Production line control integrated data synchronization method and system based on big data technology

Abstract

The present invention discloses a production line management and control integrated data synchronization method and system based on big data technology, which relates to the technical field of production line data synchronization, including: marking production order and production process data, generating production line management and control integrated data when changes are detected in these data, and triggering a synchronization mode judgment strategy; preliminarily selecting a synchronization mode based on the amount of data, and then calculating the synchronization time in combination with the network bandwidth of the serial and parallel channels, and further selecting a synchronization mode; setting up waiting queues and tag matching queues for serial and parallel synchronization; the design takes into account different situations of production order data and production process data: when only production order data is included, sorting is based on priority index; when only production process data is included, sorting is based on the order of the production order and task nodes to which it belongs; when both exist at the same time, sorting is based on the above methods in combination; this design ensures accurate and efficient synchronization of production data, and improves the integration and flexibility of production line management and control.

Description

Technical Field

[0001] The present invention relates to the technical field of production line data synchronization, and in particular to a production line management and control integrated data synchronization method and system based on big data technology. Background Art

[0002] In the manufacturing industry, digital transformation has become the key to improving the competitiveness of enterprises. Core elements such as production line efficiency, quality control, and cost optimization are directly related to the survival and development of enterprises. With the rapid development of big data technology, its application in the manufacturing industry is becoming more and more extensive, providing a new solution for production line control.

[0003] The production line is one of the most important production links in modern manufacturing. In order to ensure the efficient operation and quality control of the production line, production line site management and control become crucial. Production line site management refers to the process of monitoring the production process and managing resources on the production line, covering production planning, material management, equipment maintenance, quality control and other aspects. Its goal is to ensure that the production line runs smoothly according to plan and maintain efficient and high-quality production.

[0004] Although the existing production line management and control integrated data synchronization methods based on big data technology have shown their advantages in many aspects, they still have some defects. For example, they often use a single synchronization method (such as serial or parallel) to handle all situations, and lack the ability to flexibly select the synchronization method according to the specific scenario and data size. This may lead to low synchronization efficiency when the data volume is small or the network bandwidth is sufficient; when the data volume is huge or the network bandwidth is limited, the synchronization process may be hindered by resource contention or network congestion; in addition, the existing methods may simply judge the priority of synchronization based on the different data types, without considering the inherent correlation between the data and the actual production needs, which may lead to reduced production efficiency. Summary of the invention

[0005] 1. Technical issues to be resolved

[0006] In response to the technical problems in the background technology, the present invention proposes a production line management and control integrated data synchronization method and system based on big data technology, which dynamically selects serial or parallel synchronization methods by real-time monitoring of data volume and network bandwidth, and determines the order of data synchronization based on factors such as the data priority index and its position in the production network diagram; thereby solving the technical problems recorded in the background technology.

[0007] (II) Technical solution

[0008] To achieve the above objectives, the present invention is implemented through the following technical solutions:

[0009] The integrated data synchronization method for production line control based on big data technology includes:

[0010] Mark the production order data and production process data; monitor the production order data and production process data in real time. If data changes are detected, send corresponding synchronization signals based on the changed data type, generate corresponding production line control integrated data, and trigger the synchronization mode judgment strategy;

[0011] Execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization and parallel synchronization based on the network bandwidth of the serial channel and the parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues;

[0012] The synchronization order is determined based on the number of production order data and production process data in the serial or parallel waiting queue. When only production order data exists, a first method is executed: the synchronization order is determined based on the priority index of each production order data. When only production process data exists, a second method is executed: the synchronization order is determined based on the production order data corresponding to the production process data and the order of task nodes corresponding to each production process data in the network diagram. When both production order data and production process data exist, the synchronization order is determined by combining the first method and the second method.

[0013] Specifically, each production order data on the production line is uniquely marked, and the mark of each production order data is recorded as the main mark; the production process data is uniquely marked, and the mark of the production process data is recorded as the sub-marker;

[0014] Each production process data is matched with the corresponding production order data, and the corresponding sub-tag is spliced ​​with the main tag to obtain a comprehensive tag.

[0015] Further, if a change in the production order data is detected, a first synchronization signal is sent; the first synchronization signal carries first change data, including a main mark of the changed production order data and the changed production order data;

[0016] If a change in the production process data is detected, a second synchronization signal is sent; the second synchronization signal carries second change data, including a comprehensive mark of the changed production process data and a value of the changed production process data;

[0017] If multiple first synchronization signals are sent at the same time, the first change data in the multiple first synchronization signals are integrated to obtain the integrated data of production line control at the current moment; if multiple second synchronization signals are sent at the same time, the second change data in the multiple second synchronization signals are integrated to obtain the integrated data of production line control at the current moment; if several first synchronization signals and several second synchronization signals are sent at the same time, the first change data in several first synchronization signals and the second change data in several second synchronization signals are integrated to obtain the integrated data of production line control at the current moment;

[0018] If the production line control integrated data generated at a corresponding moment is obtained within a moment, the production line control integrated data at the corresponding moment will be stored in the database to be synchronized; when new production line control integrated data is added to the database to be synchronized, the synchronization mode judgment strategy is triggered.

