IOT-BASED ENERGY CONSUMPTION MONITORING FOR SERVO INJECTION MOLDING MACHINES IN MEDICAL EQUIPMENT MANUFACTURING

Abstract

An iot-based energy consumption monitoring for servo injection molding machines in medical equipment manufacturing comprises ECTDS_SIMNode (1000), which is equipped with an STM32 Processor Board (1600), an ESP01 Wifi Module (1100), a current sensor (1500), a voltage sensor (1400), a TFT display (1200), and a power supply (1300), is used for central processing, this seamless integration of various sensors and components allows for operators in the medical equipment manufacturing industry to gain comprehensive insights and visualization the central processing unit of ECTDS_SIMNode is the STM32 Processor Board, which is essential for gathering, evaluating, and sending real-time energy consumption data from Servo Injection Molding Machines to the cloud-based analytics platform, this ensures a smooth integration and effective functioning for improved monitoring in the production of medical equipment.

Specification

Description:FIELD OF THE INVENTION
This invention relates to iot-based energy consumption monitoring for servo injection molding machines in medical equipment manufacturing.
BACKGROUND OF THE INVENTION
A key element in the creation of medical equipment is the innovative Energy Consumption Monitoring System. It uses cloud-based analytics and Internet of Things technologies to provide real-time insights on the energy consumption of Servo Injection Molding Machines. With constant data gathering and electrical parameter analysis, the system offers a comprehensive picture of patterns in energy consumption. This capacity makes it possible to identify any problems, make well-informed decisions, and optimize the production process. As a result, it helps to increase sustainability and productivity in the manufacturing of medical equipment.
The current energy monitoring systems used in the manufacturing industry, particularly with regard to Servo Injection Molding Machines used in the production of medical equipment, lack effective data management and complete real-time insights. Current systems often don't have an intuitive interface that allows operators to track trends of energy usage, which makes it difficult to quickly spot inefficiencies and other problems.
EP0894604B1: This invention relates to a mold design, injection molding machine and a method for forming a multi-layer plastic article by over molding where the second layer of the article includes a portion having a different geometrical profile than the first one. The novel injection mold and injection molding machine for producing over-molded articles comprises an array of one or more cores which engage arrays of one or more first cavity and arrays of one or more composite cavities. Each composite cavity is formed from the combination of a second cavity and a cavity extension which carries at least a portion of the different geometrical profile, such as a thread. In one embodiment, the cavity extension comprises a pair of cavity portions which are mounted adjacent the core to laterally moveable slides on a movable plate, that can be a stripper plate. During molding of the first layer, the cavity extension elements are moved "out" of alignment with the first cavity and during molding of the second layer the cavity extension elements are moved "in" to form the composite cavity with the second cavity so that only the second layer replicates the geometrical profile of the composite cavity. In another embodiment of the invention, the cavity extension is a single element which is moved between a disengaged position wherein the core can be inserted into the first cavity and an engaged position wherein the core is inserted into the composite cavity.
RESEARCH GAP: An addon device to monitor the energy consumption of Servo Injection Molding Machine used in Medical Equipment Manufacturing using IoT and Cloud Technology is the novelty of the system.
MX354737B: A method and a machine account for changes in material properties of molten plastic material during an injection run. A change in a control signal is calculated by a controller during the injection molding run. If the change in the control signal indicates a change in material flowability, the controller alters a target injection pressure to ensure that molten plastic material completely fills and packs a mold cavity to prevent part flaws such as short shots or flashing.
RESEARCH GAP: An addon device to monitor the energy consumption of Servo Injection Molding Machine used in Medical Equipment Manufacturing using IoT and Cloud Technology 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 comprehensive strategy not only keeps an eye on energy usage, but it also gives operators an easy-to-use interface so they can successfully comprehend the data. A well-thought-out architecture made up of both hardware and cloud-based software powers the innovation. The ECTDS_SIMNode, which is the hub of the system, is furnished with a range of sensors and processing units to collect and handle pertinent data. Together, the STM32 Processor Board, ESP01 WiFi Module, Current Sensor, Voltage Sensor, TFT Display, and Power Supply-among the hardware components-cooperate to gather crucial data regarding energy usage. By measuring electrical parameters, the Current and Voltage Sensors provide real-time information on the machine's power use. Processing this data, the STM32 Processor Board functions as the ECTDS_SIMNode's brain.
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 comprehensive strategy not only keeps an eye on energy usage, but it also gives operators an easy-to-use interface so they can successfully comprehend the data. A well-thought-out architecture made up of both hardware and cloud-based software powers the innovation. The ECTDS_SIMNode, which is the hub of the system, is furnished with a range of sensors and processing units to collect and handle pertinent data. Together, the STM32 Processor Board, ESP01 WiFi Module, Current Sensor, Voltage Sensor, TFT Display, and Power Supply-among the hardware components-cooperate to gather crucial data regarding energy usage. By measuring electrical parameters, the Current and Voltage Sensors provide real-time information on the machine's power use. Processing this data, the STM32 Processor Board functions as the ECTDS_SIMNode's brain.
