HEALTH MONITORING INNOVATION FOR CHAIN CONVEYOR OVEN IN COATING CURING PROCESSES ON METAL PARTS USING LPWAN WIRELESS TECHNOLOGY

Abstract

Health Monitoring Innovation for Chain Conveyor Oven in Coating Curing Processes on Metal Parts Using LPWAN Wireless Technology This invention introduces a cutting-edge LPWAN and IoT-based health monitoring system for chain conveyor ovens used in coating curing processes on metal parts. The system integrates an HMTD_COPMote with an STM8L MCU, LoRa Module, and sensors for local data collection, and an HMRD_COPMote with NuttyFi WiFi, HMI Display, and cloud connectivity for remote monitoring. Leveraging IoT-based analytics, the system enables real-time health monitoring, proactive maintenance, and operational optimization through an intuitive web dashboard, enhancing reliability and efficiency in industrial coating processes.

Specification

Description:FIELD OF THE INVENTION
This invention relates to Health Monitoring Innovation for Chain Conveyor Oven in Coating Curing Processes on Metal Parts Using LPWAN Wireless Technology
BACKGROUND OF THE INVENTION
The chain conveyor ovens that are now used for coating curing processes on metal parts have problems that stem from poor maintenance and monitoring practices. This can lead to possible disruptions in operations and more downtime. The absence of real-time capabilities and comprehensive data analysis in conventional monitoring systems hinders the timely identification of critical problems including temperature fluctuations, vibration anomalies, and current fluctuations in the oven system. Reactive maintenance methods are used, performance is subpar, and energy usage is increased.
US9161547B2 - A conveyor oven is disclosed, comprising a housing with a cavity, a conveyor belt, a heat source, and first and second doors. The conveyor belt transports food items through the cavity via openings covered by the doors, which help retain heat during operation. The belt includes a loading and unloading section. The heat source provides customizable cooking times and thermal profiles for various food items placed on the belt within the cavity, ensuring consistent cooking efficiency.
Research Gap: The novelty lies in integrating LoRa and IoT-based innovation for health monitoring, optimizing the performance of Chain Conveyor Ovens used in the metal industry.

