Simulation and optimization method for refrigerator production system

Abstract

This invention discloses a simulation optimization method for a refrigerator production system. First, data from the existing production process is collected and abstracted into "generator," "receiver," "processor," and "operator" within the Flexsim simulation platform. Then, modeling and positioning are performed within the Flexsim platform. The model and logic built on the Flexsim platform are continuously adjusted based on the actual production process, ensuring that the model and logic are identical to the existing production process. This completes the simulation model of the factory's current production status and provides data support for the corresponding production processes and equipment. Based on the completed simulation model, the production process is adjusted and parameters optimized to calculate the corresponding production efficiency. This allows for the pre-simulation of more efficient production processes, providing data support for optimizing the production process of the actual production line.

Description

Technical Field

[0001] This invention relates to the field of refrigerator manufacturing, and in particular to a simulation optimization method for a refrigerator manufacturing system. Background Technology

[0002] In refrigerator production, the rational design of the production process and procedures is a crucial factor in improving production efficiency. The traditional approach relies on engineers' experience and data calculations, and simple experiments are conducted on existing equipment and production lines based on production targets. The drawback of this approach is that it is difficult to make the right adjustments in one go, resulting in high overall trial-and-error costs, long verification cycles, and frequent disassembly and modification. Summary of the Invention

[0003] To address the aforementioned issues, this invention provides a simulation optimization method for a refrigerator production system. This method first optimizes the production line through simulation, and then, after finding the optimal approach, makes actual adjustments to the production process and procedures.

[0004] The technical solution adopted by this invention to solve the problem is: a simulation optimization method for a refrigerator production system, comprising the following steps: Step 1: Collect information on the equipment, operating procedures, time required for each step of each equipment operation, transportation time for adjacent operating procedures, number of operators for each procedure, operator movement routes, and equipment layout in the refrigerator production workshop. Step 2: Model the process in the Flexsim simulation platform. Assume the basic materials required for the existing process are infinitely supplied, thus abstracting them as a "generator" in the modeling platform. Abstract the equipment as a "receiver" in the modeling platform. The transportation time corresponding to adjacent operation steps, and the operation time corresponding to non-manual operation steps in each piece of equipment, are abstracted as "processors" in the modeling platform. The number of operators corresponding to each process is abstracted as "operators" that need to link with the corresponding "receiver" and "processor." Similarly, the corresponding steps of equipment requiring manual operation, and their corresponding operation times, are also abstracted as "operators" that need to link with the corresponding "receiver" and "processor." The "generator" is linked with the "receiver" and "operator." Step 3: Arrange the "generator", "receiver", "processor" and "operator" models abstracted in Step 2 in the Flexsim simulation platform according to the actual location in the workshop. Then, build the relevant logistics routes in the Flexsim simulation platform according to the actual operation procedures and the movement of operators. Assign the working parameters of "generator", "receiver", "processor" and "operator" to construct the simulation logic. Step 4: After building the model and logic on the Flexsim simulation platform, start running the model to process the virtual box. Observe whether there are logical differences between the operation of each part of the model and the existing process in the workshop, and whether the action time of each "generator", "receiver", "processor" and "operator" is consistent with the setting. If the setting is inconsistent, make continuous corrections until the production efficiency and production rhythm of the existing process in the workshop are the same, thereby completing the simulation model of the current production status of the factory and the data empowerment of "generator", "receiver", "processor" and "operator". Step 5: Based on the above simulation model, adjust the position, quantity, and corresponding operating parameters of the "receiver," "processor," and "operator" to simulate the production time after the adjustment of the workshop production process, thereby providing simulation data support for production process optimization.

[0005] As a further improvement to the above technical solution, in step three, the abstracted "generator", "receiver", "processor" and "operator" models are arranged in the Flexsim simulation platform at a 1:1 scale with the actual locations in the workshop.

[0006] As a further improvement to the above technical solution, a sixth step is added between steps four and five: assigning values ​​to the virtual box being processed in the Flexsim simulation platform, and adding labels to store the time information when the virtual box arrives at each "receiver" and when it is processed by the corresponding "processor" and "operator".

[0007] As a further improvement to the above technical solution, alarm logic is set in the Flexsim simulation platform. When the waiting time for a certain process exceeds the preset time, an automatic warning is issued.

