An energy-saving-oriented die-casting machine and injection molding machine mold opening and closing parameter optimization method

Abstract

The application discloses a kind of energy-saving oriented die casting machine and injection molding machine opening and closing mold parameter optimization method, comprising: (1) by experiment respectively obtained die casting machine or injection molding machine opening mold power and opening mold speed, the relational expression of mold position and the relational expression of closing mold power and closing mold speed, mold position;(2) respectively establish opening mold and closing mold process to vibration impact as constraint, with multi-objective optimization model of minimum energy consumption, time;(3) respectively to the optimization model of opening mold process and closing mold process is solved, exports opening mold parameter and closing mold parameter's Pareto optimal solution set.The application can effectively decouple opening and closing mold parameter and the complex relationship between opening and closing mold time, energy consumption, vibration impact, and can quickly find optimal parameter, high-qualityly solve opening and closing mold process parameter optimization problem;In addition, the application can be conveniently integrated into the control system of equipment and carry out large-area popularization and application, can powerfully support manufacturing cost reduction, manufacturing quality and equipment life promotion.

Description

Technical Field

[0001] This invention belongs to the field of high-efficiency and energy-saving operation optimization technology for die casting machines and injection molding machines, specifically involving a method for optimizing the opening and closing parameters of die casting machines and injection molding machines for energy saving. Background Technology

[0002] Die casting machines are key equipment for casting non-ferrous metals such as aluminum and magnesium, characterized by their large production volume and wide application. Currently, China is the world's largest producer and consumer of die casting machines. Aluminum and magnesium alloy die castings are mainly used in the automotive industry, with over 50% of automotive aluminum and magnesium alloy castings produced through die casting. A trend in lightweighting in China's automotive sector is "replacing steel with aluminum and forging with casting" and "large-scale integrated die casting," which will further boost the use of die casting machines. Injection molding machines are the most common plastic molding equipment, producing the vast majority of plastic products, also characterized by their large production volume and wide application. China is also the world's largest producer and consumer of injection molding machines. Die casting machines and injection molding machines share many similarities, one of the biggest being their mold opening and closing mechanisms and parameters, which are essentially the same. Mold opening and closing (collectively referred to as mold opening and closing) are crucial processes in both die casting and injection molding. These parameters significantly impact product quality, machine stability, machine lifespan, and energy consumption. Efficiently determining the optimal mold opening and closing parameters is a technical challenge faced by die casting and injection molding engineers.

[0003] Energy-saving die-casting machines and injection molding machines generally use hydraulic servo control systems. Figure 1 For the mold opening and closing mechanism of die casting and injection molding machines, this type of mechanism uses a servo controller, servo motor, and fixed displacement pump as the power source for the hydraulic system, and hydraulic cylinders as the actuators for opening and closing the mold. Common three-platen die casting or injection molding machines add a double toggle mechanism between the hydraulic cylinder and the moving platen. Common two-platen die casting or injection molding machines use four small hydraulic cylinders to directly drive the moving platen. For example... Figure 2As shown in (a) and (b), most die-casting and injection molding machines divide the mold opening and closing process into four stages. The mold closing process includes high-speed mold closing, low-speed mold closing, low-pressure mold closing, and high-pressure mold closing; the mold opening process includes high-pressure mold opening, low-pressure mold opening, high-speed mold opening, and low-speed mold opening. Different manufacturers of die-casting and injection molding machines may have different names for the four stages of the mold opening and closing process, but their functions and characteristics are similar. The parameters that need to be set for the mold opening and closing process include the speed, pressure, and start and stop positions of each stage of the mold opening and closing process. The speed, pressure, and start and stop positions of each stage of the low-pressure mold closing, high-pressure mold closing, high-pressure mold opening, and low-pressure mold opening processes are related to the characteristics of the product and there are not many selectable values. They can be obtained based on experience and a few tests and do not require optimization. The pressure required for high-speed mold closing, low-speed mold closing, high-speed mold opening, and low-speed mold opening is determined by the external load (mainly friction) and does not require optimization. The speeds of high-speed mold closing, low-speed mold closing, high-speed mold opening, and low-speed mold opening, as well as the start and stop positions for high and low speeds, have a large set of adjustable ranges. Moreover, these parameters affect mold opening and closing time, machine stability, energy consumption, etc., making it difficult to obtain an optimal set of values.

