Data integration analysis system and data integration analysis method

Abstract

The embodiment of the present invention provides a data integration analysis system and a data integration analysis method, wherein the data integration analysis system comprises: a first acquisition module for acquiring machine event data; a second acquisition module for acquiring production event data; a data processing module, which is connected to the first acquisition module and the second acquisition module to acquire the original processing time of each product and the capacity index of each batch of products; an analysis module, which is connected to the data processing module and is used to acquire the first matching relationship between the capacity index of each batch of products and the original processing time of each product. Therefore, the production status can be globally analyzed through the capacity index; the matching original processing time can be verified through the first matching relationship, and then the specific production status can be deeply analyzed; thereby improving the efficiency and accuracy of data analysis.

Description

Technical Field

[0001] The embodiments of the present invention relate to the field of semiconductor technology, and in particular to a data integration and analysis system and a data integration and analysis method. Background Art

[0002] As the scale of production in the manufacturing industry expands, a massive amount of production data is generated. For efficiency reasons, traditional practices usually do not process the data, so engineers often need to manually create reports, which results in low analysis efficiency. At present, although some production machines are equipped with supporting production data analysis reports, the reports they provide are too simple to meet the needs of engineers in machine debugging and analysis.

[0003] Therefore, there is an urgent need for a reporting system that can perform customized analysis on the production process data of the machine, and integrate related production data to improve efficiency, so that engineers can conduct analysis quickly and efficiently without stopping the machine, thereby improving the utilization rate of the machine. Summary of the invention

[0004] The technical problem solved by the embodiments of the present invention is to provide a data integration analysis system and a data integration analysis method to solve the problem of low efficiency of data analysis in the production process.

[0005] To solve the above problems, an embodiment of the present invention provides a data integration and analysis system, including: a first acquisition module, used to acquire machine event data; a second acquisition module, used to acquire production event data; a data processing module, the data processing module is connected to the first acquisition module and the second acquisition module, and acquires the original processing time of each product and the production capacity index of each batch of products according to the machine event data and the production event data; an analysis module, the analysis module is connected to the data processing module, the analysis module is used to receive the original processing time of each product and the production capacity index of each batch of products imported by the data processing module, and acquire a first matching relationship between the production capacity index of each batch of products and the original processing time of each product.

[0006] In addition, the analysis module includes a display unit, which is used to visualize the original processing time of each product and the production capacity index of each batch of products.

[0007] In addition, the analysis module includes: a first analysis unit, used to obtain the first matching relationship; a second analysis unit, used to obtain a second matching relationship between the original processing time of each product and the machine event data and the production event data.

[0008] In addition, the analysis module further includes: a third analysis unit, which is used to analyze the production capacity index of each batch of products of at least one machine provided by the data processing module, and the original processing time matching the production capacity index.

[0009] In addition, the analysis module further includes: a fourth analysis unit, which is used to analyze the capacity index of each batch of products in the specified capacity index range provided by the data processing module, and the original processing time matching the capacity index.

[0010] In addition, the analysis module further includes: a fifth analysis unit, which is used to analyze the production capacity index of each batch of products under the specified production formula provided by the data processing module, and the original processing time matching the production capacity index.

[0011] In addition, the data integration and analysis system also includes: a relay database, the data processing module is connected to the first acquisition module and the second acquisition module through the relay database; the relay database is used to summarize the machine event data and the production event data, and import the summarized data into the data processing module.

[0012] In addition, the first acquisition module includes a machine event parsing unit, a network service platform and a machine event database; the machine event parsing unit is used to parse original machine event information, generate the machine event data, and upload the machine event data to the network service platform; the network service platform is used to exchange or integrate the machine event data of multiple machines; the machine event database is used to obtain or save the data imported by the network service platform; the machine event database is connected to the relay database.

[0013] In addition, the second acquisition module includes a production event database, which is used to acquire and store the production event data; the production event database is connected to the relay database.

[0014] In addition, the data processing module includes a big data platform.

