Production cycle optimization method and system for automation equipment

Abstract

The invention discloses a production cycle optimization method and system for automation equipment, and relates to the technical field of production optimization, and the method comprises the following steps: constructing a digital twinborn model of the automation equipment; the production initial coefficient and the production limit coefficient of the automation equipment are obtained, and the production process duration and the production interval duration of the automation equipment under different production efficiencies are obtained; according to the production process duration and the production interval duration, the production cycles of the automation equipment under different production efficiencies are obtained, the total production yield and the unit production yield of the automation equipment under different production efficiencies are obtained, and the production efficiency corresponding to the highest unit production yield serves as the optimal production efficiency; obtaining a theoretical yield change diagram and an actual yield change diagram of the automation equipment, judging whether the automation equipment has a production fault according to a comparison result of the two diagrams, and generating production fault information; and a targeted production mechanism can be formed for automatic equipment, and the most suitable production efficiency can be obtained.

Description

Technical Field

[0001] The present invention relates to the technical field of production optimization, and specifically to a production cycle optimization method and system for automated equipment. Background Art

[0002] Automated equipment is a mechanical, electronic or computer system capable of performing specific tasks or processes. They are designed to replace manual operations, improve production efficiency, reduce human errors, and provide continuous performance when long-term operation or repetitive operations are required. Optimizing the production cycle of automated equipment aims to improve production efficiency and reduce costs. By using technologies such as sensors, data collection and analysis, real-time monitoring and optimization of the production process can be achieved; In the prior art, a unified management method is often adopted for automated equipment in the same scenario, and the same production cycle is adopted for different automated equipment, that is, the same work and the same stop. However, this ignores the differences between different automated equipment, resulting in the inability to improve the final output capacity. In view of the deficiencies of the prior art, the present invention provides a production cycle optimization method and system for automated equipment. Summary of the Invention

[0003] The purpose of the present invention is to provide a production cycle optimization method and system for automated equipment.

[0004] The purpose of the present invention can be achieved through the following technical solutions: A production cycle optimization method for automated equipment includes the following steps: Step S1: Collect and store the equipment information of the automated equipment, and construct a digital twin model of the automated equipment according to the obtained equipment information; Step S2: Obtain the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model, obtain the production process duration for the automated equipment to reach the production limit coefficient at different production efficiencies, and obtain the production interval duration for the automated equipment to drop to the production initial coefficient at different production efficiencies; Step S3: Obtain the production cycle of the automated equipment at different production efficiencies according to the production process duration and production interval duration, obtain the total production output and unit production output of the automated equipment at different production efficiencies, and take the production efficiency corresponding to the highest unit production output as the optimal production efficiency; Step S4: Obtain the theoretical output change diagram and actual output change diagram of the automated equipment at the optimal production efficiency, judge whether there is a production fault in the automated equipment according to the comparison result of the two, and generate corresponding production fault information.

[0005] Further, the process of collecting and storing the equipment information of the automated equipment includes: Set up a collection unit and a database. Collect the device information of the automated equipment through the collection unit. The device information includes the specification parameters, process parameters, historical data, environmental data, and maintenance data of the automated equipment, and upload the collected device information to the database for storage.

[0006] Furthermore, the process of constructing a digital twin model of the automated equipment based on the obtained device information includes: Set up a data processing unit. Perform data preprocessing on the obtained device information through the data processing unit to obtain corresponding available information. The process of data preprocessing includes: outlier processing, missing value processing, and normalization processing. Set up a model construction unit. Construct a physical model and a behavior model of the automated equipment based on the available information after data preprocessing through the model construction unit, and integrate the constructed physical model and behavior model to obtain a digital twin model of the automated equipment.

[0007] Furthermore, the process of obtaining the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model includes: Monitor the temperature, pressure, and vibration frequency of the automated equipment in the digital twin model respectively and set production weights to obtain the production coefficient of the automated equipment. Mark the production coefficient before production of the automated equipment as the production initial coefficient. Gradually increase the production coefficient of the automated equipment based on the production initial coefficient to obtain the corresponding production output, obtain the output change coefficient of the automated equipment, set a change coefficient threshold, and compare the output change coefficient with the change coefficient threshold to obtain the production limit coefficient according to the comparison result.

[0008] Furthermore, the process of obtaining the production process duration when the automated equipment reaches the production limit coefficient at different production efficiencies and the production interval duration when the automated equipment drops to the production initial coefficient at different production efficiencies includes: Carry out production in the digital twin model at any production efficiency. Monitor the production coefficient of the automated equipment during the production process. Stop production and obtain the production process duration when the production coefficient reaches the production limit coefficient. Resume production and obtain the production interval duration when the production coefficient drops to the production initial coefficient.

