Discrete manufacturing task management method, electronic device, and program product

Abstract

Embodiments of the present disclosure disclose a discrete manufacturing task management method, an electronic device and a program product. The discrete manufacturing task management method comprises: obtaining description data of a task node in a set of issued task nodes, the description data comprising a node identifier, an operation role and an issue time of the corresponding task node; determining an association relationship of the task nodes according to the description data of the task nodes in the set of issued task nodes; obtaining a to-be-issued task node; determining an associated task node in the to-be-issued task node according to the to-be-issued task node and the association relationship; and merging and issuing the associated task node to a corresponding operation role.

Description

Technical Field

[0001] This disclosure relates to the field of discrete manufacturing technology, specifically to a discrete manufacturing task management method, electronic device, and program product. Background Technology

[0002] Discrete manufacturing products are often assembled from multiple parts through a series of discontinuous processes. Examples include rockets, airplanes, weapons, ships, electronic equipment, machine tools, and automobiles. Companies that process these products can be called discrete manufacturing companies. Summary of the Invention

[0003] To address the problems in the related technologies, embodiments of this disclosure provide a discrete manufacturing task management method, electronic device, and program product.

[0004] In a first aspect, this disclosure provides a discrete manufacturing task management method, including:

[0005] Obtain the description data of the task nodes in the set of task nodes that have been issued. The description data includes the node identifier, operation role and issuance time of the corresponding task node.

[0006] The association relationships of task nodes are determined based on the description data of the task nodes in the set of task nodes that have been issued.

[0007] Get the nodes of tasks to be issued;

[0008] Based on the task nodes to be issued and the association relationship, determine the associated task nodes among the task nodes to be issued;

[0009] The associated task nodes are merged and distributed to the corresponding operation roles.

[0010] In conjunction with the first aspect, in a first implementation of the first aspect of this disclosure, determining the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes includes:

[0011] The association is determined based on the overlap of the operation roles and distribution times of the task nodes in the set of task nodes that have been issued. Specifically, when two task nodes have the same operation role and their distribution times belong to the same time slice, the operation roles and distribution times of the two task nodes are considered to overlap.

[0012] In conjunction with the first implementation of the first aspect, in the second implementation of the first aspect of this disclosure, the description data of the task node includes key-value pairs, where the key includes the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. The step of determining the association relationship based on the overlap of the operation roles and issuance times of the task nodes in the set of issued task nodes includes:

[0013] The task nodes in the issued task nodes are aggregated according to the key to obtain the aggregated result of the issued task nodes, and the aggregated result includes multiple aggregated nodes;

[0014] The association relationship is determined based on the overlap of the values ​​of the aggregated nodes.

[0015] In conjunction with the second implementation of the first aspect, in the third implementation of the first aspect of this disclosure, determining the association relationship based on the overlap of the values ​​of the aggregation nodes includes:

[0016] Calculate the support and confidence of the aggregated node pairs in the aggregation result, merge the aggregated node pairs according to the support and confidence, and update the aggregation result using the merged aggregated nodes;

[0017] Repeat the merge and update operations for the updated aggregation results until the aggregation nodes in the updated aggregation results can no longer be merged, and obtain the final aggregation result;

[0018] The association relationship is determined based on the merged aggregate node pairs in the final aggregation result.

[0019] In conjunction with the third implementation of the first aspect, this disclosure provides a fourth implementation of the first aspect:

[0020] The support of the aggregate node pair is represented by the ratio of the number of overlapping values ​​between the two aggregate nodes in the aggregate node pair to the number of duplicate values ​​after merging the two aggregate nodes;

[0021] The confidence level of the aggregate node pair is represented by the ratio of the number of overlapping values ​​between the two aggregate nodes in the pair to the number of unique values ​​of one of the aggregate nodes.

[0022] In conjunction with the first aspect, in a fifth implementation of the first aspect, the method further includes:

[0023] After obtaining the task node to be issued, it is determined whether the task node to be issued has an associated task node based on the association relationship. If so, a preset time period is waited. If the associated task node of the task node to be issued is received within the preset time period, the task node to be issued and the associated task node are issued together to the corresponding operation role.

[0024] Secondly, this disclosure provides a discrete manufacturing task management method, including:

[0025] Displays the task nodes to be issued and the associated task nodes among them;

[0026] Based on user input, determine the associated task nodes to be merged and issued;

[0027] The associated task nodes are merged and distributed to the corresponding operation roles.

[0028] In conjunction with the second aspect, in a first implementation of the second aspect of this disclosure, the method further includes:

[0029] A prompt message is displayed, prompting the user to wait for the associated task node of the task node to be issued;

[0030] Upon receiving the associated task node, recommendation information is displayed, which suggests associated task nodes that can be merged to the user.

[0031] In conjunction with the second aspect, this disclosure provides a second implementation of the second aspect:

[0032] The associated task nodes have the same operating role;

[0033] The associated task node is determined by any one of the methods described in the first aspect to the fifth implementation of the first aspect.