For this innovation, the ESP01 WiFi Module makes it easier to transmit the data that has been gathered to a Tailored Cloud server. A Machine Learning algorithm that has been predefined analyzes the data in the cloud. After the data is processed by this algorithm, useful insights are produced, such as Trending Data charts that show patterns in energy consumption. The analysis's findings, along with real-time data and important alarms, are relayed back to the business premises. This data is shown locally on the ECTDS_SIMNode's TFT Display, giving users a visual depiction of the machine's energy use in real time. Operators can view the same data remotely by logging into their accounts on a customized web dashboard located within the industry premises.
BEST METHOD OF WORKING
To enable real-time monitoring and transmission of energy consumption data from Servo Injection Molding Machines to the cloud-based analytics platform, the ECTDS_SIMNode, which is equipped with an STM32 Processor Board, an ESP01 Wifi Module, a current sensor, a voltage sensor, a TFT display, and a power supply, is used for central processing. This seamless integration of various sensors and components allows for operators in the medical equipment manufacturing industry to gain comprehensive insights and visualization.
The central processing unit of ECTDS_SIMNode is the STM32 Processor Board, which is essential for gathering, evaluating, and sending real-time energy consumption data from Servo Injection Molding Machines to the cloud-based analytics platform. This ensures a smooth integration and effective functioning for improved monitoring in the production of medical equipment.
Another component of the ECTDS_SIMNode is the ESP01 Wifi Module, which is used to enable wireless communication. This allows the ECTDS_SIMNode to send real-time energy consumption data from Servo Injection Molding Machines to a specialized cloud server, guaranteeing connectivity and accessibility for thorough analytics in the production of medical equipment.
Real-time electrical data from Servo Injection Molding Machines is captured by the Current Sensor, which is connected to the ECTDS_SIMNode. This data is vital for the Energy Consumption Monitoring System to analyze and visualize energy usage trends in the manufacturing process of medical equipment.
Adding to the comprehensive energy consumption monitoring system for analysis and visualization in the medical equipment manufacturing process is the Voltage Sensor, which is also connected to the ECTDS_SIMNode. It measures and provides real-time voltage data from Servo Injection Molding Machines.
The ECTDS_SIMNode's local interface is powered by a TFT display that shows real-time energy consumption data, trend charts, and critical alerts. This gives medical equipment manufacturing operators quick visual insights into how well Servo Injection Molding Machines are performing.
ADVANTAGES OF THE INVENTION
1. The ECTDS_SIMNode serves as the central processing unit and data hub, allowing real-time monitoring and transmission of energy consumption data from Servo Injection Molding Machines to the cloud-based analytics platform through the seamless integration of several sensors and components. This connection makes it easier for operators in the medical equipment manufacturing industry to get comprehensive data and visualization.
2. Wireless communication is made possible via the ESP01 Wifi Module, which enables the ECTDS_SIMNode to send real-time energy consumption data from Servo Injection Molding Machines to a specific cloud server. This feature guarantees accessibility and connectivity, allowing for thorough analytics in the production of medical equipment.
3. The Energy Consumption Monitoring System analyzes and visualizes energy usage trends in the production process of medical equipment with the help of the Current Sensor, which is crucial in gathering real-time electrical data from Servo Injection Molding Machines.
4. The Voltage Sensor is essential for monitoring and delivering voltage data from Servo Injection Molding Machines in real time. This addition improves the overall functionality of the energy consumption monitoring system, facilitating analysis and visualization during the production process of medical equipment.
, C , Claims:1. An iot-based energy consumption monitoring for servo injection molding machines in medical equipment manufacturing comprises ECTDS_SIMNode (1000), which is equipped with an STM32 Processor Board (1600), an ESP01 Wifi Module (1100), a current sensor (1500), a voltage sensor (1400), a TFT display (1200), and a power supply (1300), is used for central processing, this seamless integration of various sensors and components allows for operators in the medical equipment manufacturing industry to gain comprehensive insights and visualization.
2. The machine as claimed in claim 1, wherein the central processing unit of ECTDS_SIMNode is the STM32 Processor Board, which is essential for gathering, evaluating, and sending real-time energy consumption data from Servo Injection Molding Machines to the cloud-based analytics platform, this ensures a smooth integration and effective functioning for improved monitoring in the production of medical equipment.
3. The machine as claimed in claim 1, wherein another component of the ECTDS_SIMNode is the ESP01 Wifi Module, which is used to enable wireless communication, this allows the ECTDS_SIMNode to send real-time energy consumption data from Servo Injection Molding Machines to a specialized cloud server, guaranteeing connectivity and accessibility for thorough analytics in the production of medical equipment.
4. The machine as claimed in claim 1, wherein real-time electrical data from Servo Injection Molding Machines is captured by the Current Sensor, which is connected to the ECTDS_SIMNode, this data is vital for the Energy Consumption Monitoring System to analyze and visualize energy usage trends in the manufacturing process of medical equipment.
5. The machine as claimed in claim 1, wherein adding to the comprehensive energy consumption monitoring system for analysis and visualization in the medical equipment manufacturing process is the Voltage Sensor, which is also connected to the ECTDS_SIMNode, it measures and provides real-time voltage data from Servo Injection Molding Machines.
6. The machine as claimed in claim 1, wherein the ECTDS_SIMNode's local interface is powered by a TFT display that shows real-time energy consumption data, trend charts, and critical alerts, this gives medical equipment manufacturing operators quick visual insights into how well Servo Injection Molding Machines are performing.

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