[0019] Further, the production line control integrated data is obtained from the database to be synchronized, and each storage unit in the production line control integrated data storage array is obtained, and the data volume of each storage unit is determined based on the storage format of the data in each storage unit and Python technology; the storage format includes string storage, integer storage, floating point storage and date storage;

[0020] Obtain the number of bytes of data in each storage unit in the production line control integrated data storage array, except for the tag data, where the tag data represents the main tag and comprehensive tag data; combine the number of bytes of data in each storage unit in the production line control integrated data storage array to obtain the data volume of the production line control integrated data ; Compare the amount of integrated data for each production line control with the preset data volume threshold Combined, if , then select the serial synchronization method to synchronize the production line control integrated data.

[0021] Furthermore, if , then further synchronization method determination is required, specifically: determine the total number of parallel channels ; Calculate the synchronization time required for serial synchronization respectively , and choose 2, 3, ... The synchronization time required for parallel channels , the expressions are:

[0022] ;

[0023] in, Indicates that the integrated data of production line control is divided into , and ; Indicates the network bandwidth of the serial channel, Indicates The network bandwidth of parallel channels is ; Indicates the maximum value operation; Indicates the time required to divide the production line control integrated data into blocks each time;

[0024] It is required to divide the data equally in a way that there is no data of the same type in multiple different parallel channels. If there is no such equal division method, the splitting strategy is executed to minimize the sum of the absolute values ​​of the differences between the amount of data in all parallel channels after splitting and the amount of data in each parallel channel in the equal division case.

[0025] Furthermore, we calculate When different values ​​are taken, it is divided into When there are multiple parallel channels, the synchronization time required to synchronize the data in each channel ; will select the synchronization time required for serial synchronization Minimum synchronization time required to synchronize with the selected In comparison, if , then select the serial synchronization mode to synchronize the production line control integrated data; if , then select The parallel synchronization method of parallel channels is used to synchronize the integrated data of production line control;

[0026] If the serial synchronization mode is selected to synchronize the production line control integrated data, all types of data except the marking data in the production line control integrated data are placed in the serial synchronization waiting queue;

[0027] If you choose The parallel synchronization method of parallel synchronization of the production line control integrated data is used to synchronize the production line control integrated data. All data except the mark in the production line control integrated data are divided into The copies are placed in the corresponding parallel waiting queue.

[0028] Furthermore, the synchronization order of various data in the serial waiting queue and each parallel waiting queue is determined; if the data in the waiting queue all belongs to production order data, a method is executed: based on the production progress of each production order , Delivery deadline urgency And the order amount ratio Calculate the priority index for each production order data , the expression is: ,in, , , Respectively indicate the production progress , Delivery deadline urgency And the order amount ratio The weight coefficient of

[0029] Among them, production progress Obtained from the production process data of the production order; Delivery urgency The difference between the delivery date and the current date is divided by the estimated completion time; the order amount is The corresponding total order amount data is obtained from the production order data, and all the total order amount data are normalized;

[0030] Reorder all production order data in the waiting queue from large to small according to the priority index.

[0031] Specifically, if all the data in the waiting queue belong to production process data, two methods are executed: based on the comprehensive mark of each production process data, it is determined whether all the production process data belong to the same production order data; if not, based on the priority index of each production order data Conduct preliminary sorting of production process data;

[0032] After the preliminary sorting, the production process data under each production order data is further sorted based on the network diagram method. Specifically, all tasks in the production process and their dependent production process data are drawn into a network diagram, and directed edges are drawn between each task node based on the processing order. Starting from the initial task node, each production process data is sorted based on the order of each task node in the network diagram. The higher the order of the task node, the higher the priority of the dependent production process data;

[0033] If the order of two task nodes is the same, that is, the priorities of the two production process data are the same, then the order of the corresponding production process data is further judged according to the number of associated task nodes of each task node. The associated task nodes are the number of adjacent task nodes pointed to by the task node. The more the number of associated task nodes is, the higher the order of the corresponding production process data is. The waiting queue is reordered based on the results of the preliminary sorting and the further sorting.

[0034] If these production process data all belong to the same production order data, the order of the production process data in the waiting queue is determined based on the network diagram method.

[0035] Specifically, if the data in the waiting queue contains both production order data and production process data, then combine the first method with the second method: take out all the production order data and calculate the priority index of each production order data , and based on the priority index Sort all production order data by size and put them back into the waiting queue;

[0036] All the production process data are taken out, and the production order data corresponding to each production process data are analyzed. The higher the priority index of the production order data, the higher the order of the corresponding production process data. Based on this method, all the production process data are preliminarily sorted; for several production process data in the same production order data, they are further sorted based on the position of each production process data in the corresponding production network diagram.