[0034] Thirdly, this disclosure provides a discrete manufacturing task management device, comprising:

[0035] The first acquisition module is configured to acquire description data of task nodes in the set of issued task nodes, the description data including the node identifier, operation role and issuance time of the corresponding task node;

[0036] The first determining module is configured to determine the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes;

[0037] The second acquisition module is configured to acquire the task nodes to be issued;

[0038] The second determining module is configured to determine the associated task node among the task nodes to be issued based on the task node to be issued and the association relationship;

[0039] The first merging module is configured to merge and distribute the associated task nodes to the corresponding operation roles.

[0040] In conjunction with the third aspect, in the first implementation of the third aspect of this disclosure, the step of determining the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes includes:

[0041] The association is determined based on the overlap of the operation roles and distribution times of the task nodes in the set of task nodes that have been issued. Specifically, when two task nodes have the same operation role and their distribution times belong to the same time slice, the operation roles and distribution times of the two task nodes are considered to overlap.

[0042] In conjunction with the first implementation of the third aspect, in the second implementation of the third aspect of this disclosure, the description data of the task node includes key-value pairs, where the key includes the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. The step of determining the association relationship based on the overlap of the operation roles and issuance times of the task nodes in the set of issued task nodes includes:

[0043] The task nodes in the issued task nodes are aggregated according to the key to obtain the aggregated result of the issued task nodes, and the aggregated result includes multiple aggregated nodes;

[0044] The association relationship is determined based on the overlap of the values ​​of the aggregated nodes.

[0045] In conjunction with the second implementation of the third aspect, in the third implementation of the present disclosure, the step of determining the association relationship based on the overlap of the values ​​of the aggregation nodes includes:

[0046] Calculate the support and confidence of the aggregated node pairs in the aggregation result, merge the aggregated node pairs according to the support and confidence, and update the aggregation result using the merged aggregated nodes;

[0047] Repeat the merge and update operations for the updated aggregation results until the aggregation nodes in the updated aggregation results can no longer be merged, and obtain the final aggregation result;

[0048] The association relationship is determined based on the merged aggregate node pairs in the final aggregation result.

[0049] In conjunction with the third implementation of the third aspect, this disclosure provides a fourth implementation of the third aspect:

[0050] The support of the aggregate node pair is represented by the ratio of the number of overlapping values ​​between the two aggregate nodes in the aggregate node pair to the number of duplicate values ​​after merging the two aggregate nodes;

[0051] The confidence level of the aggregate node pair is represented by the ratio of the number of overlapping values ​​between the two aggregate nodes in the pair to the number of unique values ​​of one of the aggregate nodes.

[0052] In conjunction with the third aspect, in a fifth implementation of the third aspect, the apparatus further includes:

[0053] The third determining module is configured to, after obtaining the task node to be issued, determine whether the task node to be issued has an associated task node based on the association relationship. If so, wait for a preset time period. If the associated task node of the task node to be issued is received within the preset time period, then issue the task node to be issued and the associated task node together to the corresponding operation role.

[0054] Fourthly, this disclosure provides a discrete manufacturing task management device, comprising:

[0055] The first display module is configured to display the task nodes to be issued and the associated task nodes among the task nodes to be issued;

[0056] The fourth module is configured to determine the associated task nodes to be merged and issued based on user input.

[0057] The second merging module is configured to merge the associated task nodes and distribute them to the corresponding operation roles.

[0058] In conjunction with the fourth aspect, in the first implementation of the fourth aspect, the method further includes:

[0059] The second display module is configured to display a prompt message that prompts the user to wait for the associated task node of the task node to be issued.

[0060] The third display module is configured to display recommendation information after receiving the associated task node, the recommendation information recommending associated task nodes that can be merged to the user.

[0061] In conjunction with the fourth aspect, this disclosure provides a second implementation of the fourth aspect:

[0062] The associated task nodes have the same operating role;

[0063] The associated task node is determined by the apparatus according to any one of the third aspect to the fifth implementation of the third aspect.

[0064] Fifthly, embodiments of this disclosure provide an electronic device including a memory and a processor, wherein the memory is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor to implement the method as described in any one of the first to second aspects, the second implementation.

[0065] In a sixth aspect, embodiments of this disclosure provide a computer-readable storage medium having computer instructions stored thereon, which, when executed by a processor, implement the method as described in any one of the second implementations of the first to second aspects.

[0066] In a seventh aspect, this disclosure provides a computer program product including computer instructions that, when executed by a processor, implement the method steps as described in any one of the second implementations of the first to second aspects.

[0067] According to the technical solution provided in this disclosure, task node description data is collected, and the association relationship between multiple task nodes is identified through an association rule algorithm. The system automatically merges tasks and issues them to the corresponding operation roles, thereby achieving batch processing of task nodes, improving concurrency, and ultimately improving overall production efficiency without affecting the overall assembly and manufacturing process and effect.