[0009] Furthermore, the process of obtaining the production cycle of the automated equipment at different production efficiencies based on the production process duration and production interval duration, obtaining the total production output and unit production output of the automated equipment at different production efficiencies, and taking the production efficiency corresponding to the highest unit production output as the optimal production efficiency includes: Take the sum of the production process duration and the production interval duration at any production efficiency as the production cycle of the automated equipment at that production efficiency, and obtain the total production output of the automated equipment at that production efficiency; Obtain the unit production output of the automated equipment at that production efficiency based on the obtained production cycle and total production output, obtain the unit production output at other production efficiencies, and take the production efficiency corresponding to the highest unit production output as the optimal production efficiency of the automated equipment.

[0010] Furthermore, the process of obtaining the theoretical output change diagram and the actual output change diagram of the automated equipment at the optimal production efficiency, and judging whether there is a production fault in the automated equipment according to the comparison result between the two, and generating corresponding production fault information includes: In the digital twin model, produce the automated equipment according to the optimal production efficiency, monitor its production output, construct a theoretical output change diagram based on the monitored production output, and obtain an actual output change diagram by the same method in actual production; Compare the obtained theoretical output change diagram and actual output change diagram, and judge whether there is a production fault in the automated equipment according to the comparison result, and generate corresponding production fault information.

[0011] A production cycle optimization system for automated equipment, including a main control center, which is communicatively connected to a data acquisition module, a model construction module, a first acquisition module, a second acquisition module, a cycle optimization module, and a fault monitoring module; The data acquisition module is used to collect and store the equipment information of the automated equipment; The model construction module is used to construct a digital twin model of the automated equipment according to the obtained equipment information; The first acquisition module is used to obtain the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model; The second acquisition module is used to obtain the production process duration of the automated equipment reaching the production limit coefficient at different production efficiencies, and obtain the production interval duration of the automated equipment dropping to the production initial coefficient at different production efficiencies; The cycle optimization module is used to obtain the production cycle of the automated equipment at different production efficiencies based on the production process duration and production interval duration, obtain the total production output and unit production output of the automated equipment at different production efficiencies, and take the production efficiency corresponding to the highest unit production output as the optimal production efficiency; The fault monitoring module is used to obtain the theoretical output change diagram and the actual output change diagram of the automated equipment at the optimal production efficiency, judge whether there is a production fault in the automated equipment according to the comparison result between the two, and generate corresponding production fault information.

[0012] Compared with the prior art, the beneficial effects of the present invention are as follows: 1. Obtain the production limit coefficient of the automated equipment in the digital twin model, and control the automated equipment to produce based on the production limit coefficient, which is beneficial to form a targeted production mechanism for different automated equipment and generally improve the production output capacity; 2. By obtaining the production cycle and total production output of the automated equipment, and then obtaining the unit production output of the automated equipment, and obtaining the best production efficiency of the automated equipment according to the unit production output, the production efficiency most suitable for different automated equipment can be obtained; 3. By obtaining the theoretical output change diagram and actual output change diagram of the automated equipment under the best production efficiency, and judging whether there is a production fault in the automated equipment according to the comparison result of the two, the fault monitoring of the automated equipment can be realized. Description of the Drawings

[0013] Figure 1 is the flowchart of the present invention; Figure 2 is the schematic diagram of the present invention. Detailed Embodiment

[0014] As Figure 1 shown, a production cycle optimization method for automated equipment includes the following steps: Step S1: Collect and store the equipment information of the automated equipment, and construct a digital twin model of the automated equipment according to the obtained equipment information; Step S2: Obtain the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model, obtain the production process duration for the automated equipment to reach the production limit coefficient at different production efficiencies, and obtain the production interval duration for the automated equipment to drop to the production initial coefficient at different production efficiencies; Step S3: Obtain the production cycle of the automated equipment at different production efficiencies according to the production process duration and production interval duration, obtain the total production output and unit production output of the automated equipment at different production efficiencies, and take the production efficiency corresponding to the highest unit production output as the best production efficiency; Step S4: Obtain the theoretical output change diagram and actual output change diagram of the automated equipment under the best production efficiency, judge whether there is a production fault in the automated equipment according to the comparison result of the two, and generate corresponding production fault information.