[0037] The production line control integrated data synchronization system based on big data technology includes:

[0038] The data marking and monitoring module is used to uniquely mark each production order data on the production line, and record the mark of each production order data as the main mark; uniquely mark the production process data, and record the mark of the production process data as the sub-mark;

[0039] The synchronization mode determination module is used to execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization and parallel synchronization based on the network bandwidth of the serial channel and the parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues;

[0040] The synchronization sequence determination module is used to determine the synchronization sequence based on the number of production order data and production process data in the serial or parallel waiting queue. When only production order data exists, a first method is executed: the synchronization sequence is determined based on the priority index of each production order data. When only production process data exists, a second method is executed: the synchronization sequence is determined based on the production order data corresponding to the production process data and the order of the task nodes corresponding to each production process data in the network diagram. When both production order data and production process data exist, the synchronization sequence is determined by combining the first method and the second method.

[0041] (III) Beneficial effects

[0042] The present invention provides a production line control integrated data synchronization method and system based on big data technology, which has the following beneficial effects:

[0043] 1. Through refined data tagging and real-time monitoring mechanisms, the real-time capture and accurate synchronization of production order data and production process data changes are ensured, which effectively improves the accuracy and efficiency of data synchronization and provides strong data support for production line management and control;

[0044] 2. By dynamically evaluating the data volume and intelligently selecting the synchronization mode (serial or parallel), combined with network bandwidth monitoring and data segmentation strategy, the synchronization efficiency is effectively optimized, the synchronization time is reduced, and the efficient and accurate synchronization of the integrated data of the production line control is ensured, thus improving the response speed and management level of the entire production system;

[0045] 3. By comprehensively considering the priority of production order data and the order of production process data in the network diagram, combining the first and second methods, the synchronization order is intelligently determined to ensure that key data is synchronized first, effectively improving the pertinence and efficiency of data synchronization, and providing a solid guarantee for the efficient and orderly operation of the production line;

[0046] 4. The efficiency and accuracy of data synchronization are significantly improved through refined tag management, real-time data monitoring, dynamic synchronization strategies, and priority sorting mechanisms. This not only ensures the accurate tracking and rapid synchronization of production order data and production process data, but also optimizes the synchronization order and reduces synchronization delays through intelligent selection of parallel synchronization and serial synchronization, as well as comprehensive priority sorting based on multiple factors. This effectively supports efficient and flexible management and control of production lines, and improves overall production efficiency and response speed. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] Figure 1 A schematic diagram of the steps of the production line management and control integrated data synchronization method based on big data technology provided by the present invention;

[0048] Figure 2 A flow chart of the production line management and control integrated data synchronization method based on big data technology provided by the present invention;

[0049] Figure 3 This is a schematic diagram of the structure of the production line management and control integrated data synchronization system based on big data technology provided by the present invention. DETAILED DESCRIPTION

[0050] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0051] refer to Figure 1 and Figure 2 The present invention provides a production line management and control integrated data synchronization method based on big data technology, including:

[0052] Step 1: Mark the production order data and production process data; monitor the production order data and production process data in real time. If data changes are detected, send corresponding synchronization signals based on the changed data type, generate corresponding production line control integrated data, and trigger the synchronization mode judgment strategy;

[0053] The step one includes the following steps:

[0054] Step 101: uniquely mark each production order data on the production line, and record the mark of each production order data as a main mark; uniquely mark each production process data, and record the mark of the production process data as a sub-mark;

[0055] Among them, production order data refers to the production task order data clearly specified in the production plan for a specific product or product combination. The production order data contains various detailed information required for production, such as product name, specification model, production quantity, production time, production process requirements, etc., and is an important basis for guiding production activities, controlling production processes, tracking production progress and ensuring product quality; marking the production order data is used to achieve accurate tracking and management of the production process of each production order data, so that when synchronizing data of the same type, it can quickly locate the corresponding production order data to distinguish data under different production order data;

[0056] Production process data refers to various information directly related to production order data, used to support, supplement or explain the execution process of production order data, including raw material data, production process parameter data, production equipment data, operator data, quality inspection data, production progress data, etc.; each production process data is marked to refine the management granularity of production order data, ensuring that these data can be accurately and completely transmitted to the management system during data synchronization;

[0057] Match each production process data with the corresponding production order data, and concatenate the corresponding sub-tag with the main tag to obtain a comprehensive tag in the form of "main tag + sub-tag"; during the processing and production process, if the production order data changes, match the corresponding production order data based on the main tag; if the production process data changes, match the corresponding production process data under the corresponding production order data based on the comprehensive tag;