[0068] It should be understood that the above general description and the following detailed description are exemplary and explanatory only, and are not intended to limit this disclosure. Attached Figure Description

[0069] Other features, objects, and advantages of this disclosure will become more apparent from the following detailed description of non-limiting embodiments, taken in conjunction with the accompanying drawings. In the drawings:

[0070] Figure 1 A flowchart illustrating a discrete manufacturing task management method according to an embodiment of the present disclosure is shown.

[0071] Figure 2 A schematic diagram of a task node that has been issued according to an embodiment of this disclosure is shown.

[0072] Figure 3 A structural block diagram of a discrete manufacturing task management apparatus according to an embodiment of the present disclosure is shown.

[0073] Figure 4 A structural block diagram of a discrete manufacturing task management apparatus according to an embodiment of the present disclosure is shown.

[0074] Figure 5 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0075] Figure 6A schematic diagram of the structure of a computer system suitable for implementing the method according to embodiments of the present disclosure is shown. Detailed Implementation

[0076] In the following, exemplary embodiments of the present disclosure will be described in detail with reference to the accompanying drawings to enable those skilled in the art to readily implement them. Furthermore, for clarity, portions unrelated to the description of exemplary embodiments have been omitted from the drawings.

[0077] In this disclosure, it should be understood that terms such as “comprising” or “having” are intended to indicate the presence of features, figures, steps, behaviors, components, parts or combinations thereof disclosed in this specification, and are not intended to exclude the possibility of the presence or addition of one or more other features, figures, steps, behaviors, components, parts or combinations thereof.

[0078] It should also be noted that, unless otherwise specified, the embodiments and features described in this disclosure can be combined with each other. This disclosure will now be described in detail with reference to the accompanying drawings and embodiments.

[0079] In this disclosure, the acquisition of user information or user data is done with the user's authorization or confirmation, or by the user's active choice.

[0080] In the process of proposing this invention, the inventors discovered that the existing manufacturing operations management systems of discrete manufacturing enterprises rely heavily on manual scheduling to issue tasks on a per-product, per-line basis when executing multiple product processes in a serial manner, resulting in low execution efficiency.

[0081] Specifically, currently, when executing multiple product processing steps in a serial manner, the manufacturing operations management system generates corresponding task nodes based on the task execution status. For example, the manufacturing process starts with the task node "grinding part A". After this task node is completed, the task node "electroplated part A" is generated, and after that task node is completed, the task node "heat surface treatment of part A" is generated. The control center distributes the generated task nodes to the corresponding operating roles (e.g., workstations or workers) in real time, and the operating role executes the corresponding task. After the task is completed, the generation of the next task node is triggered.

[0082] However, large and complex products, such as aircraft, involve numerous components, and many processes are performed simultaneously. The same or similar task nodes may be executed repeatedly multiple times within a work cycle (e.g., a day). For example, "heat surface treatment of part A" might be performed 20 times a day by an operational role (e.g., "role 1"), and "heat surface treatment of part B" might be performed 15 times a day by role 1. That is, both similar operations, "heat surface treatment of part A" and "heat surface treatment of part B," are performed by role 1 and are executed multiple times a day. Currently, the control center of the manufacturing operations management system does not consider this correlation between task nodes when issuing them; instead, it mechanically issues a task node as soon as it is received. Even identical or similar tasks can only be executed sequentially, severely impacting overall production efficiency.

[0083] Existing MES (Manufacturing Execution System Software) includes a production scheduling module called APS (Advanced Planning and Scheduling). APS is a suite of production scheduling software that helps manufacturers better manage material flow within the plant or between plants, thereby better balancing sales, supply, production, and allocation. An APS system can synchronize production, materials, and resource allocation to generate a series of conditionally constrained plans. However, APS is order-demand oriented, and many constraints must be considered in advance to achieve optimal results. This heavily relies on existing experience being solidified in the software for it to take effect. Furthermore, packaged software cannot adapt; it relies primarily on pre-defined logic, resulting in insufficient system flexibility, poor adaptability, and a heavy dependence on the experience of the planners.

[0084] This disclosure provides a discrete manufacturing task management method to address the challenges faced by discrete manufacturing enterprises in managing multiple product processes sequentially within their manufacturing operations management systems. These processes often rely heavily on manual scheduling, assigning tasks on a per-product, per-line basis, resulting in low efficiency and an inability to automatically adjust and merge tasks to improve production efficiency and shorten overall assembly and manufacturing time. This disclosure collects task node description data from the manufacturing operations management system, identifies the relationships between multiple task nodes using an association rule algorithm, and automatically merges tasks and assigns them to the corresponding operational roles. This achieves batch processing of task nodes without affecting the overall assembly and manufacturing process and its effectiveness, thereby increasing concurrency and ultimately improving overall production efficiency.

