AI-powered mold cooling system

Abstract

The invention relates to an AI-assisted mold (K) cooling system that optimizes the thermal management of molds (K) used in the molding processes of metal sheets, which includes an AI-based control and communication unit (9) that receives data measured from the mold (K) surface by temperature sensors (8), maps the heat distribution inside the mold (K) using the said data, adjusts the speed, temperature and direction of the coolant using PID or AI-based control algorithms after mapping, optimizes cooling strategies by learning the mold (K) behavior and ensures a homogeneous thermal distribution on the mold (K) surface with heat distribution from the coolant channel system (2), and exchanges data with the production line control system.

Description

1 TARIFF AI-powered mold cooling system Technical Area The invention relates to the thermal properties of molds used in the molding (pressing) processes of metal sheets. It relates to an AI-powered mold cooling system that optimizes its management. 5 The system that is the subject of this invention is therefore particularly suitable for the automotive industry, home appliance manufacturing, widely used in the manufacturing of electronic device parts and general metal processing. It relates to a mold cooling system that can be used. The system in question is particularly suitable for high-performance applications. Greatly beneficial in mass production and applications requiring precise shaping. It provides. 10 State of the Art Today, existing mold cooling systems are generally divided into two main categories: - Air Cooling Method: These are simple systems, low-powered. They are costly but inefficient. In these systems, the heat of the mold is transferred to the surface of the mold. The air is blown away. 15 - Liquid (e.g., water) Cooling Method: These systems are air-cooled. They are more effective than other methods, however, mold design and fluid channels They require certain measures. On the other hand, controlling the fluid flow rate and temperature is difficult. Shortcomings of existing systems and technical problems: The common shortcoming of existing systems is the lack of a template. This is due to the non-uniformity of heat distribution on its surface. Friction-induced heating points 20 (Hot spots) may form, which can lead to deformation of parts, shortening mold life, and This leads to problems such as decreased production efficiency, especially with liquid-cooled systems. In these systems, constant flow rate and temperature settings distribute heat evenly across different areas within the mold. It is insufficient in optimizing the distribution. This situation results in "homogeneous distribution on the mold surface". "Deformation of the part and shortening of mold life due to non-thermal dissipation" 25 This leads to a technical problem that can be described as follows. In conclusion, due to the negative aspects described above and the current solutions being the subject of discussion... Due to its shortcomings, an improvement is needed in the relevant technical field. It has been made. 2 Purpose of the Invention The invention was created by drawing inspiration from existing situations and overcoming the aforementioned drawbacks. It aims to solve the problem. The main goal of the invention is to create a mold cooling system integrated with an intelligent control system. The goal is to place it. In the aforementioned intelligent control system, the system sets the temperature on the mold surface at 5. It monitors its distribution in real time (with data from sensors) and uses this data According to this, it dynamically adjusts the speed, temperature, and direction of the refrigerant flow. The control system can operate in three different ways: Rule-Based Control: Cooling according to predefined rules. The parameters are adjusted. 10 o PID (Proportional-Integral-Derivative) Control: Temperature target is achieved through the use of feedback. AI-Based Control: Pattern shaping with machine learning algorithms The behavior is analyzed and the most suitable cooling strategies are determined. This, the system will improve itself over time and achieve more accurate results 15 It enables it to do so. Another purpose of the invention is to connect the production line control system with the communication system. It is able to be integrated and exchange data. To achieve the objectives described above: - Fluid conveying system that enables the delivery of coolant to the mold surface 20 channels, - directs coolant to heat condensation points inside the mold refrigerant duct system, - Temperature sensors that measure the temperature on the mold surface in real time. including the thermal management of molds used in the molding processes of metal sheets 25 An AI-powered mold cooling system that optimizes the aforementioned system has been developed. system: - 3 He received it measured by temperature sensors from the mold surface. Using the transmitted data and the mentioned data, the heat distribution within the mold can be determined. mapping, after that mapping, PID or AI-based control Using algorithms, the speed, temperature, and direction of the refrigerant are determined in 5 adjuster, by learning that pattern behavior, it optimizes cooling strategies and Heat dissipation on the mold surface due to the coolant channel system. providing a homogeneous thermal distribution, 10 that exchange data with the production line control system It includes an artificial intelligence-based control and communication unit. The structural and characteristic features and all the advantages of the invention are given in the figures below. This becomes clearer thanks to the detailed explanation written with references to these figures. This will be understood, and therefore the evaluation should also take these forms and detailed explanations into consideration. It needs to be done by taking precautions. 15 Figures that will help understand the invention. Figure 1 shows a representative view of the components of the mold cooling system that is the subject of this invention. Explanation of Part References 1. Fluid transmission channel 2. Refrigerant duct system 20 3. Liquid coolant tank 4. Heat Exchanger 5. Liquid pump 6. Compressor 7. Condenser 25 8. Temperature sensors 4 9. Artificial intelligence-based control and communication unit K. Mold Detailed Description of the Invention This detailed explanation describes the AI-powered mold (K) cooling that is the subject of the invention. The preferred structures of the system are only 5 aimed at a better understanding of the subject. This is explained as follows. The mold (K) cooling system, which is the subject of the invention, preferably includes the following elements: - fluid transmission channels (1), - refrigerant duct system (2), - liquid coolant tank (3), 10 - heat exchanger (4), - liquid pump (5), - compressor (6), - condenser (7), - temperature sensors (8), 15 - AI-based control and communication unit (9). Fluid conveying channels (1) ensure safe and leak-proof transfer of coolant to the mold (K) surface. It includes seals and quick-connect mechanisms that allow it to be transmitted in some way. They are channels. The coolant channel system (2) is the heat condensation inside the mold (K). optimized geometric 20 that directs coolant to hot spots It is a system designed with variable cross-section and steerable channels. Liquid cooler. The tank (3) is the tank used to store the coolant (e.g., water). The heat exchanger (4), It is used to reduce the temperature of the coolant. The liquid pump (5) is used to reduce the temperature of the coolant. It is the element used to circulate the coolant through the mold (K). Compressor (6), cooler It maintains the cooling cycle by compressing the gas. With variable speed control, energy is 25. The efficiency has been optimized. The condenser (7) is used to convert gas into liquid. It is an element. Temperature sensors (8) measure the temperature on the mold (K) surface in real time. These are sensors that measure; they are highly accurate and provide fast response. They are controlled by artificial intelligence. and communication unit (9) processes data from temperature sensors (8), control It implements algorithms and adjusts the parameters of the cooling system. AI-based control and communication unit (9), PID or AI-based 5 It offers control options. Artificial intelligence based control and communication unit (9), to analyze mold (K) behavior, learn and determine the most suitable cooling strategies It determines. Artificial intelligence-based control and communication unit (9), machine learning It is constantly improving itself with its algorithms and data through the production line control system. It facilitates exchange and supports industrial communication protocols (e.g., 10 Modbus (Modular Bus), Profibus (Process Field Bus) Data Bus)). The working principle of the mold (K) cooling system, which is the subject of the invention, is as follows: - First, the temperature is measured and received from the mold (K) surface by the temperature sensors (8). The data is transmitted to the AI-based control and communication unit (9) and pattern (K) 15 heat distribution inside, artificial intelligence based control and communication unit (9) It is mapped by. - After mapping, AI-based control and communication unit (9) PID or using artificial intelligence-based control algorithms, the refrigerant It adjusts the speed, temperature, and direction: 20 In liquid cooling systems, the liquid pump (5) and heat exchanger (4) come into play. Reduction of liquid in mold (K) cooling system through evaporation In this case, the liquid coolant tank (3) supplies the liquid line. The coolant, located between the coolant fluid channel system (2) and the mold (K) The area is connected via fluid transmission channels (1). 25 In gas refrigeration systems, there is a compressor (6) and a condenser (7). - AI-based control and communication unit (9) time pattern (K) By learning the behavior of the refrigerant, it optimizes cooling strategies. Homogeneous thermal distribution on the mold (K) surface with heat dissipation from channel system (2). This ensures even distribution. This prevents deformation in the part and extends the mold (K) life to 30 days. It is extended. - Artificial intelligence based control and communication unit (9) also, mold (K) cooling It enables the system to be integrated with the production line.