[0008] The beneficial effects of this invention are as follows: First, data from existing production processes is collected and abstracted into "generator," "receiver," "processor," and "operator" within the Flexsim simulation platform. Then, modeling and positioning are performed within the Flexsim platform. The model and logic built on the Flexsim platform are continuously adjusted based on the actual production process, ensuring that the model and logic are identical to the existing production process. This completes the simulation model of the factory's current production status and provides data support for the corresponding production processes and equipment. Then, based on the completed simulation model, the production process is adjusted and parameters optimized to calculate the corresponding production efficiency. This allows for the pre-simulation of more efficient production processes, providing data support for optimizing the production process of the actual production line. Detailed Implementation

[0009] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., indicating the orientation or positional relationship, are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation, and therefore should not be construed as a limitation of this invention.

[0010] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0011] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0012] A simulation optimization method for a refrigerator production system includes the following steps: Step 1: Collect information on the equipment, operating procedures, time required for each step of each equipment operation, transportation time for adjacent operating procedures, number of operators for each procedure, operator movement routes, and equipment layout in the refrigerator production workshop. Step 2: Model the process in the Flexsim simulation platform. Assume the basic materials required for the existing process are infinitely supplied, thus abstracting them as a "generator" in the modeling platform. Abstract the equipment as a "receiver" in the modeling platform. The transportation time corresponding to adjacent operation steps, and the operation time corresponding to non-manual operation steps in each piece of equipment, are abstracted as "processors" in the modeling platform. The number of operators corresponding to each process is abstracted as "operators" that need to link with the corresponding "receiver" and "processor." Similarly, the corresponding steps of equipment requiring manual operation, and their corresponding operation times, are also abstracted as "operators" that need to link with the corresponding "receiver" and "processor." The "generator" is linked with the "receiver" and "operator." Step 3: Arrange the "generator", "receiver", "processor" and "operator" models abstracted in Step 2 in the Flexsim simulation platform according to the actual location in the workshop. Then, build the relevant logistics routes in the Flexsim simulation platform according to the actual operation procedures and the movement of operators. Assign the working parameters of "generator", "receiver", "processor" and "operator" to construct the simulation logic. Step 4: After building the model and logic on the Flexsim simulation platform, start running the model to process the virtual box. Observe whether there are logical differences between the operation of each part of the model and the existing process in the workshop, and whether the action time of each "generator", "receiver", "processor" and "operator" is consistent with the setting. If the setting is inconsistent, make continuous corrections until the production efficiency and production rhythm of the existing process in the workshop are the same, thereby completing the simulation model of the current production status of the factory and the data empowerment of "generator", "receiver", "processor" and "operator". Step 5: Based on the above simulation model, adjust the position, quantity, and corresponding operating parameters of the "receiver," "processor," and "operator" to simulate the production time after the adjustment of the workshop production process, thereby providing simulation data support for production process optimization.

[0013] First, data from the existing production process is collected and abstracted into "generator," "receiver," "processor," and "operator" within the Flexsim simulation platform. Then, modeling and positioning are performed within the Flexsim platform. The model and logic are continuously adjusted based on the actual production process to ensure they align with the existing process. This creates a simulation model of the factory's current production status, providing data support for corresponding production processes and equipment. Based on this simulation model, production processes are adjusted and parameters optimized to calculate production efficiency. This allows for the pre-simulation of more efficient production processes, providing data support for optimizing the actual production line.

[0014] In the above technical solution, in order to ensure the accuracy of the data, it is preferable that in step three, the abstracted "generator", "receiver", "processor" and "operator" models are arranged in the Flexsim simulation platform at a 1:1 scale with the actual location in the workshop.

[0015] In the above method, the virtual box actually refers to the refrigerator being assembled and produced. In order to accurately confirm the time taken for each process and step in the production of the refrigerator, it is preferable to add a sixth step between the fourth and fifth steps: assigning values ​​to the virtual box being processed in the Flexsim simulation platform and adding labels to store the time information when the virtual box arrives at each "receiver" and is processed by the corresponding "processor" and "operator".

[0016] In the above method, considering that if the waiting time of a certain process is too long during long-term operation, it is equivalent to the production process of that simulation being unsuitable for actual application, it is preferable to set alarm logic in the Flexsim simulation platform. When the waiting time of a certain process exceeds the preset time, an automatic warning will be issued.