[0058] Step 102: Real-time monitoring of production order data is performed in the system. If a change in the production order data is detected, a first synchronization signal is sent; the first synchronization signal carries first change data, and the first change data includes a main tag of the changed production order data and the changed production order data;

[0059] Deploy various sensors, intelligent instruments and other data acquisition equipment on the production line to collect production process data in real time; if it is detected that there is a change in the production process data, send a second synchronization signal; the second synchronization signal carries second change data, and the second change data includes a comprehensive mark of the changed production process data and the changed production process data value;

[0060] If multiple first synchronization signals are sent at the same time at any moment, the first change data in the multiple first synchronization signals are integrated to obtain the production line control integrated data at the current moment; the production line control integrated data is in the form of an array, and the first change data in the multiple first synchronization signals are respectively stored in multiple storage units in the array, and the storage method of the subsequent production line control integrated data is similar;

[0061] If multiple second synchronization signals are sent at the same time at any moment, the second change data in the multiple second synchronization signals are integrated to obtain the production line control integrated data at the current moment;

[0062] If at any moment, several first synchronization signals and several second synchronization signals are sent simultaneously, the first change data in the several first synchronization signals and the second change data in the several second synchronization signals are integrated to obtain the production line control integrated data at the current moment;

[0063] If the production line control integrated data generated at a corresponding time is obtained at a time, the production line control integrated data at the corresponding time is stored in the database to be synchronized;

[0064] When new production line control integrated data is added to the database to be synchronized, the synchronization mode judgment strategy is triggered.

[0065] Through refined data labeling and real-time monitoring mechanisms, the real-time capture and accurate synchronization of production order data and production process data changes are ensured, which effectively improves the accuracy and efficiency of data synchronization and provides strong data support for production line management and control.

[0066] Step 2: Execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization and parallel synchronization based on the network bandwidth of the serial channel and the parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues;

[0067] The step 2 includes the following steps:

[0068] Step 201: execute the synchronization mode judgment strategy, obtain the production line control integrated data from the database to be synchronized, and obtain each storage unit in the production line control integrated data storage array, and determine the data volume of each storage unit based on the storage format of the data in each storage unit and the number of bytes of the data;

[0069] The storage format includes string storage, integer storage, floating point storage and date storage, wherein the production order data is stored in string format, the digital data in the production process data is stored in integer or floating point format, the date data is stored in date format, and the remaining data is stored in string format;

[0070] The number of bytes of the string format data is calculated by the len() function in Python and the encode() method of the string. The code is as follows:

[0071] mixed_string = "string data"

[0072] encoded_bytes = mixed_string.encode('utf-8')

[0073] byte_count = len(encoded_bytes)

[0074] return byte_count

[0075] The number of bytes of integer format data and floating point format data is obtained through the sys.getsizeof() function in Python. The code is as follows:

[0076] num_size = sys.getsizeof(float_var)

[0077] return num_size

[0078] The date format data is obtained by combining the string format data and the integer format data, so the number of bytes of all the string format data and the integer format data in the date format data is added to obtain the number of bytes of the date format data;

[0079] Step 202: Based on the method in step 201, the number of bytes of data in each storage unit in the production line control integrated data storage array, except for the tag data, is obtained. The tag data represents the main tag and the comprehensive tag data; the number of bytes of data in each storage unit in the production line control integrated data storage array is combined to obtain the comprehensive number of bytes of the production line control integrated data, that is, the data volume ; Compare the amount of integrated data for each production line control with the preset data volume threshold Combined, if , it means that the data volume of the production line control integrated data does not exceed the data volume threshold, that is, the data volume that needs to be synchronized at this time is moderate, and the serial synchronization method is selected to synchronize the production line control integrated data; the data volume threshold is determined by the production line control personnel based on cost analysis;

[0080] like , it means that the amount of integrated data of production line control exceeds the data volume threshold, which means that the amount of data to be synchronized is large, and further synchronization method is determined;

[0081] Step 203: Determine the total number of parallel channels The network bandwidth in the serial channel and each parallel channel is monitored by the network test tool; the network bandwidth refers to the maximum rate at which the network communication link can transmit data;

[0082] Calculate the synchronization time required for serial synchronization respectively , and choose 2, 3, ... The synchronization time required for parallel channels , the expressions are:

[0083] ;

[0084] in, Indicates that the integrated data of production line control is divided into , and ; Indicates the network bandwidth of the serial channel, Indicates The network bandwidth of parallel channels is ; Indicates the maximum value operation; Indicates the time required to block the integrated data of production line control each time, which is obtained from the block records in the historical data;

[0085] In the above-mentioned operation of splitting the integrated data of production line control, it is required to be split in an equal splitting manner in which the same type of data does not exist in multiple different parallel channels. If there is no such equal splitting manner, the splitting strategy is executed so that the sum of the absolute values ​​of the difference between the amount of data in all parallel channels after splitting and the amount of data in each parallel channel in the equal splitting case is minimized;

