Multi-production-line-oriented equipment state information aggregation display system

Abstract

The invention relates to the technical field of equipment information aggregation, in particular to a multi-production-line-oriented equipment state information aggregation display system, which comprises a production topology network construction module, a production topology network management module and a production topology network management module, and establishing a network formed by the equipment nodes, the process nodes and the cache region nodes. According to the invention, on the basis of an equipment list, a process sequence and a material circulation relation imported by a manufacturing execution system, a production topology composed of equipment nodes, process nodes and cache region nodes is established, a uniform production network with static attributes is constructed, and traceable association of an equipment structure, a material path and a process link is realized. And mapping the real-time acquired equipment operation state and the quantity of products in process to corresponding equipment node attributes, and obtaining a path comprehensive blocking index through comprehensive calculation of the beat time and the quantity of the products in process in the path, so that the dynamic nature of material circulation and the production bottleneck condition are synchronously quantified.

Description

TECHNICAL FIELD

[0001] The present application relates to the technical field of device information aggregation, in particular to a device state information aggregation display system for multiple production lines. BACKGROUND

[0002] The device state information aggregation display system is a centralized perception and dynamic presentation of the running state of production equipment. However, the prior art only relies on direct collection and global unified display of the running state of the equipment, lacks modeling and analysis of the correlation between the devices, and does not establish a structured relationship between the device state information and the process sequence, material flow, and work-in-process quantity, resulting in insufficient ability to identify the production topology structure and material path blocking conditions. When a local exception occurs in the production link, such as equipment downtime or material shortage, the prior art can only provide a local state alarm, making it difficult to accurately identify the bottleneck node and upstream and downstream transmission relationship. Therefore, improvement is needed. SUMMARY

[0003] The purpose of the present application is to solve the shortcomings in the prior art and provide a device state information aggregation display system for multiple production lines.

[0004] In order to achieve the above-mentioned purpose, the present application adopts the following technical scheme: a device state information aggregation display system for multiple production lines comprises: A production topology network construction module is configured to establish a network composed of device nodes, process nodes, and buffer area nodes based on the device list, process sequence, and material flow relationship imported from the manufacturing execution system, and generate a production network with static attributes. A real-time state dynamic mapping module is configured to map the real-time collected device running state and work-in-process quantity information to the corresponding device node attributes based on the production network with static attributes, establish a real-time device state node set, and calculate a path comprehensive blocking index based on the cycle time of each node in the real-time device state node set and the work-in-process quantity of the path, to obtain a dynamic weighted material flow path diagram. A production bottleneck correlation analysis module is configured to trace upstream from the warehouse outlet node along the path based on the dynamic weighted material flow path diagram, obtain the upstream cumulative blocking value of each node, compare the upstream cumulative blocking value of each node with a preset bottleneck threshold, filter the bottleneck node and directly associated upstream and downstream nodes, and generate a bottleneck transmission chain identification list. A disturbance propagation risk assessment module is configured to set the downtime length of the nodes in the bottleneck transmission chain identification list based on the dynamic weighted material flow path diagram, calculate the expected waiting time of all downstream paths due to material shortage, obtain a downstream equipment expected waiting time sequence, aggregate each waiting time in the downstream equipment expected waiting time sequence and the production capacity value of the corresponding node, and obtain a key propagation node risk index.

[0005] Preferably, the obtaining step of the production network with static attributes is: According to the equipment list, process sequence and material flow relationship imported from the manufacturing execution system, the equipment identification and the process to which it belongs are extracted, the connection between the front and back of the process sequence is extracted, the starting point and the end point of the material flow relationship are extracted, the entries are established according to the equipment nodes, process nodes and buffer area nodes, the path records are established according to the starting point to the end point, and the node and path corresponding relationship list is obtained; According to the node and path corresponding relationship list, the beat time field value is written for the equipment node, the beat time field value is written for the process node, the beat time field value is written for the buffer area node, and the standard flow time field value is written for each material flow path. The missing fields are checked and the source is recorded, and the node beat time and path standard flow time summary list is generated; According to the node beat time and path standard flow time summary list, the equipment nodes, process nodes and buffer area nodes are connected as a directed structure according to the material flow relationship, the beat time is attached to the corresponding node, and the standard flow time is attached to the corresponding path. The binding generation of topological structure and static attributes is completed, and the production network with static attributes is formed.

[0006] Preferably, the obtaining step of the real-time equipment state node set is: According to the production network with static attributes, the real-time equipment running state and the work-in-process quantity information are read piece by piece, the running state value is written according to the equipment node identification, the work-in-process quantity value is written according to the material flow path number, and the beat time value of each equipment node and the standard flow time value of the path are extracted, forming the real-time equipment state node set.

[0007] Preferably, the obtaining step of the dynamic weighted material flow path graph is: According to the real-time equipment state node set, the path comprehensive congestion index is calculated; According to the path comprehensive congestion index, the calculated comprehensive congestion index is written into the material flow path record piece by piece, the path attached attribute in the production network with static attributes is updated, and the dynamic weighted material flow path graph is formed.

[0008] Preferably, the obtaining step of the upstream cumulative congestion value of each node is: According to the dynamic weighted material flow path graph, the path is traced back piece by piece from the delivery port node, the non-running state time length of each equipment node passed by the path and the path comprehensive congestion index of the path are extracted together, the cumulative value is accumulated level by level according to the path order, and the corresponding cumulative value is recorded for each node. The upstream cumulative congestion value of each node is obtained.

[0009] Preferably, the obtaining step of the bottleneck conduction chain identification list is: According to the upstream accumulated blocking value of each node, the upstream blocking value of each node is compared with a preset bottleneck threshold one by one, nodes with a blocking value greater than or equal to the preset bottleneck threshold are marked, nodes with a blocking value less than the preset bottleneck threshold are removed, and a bottleneck node set meeting the condition is generated; According to the bottleneck node set, the direct upstream node and the direct downstream node of the bottleneck node in the dynamic weighted material flow path graph are extracted, are classified together with the bottleneck node, and form a bottleneck conduction chain identification list.

