MES-based digital production workshop management system

Abstract

The invention discloses a digital production workshop management system based on MES, relates to the technical field of production operation supervision, and improves the response speed of abnormity in the production process. The method comprises the following steps: establishing a standard state data interval in a corresponding state according to historical state data of each piece of workshop equipment in various states, establishing a workshop equipment distribution tree according to a spatial position of each piece of workshop equipment in a production workshop, and generating a product production sequence chain according to a product production event; matching the product production sequence chain with the workshop equipment distribution tree, traversing an optimal production sequence chain from the workshop equipment distribution tree, traversing corresponding workshop equipment in the production workshop according to the optimal production sequence chain, and continuously obtaining real-time state data of each workshop equipment; and adjusting the optimal production sequence chain in real time by judging whether each piece of real-time state data is in the corresponding standard state data interval.

Description

Technical Field

[0001] The present invention relates to the technical field of production operation supervision, and in particular to a digital production workshop management system based on MES. Background Art

[0002] With the rapid development of the manufacturing industry, traditional production workshop management methods can no longer meet the needs of modern industry for efficient, accurate and flexible production. Digital transformation has become the key to improving the competitiveness of the manufacturing industry and adapting to market changes. MES is a computerized system used to control and monitor the production process. It can collect, process and analyze production data in real time, optimize production scheduling, and improve production efficiency and product quality.

[0003] The existing workshop production supervision technology has the following defects: Lack of real-time performance: Although the MES system can collect production data in real time, the existing system still has the problem of insufficient real-time performance in data analysis and decision support. Especially in the face of emergencies or production anomalies, the response speed and decision-making ability of the MES system need to be improved.

[0004] Limited intelligence: Although the MES system combines big data and AI technology, its intelligence is still limited in actual application. For example, the existing MES system cannot fully realize automation and intelligence in predictive maintenance and production plan optimization, and still requires a lot of manual intervention.

[0005] Therefore, how to achieve automated management of each device in the production workshop while improving the response speed to abnormalities in the production process is a difficulty in the existing technology. For this purpose, a digital production workshop management system based on MES is provided. Summary of the invention

[0006] In order to solve the above technical problems, the purpose of the present invention is to provide a digital production workshop management system based on MES.

[0007] In order to achieve the above object, the present invention provides the following technical solutions: A digital production workshop management system based on MES, comprising a cloud computing platform, characterized in that the cloud computing platform is communicatively connected with a workshop equipment data acquisition module, an equipment status monitoring module, a dynamic production sequence generation module and a workshop ecological management module; The workshop equipment data acquisition module is used to set a variety of sensors for each workshop equipment, and periodically collect historical status data of each workshop equipment in various states through the sensors; The equipment status supervision module is used to establish a standard status data interval for each production equipment in a corresponding state according to the historical status data of each workshop equipment in various states, and to establish a workshop equipment distribution tree according to the spatial position of each workshop equipment in the production workshop; The dynamic production sequence generation module is used to obtain the product production events of each product, and generate the corresponding product production sequence chain according to the product production events, match the product production sequence chain with the workshop equipment distribution tree, and then traverse the corresponding optimal production sequence chain from the workshop equipment distribution tree; The workshop ecological management module is used to traverse the corresponding workshop equipment in the production workshop according to the optimal production sequence chain, and then continuously obtain the real-time status data of each workshop equipment. By judging whether each real-time status data is within the corresponding standard status data range, the dynamic production sequence generation module is enabled to adjust the optimal production sequence chain in real time according to the judgment result.

[0008] Furthermore, the process of collecting the historical status data of the workshop equipment includes: The workshop equipment data acquisition module sets a number for each workshop equipment in the production workshop, installs multiple sensors on each workshop equipment, and sets the workshop equipment to have a standby state, a shutdown state, and a working state. According to the state of each workshop equipment, a data acquisition cycle of different lengths is set for each workshop equipment; For the shutdown state and standby state, each time a data collection cycle starts, each sensor located on the workshop equipment collects the corresponding equipment status data. In the working state, each sensor collects the product status data of the product in addition to the equipment status data; When the data collection cycle ends, the equipment status data from the same workshop equipment are integrated to obtain the corresponding equipment status data set. The above process of generating the equipment status data set is adopted, and then the workshop equipment data collection module collects several historical equipment status data sets when each workshop equipment generates different products.