[0015] In addition, the big data platform includes a function for calculating the net processing time of each product according to the production event data and the machine event data, calculating the original processing time according to the net processing time, and calculating the original processing time and the capacity index according to the original processing time, and the calculation formula of the capacity index is:

[0016]

[0017] Wherein, WPH refers to the capacity index, MOVE refers to the number of products, Production Time refers to the net processing time, i refers to the i-th process, Production Time i Refers to the original processing time stated.

[0018] In addition, the data processing module is also used to calculate the product idle time and the product waiting time based on the production event data and the machine event data; the analysis module also includes an integration unit, which is used to comprehensively integrate the original processing time, the product idle time and the product waiting time of each product; the display unit is also used to visualize the original processing time, the product idle time and the product waiting time of each product.

[0019] An embodiment of the present invention also provides a data integration and analysis method, which is characterized by including: acquiring machine event data and production event data; acquiring the original processing time of each product and the production capacity index of each batch of products based on the machine event data and the production event data; acquiring a first matching relationship between the production capacity index of each batch of products and the original processing time of each product.

[0020] In addition, the data integration and analysis method also includes: setting a threshold value for the production capacity indicator of each batch of products; verifying the production capacity indicator that is lower than the threshold value, and verifying the original processing time that matches the production capacity indicator through the first matching relationship.

[0021] In addition, after obtaining the original processing time of each product and the production capacity index of each batch of products, it also includes: obtaining a second matching relationship between the original processing time of each product and the production event data and the machine event data.

[0022] In addition, after verifying the original processing time that matches the production capacity indicator, the method further includes: verifying the production event data and the machine event data that match the original processing time through the second matching relationship.

[0023] Compared with the prior art, the technical solution provided by the embodiment of the present invention has the following advantages:

[0024] The analysis module of the data integration and analysis system can obtain the first matching relationship between the capacity index of each batch of products and the original processing time of each product. Therefore, the production status can be quickly analyzed globally through the capacity index of each batch of products; the matching original processing time can be quickly checked through the first matching relationship, and then the specific production status can be deeply analyzed, thereby improving the efficiency and accuracy of the data analysis process.

[0025] In addition, the processing module includes a big data platform, which can quickly process massive amounts of data and improve data processing efficiency.

[0026] In addition, the data processing module is also used to calculate product idle time and product waiting time based on production event data and machine event data, so as to provide more comprehensive data and improve the accuracy of data analysis. BRIEF DESCRIPTION OF THE DRAWINGS

[0027] One or more embodiments are exemplarily described by pictures in the corresponding drawings, and these exemplifications do not constitute limitations on the embodiments. Unless otherwise stated, the pictures in the drawings do not constitute proportional limitations.

[0028] Figure 1 and Figure 2 A schematic diagram of a data integration and analysis system provided in a first embodiment;

[0029] Figure 3 A schematic diagram of a data integration and analysis system provided in a second embodiment;

[0030] Figure 4 A schematic diagram of a data integration and analysis method provided in a third embodiment;

[0031] Figure 5 A schematic diagram of the interface of the capacity indicator report provided in the third embodiment;

[0032] Fig. 6A , 6B 6C is a schematic diagram of the interface of the original processing time report provided in the third embodiment. DETAILED DESCRIPTION

[0033] As can be seen from the background technology, production data analysis has the problem of low efficiency.

[0034] After analysis, the main reasons include: the production data analysis report currently equipped with production machines is too simple and cannot handle the massive data brought about by the increase in production capacity; the data integration level is low and it is impossible to quickly compare various types of data; the data correlation is low and it is impossible to trace back to the original production status through the data.

[0035] To solve the above problems, the present invention provides a data integration analysis system and a data integration analysis method. The analysis module of the data integration analysis system can obtain the first matching relationship between the production capacity index of each batch of products and the original processing time of each product. Therefore, the production status can be quickly analyzed globally through the production capacity index of each batch of products; the matching original processing time can be quickly checked through the first matching relationship, and then the specific production status can be deeply analyzed; thereby improving the efficiency and accuracy of the data analysis process.