[0004] To address the parameter optimization problem of low-speed, high-speed, and high-low speed switching positions in injection molding machines, Chinese patent application CN106079333A proposes a model-free optimization-based automatic adjustment method for injection molding machine mold opening parameters. This method can obtain a relatively optimal set of parameters; however, it still has the following shortcomings: ① It does not consider the energy consumption of the mold opening and closing process; the mold opening and closing process consumes a lot of energy, and energy saving is an urgent need. The mold opening and closing process is driven by a hydraulic servo system, and the energy efficiency of the hydraulic servo system varies under different speeds and pressures. Therefore, one goal of optimizing the mold opening and closing parameters is to minimize energy consumption. ② It does not consider the mold opening and closing time; to improve production efficiency, the shorter the mold opening and closing time, the better. Therefore, another goal of optimizing the mold opening and closing parameters is to minimize the time. ③ It does not quantify and consider the impact and speed variation during the mold opening and closing process; the speed during the mold opening and closing process can increase or decrease sharply, which has a significant impact on energy consumption, equipment impact, and mold opening and closing stability, and needs to be considered.

[0005] In summary, there is still an urgent need to tackle key technological challenges and develop an automated method for optimizing the mold opening and closing parameters of die-casting and injection molding machines. This method would enable the rapid acquisition of a set of parameters that meet production quality and stability requirements while minimizing mold opening and closing time and energy consumption. This would significantly promote the intelligent and low-carbon operation of the die-casting and injection molding processes. Summary of the Invention

[0006] In view of the above, the present invention provides an energy-saving method for optimizing the mold opening and closing parameters of die casting machines and injection molding machines. This method can effectively decouple the complex relationship between mold opening and closing parameters and mold opening and closing time, energy consumption, vibration and impact, and can quickly find the optimal parameters, thus solving the problem of optimizing the parameters in the mold opening and closing process with high quality.

[0007] A method for optimizing mold opening and closing parameters in energy-saving die-casting and injection molding machines includes the following steps:

[0008] (1) Obtain the relationship between the mold opening power, mold opening speed and mold position of the die casting machine or injection molding machine and the relationship between the mold closing power, mold closing speed and mold position through experiments;

[0009] (2) Establish optimization models for the mold opening process and the mold closing process respectively, with vibration and impact as constraints and energy consumption and time as objectives;

[0010] (3) Solve the optimization models for the mold opening process and the mold closing process respectively, and output the Pareto optimal solution set for the mold opening parameters and the Pareto optimal solution set for the mold closing parameters.

[0011] Furthermore, step (1) obtains the relationship between the mold opening power, mold opening speed, and mold position of the die casting machine or injection molding machine through experiments. The specific process is as follows:

[0012] 1.1 Connect the voltage and current acquisition heads of the power analyzer to the power input line of the servo controller of the die-casting machine or injection molding machine to measure the power of the servo controller and servo motor;

[0013] 1.2 Install the product mold and product blank onto the moving platen of the die-casting machine or injection molding machine;

[0014] 1.3 From the selectable range of mold opening speed [V] min V max N points are uniformly selected within the area, with an interval of between any two adjacent points. N is a natural number greater than 2;

[0015] 1.4 Using the maximum mold opening pressure and the speed parameters corresponding to each point as mold opening parameters, the mold is pushed at a constant speed from the end position of low-pressure mold opening to the start position of mold closing.

[0016] 1.5 Use a power analyzer to measure and record the power curve corresponding to the mold opening parameters for each experiment, and transform the horizontal axis of the power curve from time to mold position. The mold position is equal to time multiplied by the mold opening speed. Then, the mold opening power is recorded as P. k (v k ,l),v k l represents the mold opening speed, and l represents the mold position.

[0017] Furthermore, step (1) obtains the relationship between the mold closing power, mold closing speed, and mold position of the die casting machine or injection molding machine through experiments. The specific process is as follows:

[0018] 1.1 Connect the voltage and current acquisition heads of the power analyzer to the power input line of the servo controller of the die-casting machine or injection molding machine to measure the total power of the servo controller and servo motor;

[0019] 1.2 Install the product mold onto the moving platen of the die-casting machine or injection molding machine;

[0020] 1.3 From the selectable range of mold closing speed [V] min V max N points are uniformly selected within the area, with an interval of between any two adjacent points. N is a natural number greater than 2;

[0021] 1.4 Using the maximum mold closing pressure and the speed parameters corresponding to each point as mold closing parameters, the mold is pushed uniformly from the starting position of mold closing to the ending position of low-speed mold closing.