[0015] It should be further noted that in the specific implementation process, the process of collecting and storing the equipment information of the automated equipment includes: Set up a collection unit and a database. Collect the device information of the automated equipment through the collection unit. The device information includes the specification parameters, process parameters, historical data, environmental data, and maintenance data of the automated equipment. Review the collected device information through the main control center, and upload the device information that passes the review to the database for storage; The specification parameters include, but are not limited to, the physical structure, components, technical specifications, etc. of the automated equipment. The process parameters include, but are not limited to, the speed of the production line, the rate of material input, process steps, etc. The historical data includes, but is not limited to, fault records, maintenance records, performance records, etc. The environmental data includes, but is not limited to, temperature, humidity, gas composition, etc. The maintenance data includes, but is not limited to, fault modes, occurrence time, maintenance measures and results, etc.

[0016] It should be further noted that in the specific implementation process, the process of constructing a digital twin model of the automated equipment based on the obtained device information includes: Set up a data processing unit. Perform data preprocessing on the obtained device information through the data processing unit to obtain corresponding available information. The process of data preprocessing includes: outlier processing, missing value processing, and normalization processing; The outlier processing is used to clean abnormal device information. The outlier processing adopts the method of absolute median deviation for outlier processing. The missing value processing is used to fill in missing device information. The missing value processing adopts the method of filling with statistics. The normalization processing is used to unify the format of device information. The normalization processing adopts the Z-Score standardization method; Set up a model construction unit. Construct a physical model of the automated equipment based on the specification parameters and process parameters in the available information after data preprocessing through the model construction unit. Construct a behavior model of the automated equipment based on the historical data, environmental data, and maintenance data in the available information after data preprocessing. Integrate the constructed physical model and behavior model to obtain a digital twin model of the automated equipment.

[0017] It should be further noted that in the specific implementation process, the process of obtaining the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model includes: In the digital twin model, monitor the temperature, pressure, and vibration frequency of the automated equipment respectively, and mark the monitored temperature, pressure, and vibration frequency as W, Y, and Z respectively. Set production weights for the temperature, pressure, and vibration frequency of the automated equipment respectively, and set the production weight of the temperature as Q w , set the production weight of the pressure as Q y , set the production weight of the vibration frequency as Q z, obtain the production coefficient of the automated equipment, and mark the obtained production coefficient as S;

[0018] Mark the production coefficient of the automated equipment before production as the initial production coefficient. Gradually increase the production coefficient of the automated equipment based on the initial production coefficient to obtain the corresponding first production coefficient, second production coefficient, third production coefficient, fourth production coefficient,..., kth production coefficient, where the production coefficient increased each time is equal. Mark the production outputs obtained by the automated equipment under different production coefficients as the first production output C1, second production output C2, third production output C3, fourth production output C4,..., kth production output C k , obtain the output change coefficient of the automated equipment, and mark the obtained output change coefficient as B;

[0019] Set the change coefficient threshold B0, compare the obtained output change coefficient with the set change coefficient threshold, and mark the production output as the normal state and abnormal state according to the comparison result. If B ≤ B0, mark it as the normal state; if B > B0, mark it as the abnormal state. Obtain the production coefficient corresponding to the production output first marked as the abnormal state, and mark it as the production limit coefficient.

[0020] It should be further noted that in the specific implementation process, the process of obtaining the production process duration of the automated equipment reaching the production limit coefficient at different production efficiencies and the production interval duration of the automated equipment dropping to the initial production coefficient at different production efficiencies includes: Taking any production efficiency as an example, keep this production efficiency in the digital twin model for production. Mark the moment when the automated equipment starts production as the production moment. Monitor the production coefficient of the automated equipment during the production process. Stop production when the production coefficient reaches the production limit coefficient. Mark the moment when the automated equipment stops production as the limit moment. Obtain the time interval between the production moment and the limit moment, and mark the obtained time interval as the production process duration; After production stops, perform operation and maintenance on the automated equipment. Monitor the production coefficient of the automated equipment during the operation and maintenance process. When the production coefficient drops to the initial production coefficient, start production again. Mark the moment when the automated equipment starts production again as the reproduction moment. Obtain the time interval between the limit moment and the reproduction moment, and mark the obtained time interval as the production interval duration; And so on. Use the same method to obtain the production process duration and production interval duration under other production efficiencies respectively, and bind the production process duration and production interval duration under the same production efficiency.