[0085] Figure 1A flowchart illustrating a discrete manufacturing task management method according to an embodiment of the present disclosure is shown. Figure 1 As shown, the discrete manufacturing task management method includes the following steps S101-S105:

[0086] In step S101, the description data of the task nodes in the set of task nodes that have been issued is obtained. The description data includes the node identifier, operation role and issuance time of the corresponding task node.

[0087] In step S102, the association relationship of the task nodes is determined based on the description data of the task nodes in the set of task nodes that have been issued.

[0088] In step S103, the task node to be issued is obtained;

[0089] In step S104, the associated task nodes in the task nodes to be issued are determined according to the task nodes to be issued and the association relationship;

[0090] In step S105, the associated task nodes are merged and distributed to the corresponding operation roles.

[0091] Figure 2 A schematic diagram of a task node that has been issued according to an embodiment of this disclosure is shown.

[0092] like Figure 2 As shown, nodes 001, 002...010,... are the task nodes that have been sequentially generated and issued in the system. For example, the metadata log information generated by the task nodes can be obtained through the system's log collection component, and the descriptive data of the task nodes can be obtained from the metadata log information. According to embodiments of this disclosure, the metadata log information may include node name, input parameters, execution conditions, output parameters, task issuance time, task end time, operation role, etc.

[0093] Taking node 001 as an example, its description data is (node ​​A, [role 1 + TS1 / 10000]) or (node ​​A, [role 1 + T1]), where node A is the node identifier, such as the node name "heat treatment of part a surface", etc. Role 1 is the operation role, such as "workstation 1", etc. TS1 is the time when node 001 was issued to the operation role, such as a Unix timestamp. T1 is TS1 divided by the time slice length ( Figure 2 The integer part of the quotient obtained by the example time slice length is 10000. For ease of description, the following text will use Ti (i = 1, 2, ...) as the delivery time. In this way, time can be divided into multiple time slices. If two nodes belong to the same time slice and have the same operating role, then these two nodes have a certain correlation.

[0094] According to embodiments of this disclosure, the time slice length can be set according to actual needs. For example, a longer time slice length can be set in the first stage to obtain as many associated task nodes as possible. By merging and issuing associated task nodes, and then iteratively determining associated task nodes, the concentration of task node issuance can be increased. Then, in the second stage, the time slice length can be reduced, and stricter time constraints can be imposed on the association of nodes to avoid the system spending too much time waiting for associated nodes to appear, thereby further optimizing the discrete manufacturing task management process.

[0095] According to embodiments of this disclosure, the description data of a task node includes key-value pairs, where the key is the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. For example, in Figure 2 In the description data of node 001, the key is "node A" and the value is "role 1+T1".

[0096] According to an embodiment of this disclosure, determining the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes includes: determining the association relationship based on the overlap of the operation roles and issuance times of task nodes in the set of issued task nodes, wherein when two task nodes have the same operation role and the issuance time belongs to the same time slice, the operation roles and issuance times of the two task nodes are considered to overlap.

[0097] According to embodiments of this disclosure, having the same operating role is the basis for merging and issuing task nodes. If two task nodes have different operating roles, they cannot be merged and issued to the same operating role. On the other hand, when the issuance times of two task nodes belong to the same time slice, it indicates that the two task nodes are relatively close in time, and they can be merged and issued to the operating role. This facilitates the operating role in batch processing these two task nodes and improves task processing efficiency.

[0098] For example, such as Figure 2 As shown, nodes 001-004 all operate under role 1, and their distribution times all fall within time slice T1. Therefore, the operation roles and distribution times of nodes 001-004 are considered to overlap. The operation roles and distribution times of nodes 005, 006, 007, and 010 do not overlap. Nodes 008 and 009 both operate under role 2, and their distribution times both fall within time slice T3. Therefore, the operation roles and distribution times of nodes 008 and 009 are considered to overlap. Note that... Figure 2 This is merely an example to illustrate the principles of this disclosure. In practice, it can have the same characteristics as... Figure 2 The different task nodes are shown.

[0099] According to embodiments of this disclosure, the description data of the task node includes key-value pairs, where the key includes the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. Determining the association relationship based on the overlap of operation roles and issuance times of task nodes in the set of issued task nodes includes: aggregating the task nodes in the set of issued task nodes according to their keys to obtain an aggregation result of the issued task nodes, the aggregation result including multiple aggregate nodes; and determining the association relationship based on the overlap of the values ​​of the aggregate nodes.

[0100] According to embodiments of this disclosure, the key of the aggregation node includes the node identifier of the aggregation node, and the value of the aggregation node includes a sequence of values ​​of the aggregated task nodes.

[0101] For example, such as Figure 2 As shown, the key of task node 001 includes the node identifier "Node A", and the value includes the operation role and the issuance time "role 1 + T1".

[0102] According to embodiments of this disclosure, task nodes with the same key among the issued task nodes are aggregated into one aggregate node, thereby obtaining an aggregation result. For example, Figure 2 The aggregate nodes 001 to 006 are obtained, which correspond to the keys "Node A", "Node B", ..., "Node F" respectively.