[0036] In order to make the purpose, technical scheme and advantages of the embodiments of the present invention clearer, the embodiments of the present invention will be described in detail below with reference to the accompanying drawings. However, it will be appreciated by those skilled in the art that in the embodiments of the present invention, many technical details are provided to enable the reader to better understand the present application. However, even without these technical details and various changes and modifications based on the following embodiments, the technical scheme claimed in the present application can be implemented.

[0037] The first embodiment of the present invention provides a data integration and analysis system. Figure 1-Figure 2 This is a schematic diagram of the data integration and analysis system provided in this embodiment.

[0038] refer to Figure 1 In this embodiment, the data integration and analysis system includes: a first acquisition module 100, used to acquire machine event data; a second acquisition module 110, used to acquire production event data; a data processing module 120, the data processing module 120 is connected to the first acquisition module 100 and the second acquisition module 110, and acquires the original processing time of each product and the production capacity index of each batch of products according to the machine event data and the production event data; an analysis module 130, the analysis module 130 is connected to the data processing module 120, and the analysis module 130 is used to receive the original processing time of each product and the production capacity index of each batch of products imported by the data processing module 120, and acquire a first matching relationship between the production capacity index of each batch of products and the original processing time of each product.

[0039] The following is a detailed description with reference to the accompanying drawings.

[0040] refer to Figure 2 The first acquisition module 100 is used to acquire machine event data. The machine event data includes data such as product, process location, occupation flag, process time and machine control command.

[0041] The first acquisition module 100 includes a machine event parsing unit 101 , a network service platform 102 , and a machine event database 103 .

[0042] The machine event analysis unit 101 is used to analyze the original machine event information, generate machine event data, and upload the machine event data to the network service platform 102. In this embodiment, the machine event analysis unit 101 is a machine event analysis software installed on each machine. The machine event analysis software automatically uploads and downloads information according to production operation requirements and generates machine event data. The machine event data records the original state of the production process. When performing machine debugging analysis, the machine event data can be used to deeply discover the problem points and improve them.

[0043] The network service platform 102 is used to exchange or integrate machine event data of multiple machines.

[0044] The machine event database 103 is used to obtain or save data imported by the network service platform 102. The machine event database 103 can perform operations such as adding, updating, and intercepting machine event data.

[0045] The second acquisition module 110 includes a production event database 111, which is used to acquire and store production event data, including production formulas, production raw materials and other related data.

[0046] The relay database 140 connects the data processing module 120 with the first acquisition module 100 and the second acquisition module 110. Specifically, the machine event database 103 and the production event database 111 are connected to the relay database 140.

[0047] The relay database 140 is used to aggregate machine event data and production event data, and import the aggregated data into the data processing module 120. The relay database 140 is conducive to improving the stability and flexibility of the data integration and analysis system, and can quickly aggregate or restore data to prevent data loss.

[0048] It is understandable that in other embodiments, the first acquisition module and the second acquisition module may also be directly connected to the data processing module. Specifically, the machine event database of the first acquisition module and the production event database of the second acquisition module are connected to the relay database.

[0049] The data processing module 120 includes a big data platform, which can handle massive data storage, calculation and uninterrupted data real-time calculation. The big data platform includes: Hive, HDFS software in Hadoop, and Rapidminer software. The big data platform can quickly process massive data, and even if the production capacity continues to increase, it will not affect the processing efficiency of the data integration and analysis system.

[0050] In other embodiments, the data processing module may also include an application program and a database.

[0051] Specifically, the big data platform calculates the net processing time of each product based on the production event data and the machine event data, calculates the original processing time based on the net processing time, and calculates the capacity index based on the original processing time.

[0052] For example, in the wafer production process, the net processing time of the wafer refers to the difference between the production start time and the production end time of the wafer in a production process. The raw processing time (RPT) refers to the difference between the production end time of the wafer in the last production process and the production start time of the wafer in the first production process. The wafer capacity index (WPH, Wafer Per Hour) refers to the number of wafers produced per hour.

[0053] The calculation formula of the capacity index is: Among them, WPH refers to the capacity index, MOVE refers to the number of products, Production Time refers to the net processing time, and i refers to the i-th process. Production Time i Refers to the original processing time, namely RPT.