[0010] Preferably, the obtaining step of the downstream equipment expected waiting time sequence is: According to the dynamic weighted material flow path graph, the shutdown time of each node in the bottleneck conduction chain identification list is set, is expanded downstream step by step along the directed connection, the affected downstream equipment node set and the shortest topological distance of each downstream equipment node to the initial node are identified, the production capacity value of each downstream equipment node and the work-in-process quantity of the upstream buffer area and the production capacity of itself are extracted, and a downstream equipment influence list is formed; According to the downstream equipment influence list, a lack-of-material signal propagation is triggered according to the initial node shutdown time, the arrival time is calculated path by path and is written into the expected waiting time of the downstream equipment node, the upstream buffer time is calculated by dividing the work-in-process quantity of the upstream buffer area by the production capacity of the downstream equipment node, the upstream buffer time of each downstream equipment node is supplemented, the shortest topological distance and the production capacity value, and the downstream equipment expected waiting time sequence is obtained.

[0011] Preferably, the obtaining step of the key propagation node risk index is: According to the downstream equipment expected waiting time sequence, the key propagation node risk index is calculated.

[0012] Compared with the prior art, the application has the advantages and positive effects that: In this invention, a production topology consisting of equipment nodes, process nodes, and cache nodes is established based on the equipment list, process sequence, and material flow relationships imported from the manufacturing execution system. This constructs a unified production network with static attributes, achieving traceable associations between equipment structure, material paths, and process links. The real-time collected equipment operating status and WIP quantity are mapped to the corresponding equipment node attributes. The comprehensive path blocking index is obtained through a comprehensive calculation of takt time and path WIP quantity, allowing the dynamic nature of material flow and production bottleneck conditions to be quantified simultaneously. Simultaneously, based on the path blocking situation, the overall production correlation is traced, the upstream blocking value of each node is cumulatively calculated, and the bottleneck nodes and their upstream and downstream associated nodes with the greatest impact are screened. A bottleneck transmission chain is generated to ensure the identification of bottleneck transmission relationships. At the same time, combined with the downtime of the nodes in the bottleneck transmission chain, the impact of material shortages is transmitted layer by layer, and the expected waiting time of downstream equipment is calculated. The equipment waiting time is then aggregated with the production capacity value to obtain the risk index of the key propagation node, thereby quantifying the actual impact of disturbance propagation on production efficiency and production capacity loss. In summary, the present invention organically integrates multi-dimensional participating items such as equipment status, number of work-in-progress, path blockage, bottleneck propagation, and production capacity value to achieve dynamic modeling and quantitative analysis of global production risks, thereby improving the visualization level of the production process, the accuracy of bottleneck identification, and the real-time performance of risk assessment, providing high-precision support for production plan optimization and resource scheduling. BRIEF DESCRIPTION OF THE DRAWINGS

[0013] Figure 1 It is a system flow chart of the present invention. DETAILED DESCRIPTION

[0014] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the present invention will be further described in detail below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0015] See also Figure 1 The present invention provides a technical solution: a multi-production line equipment status information aggregation display system comprising: The production topology network construction module is used to build a network consisting of equipment nodes, process nodes, and buffer area nodes based on the equipment list, process sequence, and material flow relationship imported from the manufacturing execution system, generating a production network with static attributes; The real-time status dynamic mapping module is used to map the real-time collected equipment operating status and WIP quantity information to the corresponding equipment node attributes based on the production network with static attributes, establish a real-time equipment status node set, and then calculate the comprehensive path blocking index based on the takt time of each node in the real-time equipment status node set and the WIP quantity of the path to obtain a dynamic weighted material flow path diagram; The production bottleneck correlation analysis module is configured to trace upstream from the egress node along the path according to the dynamic weighted material flow path diagram, obtain an upstream cumulative congestion value of each node, compare the upstream cumulative congestion value of each node with a preset bottleneck threshold, screen bottleneck nodes and directly associated upstream and downstream nodes, and generate a bottleneck conduction chain identification list; The disturbance propagation risk assessment module is configured to set a downtime of a node in the bottleneck conduction chain identification list according to the dynamic weighted material flow path diagram, calculate an expected waiting time of all downstream paths due to lack of materials, obtain a sequence of expected waiting times of downstream equipment, aggregate each waiting time in the sequence of expected waiting times of downstream equipment with a production capacity value of a corresponding node, and obtain a key propagation node risk index.

[0016] The obtaining step of the production network with static attributes is as follows: According to the equipment list, process sequence and material flow transfer relationship imported from the manufacturing execution system, the device identification and the process to which the device belongs are extracted, the connection between the front and rear of the process sequence is extracted, the starting point and the end point of the material flow transfer relationship are extracted, entries are established according to the device nodes, process nodes and buffer area nodes, path records are established according to the starting point to the end point, and a node and path correspondence list is obtained; According to the node and path correspondence list, a beat time field value is written for the device node, a beat time field value is written for the process node, a beat time field value is written for the buffer area node, a standard transfer time field value is written for each material flow transfer path, missing fields are checked and the source is recorded, a node beat time and path standard transfer time summary list is generated; According to the node beat time and path standard transfer time summary list, the device nodes, process nodes and buffer area nodes are connected as a directed structure according to the material flow transfer relationship, the beat time is attached to the corresponding node, and the standard transfer time is attached to the corresponding path, the binding of the topological structure and the static attributes is completed, and a production network with static attributes is formed.