[0022] 1.5 Use a power analyzer to measure and record the power curve corresponding to the mold closing parameters for each experiment, and transform the horizontal axis of the power curve from time to mold position. The mold position is equal to time multiplied by the mold closing speed. Then, the mold closing power is recorded as P. h (v h ,l),v h l represents the mold closing speed, and l represents the mold position.

[0023] Furthermore, the specific process of establishing an optimization model for the mold-making process in step (2) is as follows:

[0024] 2.1 Obtain known parameters for mold opening parameter optimization, including the total mold opening stroke L at both high and low speeds. k and the speed of low-pressure mold opening

[0025] 2.2 High speed during mold opening process low speed High-speed mold opening stroke coefficient α k (High-speed mold opening stroke divided by total mold opening stroke L) k ) as optimization variables, where

[0026] 2.3 An optimization model is established with the objectives of minimizing mold opening energy consumption and mold opening time. The objective function expression is as follows:

[0027]

[0028]

[0029] Wherein: T k E is the mold opening time. k For mold opening energy consumption, m m1 P is the total weight of the product mold and the product blank. k () represents the mold opening power at the corresponding mold opening speed and mold position, and t represents time;

[0030] 2.4 Vibration and impact are used as constraints in the optimization model. The specific constraint relationships are as follows:

[0031]

[0032]

[0033]

[0034] Where: θ zk This represents the maximum acceptable vibration value for mold opening.

[0035] Furthermore, the specific process of establishing an optimization model for the mold-closing process in step (2) is as follows:

[0036] 2.1 Obtain known parameters for mold closing parameter optimization, including the total mold closing stroke L at both high and low speeds. h and the speed of low-pressure mold closing

[0037] 2.2 High speed during mold closing process low speed High-speed mold closing stroke coefficient α h (High-speed mold closing stroke divided by total mold closing stroke L) h ) as optimization variables, where

[0038] 2.3 An optimization model is established with the objectives of minimizing mold closing energy consumption and mold closing time. The objective function expression is as follows:

[0039]

[0040]

[0041] Wherein: T h For mold closing time, E h For mold closing energy consumption, m m P is the weight of the product mold. h () represents the closing power at the corresponding closing speed and mold position, and t represents time;

[0042] 2.4 Vibration and impact are used as constraints in the optimization model. The specific constraint relationships are as follows:

[0043]

[0044] Where: θ zh This represents the maximum acceptable vibration value for mold closing.

[0045] Furthermore, step (3) uses a non-dominated sorting genetic algorithm to solve the optimization model of the mold-opening process. The specific process is as follows:

[0046] 3.1 Using binary encoding for high-speed... low speed High-speed mold opening stroke coefficient α k Encode;

[0047] 3.2 Randomly generate a parent population containing M solutions that satisfy the constraints, and calculate the opening time T of the M solutions in the parent population. k And mold opening energy consumption E k M is an even number;

[0048] 3.3 Based on the mold opening time T k And mold opening energy consumption E k The M solutions of the parent population are sorted in ascending order according to the non-dominated relation. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated in each non-dominated level.

[0049] 3.4 A binary tournament is used to divide the M solutions of the parent population into M / 2 groups, each containing 2 solutions. Crossover and mutation operations are performed on the 2 solutions in each group to generate an offspring population containing M solutions that satisfy the constraints.

[0050] 3.5 Calculate the opening time T of M solutions in the offspring population k And mold opening energy consumption E k And according to the mold opening time T k And mold opening energy consumption E k The M solutions of the parent population and the M solutions of the offspring population are sorted in ascending order according to the non-dominated relationship. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated in each non-dominated level. The top M solutions with low sorting level and high crowding degree are taken as the new parent population.

[0051] 3.6 Determine if the set maximum number of iterations has been reached: If yes, decode the M solutions in the new parent population and output the Pareto optimal solution set; if no, return to step 3.4 to perform the corresponding operation on the new parent population until the maximum number of iterations is reached.

[0052] Furthermore, step (3) employs a non-dominated sorting genetic algorithm to solve the optimization model of the merging process. The specific process is as follows:

[0053] 3.1 Using binary encoding for high-speed... low speed High-speed mold closing stroke coefficient α h Encode;

[0054] 3.2 Randomly generate a parent population containing M solutions that satisfy the constraints, and calculate the modular convergence time T of the M solutions in the parent population. h Energy consumption of the combined mold E h M is an even number;

[0055] 3.3 Based on the mold closing time T h Energy consumption of the combined mold E h The M solutions of the parent population are sorted in ascending order according to the non-dominated relation. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated in each non-dominated level.

