Chip mounter utilization rate calculation and operation process monitoring method and system

Abstract

The invention discloses a chip mounter utilization rate calculation and operation process monitoring method and system, and relates to the field of integrated circuit packaging. A patch equipment time utilization rate baseline calculation model is constructed based on computer software, and a patch equipment state and utilization rate real-time calculation method and a monitoring system are established through data acquisition and business analysis and data processing and analysis based on data acquisition data, so that real-time monitoring and diagnosis of the running state and utilization rate of the patch equipment are realized. According to the method, the accuracy and the calculation efficiency of the time utilization rate of the multi-chip assembly automatic chip mounting equipment can be remarkably improved, and the requirement for optimizing and improving the production efficiency of multi-chip assembly automatic chip mounting is met.

Description

Technical Field

[0001] This invention relates to the field of integrated circuit packaging, specifically to a method and system for calculating the utilization rate and monitoring the operation process of a pick-and-place machine, and further to a method and system for calculating the utilization rate and monitoring the operation process of a pick-and-place machine based on the correlation between data acquisition and business data. Background Technology

[0002] The statements in this section are provided only as background information in connection with this disclosure and may not constitute prior art.

[0003] Multi-chip modules (MCMs) are high-density microelectronic components that assemble bare chips, discrete components, and other devices onto a high-density interconnect substrate, interconnecting and packaging them to achieve specific functions. Typical assembly elements include bare chips, discrete components, flexible circuit chips, bonding wires, and package shells. Typical assembly processes include reflow soldering, die bonding, eutectic bonding, flip-chip bonding, and wire bonding. To meet the demands for improved production efficiency, process precision, and production consistency in MCMs, the proportion of automated bare chip assembly is gradually increasing. Automated assembly of bare chips in MCMs relies on automated surface mount machines (SMTs) for the placement process. With the increasing demand for increased production capacity and shorter cycle times in next-generation military electronic equipment, as well as the increasing integration density of MCMs, the types and quantities of MCMs to be assembled in the micro-assembly surface mount process are gradually expanding, placing higher demands on the placement efficiency and equipment utilization of automated SMTs. Automatic placement machines operate in various states and undergo multiple processes within the assembly workshop. The combination of these states and processes, along with their duration, significantly impacts the utilization rate of the placement machine. Real-time monitoring of the placement machine's status is a prerequisite for monitoring its utilization rate. Accurate and efficient real-time monitoring of the placement machine's status and its utilization rate calculations play a crucial role in evaluating equipment performance, production cycle time, production scheduling, and overall production efficiency. Traditional methods for monitoring placement machine utilization and operation include on-site timing observation, manual experience-based estimation, conceptual formula calculations, and log data extraction. These traditional methods heavily rely on manual observation and experience data, resulting in low efficiency and accuracy, and are no longer sufficient to meet the current application requirements for improving placement equipment utilization and achieving precise production scheduling. When acquiring relevant computational data using equipment data acquisition technology, traditional analysis methods simply treat the collected equipment status data as direct calculation data. This results in insufficient data analysis depth and a lack of correlation with the actual operating status and actions of the placement machine. Consequently, the equipment status data in the data acquisition space has a many-to-many mapping to the actual operating status, and the calculated raw data cannot reflect the true production status and utilization time of the equipment. This calculation logic based on a continuous time axis contradicts the discrete event-triggered data acquisition mode of automated die placement equipment, because the triggering of a single equipment action event does not represent that the placement machine is in an effective utilization state. Using this data, which is detached from the actual production status of the equipment, for equipment utilization calculation and operation monitoring cannot truly and accurately reflect the actual working status of the placement equipment. Furthermore, traditional methods only rely on on-site inspection, experience, logs, and data acquisition to calculate and monitor equipment utilization, lacking a correlation with actual planned tasks to further provide feedback on whether utilization targets are met.

[0004] Chinese patent CN113037970A discloses an image data acquisition and transmission device and method for a pick-and-place machine, enabling better coordination between the machine vision system and motion control module to achieve more accurate component image acquisition and faster image data transmission, resulting in better component image quality. Chinese patent CN104244605A discloses a method to improve SMT (Surface Mount Technology) production efficiency and equipment utilization. By arranging all equipment into "teams" and "groups," orders for two or more machine types can be simultaneously scheduled for production. The production line configuration is tailored to each machine type to be produced in real time, improving production efficiency and reducing equipment idle time. Chinese patent CN116723691A discloses a method, system, device, and medium for real-time monitoring of pick-and-place machine mounting. It uses a computer clock to monitor the pick-and-place machine's mounting records in real time, compares the acquired mounting record data with the source program data, and generates records of unmounted components in real time, achieving 100% accurate reading of unmounted component records and improving surface mount generation efficiency. The aforementioned patents demonstrate that monitoring relevant production data during the surface mount equipment (SMT) manufacturing process using data acquisition technology is feasible and offers significant advantages in improving equipment utilization and production line efficiency. However, in the multi-chip module industry, no patents related to SMT equipment utilization calculation and operational monitoring have been published. To address the challenges of numerous SMT equipment states, frequent state transitions, and the difficulty in correlated equipment states with actual production actions in current automated multi-chip module production, this invention proposes a method and system for calculating SMT equipment utilization and monitoring operational processes in automated multi-chip module production lines, based on the production characteristics of automated SMT equipment and the SMT process. This improves the efficiency and accuracy of production status and utilization control, better meeting the needs of increased equipment utilization and shorter production cycles in automated production lines. Summary of the Invention

[0005] The purpose of this invention is to address the problems existing in the prior art by providing a method and system for calculating the utilization rate and monitoring the operation process of a multi-chip component automated placement equipment based on data acquisition and business data correlation. This involves constructing a baseline calculation model for the time utilization rate of the placement equipment using computer software, and establishing a real-time calculation method and monitoring system for the status and utilization rate of the placement equipment through data acquisition and business analysis, data processing, and analysis based on the acquired data. This enables real-time monitoring and diagnosis of the placement equipment's operating status and utilization rate. This invention can significantly improve the accuracy and calculation efficiency of the time utilization rate of multi-chip component automated placement equipment, meeting the needs for optimizing and improving the production efficiency of multi-chip component automated placement.

[0006] The technical solution of the present invention is as follows: A method for calculating the utilization rate of a pick-and-place machine and monitoring its operation includes: Step S1: Establish a baseline set of time utilization for placement equipment; based on the physical relationship dataset and work-in-process task dataset of the placement machine, use simulation software to establish the target model and basic parameters of the placement machine, and calculate the time utilization baseline table of each placement machine within a set time period, which will be used as a reference benchmark for subsequent calculations. Step S2: Establish the original dataset of the pick-and-place machine during operation; collect discrete events and event message data of the pick-and-place machine in real time through the communication protocol, and generate and store the event table, message table, status table, alarm table and recipe table in the database; Step S3: Establish a mapping set between business data and data acquisition data; based on the business logic of the pick-and-place machine, map the business status to the data acquisition status one by one to form a status mapping set; and map business actions to data acquisition events to form an action-event mapping set, which is used to realize the association between business processes and data acquisition events; Step S4: Establish a set of business process sequences; wherein, the standard action sequence is used to define the necessary conditions for determining the category of a business process; the process identification event sequence includes key data acquisition events that can identify the start, middle and end of a business process, and are used to uniquely identify each type of business process; Step S5: Calculate the business process time; establish an independent analysis database, import the raw data collection data into the analysis database after format standardization and field unification; through time window segmentation, key event sequence matching and label filling, merge discrete event segments into corresponding business processes; and calculate the duration of each business process based on the time difference of event segments with the same label. Step S6: Calculate the time utilization rate of the pick and place machine and perform visual monitoring; obtain the calculated business process time and baseline utilization rate from the analysis database and baseline table respectively; calculate the time utilization rate of each pick and place machine and pick and place unit according to the set calculation rules; and display and compare the duration, utilization rate, in-process status, switching status and alarm status of each status through the visual interface.