[0054] The big data platform also associates machine event data with production event data, mainly including the association between machine control commands and production recipe data.

[0055] The analysis module 130 includes: a first analysis unit 131, which is used to obtain a first matching relationship. That is, the first analysis unit 131 matches the capacity index of each batch of products with the original processing time of each product. Therefore, the original processing time of each product corresponding to each batch of products can be quickly obtained through the capacity index of each batch of products.

[0056] The analysis module 130 may further include: a second analysis unit 132, which is used to obtain a second matching relationship between the original processing time of each product and the machine event data and the production event data. That is, the second analysis unit 132 matches the original processing time of each product with the machine event data and the production event data. Therefore, the corresponding machine event data and production event data can be quickly obtained through the original processing time of each product.

[0057] In this way, the first analysis unit 131 and the second analysis unit 132 are combined to match all data in the data integration process. The corresponding machine event data and production event data can be quickly obtained through the production capacity index of each batch of products. The correlation between different types of data is stronger, and the analysis is more efficient and comprehensive.

[0058] The analysis module 130 may further include: a third analysis unit 133, which is used to analyze the capacity index of each batch of products of at least one machine provided by the data processing module 120, and the original processing time matching the capacity index. That is, the third analysis unit 133 may analyze the capacity index of each batch of products of one machine and the original processing time matching the capacity index of one machine from the capacity index of all batches of products according to the instruction of the engineer; or analyze the capacity index of each batch of products of multiple machines and the original processing time matching the capacity index of multiple machines.

[0059] Furthermore, the third analysis unit 133 is also used to analyze the production event data and machine event data that match the original processing time of one machine, or to analyze the production event data and machine event data that match the original processing time of multiple machines.

[0060] For example, the third analysis unit 133 may analyze the production status of a machine in a certain production process, or analyze the production status of different machines in the same production process, or analyze the production status of different machines in several production processes.

[0061] Therefore, the third analysis unit 133 can analyze the production status of a specific machine or multiple machines according to the engineer's instructions. In this way, the analysis within a machine and between machines can be completed without stopping the machine, and by comparing the production status of multiple machines, it is easier to find the problem machine, thereby completing the debugging analysis and improving the machine's utilization rate.

[0062] The analysis module 130 may further include: a fourth analysis unit 134, which is used to analyze the capacity index of each batch of products in the specified capacity index interval provided by the data processing module 120, and the original processing time matching the capacity index. That is, the fourth analysis unit 134 can analyze the capacity index of each batch of products in the specified capacity index interval and the matching original processing time from the capacity index of all batches of products according to the instructions of the engineer. For example, the specified capacity index interval can be either a high capacity index interval or a low capacity index interval.

[0063] Furthermore, the fourth analysis unit 134 is also used to analyze the production event data and machine event data that match the original processing time.

[0064] Therefore, the fourth analysis unit 134 can analyze the production status in the specified capacity index interval quickly according to the engineer's instructions. For example, by comparing the production status in the low capacity index interval with the high capacity index interval, it is easier to improve the efficiency and accuracy of the analysis, thereby achieving the purpose of improving the production process.

[0065] The analysis module 130 may further include: a fifth analysis unit 135, which is used to analyze the capacity index of each batch of products under the specified production formula provided by the data processing module 120, and the original processing time matching the capacity index. That is, the fifth analysis unit 135 may analyze the capacity index of each batch of products under the specified production formula and the matching original processing time from the capacity index of all batches of products according to the instructions of the engineer.

[0066] Furthermore, the fifth analyzing unit 135 is also used to analyze the production event data and machine event data that match the original processing time.

[0067] Therefore, the fifth analysis unit 135 can analyze the production status under the fast specified production formula according to the engineer's instructions, that is, the fifth analysis unit 134 can integrate the production formula and the machine parameters. By comparing the production status under different production formulas, the production formula can be improved to improve the production efficiency and quality of the product.

[0068] It is understandable that in other embodiments, the third analysis unit, the fourth analysis unit and the fifth analysis unit may not be present.