[0009] Furthermore, the process of establishing the standard state data interval includes: Obtaining product production steps of various types of products through the Internet, wherein the product production steps are composed of a plurality of production sub-steps; A multidimensional coordinate system is established, and the same historical status data in each historical device status data set is mapped into the same dimensional coordinate system. Several detection time points are set on the time coordinate axis, and each historical status data is divided into several historical status data segments according to the detection time points. The historical status data segments between each detection time point are normally distributed, and then the standard status data interval of the corresponding type of historical status data is obtained according to the normal distribution result.

[0010] Furthermore, the process of establishing the workshop equipment distribution tree includes: Establish several workshop equipment nodes, and mark each workshop equipment node with the workshop equipment number in sequence, and then connect each workshop equipment node according to the spatial location distribution of each workshop equipment in the production workshop. At the same time, according to the material transfer position between two or more workshop equipment, set a transfer connection node between the corresponding workshop equipment nodes, and then obtain the workshop equipment distribution tree; At the same time, according to the time length of each historical status data in the historical equipment status data set, the standard interaction time between each workshop equipment and product is obtained; Each workshop equipment node in the workshop equipment distribution tree is marked with the production steps of the corresponding type of products that the workshop equipment can execute, and the standard status data interval in each state is bound to the corresponding workshop equipment node.

[0011] Furthermore, the process of establishing the product production sequence chain includes: Obtain the current status and various real-time status data of each workshop equipment, and map the current status and various real-time status data of each workshop equipment to the corresponding workshop equipment node in the workshop equipment distribution tree; The user uploads a product production event to the dynamic production sequence generation module, wherein the product production event includes the product name, the expected production quantity of the product, and the expected completion time point; According to the product name recorded in the product production event, the corresponding product production steps are deployed, and the corresponding product production sequence chain is established according to the sequence between each production sub-step in the product production step. The product production sequence chain is composed of multiple step nodes, and each step node has a unidirectional or parallel connection relationship.

[0012] Furthermore, the process of establishing the optimal production sequence chain includes: Obtain the production sub-step name of the step node of the first batch in the product production sequence chain, input the production sub-step name into the workshop equipment distribution tree, and then select the workshop equipment node with the corresponding production sub-step name label and the closed state or standby state in the workshop equipment distribution tree, compare and select the standard interaction time of each workshop equipment node to execute the corresponding generation sub-step, and select the workshop equipment node with the shortest standard interaction time as the production equipment node that executes the corresponding step node; Take the production equipment node of the first batch as the starting point, set the standard product transmission speed, and then the production sub-step name of one or more step nodes of the second batch in the product production sequence chain, and match the workshop equipment node with the corresponding production sub-step name in the workshop equipment distribution tree; According to the connection status between the first batch and the second matching step nodes in the product production sequence chain, the production equipment nodes of the first batch are pre-connected with the matching equipment nodes of each workshop; Determine whether each workshop equipment node pre-connected with the production equipment node is in working state, or is reserved by the best production sequence chain, and obtain a number of preparatory workshop equipment nodes according to the matching; Compare the standard interaction time of each preparatory production equipment node to execute the corresponding product, and then select the preparatory production equipment node with the smallest standard interaction time as the product production node that executes the corresponding production sub-step, repeatedly obtain the production equipment node corresponding to each step node, and then traverse the corresponding optimal production sequence chain in the workshop equipment distribution tree.

[0013] Furthermore, if there is a step node that is not matched with any workshop equipment node, it is determined that the corresponding product production event cannot be executed currently until there is a matching result later.