[0007] Further, step S1 includes: Step S11: Construct a simulation model; Based on the physical relationship dataset and work-in-process task dataset of the pick-and-place machine, use simulation software to establish the target model of the pick-and-place machine, and set the production cycle, equipment parameters, processing cycle time and process constraints. Step S12: Calculate the baseline utilization rate; Under the simulation model, run the simulation according to the set time period to obtain the running time and idle time of each pick and place machine under different working conditions, and calculate the time utilization rate baseline table of each pick and place machine within the set time period. Step S13: Generate a baseline set; summarize the time utilization baseline tables of each pick and place machine to form a pick and place equipment time utilization baseline set, which will be used as a reference benchmark for subsequent pick and place machine utilization calculation and operation status monitoring.

[0008] Further, step S2 includes: Step S21: Collect data during the operation of the pick-and-place machine; collect discrete events and event messages during the operation of the pick-and-place machine in real time through the communication protocol. The discrete events and event messages include event ID, event name, event time, event message content, equipment status, alarm information and recipe information. Step S22: Generate and store data tables; Generate event tables, message tables, status tables, alarm tables and recipe tables according to the type of the collected discrete events and event message data, and store them in the data acquisition database to form the original equipment data of the chip mounter operation process; Step S23: Construct the original equipment dataset; organize and collect the information in the data table according to the event time or event ID to form the original equipment dataset of the pick-and-place machine operation process.

[0009] Further, step S3 includes: Step S31: Establish a state mapping set; Based on the business logic and operating status of the pick-and-place machine, map the business status to the data acquisition status. The business status includes control status, switching status, idle status, alarm status, and power-off or offline status. The corresponding data acquisition status includes INIT, IDLE, HOME, READY, SETUP, ABORT, OPERATOR, LOOP, STEP, and EMERGENCY statuses defined by the SECM GEM protocol. The state mapping set of the pick-and-place machine is formed through the correspondence. Step S32: Establish an action-event mapping set; Based on the correspondence between the actual operation actions and data acquisition events during the operation of the pick-and-place machine, map the business actions and data acquisition events one by one. The business actions include power-on, initialization, loading the material box, picking up the material box, installing the nozzle, and removing the nozzle. The corresponding data acquisition events include the event ID, event name, and event meaning. The action-event mapping set of the pick-and-place machine is formed through the mapping relationship. Step S33: Establish the relationship between business processes and data acquisition; based on the state mapping set and action-event mapping set, establish the correspondence between business processes and data acquisition events to realize the association mapping between business data and data acquisition data.

[0010] Further, step S4 includes: Step S41: Establish a standard action sequence; based on the business action logic of the pick and place machine, arrange and combine the necessary actions that can determine the business process category in sequence to form a standard action sequence for business process identification. The standard action sequence is used to classify and determine different business processes in the operation of the pick and place machine. Step S42: Establish a process identification event sequence; based on the key data acquisition events during the operation of the pick-and-place machine, select key events that can identify the start, progress, and end of the business process, and form a process identification event sequence in chronological order. The process identification event sequence can uniquely identify the corresponding business process type. Step S43: Form a business process sequence set; associate the standard action sequence with the process identification event sequence to form a business process sequence set for the pick-and-place machine.

[0011] Further, step S5 includes: Step S51: Establish an analysis database; establish an analysis database independent of the data acquisition database for data retrieval and storage during the time utilization calculation process, thereby achieving read / write separation between the data acquisition database and the analysis database; Step S52: Data Processing; The original dataset of the device is processed, including data acquisition, data conversion, data acquisition-business data association and calculation, and data storage. Data acquisition involves obtaining event tables, message tables, status tables, alarm tables, and recipe tables from the data acquisition database through setting data interfaces and parameter passing. Data conversion includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation process matches the unified data to the corresponding business process through time window segmentation, data association matching, and association tag filling. The data storage process stores the processing results in the process information table and process time table of the analysis database. Step S53: Data calculation; The data in the analysis database is processed by computer software, and the business process time and total operation time are calculated based on the matching results. The business process time is equal to the end time of the data segment with the same label minus the start time, and the total operation time is the sum of the business process times within the scheduling period. Step S54: Scheduled execution; The computational program integrates data acquisition, data conversion, data processing and analysis, and data storage functions. The execution of the computational program is triggered by an independent scheduler at regular intervals. The scheduling period includes one hour, one day, one week, or one month.

[0012] Further, step S6 includes: Step S61: Utilization calculation; Obtain the business process time and baseline utilization rate from the analysis database and the time utilization baseline table respectively, and perform statistical calculation on the time utilization rate of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of states such as manufacturing time, switching time, idle time, alarm time and shutdown time, and output the utilization rate value corresponding to each state. Step S62: Visual monitoring; The calculation results are displayed through the monitoring interface, using status coloring, duration statistics and comparison charts to achieve real-time visual monitoring of the chip mounter's operating status; The visualization interface includes a device status details interface, a status duration statistics interface and a single machine and unit utilization comparison interface, used to display the time utilization and comparison results of in-process, switching, idle and alarm statuses.

[0013] This invention also proposes a system for calculating the utilization rate of a pick-and-place machine and monitoring its operation, comprising: The baseline establishment module is used to establish the target model and basic parameters of the pick and place machine based on the physical relationship dataset and work-in-process task dataset of the pick and place machine, and to calculate the time utilization baseline table of each pick and place machine within a set time period, and form a time utilization baseline set. The raw data acquisition and storage module is used to acquire discrete events and event messages during the operation of the pick-and-place machine in real time through communication protocols, and generate event tables, message tables, status tables, alarm tables and recipe tables according to event types, and store them in the data acquisition database to form the equipment's raw dataset; The mapping set management module is used to establish a mapping relationship between business status and data acquisition status according to the business logic of the pick-and-place machine, forming a status mapping set, and to establish a correspondence between business actions and data acquisition events, forming an action-event mapping set, so as to realize the association between business data and data acquisition data; The process sequence set management module is used to establish standard action sequences and process identification event sequences. The standard action sequences are necessary conditions for determining the category of business processes. The process identification event sequences consist of key data acquisition events for the start, process, and end of each business process, which are used to uniquely identify each type of business process, thereby forming a business process sequence set. The process time calculation module is used to establish an independent analysis database, standardize the format and unify the fields of the raw equipment data, and realize the correlation between discrete events and business processes through time window segmentation, key event sequence matching and label filling, and calculate the time of each business process and the total operation time; wherein, the analysis database is independent of the data acquisition database to achieve read and write separation; The time utilization calculation and visualization monitoring module is used to obtain the business process time and baseline utilization from the analysis database and baseline table, calculate the time utilization of each placement machine and placement unit according to the set rules, and display and compare the results in the visualization interface using methods such as status coloring, duration statistics and comparison charts.