[0086] Calculate separately When different values ​​are taken, it is divided into When there are multiple parallel channels, the synchronization time required to synchronize the data in each channel is ; Get the minimum value among these times , that is, the shortest synchronization time required for parallel synchronization is selected; the synchronization time required for serial synchronization is selected Minimum synchronization time required to synchronize with the selected In comparison, if , it means that the synchronization time required for parallel synchronization is not less than the synchronization time required for serial synchronization. In this case, serial synchronization is selected to synchronize the integrated data of production line control. , it means select The synchronization time required for parallel synchronization of two parallel channels is less than the synchronization time required for serial synchronization. The parallel synchronization method of parallel channels is used to synchronize the integrated data of production line control;

[0087] Step 204: If the serial synchronization mode is selected to synchronize the production line control integrated data, all types of data except the tags in the production line control integrated data are placed in the serial synchronization waiting queue, and the order of placement is based on the position of each type of data in the production line control integrated data, and the tags (main tags or comprehensive tags) corresponding to each type of data are placed in the tag matching queue in the corresponding order;

[0088] If you choose The production line control integrated data is synchronized by using a parallel synchronization method using parallel channels. All data except the mark in the production line control integrated data is divided into The data of several types in each parallel channel are preliminarily sorted according to their positions in the production line control integrated data, and the tag data of several types of data in each parallel channel are stored in the tag matching queue of the corresponding parallel channel. A parallel wait queue and a mark match queue.

[0089] By dynamically evaluating the data volume and intelligently selecting the synchronization method (serial or parallel), combined with network bandwidth monitoring and data segmentation strategy, the synchronization efficiency is effectively optimized, the synchronization time is reduced, and the efficient and accurate synchronization of production line management and control integrated data is ensured, thereby improving the response speed and management level of the entire production system.

[0090] Step 3: Based on the number of production order data and production process data in the serial or parallel waiting queue, the synchronization order is determined respectively; when only production order data exists, the first method is executed: the synchronization order is determined based on the priority index of each production order data; when only production process data exists, the second method is executed: the synchronization order is determined based on the production order data corresponding to the production process data and the order of the task nodes corresponding to each production process data in the network diagram; when both production order data and production process data exist, the synchronization order is determined by combining the first method and the second method;

[0091] Determine the synchronization order of various types of data in the serial waiting queue and each parallel waiting queue; based on the tag matching queue corresponding to each waiting queue, determine the source of the data in each waiting queue, that is, determine whether the data in each waiting queue belongs to production order data or production process data;

[0092] If the data in the waiting queue all belong to production order data, a method is executed: based on the production progress of each production order , Delivery deadline urgency And the order amount ratio Calculate the priority index for each production order data ;

[0093] Among them, the production progress of a production order is an important indicator to measure the current completion status of a production order. Selecting the production progress as a factor in calculating the priority index can ensure that production orders that are close to completion or in a critical production stage are given priority; this helps to reduce production interruptions, improve production efficiency, and ensure the smooth progress of the production process; specifically, it is obtained from the production process data of the production order;

[0094] Delivery urgency reflects the urgency of production orders to be completed and delivered to customers within a specific time. Selecting delivery urgency as a factor in calculating the priority index can ensure that production orders with approaching or overdue delivery dates are given priority. It is obtained by dividing the difference between the delivery date and the current date by the estimated completion time. The estimated completion time is predicted based on the corresponding production process data.

[0095] The order amount ratio is used as a factor in calculating the priority index to ensure that production orders with higher economic value or greater contribution to corporate revenue are given priority. Specifically, the corresponding total order amount data is obtained from the production order data, and all the total order amount data are normalized to obtain the result;

[0096] Priority Index The calculation formula is: ,in, , , Respectively indicate the production progress , Delivery deadline urgency And the order amount ratio The specific value of the weight coefficient is set by the production line control personnel, and ;

[0097] Sort all production order data from large to small according to priority index, and re-sort the waiting queue accordingly;

[0098] If all the data in the waiting queue belong to production process data, the second method is executed to determine whether all the production process data belong to the same production order data based on the comprehensive mark of each production process data; if not, the priority index of each production order data is used to determine whether all the production process data belong to the same production order data. Preliminary sorting of production process data, specifically the priority index The larger the production order data, the closer the production process data is to the front. After the preliminary sorting, the production process data under each production order data is further sorted based on the network diagram method. Specifically, all tasks in the production process and their dependent production process data are drawn into a network diagram, and directed edges are drawn between each task node based on the processing order. Starting from the initial task node, each production process data is sorted based on the order of each task node in the network diagram. The closer the order of the task node is, the higher the priority of the dependent production process data is, that is, the closer it is to the front. If the order of two task nodes is the same, that is, the priority of the two production process data is the same, then the order of the corresponding (dependent) production process data is further judged according to the number of associated task nodes of each task node. The associated task nodes are the number of adjacent (next) task nodes pointed to by the task node. The more the number of associated task nodes is, the closer the order of the corresponding production process data is.