[0056] 3.4 A binary tournament is used to divide the M solutions of the parent population into M / 2 groups, each containing 2 solutions. Crossover and mutation operations are performed on the 2 solutions in each group to generate an offspring population containing M solutions that satisfy the constraints.

[0057] 3.5 Calculate the modulus time T for M solutions in the offspring population h Energy consumption of the combined mold E h And according to the mold closing time T h Energy consumption of the combined mold E h The M solutions of the parent population and the M solutions of the offspring population are sorted in ascending order according to the non-dominated relationship. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated in each non-dominated level. The top M solutions with low sorting level and high crowding degree are taken as the new parent population.

[0058] 3.6 Determine if the set maximum number of iterations has been reached: If yes, decode the M solutions in the new parent population and output the Pareto optimal solution set; if no, return to step 3.4 to perform the corresponding operation on the new parent population until the maximum number of iterations is reached.

[0059] An electronic device includes a memory and a processor, the memory being coupled to the processor; wherein the memory is used to store program data, and the processor is used to execute the program data to implement the above-described method for optimizing the opening and closing parameters of die-casting machines and injection molding machines.

[0060] A computer-readable storage medium having a computer program stored thereon, which, when executed by a processor, implements the above-described method for optimizing the mold opening and closing parameters of a die-casting machine and an injection molding machine.

[0061] Compared with the prior art, the present invention has the following beneficial technical effects:

[0062] 1. This invention provides a novel method for optimizing mold opening and closing parameters in die-casting and injection molding machines. For the first time, this method simultaneously considers the impact of mold opening and closing parameters on mold opening and closing impact, mold opening and closing time, and mold opening and closing energy consumption, making it more aligned with practical needs. The proposed multi-objective optimization model and solution method effectively decouple the complex relationships between mold opening and closing parameters and mold opening and closing time, energy consumption, and vibration impact. It can also quickly and effectively find a set of parameters that meet impact requirements while minimizing both time and energy consumption, thus providing a high-quality solution to the challenge of optimizing parameters in the mold opening and closing process.

[0063] 2. The energy-saving die-casting and injection molding machine mold opening and closing parameter optimization method of this invention can be integrated into the control system of die-casting and injection molding machines to form a highly efficient and energy-saving mold opening and closing parameter optimization module. This can facilitate the large-scale promotion and application of this invention, effectively support the reduction of manufacturing costs, the improvement of manufacturing quality and equipment life, and help the die-casting and injection molding industry to develop in a green and low-carbon manner. Attached Figure Description

[0064] Figure 1 This is a schematic diagram of the mold opening and closing mechanism of a die-casting machine and an injection molding machine.

[0065] Figure 2 The diagram shows the mold opening and closing process of a die casting machine and an injection molding machine, where (a) corresponds to the mold closing process and (b) corresponds to the mold opening process.

[0066] Figure 3 This is a flowchart illustrating the method for optimizing the mold opening and closing parameters of the die casting machine and injection molding machine according to the present invention.

[0067] Figure 4 This is a schematic diagram of an electronic device. Detailed Implementation

[0068] To describe the present invention in more detail, the technical solution of the present invention will be described in detail below with reference to the accompanying drawings and specific embodiments.

[0069] like Figure 3 As shown, the energy-saving die-casting machine and injection molding machine mold opening and closing parameter optimization method of the present invention includes the following steps:

[0070] (1) The relationship between the mold opening power and the mold opening speed and the mold position of the die casting machine or injection molding machine was obtained by experiment. The relationship between the mold closing power and the mold closing speed and the mold position was obtained by experiment.

[0071] 1.1 Connect the voltage and current acquisition heads of the power analyzer to the power input line of the servo controller of the die-casting machine or injection molding machine to measure the total power of the servo controller and the motor;

[0072] 1.2 Install the die-casting or injection mold and the blank of the product to be produced onto the die-casting machine or injection molding machine's moving template;

[0073] 1.3 From the selectable range of mold opening speed [V] min V max Select N points uniformly within the area (N is an integer greater than 2, the larger N is, the better), with an interval of between adjacent points.