[0021] It should be further noted that in the specific implementation process, the production cycle of the automated equipment at different production efficiencies is obtained based on the production process duration and the production interval duration, the total production output and the unit production output of the automated equipment at different production efficiencies are obtained, and the process of taking the production efficiency corresponding to the highest unit production output as the optimal production efficiency includes: Taking any production efficiency as an example, the production process duration and the production interval duration at this production efficiency are obtained, and the sum of the obtained production process duration and production interval duration is used as the production cycle of the automated equipment at this production efficiency, and the obtained production cycle is marked as T; The production output of the automated equipment at this production efficiency is monitored, the sum of the monitored production output is used as the total production output, and the total production output is marked as C 总 , and the unit production output of the automated equipment at this production efficiency is obtained based on the obtained production cycle and total production output, and the obtained unit production output is marked as C 单 ;

[0022] And so on, the unit production outputs at other production efficiencies are obtained respectively by the same method, the production efficiency corresponding to the highest unit production output is taken as the optimal production efficiency of the automated equipment, and then the optimal production efficiencies of all automated equipment are obtained and applied in actual production.

[0023] It should be further noted that in the specific implementation process, the process of obtaining the theoretical output change diagram and the actual output change diagram of the automated equipment at the optimal production efficiency, judging whether there is a production fault in the automated equipment according to the comparison result of the two, and generating the corresponding production fault information includes: In the digital twin model, the automated equipment is produced according to the optimal production efficiency, its production output is monitored, and a theoretical output change diagram with the abscissa being time and the ordinate being production output is constructed based on the monitored production output. Similarly, an actual output change diagram is obtained by the same method in actual production; The obtained theoretical output change diagram and actual output change diagram are compared, and it is judged whether there is a production fault in the automated equipment according to the comparison result. If the two are the same, it is judged that there is no production fault in the automated equipment and no other operations are performed on it. If the two are different, it is judged that there is a production fault in the automated equipment and the corresponding production fault information is generated.

[0024] Such as Figure 2As shown in the figure, a production cycle optimization system for automated equipment includes a main control center, which is communicatively connected to a data acquisition module, a model construction module, a first acquisition module, a second acquisition module, a cycle optimization module, and a fault monitoring module; The data acquisition module is used to collect and store the equipment information of the automated equipment; The model construction module is used to construct a digital twin model of the automated equipment based on the obtained equipment information; The first acquisition module is used to obtain the production initial coefficient and production limit coefficient of the automated equipment in the digital twin model; The second acquisition module is used to obtain the production process duration for the automated equipment to reach the production limit coefficient at different production efficiencies, and obtain the production interval duration for the automated equipment to drop to the production initial coefficient at different production efficiencies; The cycle optimization module is used to obtain the production cycle of the automated equipment at different production efficiencies based on the production process duration and production interval duration, obtain the total production output and unit production output of the automated equipment at different production efficiencies, and take the production efficiency corresponding to the highest unit production output as the optimal production efficiency; The fault monitoring module is used to obtain the theoretical output change diagram and actual output change diagram of the automated equipment at the optimal production efficiency, judge whether there is a production fault in the automated equipment according to the comparison result of the two, and generate corresponding production fault information.

[0025] The above embodiments are only used to illustrate the technical method of the present invention and not to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those of ordinary skill in the art should understand that the technical method of the present invention can be modified or equivalently replaced without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A production cycle optimization method for automation equipment, characterized in that: The following steps are involved: Step S1: collecting and storing device information of the automation equipment, and building a digital twin model of the automation equipment based on the acquired device information; Step S2: Obtain the production initial coefficient and production limit coefficient of the automation equipment in the digital twin model, obtain the production process duration of the automation equipment to reach the production limit coefficient at different production efficiencies, and obtain the production interval duration of the automation equipment when different production efficiencies drop to the production initial coefficient; Step S3: obtaining the production cycle of the automation equipment at different production efficiencies according to the production process duration and the production interval duration, obtaining the total production output and unit production output of the automation equipment at different production efficiencies, and taking the production efficiency corresponding to the highest unit production output as the optimal production efficiency; Step S4: Obtain a theoretical output change graph and an actual output change graph of the automation equipment under optimal production efficiency, determine whether the automation equipment has a production failure based on a comparison result of the two, and generate corresponding production failure information.

2. A production cycle optimization method for automation equipment according to claim 1, characterized in that: The process of collecting and storing equipment information of automation equipment includes: A collection unit and a database are set up, and the equipment information of the automation equipment is collected through the collection unit. The equipment information includes specification parameters, process parameters, historical data, environmental data, and maintenance data of the automation equipment, and the collected equipment information is uploaded to the database for storage.