[0099] If all the production process data belong to the same production order data, the order of the production process data in the waiting queue is determined based on the network diagram method;

[0100] If the data in the waiting queue contains both production order data and production process data, then combine the first method with the second method: take out all the production order data and calculate the priority index of each production order data using the same method as above , and according to the priority index Determine the order of production order data and prioritize it based on the priority index All production order data are sorted according to their size and put back into the waiting queue; all production process data are taken out, and the production order data corresponding to each production process data are analyzed in the same way. The higher the priority index of the production order data is, the higher the order of the corresponding production process data is. Based on this method, all production process data are preliminarily sorted; for several production process data in the same production order data, they are further sorted based on the position of each production process data in the corresponding production network diagram;

[0101] When the synchronization operation starts, the data and tags ranked first are taken out from the serial synchronization waiting queue and the tag matching queue respectively, and the tag matching and the corresponding data synchronization operation are performed.

[0102] By comprehensively considering the priority of production order data and the order of production process data in the network diagram, and combining the first and second method, the synchronization order is intelligently determined to ensure that key data is synchronized first, effectively improving the pertinence and efficiency of data synchronization, and providing a solid guarantee for the efficient and orderly operation of the production line.

[0103] The above design significantly improves the efficiency and accuracy of data synchronization through mechanisms such as refined tag management, real-time data monitoring, dynamic synchronization strategies and priority sorting. It not only ensures the accurate tracking and fast synchronization of production order data and production process data, but also optimizes the synchronization order and reduces synchronization delay through intelligent selection of parallel synchronization and serial synchronization, as well as comprehensive priority sorting based on multiple factors, thereby effectively supporting efficient and flexible management and control of production lines and improving overall production efficiency and response speed.

[0104] refer to Figure 3 The present invention also provides a production line management and control integrated data synchronization system based on big data technology, including:

[0105] The data marking and monitoring module is used to uniquely mark each production order data on the production line, and record the mark of each production order data as the main mark; uniquely mark the production process data, and record the mark of the production process data as the sub-mark;

[0106] The synchronization mode determination module is used to execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization and parallel synchronization based on the network bandwidth of the serial channel and the parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues;

[0107] The synchronization sequence determination module is used to determine the synchronization sequence based on the number of production order data and production process data in the serial or parallel waiting queue. When only production order data exists, a first method is executed: the synchronization sequence is determined based on the priority index of each production order data. When only production process data exists, a second method is executed: the synchronization sequence is determined based on the production order data corresponding to the production process data and the order of the task nodes corresponding to each production process data in the network diagram. When both production order data and production process data exist, the synchronization sequence is determined by combining the first method and the second method.

[0108] In the above embodiments, all or part of the embodiments may be implemented by software, hardware, firmware or any combination thereof. When implemented by software, all or part of the embodiments may be implemented in the form of a computer program product. The computer program product includes one or more computer instructions. When the computer program instructions are loaded and executed on a computer, all or part of the processes or functions described in the embodiments of the present invention are generated. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer storage medium or transmitted via a computer storage medium.

[0109] Computer instructions can be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line (DSL)) or wireless (e.g., infrared, wireless, microwave, etc.) means. Computer storage media can be any available media that can be accessed by a computer or a data storage device such as a server or data center that includes one or more available media. Available media can be magnetic media (e.g., floppy disks, hard disks, tapes), optical media (e.g., DVDs), or semiconductor media (e.g., solid state drives (SSDs)).

[0110] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed by the present invention, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