[0017] Specifically, according to the equipment list, process sequence and material flow relationship imported by the manufacturing execution system, first, the data is parsed, wherein the equipment list is structured data containing equipment identification, equipment name, process identification and other fields, the process sequence is a list defining the connection relationship of each process identification, and the material flow relationship records the starting point and end point identification of the material flow between different positions. Then traverse the equipment list, create a unique data entry for each equipment identification, and associate its process identification. Then process the process sequence data, determine the upstream and downstream processes of each process by analyzing the connection relationship, and form a preliminary process flow chart. Then, according to the material flow relationship data, identify the starting entity identification and end entity identification of each flow step. These entities may be specific equipment or entire processes. Subsequently, based on the extracted information, the unified classification and creation of nodes are carried out, all unique equipment identifications are classified as equipment nodes, and all unique process identifications are classified as process nodes. At the same time, a buffer zone node is automatically inserted between two process nodes with material transfer, or between equipment and equipment with a clear material storage area. For example, when the output material of process A needs to pass through a conveyor belt to reach the starting equipment of process B, a buffer zone node is defined between the end equipment of process A and the starting equipment of process B, representing the storage of work-in-process on the conveyor belt. After completing the identification and creation of all nodes, the path records between nodes are established according to the material flow relationship and process sequence. Each path record contains a starting node identification and an end node identification. For example, a material flow relationship from equipment A to equipment B generates a path record from equipment node A to equipment node B. Finally, all established node entries and path records are summarized to form a list of node and path correspondence.

[0018] According to the node-path correspondence list, the assignment process of static attributes is started. Firstly, for each device node in the list, the standard unit product processing time of the device is queried and read from the pre-configured device process parameter library according to the device identifier, which is taken as the beat time field value of the node. For example, for a device with an identifier "CNC01", the standard processing time of a single part is 120 seconds, and 120 is written into the beat time field of the node. Then the process node is processed. For each process node, all device nodes contained therein are found, and the beat time values of these device nodes are obtained. The maximum value among these values is taken as the beat time of the process node. For example, a welding process contains two welding machines, and the beat times are 50 seconds and 65 seconds respectively. The beat time of the welding process node is set to 65 seconds. For the buffer node, as it has no processing capacity, its beat time is defined as the minimum operation time of the material in and out of the area, which is usually set to a fixed value close to zero, such as 0.1 seconds, to indicate that its impact on the production beat can be ignored. Then the standard transfer time of each material flow path is written. The value is obtained from the production process route file, which defines the standard time spent by the material in physical movement between two nodes. For example, the standard transfer time of the automatic guided vehicle from "buffer area A" to "assembly table B" is set to 180 seconds. After completing the preliminary assignment, the data checking program is executed to check whether there are null values in the beat time and standard transfer time fields of all nodes and paths. If the beat time of a device node is missing, the beat time of the process node to which the device belongs is used to fill it. If the beat time of the process node is also missing, the average value of the beat times of all devices of the same model is queried to fill it, and the filling source is recorded as "average estimation". If the standard transfer time of the material flow path is missing, the straight-line distance between the start and end nodes in the factory layout diagram is calculated, and multiplied by a preset average transport speed coefficient, such as 0.5 m / s, to estimate a time value, and the source is recorded as "distance estimation". Finally, the complete data set after assignment and checking is integrated to generate the node beat time and path standard transfer time summary list.

[0019] According to the node beat time and path standard flow time summary list, start to build the topology structure of the production network, first initialize a graph data structure, which supports the definition of nodes and edges of directed graph, then traverse all node records in the list, including device nodes, process nodes and buffer area nodes, create a corresponding vertex in the graph data structure for each node record, and store the unique identification of the node, node type and other information as the basic attributes of the vertex, then, the beat time value of each node recorded in the list is attached to the corresponding vertex in the graph as a static attribute, for example, add an attribute named "beat time" to the vertex representing "CNC01" device, whose value is 120, after all vertices are created and attributes are attached, then process the path records in the list, traverse each path record, find the corresponding two vertices in the graph data structure according to the start node identifier and end node identifier defined in the record, and establish a directed edge between the two vertices, the direction of the edge is from the start point to the end point, so as to accurately represent the flow direction of the material, then, the standard flow time value in the path record is attached as the weight or attribute of the newly created directed edge, for example, an attribute named "standard flow time" is attached to the directed edge between the "buffer area A" vertex and the "assembly table B" vertex, whose value is 180, by repeating this process, all material flow relationships in the list are converted into directed edges in the graph, so as to connect the discrete nodes into a complete topology network reflecting the entire production process, finally, a complete integrity check is performed on the constructed graph structure, starting from the preset production entry node, traversing along the directed edges, to ensure that all nodes on the process route are reachable and there is no interrupted path, after confirming that there is no error, the graph data structure integrated with the topology connection relationship, node static attributes and path static attributes finally forms a production network with static attributes.

[0020] The acquisition step of the real-time device state node set is: According to the production network with static attributes, read the real-time device running state and work-in-process quantity information one by one, write the running state value according to the device node identifier, write the work-in-process quantity value according to the material flow path number, and extract the beat time value of each device node and the standard flow time value of the path to form the real-time device state node set.

[0021] Specifically, according to the production network with static attributes, first, a real-time data connection channel is established with the bottom equipment control system and the manufacturing execution system database, the programmable logic controller data register of each device is periodically polled through the open platform communication unified architecture interface to obtain original state signals such as current value, running flag bit, fault code, etc., at the same time, the material scanning code information recorded between the starting point and the ending point of each material flow path in the work-in-process tracking database of the manufacturing execution system is queried, the number of work-in-process on the current path is counted by comparing the entering quantity and the output quantity, the data reading period is set to 5 seconds to ensure the timeliness of the information, then the original device state signals are analyzed and mapped, for example, when the average value of the current sensor reading of a certain device node in the past 5 seconds is greater than 1.2 times of the no-load current threshold value, the running state value is recorded as 1 (running), if it is less than the threshold value but greater than 0, it is recorded as 2 (standby), if it is equal to 0 or a specific fault code is received, it is recorded as 3 (stop), and this state value is written into the dynamic attribute field of the corresponding device node in the production network with static attributes, for the work-in-process quantity information, the counted quantity value, for example, 15 pieces, is written into the dynamic attribute field of the corresponding material flow path number, at the same time of writing these dynamic information, the preset beat time value of each device node and the standard flow time value of each material flow path are synchronously extracted from the production network with static attributes, the dynamic running state value, the work-in-process quantity value and the static beat time, standard flow time value are integrated into a temporary memory data structure, a record containing the above four fields is created for each node and path in the network, and the collection of all these records constitutes the real-time device state node set.