[0014] Furthermore, the process time calculation module includes: An analysis database is used to retrieve and store data during the time utilization calculation process. The analysis database is independent of the data acquisition database to achieve read-write separation. Its data reference sources include the event table, message table, status table, alarm table and recipe table in the data acquisition database. The data processing unit is used to process the raw dataset of the device, including data acquisition, data transformation, data acquisition-business data association and calculation, and data storage. The data transformation includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation is achieved through time window segmentation, data association matching, and association label filling. The data calculation unit is used to calculate the processing results in the analysis database, calculate the business process time based on the start and end times of data segments with the same label, and sum them up to obtain the total operation time. The scheduling unit is used to trigger the execution of the data calculation program at set time intervals, including one hour, one day, one week, or one month.

[0015] Furthermore, the time utilization calculation and visualization monitoring module includes: The time utilization calculation unit is used to obtain the business process time and baseline utilization from the analysis database and the time utilization baseline table, respectively, and calculate the time utilization of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of states such as manufacturing time, switching time, idle time, alarm time and shutdown time, and output the time utilization value corresponding to each state. The visualization monitoring unit is used to graphically display the calculation results of the time utilization calculation unit. It realizes real-time monitoring of the pick-and-place machine's operating status through status coloring, duration statistics, and comparison charts. The visualization interface includes a device status details interface, a status duration statistics interface, and a single machine and unit utilization comparison interface, which are used to display the changes and comparison results of time utilization under the conditions of operation, switching, idle, and alarm.

[0016] Compared with existing technologies, the advantages of this invention are: This invention can significantly reduce the obscurity of the operating status and utilization rate of multi-chip component placement equipment, improve the efficiency and accuracy of time utilization calculation, and better meet the needs of placement machine utilization improvement and placement production planning for a more accurate and efficient production changeover time calculation method. Attached Figure Description

[0017] To more clearly illustrate the technical solutions in the embodiments of the present invention, the accompanying drawings used in the description of the embodiments will be briefly introduced below. Obviously, the accompanying drawings described below are only some embodiments recorded in the embodiments of the present invention. For those skilled in the art, other drawings can be obtained based on these drawings.

[0018] Figure 1 A schematic diagram of the method for calculating the utilization rate of a pick-and-place machine and monitoring its operation based on the correlation between data acquisition and business data, as described in this invention, is shown. Figure 2 A schematic diagram of the overall architecture described in this invention is shown; Figure 3 A schematic diagram of the baseline establishment process described in this invention is shown; Figure 4 A schematic diagram of the time utilization calculation process described in this invention is shown. Figure 5 A schematic diagram of the service status and data acquisition status mapping set described in this invention is shown; Figure 6 A schematic diagram of the mapping set between practical actions and data acquisition events described in this invention is shown; Figure 7 A schematic diagram of the standard action sequence dataset described in this invention is shown; Figure 8 A schematic diagram of the standard action sequence dataset described in this invention is shown; Figure 9 A schematic diagram of the data acquisition-business data association process described in this invention is shown; Figure 10 A schematic diagram of the data flow described in this invention is shown; Figure 11 A schematic diagram of the standardization monitoring interface described in this invention is shown. Figure 12 A schematic diagram of the chip mounter utilization calculation and operation monitoring system based on data acquisition and business data association described in this invention is shown. Detailed Implementation

[0019] It should be noted that relational terms such as "first" and "second" are used merely to distinguish one entity or operation from another, and do not necessarily require or imply any such actual relationship or order between these entities or operations. Furthermore, the terms "comprising," "including," or any other variations thereof are intended to cover non-exclusive inclusion, such that a process, method, article, or apparatus that comprises a list of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such a process, method, article, or apparatus. Without further limitations, an element defined by the phrase "comprising one..." does not exclude the presence of other identical elements in the process, method, article, or apparatus that includes said element.

[0020] The features and performance of the present invention will be further described in detail below with reference to embodiments.

[0021] Example 1 Please see Figure 1 A method for calculating the utilization rate of a pick-and-place machine and monitoring its operation includes the following steps: Step S1: Establish a baseline set of time utilization for placement equipment; based on the physical relationship dataset and work-in-process task dataset of the placement machine, use simulation software to establish the target model and basic parameters of the placement machine, and calculate the time utilization baseline table of each placement machine within a set time period, which will be used as a reference benchmark for subsequent calculations. Step S2: Establish the original dataset of the pick-and-place machine during operation; collect discrete events and event message data of the pick-and-place machine in real time through the communication protocol, and generate and store the event table, message table, status table, alarm table and recipe table in the database; Step S3: Establish a mapping set between business data and data acquisition data; based on the business logic of the pick-and-place machine, map the business status to the data acquisition status one by one to form a status mapping set; and map business actions to data acquisition events to form an action-event mapping set, which is used to realize the association between business processes and data acquisition events; Step S4: Establish a set of business process sequences; wherein, the standard action sequence is used to define the necessary conditions for determining the category of a business process; the process identification event sequence includes key data acquisition events that can identify the start, middle and end of a business process, and are used to uniquely identify each type of business process; Step S5: Calculate the business process time; establish an independent analysis database, import the raw data collection data into the analysis database after format standardization and field unification; through time window segmentation, key event sequence matching and label filling, merge discrete event segments into corresponding business processes; and calculate the duration of each business process based on the time difference of event segments with the same label. Step S6: Calculate the time utilization rate of the pick and place machine and perform visual monitoring; obtain the calculated business process time and baseline utilization rate from the analysis database and baseline table respectively; calculate the time utilization rate of each pick and place machine and pick and place unit according to the set calculation rules; and display and compare the duration, utilization rate, in-process status, switching status and alarm status of each status through the visual interface.

[0022] In this embodiment, specifically, step S1 includes: Step S11: Construct a simulation model; Based on the physical relationship dataset and work-in-process task dataset of the pick-and-place machine, use simulation software to establish the target model of the pick-and-place machine, and set the production cycle, equipment parameters, processing cycle time and process constraints. Step S12: Calculate the baseline utilization rate; Under the simulation model, run the simulation according to the set time period to obtain the running time and idle time of each pick and place machine under different working conditions, and calculate the time utilization rate baseline table of each pick and place machine within the set time period. Step S13: Generate a baseline set; summarize the time utilization baseline tables of each pick and place machine to form a pick and place equipment time utilization baseline set, which will be used as a reference benchmark for subsequent pick and place machine utilization calculation and operation status monitoring.

[0023] In this embodiment, specifically, step S2 includes: Step S21: Collect data during the operation of the pick-and-place machine; collect discrete events and event messages during the operation of the pick-and-place machine in real time through the communication protocol. The discrete events and event messages include event ID, event name, event time, event message content, equipment status, alarm information and recipe information. Step S22: Generate and store data tables; Generate event tables, message tables, status tables, alarm tables and recipe tables according to the type of the collected discrete events and event message data, and store them in the data acquisition database to form the original equipment data of the chip mounter operation process; Step S23: Construct the original equipment dataset; organize and collect the information in the data table according to the event time or event ID to form the original equipment dataset of the pick-and-place machine operation process.