Claims

1. A production line control integrated data synchronization method based on big data technology, characterized by: The steps include: Mark the production order data and production process data; monitor the production order data and production process data in real time. If data changes are detected, send corresponding synchronization signals based on the changed data type, generate corresponding production line control integrated data, and trigger the synchronization mode judgment strategy; Execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization or parallel synchronization based on the network bandwidth of the preliminarily selected serial channel or parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues; Obtain production line control integrated data from the database to be synchronized, and obtain each storage unit in the production line control integrated data storage array, and determine the data volume of each storage unit based on the storage format of the data in each storage unit and Python technology; the storage format includes string storage, integer storage, floating point storage and date storage; Obtain the number of bytes of data in each storage unit in the production line control integrated data storage array except for the tag data, where the tag data represents the main tag and the comprehensive tag data; combine the number of bytes of data in each storage unit in the production line control integrated data storage array to obtain the data volume Ad of the production line control integrated data; combine the data volume of each production line control integrated data with the preset data volume threshold Ad0, and if Ad≤Ad0, select the serial synchronization mode to synchronize the production line control integrated data; If Ad>Ad0, further synchronization mode determination is required, specifically: determine the total number of parallel channels n; calculate the synchronization time t required for serial synchronization respectively. s , and the synchronization time required to select 2, 3, ... n parallel channels The expressions are: Where i means that the integrated data of production line control is divided into i parts, and i∈{2,3,…,n}; Nb s Indicates the network bandwidth of the serial channel, represents the network bandwidth of the jth parallel channel, and j∈{1,…,i}; Max{} represents the maximum value operation; T represents the time required to block the integrated data of production line control each time; It is required to divide the data equally in a way that there is no data of the same type in multiple parallel channels. If there is no such way, the splitting strategy is implemented so that the sum of the absolute values ​​of the difference between the amount of data in all parallel channels after splitting and the amount of data in each parallel channel in the case of equal division is minimized. Calculate the synchronization time required for synchronizing the data in each channel when i takes different values, that is, when it is divided into i parallel channels The synchronization time t required for serial synchronization will be selected s Minimum synchronization time required to synchronize with the selected In comparison, if Then select the serial synchronization mode to synchronize the production line control integrated data; if Then i parallel channels are selected to synchronize the production line control integrated data in a parallel synchronization mode; If the serial synchronization mode is selected to synchronize the production line control integrated data, all types of data in the production line control integrated data except the marking data are placed in the serial synchronization waiting queue; If i parallel channels are selected for parallel synchronization to synchronize the production line control integrated data, all data except the mark in the production line control integrated data are divided into i parts according to the corresponding division method and put into the corresponding parallel waiting queue; The synchronization order is determined based on the number of production order data and production process data in the serial or parallel waiting queue. When only production order data exists, a first method is executed: the synchronization order is determined based on the priority index of each production order data. When only production process data exists, a second method is executed: the synchronization order is determined based on the production order data corresponding to the production process data and the order of task nodes corresponding to each production process data in the network diagram. When both production order data and production process data exist, the synchronization order is determined by combining the first method and the second method.

2. The production line management and control integrated data synchronization method based on big data technology according to claim 1, characterized in that: Uniquely mark each production order data on the production line, and record the mark of each production order data as the main mark; uniquely mark the production process data, and record the mark of the production process data as the sub-mark; Each production process data is matched with the corresponding production order data, and the corresponding sub-tag is spliced ​​with the main tag to obtain a comprehensive tag.

3. The production line management and control integrated data synchronization method based on big data technology as claimed in claim 2, characterized in that: If a change in the production order data is detected, a first synchronization signal is sent; the first synchronization signal carries first change data, including a main mark of the changed production order data and the changed production order data; If a change in production process data is detected, a second synchronization signal is sent; The second synchronization signal carries second change data, including a comprehensive mark of the changed production process data and a value of the changed production process data; If multiple first synchronization signals are sent at the same time, the first change data in the multiple first synchronization signals are integrated to obtain the integrated data of production line control at the current moment; if multiple second synchronization signals are sent at the same time, the second change data in the multiple second synchronization signals are integrated to obtain the integrated data of production line control at the current moment; if several first synchronization signals and several second synchronization signals are sent at the same time, the first change data in several first synchronization signals and the second change data in several second synchronization signals are integrated to obtain the integrated data of production line control at the current moment; If the production line control integrated data generated at a corresponding moment is obtained within a moment, the production line control integrated data at the corresponding moment will be stored in the database to be synchronized; when new production line control integrated data is added to the database to be synchronized, the synchronization mode judgment strategy is triggered.

4. The production line management and control integrated data synchronization method based on big data technology according to claim 1, characterized in that: Determine the synchronization order of various data in the serial waiting queue and each parallel waiting queue; if the data in the waiting queue all belong to production order data, execute a method: calculate the priority index Pi of each production order data based on the production progress Pp, delivery urgency Udt and order amount ratio Tao of each production order, and the expression is: Pi = α1*Pp+α2*Udt+α3*Tao, where α1, α2, and α3 represent the weight coefficients of production progress Pp, delivery urgency Udt, and total order amount Tao, respectively; Among them, the production progress Pp is obtained from the production process data of the production order; the delivery urgency Udt is obtained by dividing the difference between the delivery date and the current date by the estimated completion time; the order amount ratio Tao is obtained by obtaining the corresponding order total amount data from the production order data and normalizing all the order total amount data; Reorder all production order data in the waiting queue from large to small according to the priority index.