Claims

6 REQUESTS 1. - fluid conveying that enables the transfer of coolant to the mold (K) surface channels (1), - directs the coolant to the heat condensation points inside the mold (K) 5 refrigerant duct system (2), - Temperature sensors that measure the temperature on the mold (K) surface in real time (8) containing, thermal (K) of molds used in the molding processes of metal sheets AI-powered mold (K) cooling system that optimizes its management 10 feature; - He himself, measured by temperature sensors (8) from the mold (K) surface The received data is transmitted and the mentioned data is used to determine the temperature inside the mold (K). mapping its distribution, 15 after that mapping, PID or AI-based control using algorithms, the speed, temperature, and direction of the refrigerant adjuster, by learning that pattern (K) behavior, it optimizes cooling strategies and mold (K) 20 heat dissipation due to coolant duct system (2). providing a homogeneous thermal distribution on its surface that exchanges data with the production line control system It includes an artificial intelligence-based control and communication unit (9).

2. The AI-powered mold (K) cooling system conforming to Claim 1 is characterized by its cooling system. If the fluid is liquid: 25 - fluid pump used to circulate coolant through the mold (K) (5), - heat exchanger (4) that reduces the temperature of the coolant. 7 - mold (K) reduction of liquid in cooling system by evaporation In this case, the liquid coolant tank (3) that feeds the liquid line It includes.

3. The AI-powered mold (K) cooling system conforming to Claim 1 is characterized by its cooling system. If the fluid is a gas: 5 - compressor that compresses refrigerant gas (6), - condenser used to convert gas to liquid (7) It includes.

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