[0069] The analysis module 130 includes a display unit 136, which is used to visualize the original processing time of each product and the production capacity index of each batch of products. The display unit 136 can be a Spotfire platform.

[0070] Specifically, the display unit 136 is connected to the first analysis unit 131, the second analysis unit 132, the third analysis unit 133, the fourth analysis unit 134 and the fifth analysis unit 135, and visualizes the analysis results. Therefore, engineers are no longer required to manually prepare reports, thereby saving time and improving work efficiency.

[0071] The capacity index and the original processing time are displayed in a set of report systems. Among them, the capacity index is displayed in one report, and the original processing time is displayed in another report. The capacity index report is linked to the original processing time report. For example, by clicking on the capacity index of a batch of products, you can jump to the original processing time report that matches the capacity index of the batch of products. In the original processing time report, the original processing time of each product in the batch of products is displayed. In this way, you only need to use one set of report systems to view it, and the analysis is more convenient and efficient. The original processing time of the same batch of products is displayed in the same color, so that the capacity index of each batch of products can be quickly compared. Furthermore, the display unit 136 can also display the original processing time of each batch of products in the specified production index range, or the original processing time of each batch of products under the specified production formula, or the original processing time of each batch of products on the same machine in the same color according to the instructions of the engineer.

[0072] Furthermore, for the display unit 136, you can choose to display the original production time of each product on the machine, or you can choose to display the production time of a specific position on the machine, as well as the integrated data of the production time of each position inside the machine, so that engineers can avoid manual matching work.

[0073] In summary, the data integration and analysis system provided in this embodiment can solve the problems of the dispersion of production process data of each production machine and the time-consuming operation of massive data through the settings of the first acquisition module 100, the second acquisition module 110, the data processing module 120 and the analysis module 130, and provides rapid, flexible and targeted development for subsequent data analysis.

[0074] A second embodiment of the present invention provides a data integration and analysis system. Figure 3 This is a schematic diagram of the data integration and analysis system provided in this embodiment. Figure 3 The data integration and analysis system of this embodiment is substantially the same as the data integration and analysis system of the first embodiment, and the main differences include: in this embodiment, the data processing module 220 is also used to calculate the product idle time and the product waiting time according to the production event data and the machine event data; the analysis module 230 also includes an integration unit 237, and the integration unit 237 is used to comprehensively integrate the original processing time, product idle time and product waiting time of each product; the display unit 236 is also used to visualize the original processing time, product idle time and product waiting time of each product.

[0075] The following will be described in detail with reference to the accompanying drawings. For modules in this embodiment that are the same or similar to those in the first embodiment, please refer to the first embodiment and will not be described in detail here.

[0076] The data processing module 220 is also used to calculate the product idle time and product waiting time based on the production event data and the machine event data. The product idle time (Idle Time) is the difference between the start time of a process and the end time of the previous process. The product waiting time (Wait Time) is the difference between the start time of the first process and the time when production starts. If only the production time on the machine, that is, the original production time, is considered, it is easy to ignore the overall situation of the entire production. Therefore, calculating the product idle time and product waiting time can improve the completeness and accuracy of data analysis.

[0077] The integration unit 237 is used to comprehensively integrate the original processing time, product idle time and product waiting time of each product, that is, the integration unit 237 comprehensively integrates the time of each product from the start of production to the end of production.

[0078] Furthermore, the first analysis unit 231 is also used to match the integrated original processing time, product idle time and product waiting time with the production capacity indicator.

[0079] The second analysis unit 232 is further used to match the integrated original processing time, product idle time and product waiting time with the original production event data and the machine production event data.

[0080] The third analysis unit 233 is further used to analyze the product idle time and product waiting time of at least one machine.

[0081] The fourth analyzing unit 234 is further configured to analyze the product idle time and product waiting time in the specified capacity index interval.

[0082] The fifth analyzing unit 235 is further used to analyze the product idle time and product waiting time under the specified production recipe.

[0083] The display unit 236 is also used to visualize the original processing time, product idle time and product waiting time of each product. That is, the display unit 236 presents the original processing time, product idle time and product waiting time of each product in the same report. The display unit 236 links the capacity indicator with the original processing time, product idle time and product waiting time; thus, by selecting the capacity indicator of a batch of products, the report page can jump to the original processing time, product idle time and product waiting time report that matches the capacity indicator.