[0103] The key of aggregation node 001 includes the node identifier "Node A", and the value is a sequence of values ​​from all task nodes with the key "Node A" in the assigned task nodes, i.e., "Role 1+T1, Role 1+T1, ...". Similarly, the key of aggregation node 002 includes the node identifier "Node B", and the value is a sequence of values ​​from all task nodes with the key "Node B" in the assigned task nodes, i.e., "Role 1+T1, Role 1+T1, Role 1+T2, ...", and so on.

[0104] Aggregate nodes describe the execution status of the same type of task node within each task node group. For example, the value sequence of aggregate node 001 describes the operational role and time slice to which node A is executed each time. Generally, the higher the overlap of values ​​between two aggregate nodes—that is, the greater the proportion of identical values ​​in their value sequences—the more suitable they are to be batch-processed together within the same time slice. Therefore, the relationship between task nodes can be determined based on the overlap of aggregate node values.

[0105] According to an embodiment of this disclosure, determining the association relationship based on the overlap of the values ​​of the aggregated nodes includes: calculating the support and confidence of the aggregated node pairs in the aggregation result; merging the aggregated node pairs according to the support and confidence; updating the aggregation result using the merged aggregated nodes; repeating the merging and updating operations for the updated aggregation result until the aggregated nodes in the updated aggregation result cannot be merged, thus obtaining the final aggregation result; and determining the association relationship based on the merged aggregated node pairs in the final aggregation result.

[0106] According to embodiments of this disclosure, aggregated node pairs with support greater than a first preset threshold and confidence greater than a second preset threshold are merged into one aggregated node.

[0107] According to embodiments of this disclosure, the support of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of the two aggregated nodes after merging; the confidence of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of one of the aggregated nodes.

[0108] For example, assuming the value of aggregation node X is [v1, v1, v1, v2] and the value of aggregation node Y is [v1, v1, v2, v3], the support of aggregation nodes X and Y can be calculated as follows: Specifically, the overlapping values ​​of aggregation nodes X and Y are v1 and v2, so the number of overlapping values ​​between aggregation nodes X and Y is 2, namely v1 and v2. After merging and deduplicating aggregation nodes X and Y, the values ​​are v1, v2, and v3, so the number of overlapping values ​​between aggregation nodes X and Y is 3. Therefore:

[0109] Support(X, Y) = Number of overlapping values ​​between aggregate node X and aggregate node Y / Number of duplicate values ​​between aggregate node X and aggregate node Y after merging = 2 / 3.

[0110] The higher the support of two aggregate nodes, the higher the overlap of their values, that is, the greater the proportion of identical values. Therefore, the more suitable their corresponding task nodes are to be merged together for batch processing.

[0111] According to embodiments of this disclosure, further, the confidence scores of aggregation nodes X and Y are calculated. Specifically, the overlapping values ​​of aggregation node X and aggregation node Y are v1 and v2, so the number of overlapping values ​​between aggregation node X and aggregation node Y is 2, namely v1 and v2. The deduplicated values ​​of aggregation node Y are v1, v2, and v3, so the deduplicated value of aggregation node Y is 3. Therefore, we have:

[0112] Confidence(X, Y) = Number of overlapping values ​​between aggregate node X and aggregate node Y / Number of duplicate values ​​removed from aggregate node Y = 2 / 3.

[0113] Confidence(X, Y) represents the probability that aggregate node X will appear after aggregate node Y appears. The higher the probability, the more suitable the tasks corresponding to the two aggregate nodes are to be merged together for batch processing.

[0114] According to embodiments of this disclosure, the above operation is performed on all aggregation node pairs in the aggregation result: aggregation node pairs with support greater than a first preset threshold and confidence greater than a second preset threshold are merged into one aggregation node, and aggregation node pairs with support less than or equal to the first preset threshold or confidence less than or equal to the second preset threshold are discarded. That is, the updated aggregation result only includes the aggregation node obtained by merging those aggregation node pairs with support greater than the first preset threshold and confidence greater than the second preset threshold.

[0115] According to embodiments of this disclosure, the first preset threshold can be set to 0.85, for example, and the second preset threshold can be set to 0.5, for example.

[0116] According to embodiments of this disclosure, when merging two aggregation nodes, the values ​​of the two aggregation nodes are merged and deduplicated to obtain the value of the merged aggregation node.

[0117] Then, for the updated aggregation result, repeat the above operations of calculating support and confidence and merging aggregation nodes according to support and confidence to update the aggregation result, until the aggregation nodes in the updated aggregation result can no longer be merged, and obtain the final aggregation result.

[0118] For example, if the final aggregation result contains two aggregation nodes P and Q, which are obtained by merging aggregation nodes x, y, z and s, t respectively, then it is assumed that the task nodes corresponding to aggregation nodes x, y, z are related, and the task nodes corresponding to aggregation nodes s, t are also related.