[0022] The acquisition step of the dynamically weighted material flow path diagram is: According to the real-time device state node set, the path comprehensive congestion index is calculated, the calculation formula is: ; Among them, is the comprehensive congestion index of the kth material flow path, is the work-in-process quantity value of the kth material flow path, is the bottleneck beat time value of the kth material flow path, that is, the maximum beat time on the path, is the cumulative non-running state time length sum of all device nodes on the kth material flow path, is the set observation time window value, is the actual average flow time value of the material on the kth material flow path, is the standard flow time value of the kth material flow path, is the adjustment weight coefficient for balancing the influence of the two parts; According to the path comprehensive congestion index, the calculated comprehensive congestion index is written into the material flow transfer path record piece by piece, the path attribute in the production network with static attribute is updated, and a dynamic weighted material flow path graph is formed.

[0023] Specifically, the path comprehensive congestion index calculation formula combines two dimensions of congestion sources: the first part is the "physical" congestion caused by work-in-process backlog and equipment downtime, where the number of work-in-process and the product of the bottleneck cycle time of the path reflects the theoretical time required to process the current backlog material, and the cumulative downtime of the equipment amplifies this congestion effect as a penalty term, and the second part is the "process" congestion caused by actual low efficiency, which is measured by comparing the difference between the actual transfer time and the standard time This design makes the congestion index not only reflect the static material accumulation, but also capture the impact of equipment failure and process delay.

[0024] The acquisition step is: this parameter represents the real-time work-in-process quantity on the kth material flow transfer path, which is realized by deploying radio frequency identification readers or barcode scanners at the starting point and the ending point of the path. When a work-in-process with a unique identifier enters the path, the starting point reader records its entry event and timestamp, and when it leaves the path, the ending point reader records its exit event and timestamp. The work-in-process quantity is obtained by counting the total number of work-in-process that have recorded entry events but have not recorded exit events at any observation time point. This counting process is completed by the work-in-process tracking module in real time, and provides query interfaces to the outside, for example, for path P001, at the current observation time, the system background database records that 18 work-in-process have scanned in, and only 3 work-in-process have scanned out, then the work-in-process quantity of this path is calculated as .

[0025] The acquisition step is: this parameter is the bottleneck cycle time of the kth material flow transfer path, that is, the maximum cycle time of all device nodes on the path. This parameter is directly extracted from the production network with static attributes generated in the previous step. First, identify the set of all device nodes contained in the kth path, then traverse each device node in this set, read its pre-set cycle time attribute value, and finally, select the maximum value from all read cycle time values as This process is dynamically executed every time the congestion index is calculated, for example, path P001 contains device A, device B and device C, and the cycle times recorded in their static attributes are 30 seconds, 45 seconds and 35 seconds respectively, then the bottleneck cycle time of this path is determined as seconds.

[0026] The acquisition step of the parameter is: the parameter represents the total sum of the cumulative non-running state time length of all device nodes on the kth path within the observation time window, the non-running state includes failure, waiting for material, changing type, etc., which is obtained by continuously monitoring the state signals of each device on the path. The system records the state of each device once every second. When the state is not "running", the timing starts until the state returns to "running" or the observation window ends. The time length is accumulated to the non-running time counter of the corresponding device. At the end of the observation window, the values of the counters of all device nodes on the path are added up. For example, within the observation window of 3600 seconds, device A on path P001 stops for 240 seconds due to failure, device B stops for 180 seconds due to waiting for material, and device C always runs normally. Then the total sum of the cumulative non-running state time length is seconds.

[0027] The acquisition step of the parameter is: the parameter is a set observation time window, the value of which is set according to the speed of production rhythm and the accuracy requirement of management response. For a production line with fast rhythm and frequent changes, a shorter time can be set, such as 15 minutes (900 seconds). For a production line with long production cycle and stable state, a longer time can be set, such as one shift (8 hours, i.e. 28800 seconds). In this example, considering the demand for hour-level production plan adjustment of the production line, a moderate time window is selected, and seconds, i.e. 1 hour.

[0028] The acquisition step of the parameter is: the parameter is the actual average flow-through time of the material on the kth path, which is obtained by tracking each work-in-process that completely passes through the path within the observation window. The time stamp of each work-in-process entering the path and the time stamp of each work-in-process leaving the path recorded by the work-in-process tracking module are used to calculate the difference between the two to obtain the actual flow-through time of a single work-in-process. Then the flow-through times of all the work-in-processes that completely pass through within the observation window are arithmetically averaged to obtain , for example, within the observation window of 3600 seconds, a total of 10 work-in-processes completely pass through path P001, and their respective flow-through times are 290, 310, 305, 295, 300, 315, 320, 298, 302, and 305 seconds. Then the actual average flow-through time is seconds.

[0029] The acquisition step of the parameter is that the parameter is the standard flow time of the kth material flow transfer path, the value is derived from the standard working time data defined in the process file, and is stored as a static attribute in the production network with static attributes. It represents the theoretical time required for the material to pass through the path under ideal conditions, including processing, handling and necessary waiting time. In the calculation, the attribute value is directly read from the network data according to the path number. For example, according to the process design, the standard flow time of path P001 is set to 30 seconds.