[0014] Furthermore, the execution process of the optimal production sequence chain includes: According to the optimal production sequence chain, the corresponding product raw materials are transferred to the corresponding workshop equipment, and the workshop equipment associated with the optimal production sequence chain is recorded as the preparation workshop equipment; Obtain the real-time status data set of each workshop equipment from the workshop equipment data acquisition module, and determine whether each real-time status data in the real-time status data set is within its corresponding standard status data interval and dynamic feature video; According to the judgment result, it is determined that the corresponding workshop equipment has an operation abnormality or the product has a production abnormality. Then, the workshop ecological management module sends the workshop equipment number of the operation abnormality or the workshop equipment number where the product is currently located to the dynamic production sequence generation module. Then, the dynamic production sequence generation module adjusts all current optimal production sequence chains associated with the workshop equipment according to the workshop equipment number.

[0015] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention generates a corresponding product production sequence chain according to product production events, matches the product production sequence chain with the workshop equipment distribution tree, and then traverses the best production sequence chain from the workshop equipment distribution tree, thereby realizing the automated management of each equipment in the production workshop; 2. According to the optimal production sequence chain, the corresponding workshop equipment in the production workshop is traversed, and the real-time status data of each workshop equipment is continuously obtained. By judging whether each real-time status data is within the corresponding standard status data range, the optimal production sequence chain is adjusted in real time, which effectively improves the response efficiency of the production workshop when production abnormalities occur, and improves the utilization rate of workshop equipment. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] Figure 1 It is a schematic diagram of the present invention. DETAILED DESCRIPTION

[0017] In order to further explain the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the specific implementation mode, structure, characteristics and effects of the present invention are described in detail below in combination with the accompanying drawings and preferred embodiments.

[0018] like Figure 1 As shown, a digital production workshop management system based on MES includes a cloud computing platform, and the cloud computing platform is communicatively connected with a workshop equipment data acquisition module, an equipment status monitoring module, a dynamic production sequence generation module, and a workshop ecological management module; The workshop equipment data acquisition module is used to set a variety of sensors for each workshop equipment, and periodically collect historical status data of each workshop equipment in various states through the sensors; The equipment status supervision module is used to establish a standard status data interval for each production equipment in a corresponding state according to the historical status data of each workshop equipment in various states, and to establish a workshop equipment distribution tree according to the spatial position of each workshop equipment in the production workshop; The dynamic production sequence generation module is used to obtain the product production events of each product, and generate the corresponding product production sequence chain according to the product production events, match the product production sequence chain with the workshop equipment distribution tree, and then traverse the corresponding optimal production sequence chain from the workshop equipment distribution tree; The workshop ecological management module is used to traverse the corresponding workshop equipment in the production workshop according to the optimal production sequence chain, and then continuously obtain the real-time status data of each workshop equipment. By judging whether each real-time status data is within the corresponding standard status data range, the dynamic production sequence generation module is enabled to adjust the optimal production sequence chain in real time according to the judgment result.

[0019] Further, the working principle of the present invention is described below by way of examples: The workshop equipment data acquisition module sets numbers s1, s2, s3, ..., s n , where n is a natural number greater than 0; Various sensors are installed on each workshop equipment, such as cameras, temperature sensors, pressure sensors, etc. The workshop equipment is set with a standby state, a shutdown state, and a working state. According to the state of each workshop equipment, the workshop equipment data acquisition module sets data acquisition cycles of different lengths for the workshop equipment respectively; It should be noted that the length of the data collection cycle in the standby state is the longest, the length of the data collection cycle in the off state is the second longest, and the length of the data collection cycle in the working state is the shortest; For the shutdown state and standby state, each time a data collection cycle starts, each sensor located on the workshop equipment collects the corresponding equipment status data, while in the working state, each sensor collects not only the equipment status data but also the product status data of the products being processed by the workshop equipment; When the data collection cycle is over, each sensor uploads the collected data to the workshop equipment data collection module, and then the workshop equipment data collection module integrates the equipment status data from the same workshop equipment to obtain the corresponding equipment status data set, and marks the corresponding workshop equipment number and equipment status for the equipment status data set, where the equipment status data includes video data, temperature change curve, etc. It should be noted that the equipment status data set for the workshop equipment in working state includes not only the equipment status data but also the product status data, and the equipment status data set also carries the corresponding product name; The above process of generating the equipment status data set is adopted, and then the workshop equipment data collection module collects several historical equipment status data sets when each workshop equipment generates different products.

