wrapper Machines (OCMMS_WMCMote), which addresses these challenges by providing real-time monitoring and analysis capabilities. The system integrates an ESP32 board as the central processing unit, a GSM modem for wireless communication, and sensors, including a Piezo Vibration Sensor, Temperature Sensor, and Accelerometer, to capture dynamic data during machine operation. This data is transmitted to a cloud server for analysis by a machine learning algorithm, which identifies trends, anomalies, and potential issues.

Specification

Description:FIELD OF THE INVENTION
The present invention relates to a system for real-time monitoring and analysis of manual shrink wrapper machines in the traditional packaging industry.
BACKGROUND OF THE INVENTION
Traditional manual shrink wrapper machines lack real-time monitoring and predictive maintenance capabilities, leading to unplanned downtime and operational inefficiencies. Manual inspection methods are often laborious, error-prone, and fail to detect problems before they escalate.
Followings are some prior arts to the present invention:
US10491881B1 The said prior art provides a Methods, apparatus, systems, and computer-readable media are provided that relate to using one or more vision sensors to capture images of a loaded pallet in association with application of stretch wrap to the loaded pallet by an automated pallet wrapping machine. The images are used to generate an image-based identifier for the loaded pallet that is then used for pallet identification by mobile robots and/or other automated agents in a warehouse or other environment. In some implementations, the images are captured by the vision sensor when the pallet is in the wrapping area of the automated pallet wrapping machine and while the vision sensor and/or the pallet are rotating. In some implementations, the image-based identifier may be assigned to pallet attributes and/or a de-palletizing scheme of the loaded pallet.
CN107054750B The present invention provides one kind being capable of packing machine and packing method continuous, easy and that be accurately proceed the processing carried out in the state of packaging bag closure and the processing carried out in the state of packaging bag opening. Packing machine includes: linear type delivery section is used for straight line transport package, Rotary-type delivery section, is used to rotate transport package, Junction is used to join packaging bag between linear type delivery section and rotary-type delivery section;1st processing system is used to handle the packaging bag conveyed by linear type delivery section. And the 2nd processing system, it is used to handle the packaging bag conveyed by rotary-type delivery section. Linear type delivery section includes sliding type supporting part, mobile from the 1st transfer position to the 2nd transfer position with the state for hanging packaging bag. And fixed supporting part, to hang the packaging bag of the state support of packaging bag.2nd processing system has the shedding motion for making packaging bag be open.
None of the prior art indicate above either alone or in combination with one another disclose what the present invention has disclosed.