[0119] According to embodiments of this disclosure, the association relationships between task nodes are recorded as the association relationships between the node identifiers corresponding to the task nodes. For example, the association relationships can be "node A, node B, and node C are mutually associated", "node E and node F are mutually associated", and so on.

[0120] According to an embodiment of this disclosure, the discrete manufacturing task management method further includes: after obtaining a task node to be issued, determining whether the task node to be issued has an associated task node based on the association relationship; if so, waiting for a preset time period; if an associated task node of the task node to be issued is received within the preset time period, then issuing the task node to be issued and the associated task node together to the corresponding operation role.

[0121] For example, the system periodically scans the queue of task nodes to be issued. If the queue contains related task nodes, that is, task nodes whose node identifiers have the relationship described above, then recommendation information can be displayed on the system page to recommend related task nodes that can be merged to system users.

[0122] According to embodiments of this disclosure, if a task node in the queue of task nodes to be issued has an associated node, then regardless of whether the queue contains its associated node, it can wait for a preset time period, such as 10 minutes. If an associated task node of the task node to be issued is received within the preset time period, the task node to be issued and the associated task node can be issued together to the corresponding operation role, thereby merging and issuing associated task nodes as much as possible and improving manufacturing efficiency.

[0123] This disclosure also provides a discrete manufacturing task management method, including: displaying task nodes to be issued and associated task nodes among the task nodes to be issued; determining associated task nodes to be merged and issued according to user input; and merging and issuing the associated task nodes to the corresponding operation roles.

[0124] For example, the system's user interface can display the task nodes to be assigned and their associated task nodes in real time. For instance, assuming there are task nodes P1, P2, P3, and P4 to be assigned, where P1 and P4 have the aforementioned association, the user interface can display the recommendation message "P1 and P4 can be assigned together." If the user enters "Assign P1 and P4 together," then task nodes P1 and P4 can be assigned together to the corresponding user roles.

[0125] According to embodiments of this disclosure, the user interface can also display prompts to remind the user to wait for associated task nodes of the task node to be issued. For example, if the node identifier of a task node P5 to be issued is associated with other node identifiers, but there are no associated task nodes of task node P5 among the current task nodes to be issued, the user can be prompted to wait for associated task nodes of task node P5. Upon receiving the associated task node, recommendation information is displayed, suggesting associated task nodes that can be merged with task node P5. Optionally, even if there are associated task nodes of task node P5 among the current task nodes to be issued, the user can still be prompted to wait for other associated task nodes of task node P5. Upon receiving the associated task node, recommendation information is displayed, suggesting associated task nodes that can be merged with task node P5, thereby merging and issuing associated task nodes as much as possible and improving manufacturing efficiency.

[0126] According to embodiments of this disclosure, after collecting task node metadata, an association rule algorithm is applied for iteration to automatically generate a node merging plan and feed it back to the system. This plan directly applies to subsequent similar process changes, achieving adaptive optimization. This significantly improves the system's adaptability and evolvability, enabling it to output optimization decisions stably and continuously without requiring a large amount of manual rule abstraction and embedding. In actual production processes, it can automatically help discrete equipment manufacturing processes achieve sub-process task merging and batch processing, improving concurrency and thus enhancing overall production efficiency. This solves the technical problems of traditional solutions that rely on existing experience, require the pre-creation of a large number of rules and conditions, and cannot achieve adaptability.

[0127] Figure 3 A structural block diagram of a discrete manufacturing task management device according to an embodiment of the present disclosure is shown. This device can be implemented as part or all of an electronic device through software, hardware, or a combination of both.

[0128] like Figure 3 As shown, the discrete manufacturing task management device 300 includes a first acquisition module 310, a first determination module 320, a second acquisition module 330, a second determination module 340, and a first merging module 350.

[0129] The first acquisition module 310 is configured to acquire description data of task nodes in the set of issued task nodes, the description data including the node identifier, operation role and issuance time of the corresponding task node;

[0130] The first determining module 320 is configured to determine the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes;

[0131] The second acquisition module 330 is configured to acquire the task node to be issued;

[0132] The second determining module 340 is configured to determine the associated task node among the task nodes to be issued based on the task node to be issued and the association relationship;

[0133] The first merging module 350 is configured to merge and distribute the associated task nodes to the corresponding operation roles.

[0134] According to embodiments of this disclosure, determining the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes includes:

[0135] The association is determined based on the overlap of the operation roles and distribution times of the task nodes in the set of task nodes that have been issued. Specifically, when two task nodes have the same operation role and their distribution times belong to the same time slice, the operation roles and distribution times of the two task nodes are considered to overlap.