[0030] The acquisition step of the parameter is that the parameter is the adjustment weight coefficient balancing the influence of the two parts, and the setting aims to make the contribution of physical congestion and process congestion to the total index in the same order of magnitude. The setting process is as follows: first, collect the historical data of the production line running for more than one month, calculate the historical mean of the unweighted items of the first part of the formula and the second part , denoted as and , and the calculation formula of the adjustment weight coefficient is , for example, through historical data analysis, we get , , then the setting value of is .

[0031] According to the parameters, the calculation is as follows: Substitute the parameter values obtained above into the formula:

[0032] ; ; ; ; ; ; The result shows that the comprehensive congestion index of path P001 is 0.4237, which is a dimensionless evaluation value, and the numerical value reflects the severity of congestion. Threshold values can be set for judgment, for example, set the threshold value: when , it is "smooth", when , it is "mild congestion", and when , it is "serious congestion". The current calculation result 0.4237 is in the "mild congestion" interval, indicating that there is a certain problem of running efficiency in the path, but it has not reached the degree of serious bottleneck.

[0033] ​According to the path comprehensive congestion index, the update process of the dynamic attribute of the production network is started. First, all the material flow transfer path comprehensive congestion index result sets calculated in the last stage are traversed. The set contains the unique number of each path and its corresponding comprehensive congestion index value, such as (P001, 0.4237), (P002, 0.1582), (P003, 0.6711), etc. Then, for each record in the set, the path number is used to index in the production network with static attributes to accurately locate the directed edge representing the material flow transfer path. Then, in the attribute list of the directed edge, it is checked whether there is a dynamic attribute field named "comprehensive congestion index". If it exists, the value is directly updated to the latest value calculated. If it does not exist, the dynamic attribute field is added to the directed edge, and the calculated value is written, for example, for path P001, find its corresponding directed edge, and update the "comprehensive congestion index" attribute value to 0.4237. This update operation is atomic, ensuring data consistency. By processing the congestion indexes of all paths in turn, these quantitative indicators reflecting the current production dynamics are attached to the original production network topology containing only static process parameters, so that each "edge" in the network is given a dynamic weight. The size of this weight directly represents the smoothness of the material flow on the path. After completing the attribute update of all paths, the production network with static attributes is converted into a weighted graph containing real-time running status. The updated network structure is the dynamic weighted material flow path graph.

[0034] The upstream cumulative congestion value of each node is obtained by: According to the dynamic weighted material flow path graph, the non-running state time of each device node passed by the path is extracted together with the path comprehensive congestion index of the path, and is accumulated level by level in the order of the path. The corresponding cumulative value of each node is recorded to obtain the upstream cumulative congestion value of each node.

[0035] Specifically, according to the dynamic weighted material flow path diagram, first, all the delivery port nodes are identified in the diagram, which are terminal nodes with only in-degree but no out-degree in the topological structure, then an attribute named "upstream cumulative blocking value" is initialized for each node in the diagram, and the initial value is set to zero, then a graph traversal algorithm based on reverse topological sorting is used to calculate the value, all identified delivery port nodes are put into a processing queue, when the queue is not empty, a node is taken out from it, recorded as the current node, for the current node, all upstream adjacent nodes pointing to it are traversed, for each upstream node, an update calculation of the cumulative value is performed, the calculation process is as follows: first, the path comprehensive blocking index of the material flow transfer path connecting the upstream node and the current node is extracted, then the non-running state time length of the current node in the observation period is extracted from the attribute of the current node, the "upstream cumulative blocking value" of the current node, the path comprehensive blocking index of the path and the non-running state time length of the current node are added to obtain a temporary blocking value transmitted upwards, then the temporary blocking value is compared with the "upstream cumulative blocking value" of the upstream node, and the larger one of the two is taken to update the "upstream cumulative blocking value" of the upstream node, which can ensure that the node records the cumulative effect conducted from the most serious blocking path in all downstream paths, after processing each upstream node, it is checked whether all downstream nodes of the upstream node have been processed, if so, the upstream node is added to the end of the processing queue, and the process is repeated until the queue is empty, indicating that all possible paths from the delivery port to the starting point of production have been traced back, finally, the "upstream cumulative blocking value" attribute recorded in each node of the diagram is the upstream cumulative blocking value of each node.

[0036] The obtaining step of the bottleneck conduction chain identification list is: According to the upstream cumulative blocking value of each node, the upstream blocking value of each node is compared with the preset bottleneck threshold one by one, the nodes with a blocking value greater than or equal to the preset bottleneck threshold are marked, and the nodes with a blocking value less than the preset bottleneck threshold are removed, to generate a bottleneck node set meeting the condition; According to the bottleneck node set, the direct upstream node and the direct downstream node of the bottleneck node in the dynamic weighted material flow path diagram are extracted, and are classified together with the bottleneck node to form a bottleneck conduction chain identification list.

[0037] Specifically, according to the upstream cumulative congestion value of each node, a preset bottleneck threshold for judgment needs to be set first, and the determination of the threshold is based on statistical analysis of historical production data. The specific steps are as follows: collect the upstream cumulative congestion values of all nodes calculated in each observation window in the past production cycle of at least three months to form a large historical congestion value dataset, then calculate the mean and standard deviation of the dataset, and the calculation method of the preset bottleneck threshold is: threshold = mean + adjustment coefficient × standard deviation, wherein the adjustment coefficient is a parameter set according to the management sensitivity requirement. For example, if it is hoped to identify more serious congestion conditions accounting for about 5% of the historical data, the adjustment coefficient can be set to 1.65. If the mean calculated from the historical dataset is 85.4 and the standard deviation is 22.5, the preset bottleneck threshold is calculated as 85.4 + 1.65 × 22.5 = 85.4 + 37.125 = 122.525. After the preset bottleneck threshold is determined, the upstream cumulative congestion values calculated in the current observation period are processed one by one, an empty list is created to store the bottleneck nodes that meet the conditions, and the upstream cumulative congestion value of each node is compared with the calculated preset bottleneck threshold 122.525. If the upstream cumulative congestion value of the node is greater than or equal to 122.525, for example, the calculated value of a certain device node is 135.8, the unique identifier of the node is added to the bottleneck node list. If the upstream cumulative congestion value of the node is less than 122.525, for example, the calculated value of another process node is 98.2, no operation is performed on it, that is, it is excluded from the candidate set. When the upstream cumulative congestion values of all nodes are compared, the node identifiers in the list constitute the bottleneck node set that meets the conditions.