[0020] Furthermore, the workshop equipment data collection module sends all historical equipment status data sets to the equipment status supervision module, and the equipment status supervision module obtains the product production steps of various types of products through the Internet. It should be noted that the product production steps are composed of several production sub-steps; Establish n workshop equipment nodes, and mark each workshop equipment node with the workshop equipment number in turn, and then connect each workshop equipment node according to the spatial location distribution of each workshop equipment in the production workshop. At the same time, according to the material transfer position between two or more workshop equipment, set a transfer connection node between the corresponding workshop equipment nodes, and then obtain the workshop equipment distribution tree; It should be noted that the connection lines between the equipment nodes of each workshop are set in proportion to the length of the conveyor belts between the corresponding workshop equipment; First, historical equipment status data sets with the same product name are extracted from all historical equipment status data sets of equipment in different workshops. Then, the corresponding historical equipment status data sets are sorted in sequence according to the production sub-step sequence of each product. Based on the time length of each historical status data in the historical equipment status data set, the standard interaction time between each workshop equipment and the product is obtained. It should be noted that there are one or more production sub-steps of a product that can be performed by multiple workshop equipment, and there are multiple production sub-steps that can be performed simultaneously; A multi-dimensional coordinate system is established to centralize the historical device status data. The same historical status data except the video data is mapped to the same dimensional coordinate system. It should be noted that the dimensional coordinate systems where different types of data are located share a time coordinate axis. A number of detection time points are set on the time coordinate axis, and each historical state data is divided into a number of historical state data segments according to the detection time points, and the historical state data segments between each detection time point are normally distributed, and then the standard state data segment interval between each detection time point is obtained according to the normal distribution result; Connect the standard state data segment intervals between each detection time point in sequence to obtain the standard state data interval of the corresponding type of historical state data; For the historical state data whose data type is video data, several feature extraction pointers are set, and the historical state data whose data type is video data is divided into multiple historical state image data, and then corresponding feature image areas are extracted from each historical state image data through the feature extraction pointer, such as the part where the workshop equipment interacts with the product, etc.; Mapping the characteristic image areas in the historical state image data from different data collection cycles but corresponding to the same workshop equipment and the same product name at the same detection time point onto the same two-dimensional coordinate system; Select the pixel point at the center position of each feature image area as the center pixel, set the distance threshold, compare the distance between each center pixel on the same two-dimensional coordinate system with the distance threshold, if the distance between the two is less than or equal to the distance threshold, then the corresponding feature image area is fused and spliced, otherwise no operation is performed, after the distance comparison between each feature image area is completed, the feature image area that has not been fused and spliced ​​with any feature image area is directly eliminated; The feature image areas retained at each detection time point are overlapped and spliced ​​in chronological order to obtain dynamic feature videos between corresponding workshop equipment and product names; The process of generating standard state data intervals and dynamic feature videos of various types of historical state data in the working state is adopted to obtain standard state data intervals and dynamic feature videos in the standby state and the off state; Each workshop equipment node in the workshop equipment distribution tree is labeled with the production steps of the type of products that the corresponding workshop equipment can execute, and the standard status data interval and dynamic feature video in each state are bound to the corresponding workshop equipment node. Then the equipment status supervision module sends the workshop equipment distribution tree to the dynamic production sequence generation module.