[0136] According to embodiments of this disclosure, the description data of the task node includes key-value pairs, where the key includes the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. Determining the association relationship based on the overlap of operation roles and issuance times of task nodes in the set of issued task nodes includes:

[0137] The task nodes in the issued task nodes are aggregated according to the key to obtain the aggregated result of the issued task nodes, and the aggregated result includes multiple aggregated nodes;

[0138] The association relationship is determined based on the overlap of the values ​​of the aggregated nodes.

[0139] According to embodiments of this disclosure, determining the association relationship based on the overlap of the values ​​of the aggregation nodes includes:

[0140] Calculate the support and confidence of the aggregated node pairs in the aggregation result, merge the aggregated node pairs according to the support and confidence, and update the aggregation result using the merged aggregated nodes;

[0141] Repeat the merge and update operations for the updated aggregation results until the aggregation nodes in the updated aggregation results can no longer be merged, and obtain the final aggregation result;

[0142] The association relationship is determined based on the merged aggregate node pairs in the final aggregation result.

[0143] According to embodiments of this disclosure, the support of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of the two aggregated nodes after merging; the confidence of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of one of the aggregated nodes.

[0144] According to an embodiment of this disclosure, the device 300 further includes: a third determining module 360, configured to, after obtaining the task node to be issued, determine whether the task node to be issued has an associated task node based on the association relationship; if so, wait for a preset time period; if an associated task node of the task node to be issued is received within the preset time period, then issue the task node to be issued and the associated task node together to the corresponding operating role.

[0145] Figure 4 A structural block diagram of a discrete manufacturing task management device according to an embodiment of the present disclosure is shown. This device can be implemented as part or all of an electronic device through software, hardware, or a combination of both.

[0146] like Figure 4 As shown, the discrete manufacturing task management device 400 includes a first display module 410, a fourth determination module 420, and a second merging module 430.

[0147] The first display module 410 is configured to display the task node to be issued and the associated task node among the task nodes to be issued;

[0148] The fourth determination module 420 is configured to determine the associated task nodes to be merged and issued based on user input;

[0149] The second merging module 430 is configured to merge and distribute the associated task nodes to the corresponding operation roles.

[0150] According to embodiments of this disclosure, the device 400 further includes:

[0151] The second display module 440 is configured to display a prompt message that prompts the user to wait for the associated task node of the task node to be issued.

[0152] The third display module 450 is configured to display recommendation information after receiving the associated task node, the recommendation information recommending merging associated task nodes to the user.

[0153] According to embodiments of this disclosure, the associated task nodes have the same operational role, and the associated task nodes are determined by the discrete task management device 300.

[0154] This disclosure also discloses an electronic device. Figure 5 A structural block diagram of an electronic device according to an embodiment of the present disclosure is shown.

[0155] like Figure 5 As shown, the electronic device 500 includes a memory 501 and a processor 502, wherein the memory 501 is used to store one or more computer instructions, wherein the one or more computer instructions are executed by the processor 502 to implement the method according to embodiments of the present disclosure.

[0156] This disclosure provides a discrete manufacturing task management method, including:

[0157] Obtain the description data of the task nodes in the set of task nodes that have been issued. The description data includes the node identifier, operation role and issuance time of the corresponding task node.

[0158] The association relationships of task nodes are determined based on the description data of the task nodes in the set of task nodes that have been issued.

[0159] Get the nodes of tasks to be issued;

[0160] Based on the task nodes to be issued and the association relationship, determine the associated task nodes among the task nodes to be issued;

[0161] The associated task nodes are merged and distributed to the corresponding operation roles.

[0162] According to embodiments of this disclosure, determining the association relationship of task nodes based on the description data of task nodes in the set of issued task nodes includes:

[0163] The association is determined based on the overlap of the operation roles and distribution times of the task nodes in the set of task nodes that have been issued. Specifically, when two task nodes have the same operation role and their distribution times belong to the same time slice, the operation roles and distribution times of the two task nodes are considered to overlap.

[0164] According to embodiments of this disclosure, the description data of the task node includes key-value pairs, where the key includes the node identifier of the corresponding task node, and the value includes the operation role and issuance time of the corresponding task node. Determining the association relationship based on the overlap of operation roles and issuance times of task nodes in the set of issued task nodes includes:

[0165] The task nodes in the issued task nodes are aggregated according to the key to obtain the aggregated result of the issued task nodes, and the aggregated result includes multiple aggregated nodes;

[0166] The association relationship is determined based on the overlap of the values ​​of the aggregated nodes.

[0167] According to embodiments of this disclosure, determining the association relationship based on the overlap of the values ​​of the aggregation nodes includes:

[0168] Calculate the support and confidence of the aggregated node pairs in the aggregation result, merge the aggregated node pairs according to the support and confidence, and update the aggregation result using the merged aggregated nodes;

[0169] Repeat the merge and update operations for the updated aggregation results until the aggregation nodes in the updated aggregation results can no longer be merged, and obtain the final aggregation result;

[0170] The association relationship is determined based on the merged aggregate node pairs in the final aggregation result.