[0024] In this embodiment, specifically, step S3 includes: Step S31: Establish a state mapping set; Based on the business logic and operating status of the pick-and-place machine, map the business status to the data acquisition status. The business status includes control status, switching status, idle status, alarm status, and power-off or offline status. The corresponding data acquisition status includes INIT, IDLE, HOME, READY, SETUP, ABORT, OPERATOR, LOOP, STEP, and EMERGENCY statuses defined by the SECM GEM protocol. The state mapping set of the pick-and-place machine is formed through the correspondence. Step S32: Establish an action-event mapping set; Based on the correspondence between the actual operation actions and data acquisition events during the operation of the pick-and-place machine, map the business actions and data acquisition events one by one. The business actions include power-on, initialization, loading the material box, picking up the material box, installing the nozzle, and removing the nozzle. The corresponding data acquisition events include the event ID, event name, and event meaning. The action-event mapping set of the pick-and-place machine is formed through the mapping relationship. Step S33: Establish the relationship between business processes and data acquisition; based on the state mapping set and action-event mapping set, establish the correspondence between business processes and data acquisition events to realize the association mapping between business data and data acquisition data.

[0025] In this embodiment, specifically, step S4 includes: Step S41: Establish a standard action sequence; based on the business action logic of the pick and place machine, arrange and combine the necessary actions that can determine the business process category in sequence to form a standard action sequence for business process identification. The standard action sequence is used to classify and determine different business processes in the operation of the pick and place machine. Step S42: Establish a process identification event sequence; based on the key data acquisition events during the operation of the pick-and-place machine, select key events that can identify the start, progress, and end of the business process, and form a process identification event sequence in chronological order. The process identification event sequence can uniquely identify the corresponding business process type. Step S43: Form a business process sequence set; associate the standard action sequence with the process identification event sequence to form a business process sequence set for the pick-and-place machine.

[0026] In this embodiment, specifically, step S5 includes: Step S51: Establish an analysis database; establish an analysis database independent of the data acquisition database for data retrieval and storage during the time utilization calculation process, thereby achieving read / write separation between the data acquisition database and the analysis database; Step S52: Data Processing; The original dataset of the device is processed, including data acquisition, data conversion, data acquisition-business data association and calculation, and data storage. Data acquisition involves obtaining event tables, message tables, status tables, alarm tables, and recipe tables from the data acquisition database through setting data interfaces and parameter passing. Data conversion includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation process matches the unified data to the corresponding business process through time window segmentation, data association matching, and association tag filling. The data storage process stores the processing results in the process information table and process time table of the analysis database. Step S53: Data calculation; The data in the analysis database is processed by computer software, and the business process time and total operation time are calculated based on the matching results. The business process time is equal to the end time of the data segment with the same label minus the start time, and the total operation time is the sum of the business process times within the scheduling period. Step S54: Scheduled execution; The computational program integrates data acquisition, data conversion, data processing and analysis, and data storage functions. The execution of the computational program is triggered by an independent scheduler at regular intervals. The scheduling period includes one hour, one day, one week, or one month.

[0027] In this embodiment, specifically, step S6 includes: Step S61: Utilization calculation; Obtain the business process time and baseline utilization rate from the analysis database and the time utilization baseline table respectively, and perform statistical calculation on the time utilization rate of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of states such as manufacturing time, switching time, idle time, alarm time and shutdown time, and output the utilization rate value corresponding to each state. Step S62: Visual monitoring; The calculation results are displayed through the monitoring interface, using status coloring, duration statistics and comparison charts to achieve real-time visual monitoring of the chip mounter's operating status; The visualization interface includes a device status details interface, a status duration statistics interface and a single machine and unit utilization comparison interface, used to display the time utilization and comparison results of in-process, switching, idle and alarm statuses.

[0028] This embodiment also proposes a pick-and-place machine utilization calculation and operation monitoring system, which can realize the above-mentioned pick-and-place machine utilization calculation and operation monitoring method, specifically including the following modules: The baseline establishment module is used to establish the target model and basic parameters of the pick and place machine based on the physical relationship dataset and work-in-process task dataset of the pick and place machine, and to calculate the time utilization baseline table of each pick and place machine within a set time period, and form a time utilization baseline set. The raw data acquisition and storage module is used to acquire discrete events and event messages during the operation of the pick-and-place machine in real time through communication protocols, and generate event tables, message tables, status tables, alarm tables and recipe tables according to event types, and store them in the data acquisition database to form the equipment's raw dataset; The mapping set management module is used to establish a mapping relationship between business status and data acquisition status according to the business logic of the pick-and-place machine, forming a status mapping set, and to establish a correspondence between business actions and data acquisition events, forming an action-event mapping set, so as to realize the association between business data and data acquisition data; The process sequence set management module is used to establish standard action sequences and process identification event sequences. The standard action sequences are necessary conditions for determining the category of business processes. The process identification event sequences consist of key data acquisition events for the start, process, and end of each business process, which are used to uniquely identify each type of business process, thereby forming a business process sequence set. The process time calculation module is used to establish an independent analysis database, standardize the format and unify the fields of the raw equipment data, and realize the correlation between discrete events and business processes through time window segmentation, key event sequence matching and label filling, and calculate the time of each business process and the total operation time; wherein, the analysis database is independent of the data acquisition database to achieve read and write separation; The time utilization calculation and visualization monitoring module is used to obtain the business process time and baseline utilization from the analysis database and baseline table, calculate the time utilization of each placement machine and placement unit according to the set rules, and display and compare the results in the visualization interface using methods such as status coloring, duration statistics and comparison charts.

[0029] In this embodiment, specifically, the process time calculation module includes: An analysis database is used to retrieve and store data during the time utilization calculation process. The analysis database is independent of the data acquisition database to achieve read-write separation. Its data reference sources include the event table, message table, status table, alarm table and recipe table in the data acquisition database. The data processing unit is used to process the raw dataset of the device, including data acquisition, data transformation, data acquisition-business data association and calculation, and data storage. The data transformation includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation is achieved through time window segmentation, data association matching, and association label filling. The data calculation unit is used to calculate the processing results in the analysis database, calculate the business process time based on the start and end times of data segments with the same label, and sum them up to obtain the total operation time. The scheduling unit is used to trigger the execution of the data calculation program at set time intervals, including one hour, one day, one week, or one month.

[0030] In this embodiment, specifically, the time utilization calculation and visualization monitoring module includes: The time utilization calculation unit is used to obtain the business process time and baseline utilization from the analysis database and the time utilization baseline table, respectively, and calculate the time utilization of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of states such as manufacturing time, switching time, idle time, alarm time and shutdown time, and output the time utilization value corresponding to each state. The visualization monitoring unit is used to graphically display the calculation results of the time utilization calculation unit. It realizes real-time monitoring of the pick-and-place machine's operating status through status coloring, duration statistics, and comparison charts. The visualization interface includes a device status details interface, a status duration statistics interface, and a single machine and unit utilization comparison interface, which are used to display the changes and comparison results of time utilization under the conditions of operation, switching, idle, and alarm.

[0031] Example 2 Example 2 is a further explanation of the method and system for calculating the utilization rate of a chip mounter and monitoring its operation process proposed in Example 1.

[0032] This embodiment proposes a method for real-time monitoring of the status and utilization of a chip mounter based on data acquisition, referencing... Figure 1 and Figure 2 As shown, it includes: Step S1: Establish a baseline set for the time utilization of the chip placement equipment; The baseline set of pick-and-place machine time utilization (MA) is calculated by computer software using physical relationship datasets and in-process task datasets, resulting in a set of pick-and-place machine cluster utilization rates over a continuous computing period under the current task load. This includes the utilization rate of a single machine. .

[0033] like Figure 3 As shown, the establishment of the baseline set for the time utilization of the patch device includes three steps: the creation of the physical relationship dataset, the creation of the in-process task dataset, and the computation by computer software.