[0021] Furthermore, the dynamic production sequence generation module obtains the current status and various real-time status data of each workshop equipment from the workshop equipment data acquisition module, and then maps the current status and various real-time status data of each workshop equipment to the corresponding workshop equipment node in the workshop equipment distribution tree; The user uploads a product production event to the dynamic production sequence generation module, wherein the product production event includes the product name, the expected production quantity of the product, and the expected completion time point; The dynamic production sequence generation module allocates corresponding product production steps according to the product name recorded in the product production event, and establishes a corresponding product production sequence chain according to the sequence between each production sub-step in the product production step. The product production sequence chain is composed of multiple step nodes, and each step node has a unidirectional or parallel connection relationship; Match each step node in the product production sequence chain in sequence with the workshop equipment nodes that can execute the corresponding production sub-steps in the workshop equipment distribution tree. The specific process includes: First, obtain the production sub-step name of the step node of the first batch in the product production sequence chain, input the production sub-step name into the workshop equipment distribution tree, and then select the workshop equipment node with the corresponding production sub-step name label and the closed state or standby state in the workshop equipment distribution tree, compare and select the standard interaction time of each workshop equipment node to execute the corresponding generation sub-step, and then select the workshop equipment node with the shortest standard interaction time as the production equipment node that executes the corresponding step node; It should be noted that if there is a step node without a matching result, it is determined that the corresponding product production event cannot be executed currently until there is a matching result later; Take the production equipment node of the first batch as the starting point, set the standard product transmission speed, and then the production sub-step name of one or more step nodes of the second batch in the product production sequence chain, and match the workshop equipment node with the corresponding production sub-step name in the workshop equipment distribution tree; According to the connection status between the first batch and the second matching step nodes in the product production sequence chain, the production equipment nodes of the first batch are pre-connected with the matching equipment nodes of each workshop; The optimal production sequence chain being executed is mapped to the workshop equipment distribution tree, and the estimated product transmission time between each production equipment node and its pre-connected workshop equipment node is obtained based on the standard product transmission speed; Determine whether each workshop equipment node pre-connected with the production equipment node is in working state or reserved by the best production sequence chain; If it is not in working state and has not been reserved by any optimal production sequence chain, the corresponding workshop equipment node will be recorded as a pre-production equipment node; If it is only in working state but not reserved by any optimal production sequence chain, then determine whether the remaining working time of the workshop equipment corresponding to the corresponding workshop equipment node is less than or equal to the sum of the standard interaction time of the production equipment node and the expected product transmission time between the corresponding workshop equipment node; If it is less than or equal to, the corresponding workshop equipment node is recorded as a pre-production equipment node, otherwise the corresponding workshop equipment node is ignored; If it is not in working state but reserved by other optimal production sequence chains, the time starts from when the production equipment node starts to execute the production sub-step, and the time length when the corresponding optimal production sequence chain starts to use the corresponding workshop equipment node is obtained, and the first time length is added to the standard interaction time length of the corresponding workshop equipment to execute the corresponding production sub-step, and the second time length when the use ends; Determine whether the first time length is greater than or equal to the sum of the standard interaction time of the production equipment node and the expected product transmission time between the production equipment node and the corresponding workshop equipment node. If so, the corresponding workshop equipment node is recorded as a preparatory production equipment node; otherwise, the corresponding workshop equipment node is ignored. Alternatively, it is determined whether the second time length is less than or equal to the sum of the standard interaction time of the production equipment node and the expected product transmission time between the production equipment node and the corresponding workshop equipment node. If so, the corresponding workshop equipment node is recorded as a preparatory production equipment node; otherwise, the corresponding workshop equipment node is ignored. If it is in working state and is reserved by other optimal production sequence chains, it is determined whether there is a time interval between the corresponding workshop equipment node ending the working state and executing the scheduled optimal production sequence. If not, the corresponding workshop equipment node is ignored. If it exists, determine whether the time interval is greater than or equal to the standard interaction time between the corresponding workshop equipment and the corresponding product. If it is less than, ignore the corresponding workshop equipment node. If it is greater than or equal to, determine whether the remaining working time of the workshop equipment corresponding to the corresponding workshop equipment node is less than or equal to the standard interaction time of the production equipment node, and the sum of the expected product transmission time between the corresponding workshop equipment nodes; If it is less than or equal to, the corresponding workshop equipment node is recorded as a pre-production equipment node, otherwise the corresponding workshop equipment node is ignored; Compare the standard interaction time of each preparatory production equipment node to execute the corresponding product, and then select the preparatory production equipment node with the smallest standard interaction time as the product production node that executes the corresponding production sub-step; It should be noted that if the production sub-step name in the second batch can be executed on the production equipment node of the first batch, the corresponding production equipment node in the first batch is directly recorded as the production equipment node of the corresponding step node; Repeat the above steps to obtain the production equipment nodes corresponding to each step node, and traverse the corresponding optimal production sequence chain in the workshop equipment distribution tree.