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.
The present invention provides an Online Condition Monitoring Device for Manual Shrink Wrapper Machines (OCMMS_WMCMote), which addresses these challenges by providing real-time monitoring and analysis capabilities. The system integrates an ESP32 board as the central processing unit, a GSM modem for wireless communication, and sensors, including a Piezo Vibration Sensor, Temperature Sensor, and Accelerometer, to capture dynamic data during machine operation. This data is transmitted to a cloud server for analysis by a machine learning algorithm, which identifies trends, anomalies, and potential issues.
The OCMMS_WMCMote provides feedback to end-users through an HMI display for on-site operators and a personalized web dashboard for remote monitoring. The system also sends email notifications to operators, enabling proactive maintenance and optimizing machine performance in the packaging industry.
To further clarify advantages and features of the present invention, a more particular description of the invention is rendering by reference to specific embodiments thereof, which is illustrated in the appended drawing.
It is appreciated that the drawing depicts only typical embodiments of the invention and are therefore not to be considered limiting of its scope. The invention is being described and explained with additional specificity and detail with the accompanying drawing.
BRIEF DESCRIPTION OF DRAWINGS
The foregoing detailed description of embodiments is better understood when read in conjunction with the attached drawing. For better understanding, each component is represented by a specific number which is further illustrated as a reference number for the components used with the figures.
Figure 1 represents block diagram of present system
Further, skilled artisans will appreciate that elements in the drawings are illustrated for simplicity and may not have necessarily been drawn to scale. Furthermore, in terms of the construction of the system, one or more components of the system may have been represented in the drawing by conventional symbols, and the drawing may show only those specific details that are pertinent to understanding the embodiments of the present invention so as not to obscure the drawing with details that will be readily apparent to those of ordinary skill in the art having benefit of the description herein. DETAILED DESCRIPTION OF THE INVENTION
For the purpose of promoting an understanding of the principles of the invention, reference will now be made to the embodiment illustrated in the drawing and specific language will be used to describe the same. It will nevertheless be understood that no limitation of the scope of the invention is thereby intended, such alterations and further modifications in the illustrated system, and such further applications of the principles of the invention as illustrated therein being contemplated as would normally occur to one skilled in the art to which the invention relates. Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skilled in the art to which this invention belongs.
Embodiments of the present invention will be described below in detail with reference to the accompanying drawings.
The present invention provides an Online Condition Monitoring Device for Manual Shrink Wrapper Machines (OCMMS_WMCMote), which addresses these challenges by providing real-time monitoring and analysis capabilities. The system integrates an ESP32 board as the central processing unit, a GSM modem for wireless communication, and sensors, including a Piezo Vibration Sensor, Temperature Sensor, and Accelerometer, to capture dynamic data during machine operation. This data is transmitted to a cloud server for analysis by a machine learning algorithm, which identifies trends, anomalies, and potential issues.
The OCMMS_WMCMote provides feedback to end-users through an HMI display for on-site operators and a personalized web dashboard for remote monitoring. The system also sends email notifications to operators, enabling proactive maintenance and optimizing machine performance in the packaging industry.
The OCMMS_WMCMote system comprises:
1. ESP32 Board: This serves as the central processing unit, responsible for collecting, processing, and transmitting data from various sensors.
2. GSM Modem: Enables wireless communication and real-time data transmission to the cloud server.
3. Piezo Vibration Sensor: Captures dynamic data on machine vibrations.
4. Temperature Sensor: Monitors machine temperature.
5. Accelerometer: Records changes in velocity.
6. HMI Display: Provides on-site operators with real-time visual feedback on machine status.
7. Power Supply: Ensures continuous power for the system's operation.
The data collected by the sensors is transmitted to a customized cloud server, where it undergoes analysis by a machine learning algorithm. This analysis helps identify trends, anomalies, and potential issues with the shrink wrapper machine. The results are relayed to end-users through the HMI display and a personalized web dashboard. Email notifications alert operators of potential issues.
While specific language has been used to describe the present invention, any limitations arising on account thereto, are not intended. As would be apparent to a person in the art, various working modifications may be made to the method in order to implement the inventive concept as taught herein.
Those skilled in the art will appreciate that one or more of the described elements may well be combined into a single functional element. Alternatively, certain elements may be split into multiple functional elements. Elements from one embodiment may be added to another embodiment.
, Claims:1. A system for real-time condition monitoring of a manual shrink wrapper machine, comprising:
an ESP32 board as a central processing unit configured to receive and process data from a plurality of sensors;
a plurality of sensors configured to capture dynamic data during the operation of the machine, the plurality of sensors including at least a Piezo Vibration Sensor, a Temperature Sensor, and an Accelerometer;
a GSM modem configured to transmit real-time data from the sensors to a cloud server;
an HMI display configured to provide visual feedback on machine status; and
a power supply configured to provide continuous power for the operation of the system.
2. The system as claimed in claim 1, wherein the cloud server is further configured to:
analyze the real-time data using a machine learning algorithm to identify trends and anomalies.
3. The system as claimed in claim 1, further comprising a web dashboard configured to provide remote access to historical data, machine status, and analytics.
4. The system as claimed in claim 3, wherein the web dashboard is further configured to provide email notifications to authorized personnel regarding potential issues or anomalies detected by the system.
5. The system as claimed in claim 1, wherein the HMI display is configured to provide on-site operators with real-time visual insights into the machine's status, enabling proactive maintenance and facilitating prompt responses to critical alerts.

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