[0074] 1.4 At maximum mold opening pressure and [V min V max The velocity parameters v of N points in the image N Given the mold opening parameters, the mold is pushed at a constant speed from the end position of low-pressure mold opening to the start position of mold closing, where these two positions are known parameters;

[0075] 1.5 Use a power analyzer to measure and record the power curves corresponding to the mold opening parameters for each experiment, and transform the abscissa of the power curve from the time coordinate to the position coordinate. The transformation method is that the position coordinate equals time multiplied by velocity, and the mold opening power is recorded as P. k (v,l), where v is the mold opening speed and l is the mold position.

[0076] The steps for obtaining the relationship between mold closing power, mold closing speed, and mold position are basically the same as those for obtaining the relationship between mold opening power, mold opening speed, and mold position, except that: step 1.2 does not require placing the cast or injection molded product blank onto the mold; step 1.4 involves uniformly pushing the mold from the initial mold closing position to the initial low-pressure mold closing position; and step 1.5 denotes the mold closing power as P. h (v,l).

[0077] (2) Establish multi-objective optimization models for the mold opening and closing processes with vibration and impact as constraints, and with minimum energy consumption and time.

[0078] The steps for establishing a multi-objective optimization model for the mold-opening process, with vibration and impact as constraints and minimizing energy consumption and time, are as follows:

[0079] 2.1 Obtain known parameters for mold opening parameter optimization, including the mold opening stroke L for both high-speed and low-speed operations. k Low-pressure mold opening speed

[0080] 2.2 High speed of the mold opening process low speed High-speed mold opening stroke coefficient α k (High-speed mold opening stroke divided by the total high-speed and low-speed mold opening stroke) is used as the optimization variable, where

[0081] 2.3 Establish an objective function that minimizes both energy consumption and time. The expression for the objective function is as follows:

[0082]

[0083]

[0084]

[0085] Wherein: T k It is the mold opening time, E k It is the energy consumption for mold opening, m m1 It is the total weight of the mold and the product blank;

[0086] 2.4 Vibration and shock are used as constraints in the optimization model. The expressions for the constraints are as follows:

[0087]

[0088]

[0089]

[0090] Where: θ zk This represents the maximum acceptable vibration value for mold opening.

[0091] The steps for establishing a multi-objective optimization model for the mold clamping process, with vibration and impact as constraints and minimizing energy consumption and time, are as follows:

[0092] 2.1 Obtain known parameters for mold clamping parameter optimization, including the mold clamping stroke L at high and low speeds. h Low-pressure mold closing speed

[0093] 2.2 High speed of the mold closing process low speed High-speed and low-speed switching position coefficient α h (High-speed mold closing stroke divided by the total high-speed and low-speed mold closing stroke) is used as the optimization variable, where

[0094] 2.3 Establish an objective function that minimizes both energy consumption and time. The expression for the objective function is as follows:

[0095]

[0096]

[0097] Wherein: T h It is the mold closing time, E h It is the energy consumption of mold closing, m m It is the weight of the mold;

[0098] 2.4 Vibration and shock are used as constraints in the optimization model. The expressions for the constraints are as follows:

[0099]

[0100] Where: θ zh This represents the maximum acceptable vibration value for mold closing.

[0101] (3) Heuristic algorithms are used to solve the multi-objective optimization models of the mold opening and mold closing processes respectively, and output the Pareto optimal solution set of the mold opening parameters and the Pareto optimal solution set of the mold closing parameters.

[0102] For the mold-opening process, this invention uses the Non-Dominated Sorting Genetic Algorithm (NSGA-II) to solve a bi-objective optimization model for minimizing mold-opening time and energy consumption. The specific steps are as follows:

[0103] 3.1 The high-speed, low-speed, and high-speed / low-speed switching position coefficients are encoded using binary encoding.

[0104] 3.2 Randomly generate a parent population containing M solutions that satisfy the constraints, and calculate the opening time and energy consumption of the M solutions in the parent population, where M is an even number;

[0105] 3.3 Sort the M solutions of the parent population in ascending order according to the non-dominated relation, divide the sorted solutions into multiple non-dominated levels, and calculate the crowding degree of each solution in each non-dominated level.

[0106] 3.4 A binary tournament is used to select M / 2 sets of solutions from the M solutions of the parent population to form an intermediate generation population. Each set contains 2 solutions. Crossover and mutation operations are performed on the 2 solutions of each set of intermediate generation populations to generate offspring containing M solutions that satisfy the constraints.

[0107] 3.5 Calculate the mold opening time and energy consumption of M solutions in the offspring, and sort the M solutions of the parent population and the M solutions of the offspring population in ascending order according to the non-dominated relationship. Divide the sorted solutions into multiple non-dominated levels, and calculate the crowding degree of each solution in each non-dominated level. Take the top M solutions with low sorting level and high crowding degree as the new parent.