[0038] According to the bottleneck node set, an empty list structure is initialized, which will be used to store the final bottleneck conduction chain information, and then each bottleneck node identifier in the bottleneck node set is traversed, and for each bottleneck node, its identifier is used to search in the dynamic weighted material flow path diagram to obtain its adjacency relationship in the production network topology. First, all directed edges starting from the bottleneck node are found, and the end nodes of these directed edges are the direct downstream nodes of the bottleneck node. Collect the identifiers of all found direct downstream nodes to form a downstream node list. Then, all directed edges pointing to the bottleneck node are found, and the starting nodes of these directed edges are the direct upstream nodes of the bottleneck node. Similarly, collect the identifiers of all found direct upstream nodes to form an upstream node list. After obtaining the three key information (the bottleneck node itself, its direct upstream node list, and its direct downstream node list), a structured record containing the three parts is created, for example, for the bottleneck node "CNC05", if its upstream nodes are found to be "Buffer03" and "AGV02", and the downstream node is "Cleaning01", a record is generated as {Bottleneck Node: "CNC05", Upstream Nodes: ["Buffer03", "AGV02"], Downstream Nodes: ["Cleaning01"]}. Add this newly created record to the list initialized earlier. Repeat this operation for all nodes in the bottleneck node set until all bottleneck nodes have been processed. The final list obtained is the bottleneck conduction chain identification list.

[0039] The downstream device expected waiting time sequence acquisition step is: According to the dynamic weighted material flow path diagram, set the downtime of each node in the bottleneck conduction chain identification list, expand downstream along the directed connection, identify the affected downstream device node set and the shortest topological distance from each downstream device node to the initial node, extract the production capacity value of each downstream device node and the work-in-process quantity of the upstream buffer area and its own production capacity, and form a downstream device impact list; According to the downstream device impact list, trigger the lack of material signal propagation according to the initial node downtime, calculate the arrival time and write the expected waiting time of the downstream device node, calculate the upstream buffer time according to the upstream work-in-process quantity divided by the production capacity of the downstream device node, and supplement the upstream buffer time of each downstream device node, the shortest topological distance and the production capacity value, to obtain the downstream device expected waiting time sequence.

[0040] Specifically, according to the dynamic weighted material flow path diagram and the bottleneck conduction chain identification list, the influence analysis is performed on each node in the list as an initial disturbance source. First, a standard downtime is set for each initial node. The downtime is not randomly set, but is calculated based on historical fault maintenance data of the equipment. Specifically, all fault records of the equipment in the past year are extracted, and the 80% quantile value of the maintenance time (MTTR) is calculated as a representative and conservative evaluation time. For example, for the "CNC05" node in the list, the 80% quantile value of the historical maintenance time is 5400 seconds, and the downtime is set to 5400 seconds. Then, the breadth-first search (BFS) algorithm is performed on the dynamic weighted material flow path diagram, starting from the initial node, and traversing all directed connections downstream step by step. All traversed equipment nodes are identified as affected nodes and are included in a temporary downstream equipment node set. During the traversal process, the level depth of the BFS algorithm naturally records the number of nodes passed through by the shortest path from each downstream node to the initial node, which is the shortest topological distance. Subsequently, for each downstream equipment node in the set, its capacity value is extracted from the pre-established equipment basic information library. The value is pre-calculated and stored through the formula (product unit profit × equipment standard hour capacity). At the same time, the real-time work-in-process quantity of the node with the type of "buffer zone" in the direct upstream node of the downstream equipment node is queried, and the standard capacity (unit: piece / second) of the downstream equipment itself is read from the equipment basic information library. The identifiers, shortest topological distance, capacity value, upstream buffer work-in-process quantity, and self-capacity of all downstream equipment nodes collected for each initial node are integrated into a record, and finally a downstream equipment influence list is formed.

[0041] According to the downstream equipment impact list, the impact data caused by each initial node in the list is processed. First, the propagation process of the material shortage signal is simulated. The signal is triggered from the initial node at time 0. The time when it arrives at each downstream node depends on the physical time of material flow. To calculate this time, the Dijkstra algorithm is used on the dynamic weighted material flow path diagram. With the initial node as the source point, the shortest weighted path to each affected downstream equipment node is calculated. The weight of the path uses the "standard flow time" in the path attributes. The shortest weighted path length obtained by the algorithm is the arrival time of the material shortage signal. This value is recorded as the expected waiting time of the corresponding downstream equipment node. For example, the cumulative flow time of the shortest time path from the initial node to the downstream node "Inspection02" is 1800 seconds, then its expected waiting time is 1800 seconds. Then, the upstream buffer time of each downstream equipment node is calculated. This time represents the length of time that production can be maintained by relying solely on the WIP in its upstream buffer without receiving upstream incoming materials. It is calculated by dividing the "number of WIP in the upstream buffer" of the node recorded in the list by its "own production capacity". For example, if "Inspection02" has 240 WIP in its upstream buffer and its own production capacity is 0.2 pieces / second, its upstream buffer time is 240 divided by 0.2, which equals 1200 seconds. After completing these two key calculations, they are added to the corresponding records in the downstream equipment impact list. At the same time, the existing minimum topological distance and production capacity value data in the list are also organized to form a complete data record for each downstream equipment node, including its identity, expected waiting time, upstream buffer time, shortest topological distance, and production capacity value. All these records are organized according to the affiliation of the initial node, and the final result is the expected waiting time sequence of downstream equipment.