[0034] ① Physical Relationship Dataset Creation. Physical relationships refer to the physical location of a single piece of equipment in the workshop and the positional relationships between multiple pieces of equipment. This data is divided into two parts: equipment information and inter-equipment information. Equipment information refers to the basic information of a single piece of equipment, including but not limited to equipment number, equipment name, capacity type, production area, and equipment location coordinates. Inter-equipment information refers to the physical location information between multiple pieces of equipment, including but not limited to the number of equipment and the distance between them.

[0035] ② Creation of the in-process task dataset. In-process tasks refer to all production tasks received by the surface mount equipment or surface mount process from the production management information system that have been issued but not yet completed. The production management information system includes, but is not limited to, a manufacturing execution system, an APS system, and a central control system. The in-process task dataset includes, but is not limited to, the following data: real-time in-process task dataset, pending task dataset, and production time dataset. The real-time in-process task dataset refers to production tasks issued by the production management information system and already being processed on the surface mount equipment. The created dataset attributes include, but are not limited to, product number, product name, work order to which the product belongs, planning period, planned production batch, operating equipment number, and start-up time. The pending task dataset refers to production tasks issued by the production management information system but not yet being processed on the equipment due to resource constraints, material constraints, etc. The created dataset attributes include, but are not limited to, product number, product name, work order to which the product belongs, planning period, planned production batch, and operating equipment. The production time dataset refers to the time consumption dataset generated by production tasks entering the production workshop due to processing, switching, and transfer, including but not limited to operation time, switching time, logistics time, and waiting time; the operation time refers to the processing time period from the start to the end of processing of a production task on the corresponding process equipment; the switching time refers to the time period consumed from the start of the previous production task on the corresponding process equipment to the start of the current production task; the logistics time refers to the time consumed by the production task from the processing position of the previous process to the processing position of the current process; the waiting time is the time period of waiting for the pending task after it arrives at the inventory position of the production line where the pending process is located; the real-time work-in-process dataset and the pending task dataset can be obtained from the production management information system.

[0036] ③ Computer software calculation. The computer software includes, but is not limited to, Plant Simulation or equivalent production simulation software; the calculation refers to performing calculations using the acquired work-in-process data, including, but not limited to, the calculation and solution process and the result output process; the calculation and solution process includes, but is not limited to, parameter setting, parameter assignment, and calculation execution; the parameter setting includes, but is not limited to, setting the target parameters and setting the basic parameters; the target parameters are calculated based on all work-in-process tasks and their corresponding production batch values, work hours, changeover time, logistics time, and waiting time, for each pick-and-place machine during the production process of all work-in-process tasks within the required calculation time. Effective device occupancy time and duration of calculation period ratio ;

[0037] The fundamental parameters for solving include, but are not limited to, equipment operating time parameters and equipment non-operating time parameters. Equipment operating time parameters include, but are not limited to, equipment processing time, material switching time within the equipment, and tooling calibration time. Equipment non-operating time parameters include, but are not limited to, material preparation time and tooling preparation time. Parameter assignment refers to assigning specific values ​​to the set parameters. This assignment is done manually in the computer software. The calculation execution refers to the computer software being manually controlled to perform the calculations. The resulting MA set is as follows:

[0038]

[0039] The result output process refers to outputting the time utilization results of each patch device obtained by the computer software in the form of parameters to an external table and writing them into the database system. The table rows are the device numbers. Listed as time periods The data is , The following time utilization results .

[0040] Step S2: Establish the original data set of the equipment during the operation of the pick-and-place machine; The raw data of the pick-and-place machine during operation refers to the data directly measured by the machine through sensors or monitoring equipment installed on the machine and reported to the data acquisition system when the machine is in operation. Mainly includes events Event message A piece of raw equipment data The events correspond to equipment actions that trigger sensor measurements and data reporting. A single event report includes, but is not limited to, event ID, event name, event description, and event occurrence time. The pick-and-place machine actions include, but are not limited to, a single movement of the robotic arm, a single focusing of the image acquisition camera, a single rotation of the equipment transport track, and a single click during human-machine interaction. The event message is a detailed description of the relevant parameters for the corresponding event. Different event types correspond to different message contents. For example, a material pick-up event by the pick-and-place machine nozzle would include, but is not limited to, pick-up time, pick-up pressure, pick-up position coordinates, and the name of the picked-up material. The raw equipment data reported by the pick-and-place machine is acquired and converted by the data acquisition system through a communication protocol and stored in the data acquisition database in real time. The data communication protocol includes, but is not limited to, the SECS GEM communication protocol. The constructed data acquisition database system uses an independent data table storage structure composed of different fields. The table structure includes, but is not limited to, event tables. Event message table Alarm meter Status table Formula table A complete set of raw device data:

[0041] Step S3: Establish a mapping set between business data and data acquisition data; Business data includes device business status and business operations, while the data acquisition data includes data acquisition status and data acquisition events, corresponding to the following two types of mapping sets: ① Creation and management of the correspondence set between the business status of the placement machine and the data acquisition status of the equipment. The business status of the placement machine refers to the business status dimensions categorized from a business perspective based on the business performance of the placement equipment. According to the correspondence between the actual operation of the equipment and its business performance, the definition of the actual operating status of the placement equipment includes, but is not limited to, in-process status, switching status, idle status, alarm status, and shutdown status. The in-process status indicates that the placement equipment is in the processing stage, performing surface mounting of a certain product; the switching status indicates that the placement equipment is in the production switching process, performing the switching process from the off-line of product A to the on-line of product B; the idle status indicates that the placement equipment is in an inactive state, with no action or process occurring on the equipment at this time; the alarm status indicates that the placement equipment has generated an alarm and cannot perform normal operations; the shutdown status indicates that the equipment is powered off and there is no communication. The device data acquisition status refers to the device status reported by the device sensors as defined by the communication protocol at the device data acquisition level, including but not limited to the INIT, IDLE, HOME, READY, SETUP, ABORT, OPERATOR, LOOP, STEP, and EMERGENCY statuses defined by the SECM GEM protocol. The creation and management of the mapping relationship set refers to establishing a correspondence mapping set between the data acquisition status reported by the device during actual operation and the service status of the device at the time of reporting that status. The established correspondence set includes, but is not limited to, the following: service status ID, data acquisition status, and meaning. The specific structure is as follows... Figure 4 As shown.

[0042] ② Creation and management of the mapping relationship set between pick-and-place machine operations and data acquisition events. The pick-and-place machine operations refer to a single operational action performed by the operator while using the pick-and-place machine, including but not limited to: powering on, performing initialization, clicking "Start Production," clicking "Move Feed Tray," clicking "OK" or "Close Prompt and Alarm Information," moving the joystick, installing the nozzle, removing the nozzle, loading the feed tray, loading the hopper, removing the feed tray, and removing the hopper. The data acquisition events are equipment action events defined in the SECS GEM data acquisition protocol. Each event includes information including but not limited to event ID, event name, and event meaning. One data acquisition event corresponds to one or more operational actions on the pick-and-place machine, but one operational action may correspond to zero data acquisition events. The creation and management of the mapping relationship set refers to establishing a mapping relationship between the data acquisition events reported during actual equipment operation and the operational actions being performed by the equipment at the time the event was reported. The established mapping relationship set includes, but is not limited to: event ID, event meaning, action ID, and action meaning. The specific structure is as follows: Figure 5 As shown.