[0108] 3.6 Determine if the set number of iterations has been reached: If yes, decode the M solutions in the new parent generation from step 3.5 and output the Pareto optimal solution set; if no, use the M solutions in the new parent generation from step 3.5 as input and execute steps 3.4 to 3.6 sequentially until the number of iterations is reached.

[0109] For the mold-closing process, the non-dominated sorting genetic algorithm is also used to solve the dual-objective optimization model of minimum mold-closing time and energy consumption. The specific steps are the same as those for solving the multi-objective optimization model of the mold-opening process.

[0110] Example

[0111] The following is an example of the optimization process of mold opening and closing parameters for producing a five-star base office chair using a die-casting machine. The specific steps are as follows:

[0112] Step (1): Connect the power analyzer to the power input line of the servo controller of the die-casting machine. Install the mold and blank of the five-star foot onto the moving mold. Set the mold opening pressure of the die-casting machine to 100 bar. Start the mold opening speed from 50 mm / s and increase it by 10 mm / s each time until it reaches 500 mm / s. Measure the power of pushing the mold from the end position of the low-pressure mold opening to the beginning position of the mold closing at different speeds. Then remove the five-star foot. Set the mold opening pressure of the die-casting machine to 100 bar. Start the mold opening speed from 50 mm / s and increase it by 10 mm / s each time until it reaches 500 mm / s. Measure the power of pushing the mold from the beginning position of the mold closing to the beginning position of the low-pressure mold closing at different speeds. Finally, convert the coordinates of the mold opening power curve and the mold closing power curve at different speeds into time.

[0113] Step (2): Obtain the parameters required for mold opening and closing optimization, including the total stroke of the high-speed and low-speed mold opening (625mm), the low-pressure mold opening speed (100mm / s), the total stroke of the high-speed and low-speed mold closing (565mm), the low-pressure mold closing speed (100mm / s), the mold weight (4520kg), the weight of the five-star base blank (2.5kg), the maximum and minimum opening and closing speeds (500mm / s and 50mm / s, respectively), and θ. zk and θ zh 300kg.m 2 / s 2 .

[0114] Step (3): The objective function, constraints, variables, and non-dominated sorting genetic algorithm of the open and closed multi-objective optimization model are encoded into a runnable program in Matlab software. The parameters of the non-dominated sorting genetic algorithm are set as follows: population size 100, crossover rate 0.6, mutation rate 0.05, maximum number of iterations 500 generations. The solution program is then run to obtain the Pareto optimal front parameters for open and closed models.

[0115] Step (4): Based on the actual situation of the die-casting machine and other peripheral equipment, the process personnel select a parameter from the Pareto optimal solution set that satisfies line balance and has the lowest energy consumption. In this embodiment, the optimal mold opening parameters for die-casting five-star feet are 300mm / s high speed, 150mm / s low speed, and 0.6 high speed mold opening stroke coefficient; the optimal mold closing parameters are 320mm / s high speed, 190mm / s low speed, and 0.8 high speed mold opening stroke coefficient. This set of optimal parameters achieves a 10% reduction in mold opening and closing time and an 8% energy saving compared to the parameters previously used by the company.

[0116] Accordingly, this application also provides an electronic device, comprising: one or more processors; a memory for storing one or more programs; and, when the one or more programs are executed by the one or more processors, causing the one or more processors to implement the die-casting machine and injection molding machine mold opening and closing parameter optimization method as described above. Figure 4 The diagram shown is a hardware structure diagram of any device with data processing capabilities, used in the die-casting machine and injection molding machine mold opening and closing parameter optimization method provided in this embodiment of the invention, except... Figure 4 In addition to the processor, memory, and network interface shown, any data processing device in the embodiment may also include other hardware depending on the actual function of the data processing device, which will not be described in detail here.

[0117] Accordingly, this application also provides a computer-readable storage medium storing computer instructions, which, when executed by a processor, implement the aforementioned method for optimizing the mold opening and closing parameters of die-casting and injection molding machines. The computer-readable storage medium can be an internal storage unit of any data-processing device as described in any of the foregoing embodiments, such as a hard disk or memory. The computer-readable storage medium can also be an external storage device, such as a plug-in hard disk, smart media card (SMC), SD card, flash card, etc., equipped on the device. Furthermore, the computer-readable storage medium can include both internal storage units of any data-processing device and external storage devices. The computer-readable storage medium is used to store the computer program and other programs and data required by the data-processing device, and can also be used to temporarily store data that has been output or will be output.