3. A production cycle optimization method for automation equipment according to claim 2, characterized in that: The process of building a digital twin model of automation equipment based on the acquired equipment information includes: Setting a data processing unit, through which the acquired device information is preprocessed to obtain corresponding usable information, wherein the data preprocessing process includes: outlier processing, missing value processing, and normalization processing; A model building unit is set up, and the physical model and behavioral model of the automation equipment are built by the model building unit according to the available information after data preprocessing, and the constructed physical model and behavioral model are integrated to obtain the digital twin model of the automation equipment.

4. A production cycle optimization method for automation equipment according to claim 3, characterized in that: The process of obtaining the initial production coefficient and production limit coefficient of the automation equipment in the digital twin model includes: In the digital twin model, the temperature, pressure, and vibration frequency of the automation equipment are monitored and production weights are set to obtain the production coefficient of the automation equipment. The production coefficient of the automation equipment before production is marked as the initial production coefficient. On the basis of the initial production coefficient, the production coefficient of the automation equipment is gradually increased to obtain the corresponding production output, the production change coefficient of the automation equipment is obtained, the change coefficient threshold is set, and the production change coefficient is compared with the change coefficient threshold, and the production limit coefficient is obtained according to the comparison result.

5. A production cycle optimization method for automation equipment according to claim 4, characterized in that: The process of obtaining the production process duration when the automation equipment reaches the production limit coefficient at different production efficiencies and obtaining the production interval duration when the automation equipment drops to the production initial coefficient at different production efficiencies includes: In the digital twin model, production is carried out at any production efficiency, and the production coefficient of the automation equipment is monitored during the production process. When the production coefficient reaches the production limit coefficient, production is stopped and the production process duration is obtained. When the production coefficient drops to the initial production coefficient, production is resumed and the production interval duration is obtained.

6. A production cycle optimization method for automation equipment according to claim 5, characterized in that: The process of obtaining the production cycle of the automation equipment at different production efficiencies based on the production process duration and the production interval duration, obtaining the total production output and unit production output of the automation equipment at different production efficiencies, and taking the production efficiency corresponding to the highest unit production output as the optimal production efficiency includes: The sum of the production process duration and the production interval duration under any production efficiency is taken as the production cycle of the automation equipment under the production efficiency, and the total production output of the automation equipment under the production efficiency is obtained; According to the obtained production cycle and total production output, the unit production output of the automation equipment at this production efficiency is obtained, and the unit production output under other production efficiencies is obtained. The production efficiency corresponding to the highest unit production output is taken as the optimal production efficiency of the automation equipment.

7. A production cycle optimization method for automation equipment according to claim 6, characterized in that: The process of obtaining a theoretical output change graph and an actual output change graph of the automation equipment under the best production efficiency, judging whether the automation equipment has a production failure based on the comparison results of the two, and generating corresponding production failure information includes: In the digital twin model, the automation equipment is produced at the best production efficiency, its production output is monitored, and a theoretical output change graph is constructed based on the monitored production output. The same method is used in actual production to obtain the actual output change graph; The obtained theoretical output change graph is compared with the actual output change graph, and based on the comparison result, it is determined whether there is a production failure in the automation equipment and corresponding production failure information is generated.

8. A production cycle optimization system for automated equipment, characterized in that: The enterprise information security interaction method used to implement any one of claims 1 to 7 comprises a main control center, wherein the main control center is communicatively connected to a data acquisition module, a model building module, a first acquisition module, a second acquisition module, a cycle optimization module, and a fault monitoring module; The data acquisition module is used to collect and store equipment information of the automation equipment; The model building module is used to build a digital twin model of the automation equipment according to the obtained equipment information; The first acquisition module is used to obtain the initial production coefficient and the production limit coefficient of the automation equipment in the digital twin model; The second acquisition module is used to obtain the production process duration of the automation equipment to reach the production limit coefficient at different production efficiencies, and obtain the production interval duration of the automation equipment when the production efficiency drops to the production initial coefficient; The cycle optimization module is used to obtain the production cycle of the automation equipment at different production efficiencies according to the production process duration and the production interval duration, obtain the total production output and unit production output of the automation equipment at different production efficiencies, and take the production efficiency corresponding to the highest unit production output as the optimal production efficiency; The fault monitoring module is used to obtain a theoretical output change diagram and an actual output change diagram of the automation equipment under optimal production efficiency, determine whether the automation equipment has a production fault based on a comparison result of the two, and generate corresponding production fault information.

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