[0022] Furthermore, whenever the dynamic production sequence generation module generates an optimal production sequence chain, the optimal production sequence chain is automatically sent to the workshop ecological management module; The workshop ecological management module retrieves the corresponding product raw materials to the corresponding workshop equipment according to the optimal production sequence chain, and records the workshop equipment associated with the optimal production sequence chain as the preparatory workshop equipment; Obtain the real-time status data set of each workshop equipment from the workshop equipment data acquisition module, and determine whether each real-time status data in the real-time status data set is within its corresponding standard status data interval and dynamic feature video; If any real-time status data of a workshop equipment or product is not within its corresponding standard status data interval or the feature image area in the dynamic feature video for three consecutive detection time points, it is judged that the corresponding workshop equipment has an operation abnormality or the product has a production abnormality, and then the workshop ecological management module sends the workshop equipment number with the operation abnormality or the workshop equipment number where the product is currently located to the dynamic production sequence generation module, and then the dynamic production sequence generation module adjusts all current optimal production sequence chains associated with the workshop equipment according to the workshop equipment number; The above judgment process is repeated until each production equipment node in the optimal production sequence chain is judged to have completed execution.

[0023] The above description is only a preferred embodiment of the present invention and does not limit the present invention in any form. Although the present invention has been disclosed as a preferred embodiment as above, it is not used to limit the present invention. Any technical personnel in this field can make some changes or modify the technical contents disclosed above into equivalent embodiments without departing from the scope of the technical solution of the present invention. However, any brief modifications, equivalent changes and modifications made to the above embodiments based on the technical essence of the present invention without departing from the content of the technical solution of the present invention are still within the scope of the technical solution of the present invention.

Claims

1. A digital production workshop management system based on MES, including a cloud computing platform, characterized in that: The cloud computing platform is communicatively connected to a workshop equipment data acquisition module, an equipment status monitoring module, a dynamic production sequence generation module, and a workshop ecological management module; The workshop equipment data acquisition module is used to set a variety of sensors for each workshop equipment, and periodically collect historical status data of each workshop equipment in various states through the sensors; The equipment status supervision module is used to establish a standard status data interval for each production equipment in a corresponding state according to the historical status data of each workshop equipment in various states, and to establish a workshop equipment distribution tree according to the spatial position of each workshop equipment in the production workshop; The dynamic production sequence generation module is used to obtain the product production events of each product, and generate the corresponding product production sequence chain according to the product production events, match the product production sequence chain with the workshop equipment distribution tree, and then traverse the best production sequence chain from the workshop equipment distribution tree; The workshop ecological management module is used to traverse the corresponding workshop equipment in the production workshop according to the optimal production sequence chain, and then continuously obtain the real-time status data of each workshop equipment. By judging whether each real-time status data is within the corresponding standard status data range, the dynamic production sequence generation module is enabled to adjust the optimal production sequence chain in real time according to the judgment result.

2. According to the MES-based digital production workshop management system of claim 1, it is characterized in that: The process of collecting the historical status data of the workshop equipment includes: Each workshop equipment in the production workshop is numbered and multiple sensors are installed. The workshop equipment is set with a standby state, a shutdown state and a working state. According to the state of each workshop equipment, a data collection cycle of different lengths is set for each workshop equipment; For the shutdown state and standby state, each sensor located on the workshop equipment collects equipment status data every time a data collection cycle starts. In the working state, each sensor collects not only equipment status data but also product status data of the product; When the data collection cycle is over, the equipment status data from the same workshop equipment are integrated to obtain the equipment status data set. The process of generating the equipment status data set is adopted to collect several historical equipment status data sets when each workshop equipment generates different products.