[0084] In summary, the data analysis system of this embodiment calculates, analyzes and displays product idle time and product waiting time, which can improve the completeness and accuracy of data analysis.

[0085] The third embodiment of the present invention provides a data integration and analysis method. The data integration and analysis method of this embodiment can be implemented using the data integration and analysis system of the first embodiment or the second embodiment. Figure 4 Schematic diagram of the data integration analysis method.

[0086] The following is a detailed description with reference to the accompanying drawings.

[0087] refer to Figure 4 , data integration and analysis methods include:

[0088] S301: Acquire machine event data and production event data.

[0089] S302: Obtain the original processing time of each product and the production capacity index of each batch of products according to the machine event data and the production event data.

[0090] Among them, machine event data and production event data are relatively complex and difficult to analyze, and need to be converted into raw processing time and capacity indicators. The capacity indicator of each batch of products is the most intuitive, and problems can be directly discovered by comparing the shipment volume in a specific time period; the raw processing time is not intuitive enough relative to the capacity indicator, but it can reflect a more detailed production situation.

[0091] S303: Obtain a first matching relationship between the production capacity index of each batch of products and the original processing time of each product.

[0092] S304: Obtain a second matching relationship between the original processing time of each product and the production event data and the machine event data.

[0093] S305: Setting a threshold value of the production capacity indicator for each batch of products.

[0094] To improve the efficiency of analysis, each batch of products can be divided into time segments, and multiple batches of products within a specific time period can be selected to set the capacity indicator threshold.

[0095] S306: Check the production capacity indicators that are below the threshold.

[0096] Capacity indicators that are below the threshold are abnormal capacity indicators. Engineers can analyze abnormal capacity indicators.

[0097] refer to Figure 5 , Figure 5 This is a schematic diagram of an interface for displaying production capacity indicators in a report, wherein each dot 501 represents each batch of products, and the threshold 502 may be a value preset in advance by an engineer.

[0098] S307: Checking the original processing time that matches the production capacity indicator through the first matching relationship.

[0099] That is, check the abnormal original processing time that matches the abnormal capacity index.

[0100] S308: Verify the production event data and machine event data that match the original processing time through the second matching relationship.

[0101] That is, check the production event data and machine event data that match the abnormal original processing time.

[0102] refer to Fig. 6A , 6B , 6C, Fig. 6A This is a diagram of the interface that visualizes the original processing time of each product. Figure 6B A diagram of the interface that visualizes the original processing time and product idle time of each product. Figure 6C A diagram of the interface that visualizes the original processing time and product idle time and product waiting time of each product. Figure 5 When selecting the dot 501 in FIG. 6 , the data integration and analysis system can obtain the original processing time corresponding to the selected dot 501 and visualize the multiple products corresponding to the batch of products through reports such as those shown in 6A, 6B or 6C.

[0103] In summary, the abnormal capacity index is checked, and the production event data and machine event data corresponding to the abnormal capacity index are found through the first matching relationship and the second matching relationship. In this way, the original production status can be traced back through the data, thereby improving the analysis efficiency and improving the production process.

[0104] Those skilled in the art will appreciate that the above embodiments are specific examples of the present invention, and in practical applications, various changes may be made to the embodiments in form and detail without departing from the spirit and scope of the present invention. Any person skilled in the art may make changes and modifications without departing from the spirit and scope of the present invention, and therefore the scope of protection of the present invention shall be subject to the scope defined in the claims.

Claims

1. A data integration and analysis system, characterized in that: include: The first acquisition module is used to acquire machine event data; The second acquisition module is used to acquire production event data; A data processing module, the data processing module includes a big data platform, the data processing module is connected to the first acquisition module and the second acquisition module, and acquires the original processing time of each product and the capacity index of each batch of products according to the machine event data and the production event data, wherein the net processing time of each product is calculated according to the production event data and the machine event data, the original processing time is calculated according to the net processing time, and the capacity index is calculated according to the original processing time, and the calculation formula of the capacity index is: Wherein, WPH refers to the capacity index, MOVE refers to the number of products, Production Time refers to the net processing time, i refers to the i-th process, Production Time i refers to the stated original processing time; An analysis module is connected to the data processing module, and is used to receive the original processing time of each product and the production capacity index of each batch of products imported by the data processing module, and obtain a first matching relationship between the production capacity index of each batch of products and the original processing time of each product.