[0043] Step S4: Establish a set of business process sequences; ① Business Process Set Establishment. The business process refers to a set of practical actions performed by equipment operators when using placement equipment or its automated operation. Depending on the specific equipment operation purpose, the business process includes, but is not limited to, work-in-process. Switching process Auxiliary processes Each It consists of multiple business sub-processes. For example, the manufacturing sub-process of equipment under manufacturing conditions includes manufacturing-mounting. In-process - Auxiliary Identification In-process - Replacement of material box The device switching sub-process in the switching state includes switching-nozzle calibration. Switch - Chip Calibration Switch to product calibration Switching - Device Placement Calibration .

[0044] ②Standard action sequence With process identification event sequence Establish. The standard action sequence. It refers to the set of inherent practical actions that must be performed to successfully and completely complete a business process under the conditions of complete material and tooling, no material loss, no tooling loss, clear material and tooling correspondence, and no unexpected disturbances. This set of actions must be performed when the process is repeated multiple times. It has the following characteristics: ① A mapping exists Standard action sequence It can determine the current business process that the device is in. ② The standard action sequence is a necessary condition, but not a sufficient condition, for determining the current business process category of the device; ③ The constructed set of standard action sequences includes, but is not limited to, the following information: sequence code, status ID, event ID, event message, and action ID. The specific structure is as follows: Figure 6 As shown.

[0045] The process identifier event sequence A set of data collection events that can uniquely identify a business process. It has the following characteristics: ① The identifying event must be a key event that represents the process to which it belongs; ② The correspondence between practical actions and data acquisition events is one-to-one, many-to-one, and one-to-zero; ③ The process identifier event sequence consists of a start process, intermediate processes, and an end process, where the first event in the start process is... The last event in the process is The intermediate process may not exist, and there can be multiple termination processes; ④ The constructed process identifier event sequence set should include, but is not limited to: sequence code, segment ID, state ID, event ID, event message, and action ID. The specific structure is as follows: Figure 7 As shown.

[0046] Step S5: Calculate the business process time; The constructed original dataset of devices It is a collection of discrete event information, independent of the business context, that is... There is no clear correlation between a single record and business operation information, or between a combination of multiple event records and business operation process information. Therefore, before performing calculations such as the time utilization rate of the placement equipment, the data acquisition database needs to be cleaned up. The data is processed to establish a connection with the business action processes described in steps S3 and S4 above.

[0047] The business process time calculation refers to calculating the time by calling the dataset. , The calculations are performed by computer software, and the scheduling software schedules the calculation program to obtain the time utilization rate of the pick-and-place machine under the actual production conditions within the scheduled time period. The specific calculation process is as follows: Figure 8 As shown. The computer software refers to programming software with computer language programming capabilities. The computation refers to using the acquired dataset... , This process involves using big data analytics combined with programming languages ​​and tools to correlate a large amount of data acquisition events and event messages stored in the analysis database with actual business operations and processes. This includes, but is not limited to, data acquisition, data transformation, data acquisition-business data association and calculation, and data storage. The analysis database is specifically designed for the retrieval and storage of data during the time utilization calculation process, and its data sources include, but are not limited to, data from the data acquisition database. , , , , , by mapping , , , , Table, forming the original equipment data The analysis database is independent of the data acquisition database, thus achieving read-write separation and avoiding data communication and read-write chaos.

[0048] The data acquisition process includes, but is not limited to, interface settings and parameter passing; the interface settings refer to the parameters required for computation. Data development and data acquisition interface; the parameter passing refers to... The data source information input interface includes, but is not limited to, database name, database address, database username, database password, data table name, and data filtering information. The data transformation process refers to the conversion of the acquired data... Standardization processes are implemented, including but not limited to standardizing data formats, field names, time series data, and merging data; the data merging refers to unifying scattered... , , , , Data, with At the core, key event message content, status information, formula information, and alarm information from various tables are horizontally merged to form a single, connected record. .

[0049] The data acquisition-business data association and calculation process is as follows: Figure 9 As shown, this refers to the unified processing. Data is correlated and matched with business processes, i.e., time windows. within Data matching for corresponding business processes And marking, including but not limited to time window segmentation, data association matching, and association label filling.

[0050] The time window segmentation refers to traversing line by line through a data processing program. until found The start event Record all Corresponding time of occurrence Divide into segments based on the corresponding time point t. ,form a time window The data association and matching refers to... Traversal within the time window until found End event If not found This data segment will not be processed. Otherwise, for Within the time window Perform deduplication operation, and then process the deduplicated data segments. With process key event sequence The event ID and event message are matched one by one. ,and ,and but The segment data was matched to the business process. The aforementioned associated tag filling refers to matching the business process. of Iterate through the data within the segment and label each row of data. Repeat the above process until completion. All processes in the set The match, .

[0051] The data calculation includes the calculation of business process time and total operation time, wherein the business process time Calculation refers to pairing data with the same label The duration was statistically calculated. equal Record line time minus Record line time , The total operation time It equals the sum of the times of all processes within the scheduling period. .

[0052] The data storage process refers to storing the data results generated by the data processing and calculation processes into different tables in the analysis database, including a process information table and a process timetable. The process information table stores the final output data content of the data processing stage, including but not limited to time, event ID, event message, status ID, recipe, and data tag. The process timetable stores the final output time result information of the data calculation process, including but not limited to process sequence code, process time, and total process time. The computation program refers to a program file that integrates the data acquisition program, data cleaning and transformation program, data processing and analysis program, and data storage program to complete all the above functions. The scheduler refers to a program file that is independent of the computation program, has a timed triggering mechanism, and schedules the execution of the computation program according to a scheduled time period. The scheduling time period refers to the timed triggering interval of the scheduler, including but not limited to one hour, one day, one week, and one month.

[0053] Step S6: Calculate the time utilization rate of the pick-and-place machine and perform visual monitoring; The time utilization calculation and visualization monitoring involves calculating and graphically displaying the equipment status and utilization-related data stored in the visualization database through an interface call. The visualization database is specifically designed for displaying data links in the visualization interface, and its data sources include, but are not limited to, process timetables, total timetables, and baseline tables in the analysis database. The equipment status and utilization-related data includes, but is not limited to, status tables, timetables, total timetables, and baseline tables. The interfaces include, but are not limited to, status conversion and monitoring interfaces and utilization calculation and monitoring interfaces. The status conversion and monitoring interface converts the equipment status information linked in the visualization database into corresponding business status information according to the status mapping set information, and displays the corresponding business status information in the visualization interface with corresponding colors. The utilization calculation and monitoring interface converts the process time information linked in the visualization database into the data acquisition time utilization value for each device according to the utilization calculation rules. It also synchronously retrieves the corresponding utilization baseline value for the device from the baseline table; the time utilization calculation rules are as follows:

[0054]

[0055] Data flow diagrams in the visualization implementation process, such as Figure 9As shown in the diagram. The visualization interface for monitoring the status and utilization of the surface mount equipment refers to the use of charts, graphs, and other methods to present information such as the processed data collected by the surface mount equipment and time statistics. The information presented in the visualization interface for monitoring the status and utilization of the surface mount equipment includes, but is not limited to, details of different statuses of each piece of equipment, statistics of the duration of different statuses of each piece of equipment, and comparison of time utilization. The details of different statuses of each piece of equipment include, but are not limited to, equipment number, status-event, duration, material description, total work-in-process duration, and total power-on duration; the statistics of the duration of different statuses of each piece of equipment include, but are not limited to, equipment number, work-in-process, switching, idle, and alarm; the time utilization includes monitoring the time utilization of each piece of equipment, monitoring the time utilization of the unit composed of all equipment, and monitoring the time utilization of work-in-process and shunting. The interface diagram is shown in the diagram. Figure 10 As shown. This completes all steps of the proposed method for monitoring the status and utilization of the pick-and-place machine. The overall architecture is as follows. Figure 2 As shown.