[0017] In this scheme, a trolley-type refrigerator body foaming system is used as an example: In the trolley-type refrigerator body foaming system, the main sub-objects are the foaming mold, the trolley transporting the refrigerator, the foaming worker, and the foaming gun head. In this system, the refrigerator pre-assembly line and the hanging cage are the preliminary work of the simulation. In this simulation process, they are one of the basic materials that have been completed. They should be assumed to be an infinite supply source, and thus abstracted as a "generator". In a trolley-type refrigerator body foaming system, the refrigerator pre-assembly section is a device that receives the "generator," and therefore should be abstracted as a "receiver" in the model. The foaming mold involves actions such as mold opening and closing, mold lifting and lowering, and entering and exiting the refrigerator body during production, but these actions occur at fixed times. Therefore, it can be abstracted as a "processor" in the model with relevant time parameters set. The trolley transporting the refrigerator body is responsible for transporting the refrigerator body, and its time is also fixed, so it can also be abstracted as a "processor" with relevant time parameters set. The foaming worker confirms the refrigerator body status based on the actual site conditions and needs to manually confirm the entry request and mold closing instruction; therefore, it can be abstracted as an "operator" in the model. The foaming gun head needs to interact with the foaming worker and the foaming mold, which is an operational process, and can also be abstracted as an "operator." Thus, the workflow of the foaming mold, trolley, foaming worker, and foaming gun head can be abstracted in the model as the running times of the "generator," "receiver," "processor," and "operator." For example, the workflow of a box transport trolley is: box entry / exit → waiting for mold opening signal → moving to the mold opening position → waiting for mold opening and bubble removal to be completed → box entry → trolley movement → box exit → returning to the origin → box entry / exit. In the model, this can be abstracted as a "processor" and replaced by setting the time parameters of its corresponding processing steps, thereby completing the model construction.

[0018] The above are merely preferred embodiments of the present invention and do not limit the scope of the patent. Any equivalent structural transformations made using the contents of the present invention under the inventive concept of the present invention, or direct or indirect applications in other related technical fields, are included within the scope of patent protection of the present invention.

Claims

1. A simulation optimization method of a refrigerator production system, characterized by, Includes the following steps: Step 1: Collect information on the equipment, operating procedures, time required for each step of each equipment operation, transportation time for adjacent operating procedures, number of operators for each procedure, operator movement routes, and equipment layout in the refrigerator production workshop. Step 2: Model the process in the Flexsim simulation platform, assuming that the basic materials required in the existing process are available indefinitely, and then abstract them as a "generator" in the modeling platform. The equipment is abstracted as a "receiver" in the modeling platform; the transportation time corresponding to adjacent operation procedures and the operation time corresponding to non-manual operation steps in each piece of equipment are abstracted as "processors" in the modeling platform. The number of operators corresponding to each process is abstracted as "operators" that need to be linked with the corresponding "receiver" and "processor". The corresponding steps of equipment that require manual operation and their corresponding operation time are also abstracted as "operators" that need to be linked with the corresponding "receiver" and "processor". The "generator" is linked with the "receiver" and "operator". Step 3: Arrange the "generator", "receiver", "processor" and "operator" models abstracted in Step 2 in the Flexsim simulation platform according to the actual location in the workshop. Then, build the relevant logistics routes in the Flexsim simulation platform according to the actual operation procedures and the movement of operators. Then, empower the working parameters of the "generator", "receiver", "processor" and "operator" to build the simulation logic. Step 4: After building the model and logic on the Flexsim simulation platform, start running the model to process the virtual box. Observe whether there are logical differences between the operation of each part of the model and the existing process in the workshop, and whether the action time of each "generator", "receiver", "processor" and "operator" is consistent with the setting. If the setting is inconsistent, make continuous corrections until the production efficiency and production rhythm of the existing process in the workshop are the same, thereby completing the simulation model of the current production status of the factory and the data empowerment of "generator", "receiver", "processor" and "operator". Step 5: Based on the above simulation model, adjust the position, quantity, and corresponding operating parameters of the "receiver," "processor," and "operator" to simulate the production time after the adjustment of the workshop production process, thereby providing simulation data support for production process optimization.

2. The simulation optimization method for a refrigerator production system as described in claim 1, characterized in that: In step three, the abstracted "generator", "receiver", "processor" and "operator" models are arranged in the Flexsim simulation platform at a 1:1 scale with the actual locations in the workshop.

3. The simulation optimization method for a refrigerator production system as described in claim 1, characterized in that: Add step six between steps four and five: Assign values ​​to the virtual box being processed in the Flexsim simulation platform, and add labels to store the time information when the virtual box arrives at each "receiver" and when it is processed by the corresponding "processor" and "operator".

4. The simulation optimization method for a refrigerator production system as described in claim 1, characterized in that: Configure alarm logic in the Flexsim simulation platform to issue an automatic warning when the waiting time for a certain process exceeds a preset time.