[0118] The above description of the embodiments is provided to enable those skilled in the art to understand and apply the present invention. Those skilled in the art can readily make various modifications to the above embodiments and apply the general principles described herein to other embodiments without creative effort. Therefore, the present invention is not limited to the above embodiments, and any improvements and modifications made to the present invention by those skilled in the art based on the disclosure thereof should be within the scope of protection of the present invention.

Claims

1. A method for optimizing mold opening and closing parameters of die-casting machines and injection molding machines for energy saving, comprising the following steps: (1) Obtain the relationship between the mold opening power, mold opening speed and mold position of the die casting machine or injection molding machine and the relationship between the mold closing power, mold closing speed and mold position through experiments; (2) Establish optimization models for the mold opening process and the mold closing process respectively, with vibration and impact as constraints and energy consumption and time as objectives; (3) Solve the optimization models for the mold opening process and the mold closing process respectively, and output the Pareto optimal solution sets for the mold opening parameters and the mold closing parameters; among them, the non-dominated sorting genetic algorithm is used to solve the optimization model for the mold opening process, and the specific process is as follows: 3.1 Using binary encoding for high-speed... low speed High-speed mold opening stroke coefficient Encode; 3.2 Randomly generate a list containing M The parent population of the given solutions satisfying the constraints is calculated, and the values ​​of the parent population are... M The mold opening time for each solution Energy consumption for mold opening , M It is an even number; 3.3 Based on mold opening time Energy consumption for mold opening For the parent population M The solutions are sorted in ascending order of non-dominated relations. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated within each non-dominated level. 3.4 Using a binary tournament to select the parent population M Each solution is divided into M There are 2 groups, each containing 2 solutions. The process iterates through each group, performing crossover and mutation operations on the two solutions to generate a solution containing... M A population of offspring that satisfy the constraints. 3.5 Calculating the offspring population M The mold opening time for each solution Energy consumption for mold opening And according to the mold opening time Energy consumption for mold opening For the parent population M Individual solutions and offspring population M The solutions are sorted in ascending order of non-dominated relation. The sorted solutions are then divided into multiple non-dominated levels. Within each non-dominated level, the crowding degree of each solution is calculated. The solutions with lower sorting levels and higher crowding degrees are ranked first. M Each solution serves as a new parent population; 3.6 Determine if the set maximum number of iterations has been reached: If yes, then process the new parent population... M Decode each solution and output the Pareto optimal solution set; otherwise, return to step 3.4 to perform the corresponding operation on the new parent population until the maximum number of iterations is reached. The optimization model of the merging process is solved using a non-dominated sorting genetic algorithm. The specific process is as follows: 3.7 Uses binary encoding for high-speed... low speed High-speed mold closing stroke coefficient Encode; 3.8 Randomly generate a list containing M The parent population of the given solutions satisfying the constraints is calculated, and the values ​​of the parent population are... M The time to combine solutions Energy consumption of the mold , M It is an even number; 3.9 Based on mold closing time Energy consumption of the mold For the parent population M The solutions are sorted in ascending order of non-dominated relations. The sorted solutions are divided into multiple non-dominated levels, and the crowding degree of each solution is calculated within each non-dominated level. 3.10 Using a binary tournament format to select the parent population M Each solution is divided into M There are 2 groups, each containing 2 solutions. The process iterates through each group, performing crossover and mutation operations on the two solutions to generate a solution containing... M A population of offspring that satisfy the constraints. 3.11 Calculating the offspring population M The time to combine solutions Energy consumption of the mold And according to the mold closing time Energy consumption of the mold For the parent population M Individual solutions and offspring population M The solutions are sorted in ascending order of non-dominated relation. The sorted solutions are then divided into multiple non-dominated levels. Within each non-dominated level, the crowding degree of each solution is calculated. The solutions with lower sorting levels and higher crowding degrees are ranked first. M Each solution serves as a new parent population; 3.12 Determine if the set maximum number of iterations has been reached: If yes, then process the new parent population... M Decode each solution and output the Pareto optimal solution set; otherwise, return to step 3.10 to perform the corresponding operation on the new parent population until the maximum number of iterations is reached.