[0042] The steps to obtain the risk index of key propagation nodes are as follows: According to the expected waiting time sequence of downstream devices, the risk index of key propagation nodes is calculated using the following formula: ; in, is the propagation node risk index of the c-th node, is the set of downstream device nodes waiting due to the downtime of the cth node, For collection Any downstream device node in is the disturbance propagation attenuation factor, is the shortest topological distance between downstream device node j and the cth node, is the expected waiting time of downstream device node j, is the upstream buffering time of downstream device node j, is the production capacity value of downstream device node j, Initial downtime length of the cth node.

[0043] Specifically, the formula is: The above formula is to construct a quantitative evaluation index of the propagation risk of node disturbance, by The term accurately calculates the "net downtime" (unit: seconds) of each downstream node, acknowledging that the upstream buffer can absorb part of the disturbance, and only when the expected waiting time exceeds the buffer capacity will there be actual loss, which is more in line with production reality; secondly, the disturbance propagation attenuation factor is introduced as the index, that is, This simulates the physical phenomenon that the influence of disturbance will decay with distance when it propagates in the production chain; finally, the net downtime is multiplied by the capacity value (unit: yuan / second) representing economic importance to obtain the weighted economic loss (unit: yuan) of each downstream node, and the total downstream economic loss is obtained after summation, and then this total loss is divided by the initial downtime length (unit: seconds), and the final risk index is the weighted average economic loss rate (unit: yuan / second) caused by unit downtime, making events of different downtime lengths comparable, so as to identify those key propagation nodes that are most likely to amplify local problems into global losses.

[0044] The acquisition step is: this parameter represents the set of downstream equipment nodes affected by the downtime of the cth node, this set has been determined in the aforementioned step of generating the downstream equipment impact list, it is a list of identifiers of all downstream reachable equipment nodes found by taking node c as the initial node through a graph traversal algorithm (such as breadth-first search), without additional calculation, all downstream equipment entries associated with the initial node c can be extracted from the downstream equipment expected waiting time sequence to form the set, for example, if the initial node c is "CNC05", the downstream equipment expected waiting time sequence records that the downstream nodes affected by it are "Cleaning01", "Inspection02" and "Assembly03", then the set is {"Cleaning01", "Inspection02", "Assembly03"}.

[0045] The steps to obtain are as follows: This parameter is the disturbance propagation attenuation factor, which is a dimensionless number between 0 and 1 and is used to describe the inherent resilience of the production system. The closer its value is to 1, the easier it is for the disturbance to propagate downstream without attenuation. Its setting is based on expert evaluation of the tightness of production line coupling and historical data analysis. The evaluation dimensions include the buffer area capacity between each process, the reliability correlation of equipment, the flexibility of the material handling system, etc. A scoring standard (1-5 points) is set for each dimension. After multiple production line engineers score, the average value is taken and then converted into a value between 0.7 and 0.95 through a linear mapping function. For example, a production line with a small buffer capacity and closely related equipment has a comprehensive score of 4.5 points (out of 5 points). Through the mapping formula , calculated ,Pick .

[0046] The steps for obtaining are as follows: This parameter is the shortest topological distance of the downstream device node j relative to the initial node c, that is, the minimum number of path segments from c to j in the production network. This value has been calculated by the breadth-first search algorithm when building the downstream device impact list and recorded in the downstream device expected waiting time sequence. It can be directly queried based on the identifier of the downstream device node j. It is a non-negative integer. For example, in the downstream device expected waiting time sequence, the shortest topological distance record value corresponding to the downstream node "Inspection02" is 2, then .

[0047] The steps for obtaining are as follows: This parameter is the expected waiting time of the downstream device node j, which means the time required from the shutdown of the initial node c to the transmission of the material shortage impact to the node j. This value has been obtained by calculating the shortest weighted path from the initial node to each downstream node (with the standard flow time as the weight) through the Dijkstra algorithm when generating the expected waiting time sequence of the downstream equipment. The unit is seconds and can be directly queried according to the identifier of the downstream device node j. For example, if the expected waiting time corresponding to the downstream node "Inspection02" is 1800 seconds, then .

[0048] The steps to obtain is as follows: This parameter is the upstream buffer time of the downstream device node j, which represents the time that its upstream cached work-in-process can support its continuous production. This value has been calculated by dividing the number of work-in-process in its upstream cache area by its own production capacity when generating the expected waiting time sequence of the downstream device. The unit is seconds and can be directly queried. For example, if the upstream buffer time corresponding to the downstream node "Inspection02" is 1200 seconds, then .

[0049] The acquisition steps are as follows: This parameter is the capacity value of the downstream device node j, which measures the economic value of its output per unit time. This value is equal to the product of the unit profit of the product produced by the device and its standard hourly capacity. It has been converted into a value in "yuan / second" and stored in the downstream device expected waiting time sequence. It can be directly queried. For example, if the capacity value of the downstream node "Inspection02" is 0.15 yuan / second, then .

[0050] The steps for obtaining are as follows: This parameter is the downtime set for the initial node c, which is used to simulate and evaluate the impact of disturbances. This value has been set according to historical maintenance data in the first step of analysis, and the unit is seconds. When calculating the risk index for a specific initial node c, the value set for it at that time is used. For example, when analyzing the initial node "CNC05", its downtime is set to 5400 seconds, then .

[0051] Calculate based on parameters: Taking the initial node c = "CNC05" as an example, the set of downstream affected nodes is Contains three nodes, and the relevant parameters are as follows: Initial downtime Seconds, decay factor .

[0052] Node j1 = "Cleaning01": , Second, Second, Yuan / second.

[0053] Node j2 = "Inspection02": , Second, Second, Yuan / second.

[0054] Node j3 = "Assembly03": , Second, Second, Yuan / second.