3. According to the MES-based digital production workshop management system of claim 2, it is characterized in that: The process of establishing the standard state data interval includes: Obtaining product production steps of various types of products through the Internet, wherein the product production steps are composed of a plurality of production sub-steps; A multidimensional coordinate system is established, and the same historical status data in each historical device status data set is mapped into the same dimensional coordinate system. Several detection time points are set on the time coordinate axis, and each historical status data is divided into several historical status data segments according to the detection time points. The historical status data segments between each detection time point are normally distributed, and then the standard status data interval of the corresponding type of historical status data is obtained according to the normal distribution result.

4. According to the MES-based digital production workshop management system of claim 3, it is characterized in that: The process of establishing the workshop equipment distribution tree includes: Establish several workshop equipment nodes, and mark each workshop equipment node with a workshop equipment number in sequence, and then connect each workshop equipment node to obtain a workshop equipment distribution tree according to the spatial location distribution of each workshop equipment in the production workshop; At the same time, according to the time length of each historical status data in the historical equipment status data set, the standard interaction time between each workshop equipment and product is obtained, and each workshop equipment node in the workshop equipment distribution tree is marked with the production steps of the corresponding workshop equipment executable product type, and the standard status data interval in each state is bound to the corresponding workshop equipment node.

5. According to the MES-based digital production workshop management system of claim 4, it is characterized in that: The process of establishing the product production sequence chain includes: The current status of each workshop equipment and various real-time status data are mapped to the corresponding workshop equipment node in the workshop equipment distribution tree. The user uploads the product production event to the dynamic production sequence generation module. The product production event includes the product name and the expected production quantity of the product; The corresponding product production steps are allocated according to the product names recorded in the product production events, and the corresponding product production sequence chain is established according to the sequence between the various production sub-steps in the product production steps. The product production sequence chain is composed of multiple step nodes, and each step node has a unidirectional or parallel connection relationship.

6. According to the MES-based digital production workshop management system of claim 5, it is characterized in that: The process of establishing the optimal production sequence chain includes: Obtain the production sub-step name of the step node of the first batch in the product production sequence chain, input the production sub-step name into the workshop equipment distribution tree, and then select the workshop equipment node with the corresponding production sub-step name label and the closed state or standby state in the workshop equipment distribution tree, compare and select the standard interaction time of each workshop equipment node to execute the corresponding generation sub-step, and select the workshop equipment node with the shortest standard interaction time as the production equipment node that executes the corresponding step node; Starting from the production equipment node of the first batch, the production sub-step names of one or more step nodes of the second batch in the product production sequence chain are matched with the workshop equipment nodes marked with the corresponding production sub-step names in the workshop equipment distribution tree; According to the connection status between the first batch and the second matching step nodes in the product production sequence chain, the production equipment nodes of the first batch are pre-connected with the matching equipment nodes of each workshop; Determine whether each workshop equipment node pre-connected with the production equipment node is in working state, or is reserved by the best production sequence chain, and obtain a number of preparatory workshop equipment nodes according to the matching; Compare the standard interaction time of each preparatory production equipment node to execute the corresponding product, and then select the preparatory production equipment node with the smallest standard interaction time as the product production node to execute the corresponding production sub-step, repeat the process of obtaining the production equipment node corresponding to each step node, and then traverse the corresponding optimal production sequence chain in the workshop equipment distribution tree.

7. The MES-based digital production workshop management system according to claim 6 is characterized in that: If there is a step node that is not matched with any workshop equipment node, it is determined that the corresponding product production event cannot be executed currently until there is a matching result later.

8. The MES-based digital production workshop management system according to claim 6 is characterized in that: The execution process of the optimal production sequence chain includes: According to the best production sequence chain, the raw materials of the products are transferred to the corresponding workshop equipment, and the workshop equipment associated with the best production sequence chain is recorded as the preparation workshop equipment; Obtain the real-time status data set of each workshop equipment, and determine whether each real-time status data in the real-time status data set is within its corresponding standard status data interval and dynamic feature video; According to the judgment results, it is determined that the corresponding workshop equipment has an operation abnormality or the product has a production abnormality. Then, the workshop ecological management module sends the workshop equipment number of the operation abnormality or the workshop equipment number where the product is currently located to the dynamic production sequence generation module, and then adjusts all current optimal production sequence chains associated with the workshop equipment according to the workshop equipment number.

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