2. The data integration and analysis system according to claim 1, characterized in that: The analysis module includes a display unit, which is used to visualize the original processing time of each product and the production capacity index of each batch of products.

3. The data integration and analysis system according to claim 1, characterized in that: The analysis module includes: a first analysis unit, used to obtain the first matching relationship; a second analysis unit, used to obtain a second matching relationship between the original processing time of each product and the machine event data and the production event data.

4. The data integration and analysis system according to claim 1 or 3, characterized in that: The analysis module further includes: a third analysis unit, configured to analyze the production capacity index of each batch of products of at least one machine provided by the data processing module, and the original processing time matching the production capacity index.

5. The data integration and analysis system according to claim 1 or 3, characterized in that: The analysis module further includes: a fourth analysis unit, configured to analyze the capacity index of each batch of products in the specified capacity index range provided by the data processing module, and the original processing time matching the capacity index.

6. The data integration and analysis system according to claim 1 or 3, characterized in that: The analysis module also includes: a fifth analysis unit, which is used to analyze the production capacity index of each batch of products under the specified production formula provided by the data processing module, and the original processing time matching the production capacity index.

7. The data integration and analysis system according to claim 1, characterized in that: Also includes: A relay database, the data processing module is connected to the first acquisition module and the second acquisition module through the relay database; the relay database is used to summarize the machine event data and the production event data, and import the summarized data into the data processing module.

8. The data integration and analysis system according to claim 7, characterized in that: The first acquisition module includes a machine event parsing unit, a network service platform and a machine event database; the machine event parsing unit is used to parse original machine event information, generate the machine event data, and upload the machine event data to the network service platform; the network service platform is used to exchange or integrate the machine event data of multiple machines; the machine event database is used to acquire or save data imported by the network service platform; the machine event database is connected to the relay database.

9. The data integration and analysis system according to claim 7, characterized in that: The second acquisition module includes a production event database, which is used to acquire and store the production event data; the production event database is connected to the relay database.

10. The data integration and analysis system according to claim 2, characterized in that: The data processing module is also used to calculate the product idle time and the product waiting time based on the production event data and the machine event data; the analysis module also includes an integration unit, which is used to comprehensively integrate the original processing time, the product idle time and the product waiting time of each product; the display unit is also used to visualize the original processing time, the product idle time and the product waiting time of each product.

11. A data integration analysis method, characterized in that: include: Obtain machine event data and production event data; The original processing time of each product and the capacity index of each batch of products are obtained according to the machine event data and the production event data, including: calculating the net processing time of each product according to the production event data and the machine event data, calculating the original processing time according to the net processing time, and calculating the capacity index according to the original processing time, and the calculation formula of the capacity index is: Wherein, WPH refers to the capacity index, MOVE refers to the number of products, Production Time refers to the net processing time, i refers to the i-th process, Production Time i refers to the stated original processing time; A first matching relationship between the production capacity indicator of each batch of products and the original processing time of each product is obtained.

12. The data integration and analysis method according to claim 11, characterized in that: Also includes: A threshold value of the production capacity indicator for each batch of products is set; the production capacity indicator that is lower than the threshold value is checked, and the original processing time that matches the production capacity indicator is checked through the first matching relationship.

13. The data integration and analysis method according to claim 12, characterized in that: After obtaining the original processing time of each product and the production capacity index of each batch of products, the method further includes: obtaining a second matching relationship between the original processing time of each product and the production event data and the machine event data.

14. The data integration and analysis method according to claim 13, characterized in that: After checking the original processing time that matches the production capacity indicator, the method further includes: checking the production event data and the machine event data that match the original processing time through the second matching relationship.

Images