2. The method for optimizing the mold opening and closing parameters of die-casting machines and injection molding machines according to claim 1, characterized in that: Step (1) involves obtaining the relationship between the mold opening power, mold opening speed, and mold position of the die casting machine or injection molding machine through experiments. The specific process is as follows: 1.1 Connect the voltage and current acquisition heads of the power analyzer to the power input line of the servo controller of the die-casting machine or injection molding machine to measure the power of the servo controller and servo motor; 1.2 Install the product mold and product blank onto the moving platen of the die-casting machine or injection molding machine; 1.3 From the selectable range of mold opening speed Take evenly inside N There are points, and the interval between any two adjacent points is... , N It is a natural number greater than 2; 1.4 Using the maximum mold opening pressure and the speed parameters corresponding to each point as mold opening parameters, the mold is pushed at a constant speed from the end position of low-pressure mold opening to the start position of mold closing. 1.5 Use a power analyzer to measure and record the power curve corresponding to the mold opening parameters for each experiment. Transform the horizontal axis of the power curve from time to mold position, where mold position equals time multiplied by mold opening speed. Then, record the mold opening power as... , For mold opening speed, This indicates the mold position.

3. The method for optimizing the mold opening and closing parameters of die-casting machines and injection molding machines according to claim 1, characterized in that: Step (1) involves obtaining the relationship between the mold closing power, mold closing speed, and mold position of the die casting machine or injection molding machine through experiments. The specific process is as follows: 1.6 Connect the voltage and current acquisition heads of the power analyzer to the power input line of the servo controller of the die-casting machine or injection molding machine to measure the total power of the servo controller and servo motor; 1.7 Install the product mold onto the moving platen of the die-casting machine or injection molding machine; 1.8 Selectable range of mold closing speed Take evenly inside N There are points, and the interval between any two adjacent points is... , N It is a natural number greater than 2; 1.9 Using the maximum mold closing pressure and the speed parameters corresponding to each point as mold closing parameters, the mold is pushed uniformly from the starting position of mold closing to the ending position of low-speed mold closing. 1.10 Use a power analyzer to measure and record the power curve corresponding to the mold closing parameters for each test, and transform the horizontal axis of the power curve from time to mold position. The mold position is equal to time multiplied by the mold closing speed. The mold closing power is then recorded as follows: , For mold closing speed, This indicates the mold position.

4. The method for optimizing the mold opening and closing parameters of die-casting machines and injection molding machines according to claim 2, characterized in that: The specific process of establishing an optimization model for the mold-making process in step (2) is as follows: 2.1 Obtain known parameters for mold opening parameter optimization, including the total mold opening stroke at both high and low speeds. and the speed of low-pressure mold opening ; 2.2 High speed during mold opening process low speed High-speed mold opening stroke coefficient As optimization variables, among which , , , ; 2.3 An optimization model is established with the objectives of minimizing mold opening energy consumption and mold opening time. The objective function expression is as follows: in: For mold opening time, Energy consumption for mold opening The total weight of the product mold and the product blank. To represent the mold opening power at the corresponding mold opening speed and mold position, t Indicates time; 2.4 Vibration and impact are used as constraints in the optimization model. The specific constraint relationships are as follows: in: This represents the maximum acceptable vibration value for mold opening.

5. The method for optimizing the mold opening and closing parameters of die-casting machines and injection molding machines according to claim 3, characterized in that: The specific process of establishing an optimization model for the mold-closing process in step (2) is as follows: 2.5 Obtain known parameters for mold closing parameter optimization, including the total mold closing stroke at both high and low speeds. and the speed of low-pressure mold closing ; 2.6 High speed during mold closing process low speed High-speed mold closing stroke coefficient As optimization variables, among which , , , ; 2.7 An optimization model is established with the objectives of minimizing mold closing energy consumption and mold closing time. The objective function expression is as follows: in: For mold closing time, For mold closing energy consumption, The weight of the product mold. To represent the closing power at the corresponding closing speed and mold position, t Indicates time; 2.8 The constraints for the vibration and impact optimization model are as follows: in: This represents the maximum acceptable vibration value for mold closing.

6. An electronic device comprising a memory and a processor, characterized in that: The memory is coupled to the processor, wherein the memory is used to store program data, and the processor is used to execute the program data to implement the die-casting machine and injection molding machine mold opening and closing parameter optimization method according to any one of claims 1 to 5.

7. A computer-readable storage medium storing a computer program, characterized in that: When the computer program is executed by the processor, it implements the method for optimizing the mold opening and closing parameters of the die casting machine and injection molding machine as described in any one of claims 1 to 5.

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