5. The production line control integrated data synchronization method based on big data technology according to claim 4, characterized in that: If all the data in the waiting queue belong to production process data, the second method is executed: based on the comprehensive tag of each production process data, it is determined whether all the production process data belong to the same production order data; If not, the production process data is preliminarily sorted based on the priority index Pi of each production order data; After the preliminary sorting, the production process data under each production order data is further sorted based on the network diagram method. Specifically, all tasks in the production process and their dependent production process data are drawn into a network diagram, and directed edges are drawn between each task node based on the processing order. Starting from the initial task node, each production process data is sorted based on the order of each task node in the network diagram. The higher the order of the task node, the higher the priority of the dependent production process data; If the order of two task nodes is the same, that is, the priorities of the two production process data are the same, then the order of the corresponding production process data is further judged according to the number of associated task nodes of each task node. The associated task nodes are the number of adjacent task nodes pointed to by the task node. The more the number of associated task nodes is, the higher the order of the corresponding production process data is. The waiting queue is reordered based on the results of the preliminary sorting and the further sorting. If all the production process data belong to the same production order data, the order of the production process data in the waiting queue is determined based on the network diagram method.

6. The production line control integrated data synchronization method based on big data technology according to claim 5, characterized in that: If the data in the waiting queue contains both production order data and production process data, then combine the first method with the second method: take out all the production order data, calculate the priority index Pi of each production order data, and sort all the production order data based on the size of the priority index Pi and put them back into the waiting queue; All the production process data are taken out, and the production order data corresponding to each production process data are analyzed. The higher the priority index of the production order data, the higher the order of the corresponding production process data. Based on this method, all the production process data are preliminarily sorted; for several production process data in the same production order data, they are further sorted based on the position of each production process data in the corresponding production network diagram.

7. The production line control integrated data synchronization system based on big data technology is characterized by: include: The data marking and monitoring module is used to uniquely mark each production order data on the production line and record the mark of each production order data as the main mark; Uniquely mark the production process data respectively, and record the mark of the production process data as a sub-mark; The synchronization mode determination module is used to execute the synchronization mode judgment strategy, determine the data volume of the production line control integrated data, and preliminarily select the synchronization mode based on the relationship between the data volume and the data volume threshold; calculate the synchronization time required for serial synchronization or parallel synchronization based on the network bandwidth of the preliminarily selected serial channel or parallel channel, and further select the synchronization mode; set the serial and parallel synchronization waiting queues and the corresponding tag matching queues; Obtain production line control integrated data from the database to be synchronized, and obtain each storage unit in the production line control integrated data storage array, and determine the data volume of each storage unit based on the storage format of the data in each storage unit and Python technology; the storage format includes string storage, integer storage, floating point storage and date storage; Obtain the number of bytes of data in each storage unit in the production line control integrated data storage array except for the tag data, where the tag data represents the main tag and the comprehensive tag data; combine the number of bytes of data in each storage unit in the production line control integrated data storage array to obtain the data volume Ad of the production line control integrated data; combine the data volume of each production line control integrated data with the preset data volume threshold Ad0, and if Ad≤Ad0, select the serial synchronization mode to synchronize the production line control integrated data; If Ad>Ad0, further synchronization mode determination is required, specifically: determine the total number of parallel channels n; calculate the synchronization time t required for serial synchronization respectively. s , and the synchronization time required to select 2, 3, ... n parallel channels The expressions are: Where i means that the integrated data of production line control is divided into i parts, and i∈{2,3,…,n}; Nb s Indicates the network bandwidth of the serial channel, represents the network bandwidth of the jth parallel channel, and j∈{1,…,i}; Max{} represents the maximum value operation; T represents the time required to block the integrated data of production line control each time; It is required to divide the data equally in a way that there is no data of the same type in multiple parallel channels. If there is no such way, the splitting strategy is implemented so that the sum of the absolute values ​​of the difference between the amount of data in all parallel channels after splitting and the amount of data in each parallel channel in the case of equal division is minimized. Calculate the synchronization time required for synchronizing the data in each channel when i takes different values, that is, when it is divided into i parallel channels The synchronization time t required for serial synchronization will be selected s Minimum synchronization time required to synchronize with the selected In comparison, if Then select the serial synchronization mode to synchronize the production line control integrated data; if Then i parallel channels are selected to synchronize the production line control integrated data in a parallel synchronization mode; If the serial synchronization mode is selected to synchronize the production line control integrated data, all types of data in the production line control integrated data except the marking data are placed in the serial synchronization waiting queue; If i parallel channels are selected for parallel synchronization to synchronize the production line control integrated data, all data except the mark in the production line control integrated data are divided into i parts according to the corresponding division method and put into the corresponding parallel waiting queue; The synchronization sequence determination module is used to determine the synchronization sequence based on the number of production order data and production process data in the serial or parallel waiting queue. When only production order data exists, a first method is executed: the synchronization sequence is determined based on the priority index of each production order data. When only production process data exists, a second method is executed: the synchronization sequence is determined based on the production order data corresponding to the production process data and the order of the task nodes corresponding to each production process data in the network diagram. When both production order data and production process data exist, the synchronization sequence is determined by combining the first method and the second method.

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