US9585401B2 - This invention pertains to a conveyor oven with dual operation modes, featuring a tunnel for cooking food, a conveyor for moving food through the tunnel, and two sets of burners providing heat. The system includes a controller that adjusts burner operation based on food detection within the tunnel, transitioning between modes depending on the presence or absence of food, thereby improving energy efficiency and operational precision.
Research Gap: The system incorporates a LoRa and IoT-based health monitoring solution, enhancing the maintenance and operational reliability of Chain Conveyor Ovens in the metal industry.
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.
This innovative solution offers a state-of-the-art way to increase the reliability and operational efficiency of Chain Conveyor Ovens used in Metal Part Coating Curing Processes. It makes use of cutting-edge wireless and cloud-based technology to provide real-time monitoring of critical oven system parameters. The integration of many sensors facilitates continuous data gathering by offering insightful data on vibration, temperature, and current levels.
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.
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 invention combines cutting-edge wireless technologies like LoRa and Wifi with hardware components like sensors and MCUs in a seamless way. It also combines cloud-based solutions with machine learning techniques. The system is composed of two primary devices: the HMTD_COPMote (Health Monitoring Transmitter Device) and the HMRD_COPMote (Health Monitoring Receiver Device). It functions by combining hardware and software components in a synergistic manner. Positioned carefully inside the chain conveyor oven, the HMTD_COPMote is outfitted with an STM8L MCU, LoRa Module, Temperature Sensor, MEMS Vibration Sensor, Current Sensor, and Power Supply. The sensors continuously record important information about temperature changes, conveyor system vibrations, and current consumption in real time during the curing process. This data is processed locally by the STM8L MCU, which contains pre-programmed algorithms and provides insights on the state of the curing process.
Concurrently, the distant HMRD_COPMote uses its LoRa Module and STM8L MCU to wirelessly receive the processed data from the transmitter. The NuttyFiWifi module provides an additional connection channel for greater versatility. The local interface for on-site monitoring is the receiver device's HMI Display, which shows real-time data. By using IoT technology, the invention expands its capabilities to the cloud. A customized cloud server created especially for this health monitoring application receives the data from both devices. The data is subjected to additional analysis using pre-established machine learning algorithms once it is in the cloud. Based on the processed data, the cloud-based system creates vital alerts, daily analytics, and trending data visualizations. A customized online dashboard that offers an easy-to-use interface for remote monitoring can be accessed via user accounts. Operators have the ability to log in and view real-time information on the chain conveyor ovens' health. With the help of the online dashboard's extensive insights, customers can easily watch trends, receive important warnings, and examine daily charts.
BEST METHOD OF WORKING
1. During coating curing processes, real-time data from various sensors embedded in chain conveyor ovens is collected by the HMTD_COPMote, which is equipped with an STM8L MCU, Lora Module, Temperature Sensor, MEMS Vibration Sensor, Current Sensor, and Power Supply. The data is processed using a predefined algorithm, and the results are wirelessly transmitted to enable comprehensive health monitoring, facilitate proactive maintenance, and optimize operational efficiency.
2. Wirelessly transmitted data from HMTD_COPMote is received by the HMRD_COPMote, which is outfitted with an STM8L MCU, Lora Module, NuttyFiWifi, HMI Display, and Power Supply. The processed results are displayed locally on an HMI display for immediate feedback, and the data is simultaneously forwarded to a customized cloud server, giving operators access to an intuitive web dashboard for timely decision-making, remote monitoring, and analysis of coating curing processes on metal parts.
3. The LoRa module, which is built into both motes, allows for long-range, low-power wireless communication between the HMRD_COPMote and the HMTD_COPMote. This makes it possible to transmit real-time data from sensors embedded in coating curing processes with efficiency, enabling proactive maintenance and seamless health monitoring.
4. The Temperature Sensor, MEMS Vibration Sensor, and Current Sensor-all of which are connected to the HMTD_COPMote-are utilized to provide vital information for the real-time health monitoring of chain conveyor ovens during coating curing processes. This allows for the detection of variations in temperature, irregularities in vibration, and fluctuations in current, which promotes proactive maintenance and maximizes the system's overall efficiency.
5. The built-in NuttyFiWiFi in HMRD_COPMote is utilized to improve connectivity and enable smooth communication between the components of HMTD_COPMote and HMRD_COPMote. This enables the effective transfer of processed data in real-time to the customized cloud server, enabling remote monitoring, analysis, and decision-making in the coating curing processes on metal parts.
6. The HMI Display, which is interfaced with HMRD_COPMote, is utilized to present processed results locally on HMRD_COPMote and provide real-time feedback. This allows operators to keep an eye on the state of the chain conveyor ovens during coating curing processes and provides prompt insights for proactive decision-making.
ADVANTAGES OF THE INVENTION
1. During coating curing procedures, the HMTD_COPMote is an essential component of this novel process, collecting data in real time from several sensors installed in chain conveyor ovens. It enables thorough health monitoring by processing this data using a preset algorithm and wirelessly transmitting the results. By supporting preventive maintenance, this feature eventually maximizes operational effectiveness.
2. This innovation uses the HMTD_COPMote to communicate data wirelessly to the HMRD_COPMote, which functions as a central hub. It simultaneously forwards the data to a customized cloud server and displays the processed findings on a local HMI display for real-time feedback. This allows operators to remotely monitor, analyze, and make timely decisions during coating curing operations on metal parts through an intuitive online dashboard.
3. A key element of this innovation is the LoRa module, which enables low-power, long-range wireless communication between the HMRD_COPMote and HMTD_COPMote. This guarantees the effective transfer of data in real-time from sensors integrated into coating curing processes in chain conveyor ovens, enabling smooth health monitoring and preventive maintenance.
4. This inventive system's Temperature Sensor, MEMS Vibration Sensor, and Current Sensor provide vital data points for the real-time health monitoring of chain conveyor ovens used in coating curing procedures. By enabling the monitoring of temperature changes, unusual vibrations, and current fluctuations, this promotes proactive maintenance and maximizes the system's overall efficiency.
5. NuttyFiWifi improves connectivity, enabling smooth communication between the components of HMTD_COPMote and HMRD_COPMote. This facilitates the effective real-time transfer of processed data to the customized cloud server, allowing for remote decision-making, analysis, and monitoring of coating curing processes on metal parts.
, Claims:1. A Health Monitoring Innovation device for Chain Conveyor Oven in Coating Curing Processes on Metal Parts Using LPWAN Wireless Technology, comprises an HMTD_COPMote equipped with an STM8L MCU, LoRa Module, Temperature Sensor, MEMS Vibration Sensor, Current Sensor, and Power Supply, and an HMRD_COPMote equipped with an STM8L MCU, LoRa Module, NuttyFi WiFi Module, HMI Display, and Power Supply, enabling seamless wireless communication, real-time health monitoring, and IoT-based remote analytics to enhance operational efficiency and preventive maintenance in coating curing processes.
2. The device, as claimed in Claim 1, wherein the LoRa Module integrated into both HMTD_COPMote and HMRD_COPMote facilitates long-range, low-power wireless communication, enabling real-time data exchange between the transmitter and receiver for health monitoring and decision-making.
3. The device, as claimed in Claim 1, wherein the Temperature Sensor, MEMS Vibration Sensor, and Current Sensor in the HMTD_COPMote provide vital real-time data, enabling the detection of temperature fluctuations, vibration irregularities, and current anomalies during coating curing processes on metal parts.
4. The device, as claimed in Claim 1, wherein the NuttyFi WiFi Module in the HMRD_COPMote extends connectivity to a cloud-based server, enabling remote monitoring and analysis of the coating curing process via an intuitive web dashboard.
5. The device, as claimed in Claim 1, wherein the HMI Display interfaced with the HMRD_COPMote provides localized visualization of processed data and alerts, enabling operators to monitor the real-time health status of the chain conveyor oven and take prompt actions.
6. The device, as claimed in Claim 1, wherein IoT cloud integration processes data collected by the HMTD_COPMote and HMRD_COPMote using advanced machine learning algorithms, generating actionable insights, trend analyses, and maintenance alerts for improved operational efficiency.

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