[0055] Calculate the contribution of each node j in the sum (total weighted economic loss): j1 contribution value = Yuan.

[0056] j2 contribution value = Yuan.

[0057] j3 contribution value = Total weighted economic loss:

[0058] Total weighted economic loss:

[0059] Risk index of critical propagation node: ; The result shows that the risk index of the initial node "CNC05" is 0.1006, the unit of which is "yuan / second", representing that for every second of downtime of this node, it will cause an average of about 0.1006 yuan of weighted economic loss in the downstream production chain. By calculating this risk index for all bottleneck nodes, their criticality can be ranked, and the higher the index, the greater the impact of the downtime failure of the node on the entire production system, which is the object that needs to be prioritized and risk-controlled. For example, the risk level can be set as follows: an index greater than 0.1 yuan / second is high risk, 0.05 to 0.1 yuan / second is medium risk, and less than 0.05 yuan / second is low risk, so "CNC05" belongs to a high-risk propagation node.​

Claims

1. A multi-line oriented device status information aggregation and presentation system, characterized by, The system comprises: A production topology network construction module for establishing a network composed of device nodes, process nodes and buffer zone nodes, and generating a production network with static attributes according to the device list, process sequence and material flow transfer relationship imported by the manufacturing execution system; A real-time state dynamic mapping module for mapping the real-time collected device running state and work-in-process quantity information to the corresponding device node attributes according to the production network with static attributes, establishing a real-time device state node set, and calculating the path comprehensive congestion index according to the tact time and path of each node in the real-time device state node set to obtain a dynamic weighted material flow path diagram; A production bottleneck correlation analysis module for obtaining the upstream cumulative congestion value of each node, comparing the upstream cumulative congestion value of each node with a preset bottleneck threshold, screening the bottleneck nodes and directly correlated upstream and downstream nodes, and generating a bottleneck conduction chain identification list according to the dynamic weighted material flow path diagram; A disturbance propagation risk assessment module for setting the downtime of the nodes in the bottleneck conduction chain identification list, calculating the expected waiting time of all downstream paths due to material shortage, obtaining a downstream device expected waiting time sequence, aggregating each waiting time in the downstream device expected waiting time sequence and the capacity value of the corresponding node, and obtaining a key propagation node risk index.

2. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The obtaining step of the production network with static attributes is: According to the device list, process sequence and material flow transfer relationship imported by the manufacturing execution system, extracting the device identification and the process to which the device belongs, extracting the connection between the front and rear of the process sequence, extracting the starting point and ending point of the material flow transfer relationship, establishing entries according to the device nodes, process nodes and buffer zone nodes, recording paths according to the starting point to the ending point, and obtaining a node and path correspondence list; According to the node and path correspondence list, writing the tact time field value for the device node, writing the tact time field value for the process node, writing the tact time field value for the buffer zone node, and writing the standard transfer time field value for each material flow transfer path, correcting the missing fields and recording the source, and generating a node tact time and path standard transfer time summary list; According to the node tact time and path standard transfer time summary list, connecting the device nodes, process nodes and buffer zone nodes into a directed structure according to the material flow transfer relationship, attaching the tact time to the corresponding node, and attaching the standard transfer time to the corresponding path, completing the binding of the topology structure and the static attributes, and forming the production network with static attributes.

3. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The obtaining step of the real-time device state node set is: According to the production network with static attributes, reading the real-time device running state and work-in-process quantity information, writing the running state value according to the device node identification, writing the work-in-process quantity value according to the material flow transfer path number, and simultaneously extracting the tact time value of each device node and the standard transfer time value of the path to form a real-time device state node set.

4. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The obtaining step of the dynamic weighted material flow path diagram is: According to the real-time device state node set, calculating the path comprehensive congestion index; According to the path comprehensive congestion index, the calculated comprehensive congestion index is written into the material flow transfer path record, the path attribute of the production network with static attribute is updated, and a dynamic weighted material flow path diagram is formed.

5. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The upstream accumulated congestion value of each node is obtained by: According to the dynamic weighted material flow path diagram, the non-operation state duration of each device node passed by the path is extracted together with the path comprehensive congestion index of the path, and the accumulated value of each node is recorded to obtain the upstream accumulated congestion value of each node.

6. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The bottleneck conduction chain identification list is obtained by: According to the upstream accumulated congestion value of each node, the upstream congestion value of each node is compared with the preset bottleneck threshold value, the node with a congestion value greater than or equal to the preset bottleneck threshold value is marked, and the node with a congestion value less than the preset bottleneck threshold value is removed, to generate a bottleneck node set meeting the condition; According to the bottleneck node set, the direct upstream node and the direct downstream node of the bottleneck node in the dynamic weighted material flow path diagram are extracted and classified together with the bottleneck node to form a bottleneck conduction chain identification list.

7. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The downstream device expected waiting time sequence is obtained by: According to the dynamic weighted material flow path diagram, the shutdown duration of each node in the bottleneck conduction chain identification list is set, and the affected downstream device node set and the shortest topological distance from each downstream device node to the initial node are identified by expanding downstream along the directed connection, the production capacity value of each downstream device node and the work-in-process quantity of the upstream buffer area and the production capacity of itself are extracted, to form a downstream device influence list; According to the downstream device influence list, a material shortage signal is propagated according to the shutdown duration of the initial node, the arrival time is calculated and written into the expected waiting time of the downstream device node, the upstream buffer time is calculated by dividing the work-in-process quantity of the upstream buffer area by the production capacity of the downstream device node, and the upstream buffer time, the shortest topological distance and the production capacity value of each downstream device node are supplemented, to obtain the downstream device expected waiting time sequence.

8. The multi-line facing device state information aggregation and presentation system of claim 1, wherein, The key propagation node risk index is obtained by: According to the downstream device expected waiting time sequence, the key propagation node risk index is calculated.

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