[0056] Furthermore, this embodiment also proposes a real-time monitoring system for the status and utilization of a chip mounter based on data acquisition, referencing... Figure 12 As shown, it includes: The baseline establishment module is used to implement step S1, creating and managing the datasets, result sets, attributes, and interfaces required for the time utilization baseline. This includes the physical relationship dataset, the work-in-process dataset, the equipment utilization baseline result set, the calculation software interface, and the database interface. The physical relationship dataset includes management of basic equipment information tables and inter-equipment information tables. The work-in-process dataset includes management of tables related to real-time work-in-process datasets, pending task datasets, and production time datasets. The equipment utilization baseline result set manages the utilization results of each piece of equipment over different time periods. The computer software interface refers to the interface for accessing the utilization baseline simulation data, and the database interface refers to the interface for calling the above datasets.

[0057] The real-time acquisition and storage module for raw equipment data is used to implement step S2, completing the acquisition and conversion of raw data from the patch panel equipment and storing it in the database in real time. It includes the data acquisition system's acquisition protocol, data conversion rules, database system table structure, database table storage content, and the definition of the stored data content. It manages the data acquisition database, and the constructed data acquisition database system uses an independent data table storage structure composed of different fields. This table structure includes, but is not limited to, event tables. Event message table Alarm meter Status table Formula table .

[0058] The business data and data acquisition data mapping set management module is used to implement step S3. It creates and manages the correspondence and attributes between business states and data acquisition states, and between business operations and data acquisition events within the chip placement equipment operation. It includes two sub-modules: a business state and data acquisition state mapping set, and an operation action and data acquisition event mapping set. The established business state and data acquisition state mapping set includes attributes such as business state ID, data acquisition status code, and meaning; the established operation action and data acquisition event mapping set includes attributes such as event ID, action ID, and meaning.

[0059] The business process sequence set management module is used to implement step S4, which involves creating and managing the action sequence components and their attributes included in equipment operations. It includes two sub-modules: standard action sequences and process identification event sequences. Standard action sequence attributes include sequence code, status ID, event ID, event message, and action ID; process identification time sequence attributes include sequence code, segment ID, status ID, event ID, event message, and action ID.

[0060] The process time calculation module implements step S5, creating and managing the execution of the business process time calculation program and the scheduling program. The business process time calculation program includes a data acquisition module, a data conversion module, a data acquisition-business data association and calculation module, and a data storage module, completing the calculation and storage of the duration of different business processes during the surface mount equipment production process. The scheduling program module is independent of the calculation program and has a timed triggering mechanism, scheduling the program files executed by the calculation program according to the scheduled time period. The scheduled time period refers to the timed triggering interval of the scheduling program, including but not limited to one hour, one day, one week, and one month.

[0061] The time utilization calculation and visualization monitoring module is used to implement step S6. It creates and manages the equipment time utilization calculation and equipment status / utilization visualization monitoring process, and includes a data link module, a status mapping and utilization calculation module, and an interface display module. The data link module retrieves data from the visualization database, including but not limited to process timetables, total timetables, baseline tables, status tables, and baseline tables. The status mapping and utilization calculation module completes the production status mapping and utilization calculation for each piece of equipment based on the status mapping set information and utilization calculation rules. The interface display module displays the production status and utilization baseline data, data acquisition and calculation data, utilization percentage data, and business process time percentage data for each piece of equipment.

[0062] The embodiments described above merely illustrate specific implementation methods of this application, and while the descriptions are detailed and specific, they should not be construed as limiting the scope of protection of this application. It should be noted that those skilled in the art can make various modifications and improvements without departing from the concept of the technical solution of this application, and these modifications and improvements all fall within the scope of protection of this application.

[0063] This background section is provided to generally present the context of the invention. The work of the currently named inventors, the work to the extent described in this background section, and aspects of this section that did not constitute prior art at the time of application are neither expressly nor impliedly acknowledged as prior art to the invention.

Claims

1. A method for calculating the utilization rate of a pick-and-place machine and monitoring its operation, characterized in that, include: Step S1: Establish a baseline set for the time utilization of the chip placement equipment; Based on the physical relationship dataset and work-in-process task dataset of the pick-and-place machine, the target model and basic parameters of the pick-and-place machine are established using simulation software. The time utilization baseline table of each pick-and-place machine within a set time period is calculated and used as a reference benchmark for subsequent calculations. Step S2: Establish the original data set of the equipment during the operation of the pick-and-place machine; Through communication protocols, discrete events and event message data during the operation of the pick-and-place machine are collected in real time, and event tables, message tables, status tables, alarm tables and recipe tables are generated and stored in the database. Step S3: Establish a mapping set between business data and data acquisition data; based on the business logic of the pick-and-place machine, map the business status to the data acquisition status one by one to form a status mapping set; and map business actions to data acquisition events to form an action-event mapping set, which is used to realize the association between business processes and data acquisition events; Step S4: Establish a set of business process sequences; wherein, the standard action sequence is used to define the necessary conditions for determining the category of a business process; the process identification event sequence includes key data acquisition events that can identify the start, middle and end of a business process, and are used to uniquely identify each type of business process; Step S5: Calculate the business process time; establish an independent analysis database, import the raw data collection data into the analysis database after format standardization and field unification; through time window segmentation, key event sequence matching and label filling, merge discrete event segments into corresponding business processes; and calculate the duration of each business process based on the time difference of event segments with the same label. Step S6: Calculate the time utilization rate of the pick and place machine and perform visual monitoring; obtain the calculated business process time and baseline utilization rate from the analysis database and baseline table respectively; calculate the time utilization rate of each pick and place machine and pick and place unit according to the set calculation rules; and display and compare the duration, utilization rate, in-process status, switching status and alarm status of each status through the visual interface.

2. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 1, characterized in that, Step S1 includes: Step S11: Construct a simulation model; Based on the physical relationship dataset and work-in-process task dataset of the pick-and-place machine, use simulation software to establish the target model of the pick-and-place machine, and set the production cycle, equipment parameters, processing cycle time and process constraints. Step S12: Calculate the baseline utilization rate; Under the simulation model, run the simulation according to the set time period to obtain the running time and idle time of each pick and place machine under different working conditions, and calculate the time utilization rate baseline table of each pick and place machine within the set time period. Step S13: Generate a baseline set; summarize the time utilization baseline tables of each pick and place machine to form a pick and place equipment time utilization baseline set, which will be used as a reference benchmark for subsequent pick and place machine utilization calculation and operation status monitoring.

3. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 2, characterized in that, Step S2 includes: Step S21: Collect data during the operation of the pick-and-place machine; collect discrete events and event messages during the operation of the pick-and-place machine in real time through the communication protocol. The discrete events and event messages include event ID, event name, event time, event message content, equipment status, alarm information and recipe information. Step S22: Generate and store data tables; Generate event tables, message tables, status tables, alarm tables and recipe tables according to the type of the collected discrete events and event message data, and store them in the data acquisition database to form the original equipment data of the chip mounter operation process; Step S23: Construct the original equipment dataset; organize and collect the information in the data table according to the event time or event ID to form the original equipment dataset of the pick-and-place machine operation process.

4. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 3, characterized in that, Step S3 includes: Step S31: Establish a state mapping set; Based on the business logic and operating status of the pick-and-place machine, map the business status to the data acquisition status. The business status includes control status, switching status, idle status, alarm status, and power-off or offline status. The corresponding data acquisition status includes INIT, IDLE, HOME, READY, SETUP, ABORT, OPERATOR, LOOP, STEP, and EMERGENCY statuses defined by the SECM GEM protocol. The state mapping set of the pick-and-place machine is formed through the correspondence. Step S32: Establish an action-event mapping set; Based on the correspondence between the actual operation actions and data acquisition events during the operation of the pick-and-place machine, map the business actions and data acquisition events one by one. The business actions include power-on, initialization, loading the material box, picking up the material box, installing the nozzle, and removing the nozzle. The corresponding data acquisition events include the event ID, event name, and event meaning. The action-event mapping set of the pick-and-place machine is formed through the mapping relationship. Step S33: Establish the relationship between business processes and data acquisition; based on the state mapping set and action-event mapping set, establish the correspondence between business processes and data acquisition events to realize the association mapping between business data and data acquisition data.

5. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 4, characterized in that, Step S4 includes: Step S41: Establish a standard action sequence; based on the business action logic of the pick and place machine, arrange and combine the necessary actions that can determine the business process category in sequence to form a standard action sequence for business process identification. The standard action sequence is used to classify and determine different business processes in the operation of the pick and place machine. Step S42: Establish a process identification event sequence; based on the key data acquisition events during the operation of the pick-and-place machine, select key events that can identify the start, progress, and end of the business process, and form a process identification event sequence in chronological order. The process identification event sequence can uniquely identify the corresponding business process type. Step S43: Form a business process sequence set; associate the standard action sequence with the process identification event sequence to form a business process sequence set for the pick-and-place machine.

6. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 5, characterized in that, Step S5 includes: Step S51: Establish an analysis database; establish an analysis database independent of the data acquisition database for data retrieval and storage during the time utilization calculation process, thereby achieving read / write separation between the data acquisition database and the analysis database; Step S52: Data Processing; The original dataset of the device is processed, including data acquisition, data conversion, data acquisition-business data association and calculation, and data storage. Data acquisition involves obtaining event tables, message tables, status tables, alarm tables, and recipe tables from the data acquisition database through setting data interfaces and parameter passing. Data conversion includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation process matches the unified data to the corresponding business process through time window segmentation, data association matching, and association tag filling. The data storage process stores the processing results in the process information table and process time table of the analysis database. Step S53: Data calculation; The data in the analysis database is processed by computer software, and the business process time and total operation time are calculated based on the matching results. The business process time is equal to the end time of the data segment with the same label minus the start time, and the total operation time is the sum of the business process times within the scheduling period. Step S54: Scheduled execution; The computing program integrates data acquisition, data conversion, data processing and analysis, and data storage functions. The execution of the computing program is triggered by an independent scheduler at regular intervals, including one hour, one day, one week, or one month.

7. The method for calculating the utilization rate and monitoring the operation process of a pick-and-place machine according to claim 6, characterized in that, Step S6 includes: Step S61: Utilization calculation; Obtain the business process time and baseline utilization rate from the analysis database and the time utilization baseline table respectively, and perform statistical calculation on the time utilization rate of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of manufacturing time, switching time, idle time, alarm time and shutdown time, and output the utilization rate value corresponding to each state. Step S62: Visual monitoring; The calculation results are displayed through the monitoring interface, using status coloring, duration statistics and comparison charts to achieve real-time visual monitoring of the chip mounter's operating status; The visualization interface includes a device status details interface, a status duration statistics interface and a single machine and unit utilization comparison interface, used to display the time utilization and comparison results of in-process, switching, idle and alarm statuses.

8. A system for calculating the utilization rate of a pick-and-place machine and monitoring its operation, characterized in that, include: The baseline establishment module is used to establish the target model and basic parameters of the pick and place machine based on the physical relationship dataset and work-in-process task dataset of the pick and place machine, and to calculate the time utilization baseline table of each pick and place machine within a set time period, and form a time utilization baseline set. The raw data acquisition and storage module is used to acquire discrete events and event messages during the operation of the pick-and-place machine in real time through communication protocols, and generate event tables, message tables, status tables, alarm tables and recipe tables according to event types, and store them in the data acquisition database to form the equipment's raw dataset; The mapping set management module is used to establish a mapping relationship between business status and data acquisition status according to the business logic of the pick-and-place machine, forming a status mapping set, and to establish a correspondence between business actions and data acquisition events, forming an action-event mapping set, so as to realize the association between business data and data acquisition data; The process sequence set management module is used to establish standard action sequences and process identification event sequences. The standard action sequences are necessary conditions for determining the category of business processes. The process identification event sequences consist of key data acquisition events for the start, process, and end of each business process, which are used to uniquely identify each type of business process, thereby forming a business process sequence set. The process time calculation module is used to establish an independent analysis database, standardize the format and unify the fields of the raw equipment data, and realize the correlation between discrete events and business processes through time window segmentation, key event sequence matching and label filling, and calculate the time of each business process and the total operation time; wherein, the analysis database is independent of the data acquisition database to achieve read and write separation; The time utilization calculation and visualization monitoring module is used to obtain the business process time and baseline utilization from the analysis database and baseline table, calculate the time utilization of each placement machine and placement unit according to the set rules, and display and compare the results in the visualization interface with status coloring, duration statistics and comparison charts.

9. The chip mounter utilization calculation and operation monitoring system according to claim 8, characterized in that, The process time calculation module includes: An analysis database is used to retrieve and store data during the time utilization calculation process. The analysis database is independent of the data acquisition database to achieve read-write separation. Its data reference sources include the event table, message table, status table, alarm table and recipe table in the data acquisition database. The data processing unit is used to process the raw dataset of the device, including data acquisition, data transformation, data acquisition-business data association and calculation, and data storage. The data transformation includes data format unification, field name unification, time series unification, and data merging. The data acquisition-business data association and calculation is achieved through time window segmentation, data association matching, and association label filling. The data calculation unit is used to calculate the processing results in the analysis database, calculate the business process time based on the start and end times of data segments with the same label, and sum them up to obtain the total operation time. The scheduling unit is used to trigger the execution of the data calculation program at set time intervals, including one hour, one day, one week, or one month.

10. The chip mounter utilization calculation and operation monitoring system according to claim 9, characterized in that, The time utilization calculation and visualization monitoring module includes: The time utilization calculation unit is used to obtain the business process time and baseline utilization from the analysis database and the time utilization baseline table, respectively, and calculate the time utilization of each pick-and-place machine and pick-and-place unit according to the set calculation rules. The calculation results include the duration of processing time, switching time, idle time, alarm time and shutdown time, and output the time utilization value corresponding to each state. The visualization monitoring unit is used to graphically display the calculation results of the time utilization calculation unit. It realizes real-time monitoring of the pick-and-place machine's operating status through status coloring, duration statistics, and comparison charts. The visualization interface includes a device status details interface, a status duration statistics interface, and a single machine and unit utilization comparison interface, which are used to display the changes and comparison results of time utilization under the conditions of operation, switching, idle, and alarm.

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