[0171] According to embodiments of this disclosure, the support of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of the two aggregated nodes after merging; the confidence of the aggregated node pair represents the ratio of the number of overlapping values ​​of the two aggregated nodes in the aggregated node pair to the number of duplicate values ​​of one of the aggregated nodes.

[0172] According to an embodiment of this disclosure, the method further includes: after obtaining the task node to be issued, determining whether the task node to be issued has an associated task node based on the association relationship; if so, waiting for a preset time period; if an associated task node of the task node to be issued is received within the preset time period, then issuing the task node to be issued and the associated task node together to the corresponding operation role.

[0173] This disclosure also provides a discrete manufacturing task management method, including:

[0174] Displays the task nodes to be issued and the associated task nodes among them;

[0175] Based on user input, determine the associated task nodes to be merged and issued;

[0176] The associated task nodes are merged and distributed to the corresponding operation roles.

[0177] According to embodiments of this disclosure, the method further includes:

[0178] A prompt message is displayed, prompting the user to wait for the associated task node of the task node to be issued;

[0179] Upon receiving the associated task node, recommendation information is displayed, which suggests associated task nodes that can be merged to the user.

[0180] According to embodiments of this disclosure, the associated task nodes have the same operational role; the associated task nodes are determined through the discrete manufacturing task management method described above.

[0181] Figure 6 A schematic diagram of the structure of a computer system suitable for implementing the method according to embodiments of the present disclosure is shown.

[0182] like Figure 6 As shown, the computer system 600 includes a processing unit 601, which can execute various processes described in the above embodiments according to a program stored in a read-only memory (ROM) 602 or a program loaded from a storage section 608 into a random access memory (RAM) 603. The RAM 603 also stores various programs and data required for the operation of the system 600. The processing unit 601, ROM 602, and RAM 603 are interconnected via a bus 604. An input / output (I / O) interface 605 is also connected to the bus 604.

[0183] The following components are connected to I / O interface 605: an input section 606 including a keyboard, mouse, etc.; an output section 607 including a cathode ray tube (CRT), liquid crystal display (LCD), etc., and a speaker, etc.; a storage section 608 including a hard disk, etc.; and a communication section 609 including a network interface card such as a LAN card, modem, etc. The communication section 609 performs communication processing via a network such as the Internet. A drive 610 is also connected to I / O interface 605 as needed. A removable medium 611, such as a disk, optical disk, magneto-optical disk, semiconductor memory, etc., is installed on drive 610 as needed so that computer programs read from it can be installed into storage section 608 as needed. The processing unit 601 can be implemented as a CPU, GPU, TPU, FPGA, NPU, etc.

[0184] In particular, according to embodiments of this disclosure, the methods described above can be implemented as computer software programs. For example, embodiments of this disclosure include a computer program product comprising computer instructions that, when executed by a processor, implement the steps of the methods described above. In such embodiments, the computer program product can be downloaded and installed from a network via communication section 609, and / or installed from removable media 611.

[0185] The flowcharts and block diagrams in the accompanying drawings illustrate the architecture, functionality, and operation of possible implementations of systems, methods, and computer program products according to various embodiments of this disclosure. In this regard, each block in a flowchart or block diagram may represent a module, segment, or portion of code containing one or more executable instructions for implementing a specified logical function. It should also be noted that in some alternative implementations, the functions indicated in the blocks may occur in a different order than those indicated in the drawings. For example, two consecutively indicated blocks may actually be executed substantially in parallel, and they may sometimes be executed in reverse order, depending on the functions involved. It should also be noted that each block in the block diagrams and / or flowcharts, and combinations of blocks in the block diagrams and / or flowcharts, can be implemented using a dedicated hardware-based system that performs the specified function or operation, or using a combination of dedicated hardware and computer instructions.

[0186] The units or modules described in the embodiments of this disclosure can be implemented in software or programmable hardware. The described units or modules can also be located in a processor, and the names of these units or modules do not necessarily constitute a limitation on the unit or module itself.

[0187] In another aspect, this disclosure also provides a computer-readable storage medium, which may be a computer-readable storage medium included in the electronic device or computer system described above; or it may be a standalone computer-readable storage medium not assembled into a device. The computer-readable storage medium stores one or more programs, which are used by one or more processors to perform the methods described in this disclosure.

[0188] The above description is merely a preferred embodiment of this disclosure and an explanation of the technical principles employed. Those skilled in the art should understand that the scope of the invention involved in this disclosure is not limited to technical solutions formed by specific combinations of the above-described technical features, but should also cover other technical solutions formed by arbitrary combinations of the above-described technical features or their equivalents without departing from the inventive concept. For example, technical solutions formed by substituting the above-described features with (but not limited to) technical features disclosed in this disclosure that have similar functions.

Claims

1. A discrete manufacturing task management method, comprising: obtaining description data of task nodes in a set of issued task nodes, the description data comprising node identification, operation role and issue time of a corresponding task node; determining an association relationship of the task nodes according to the description data of the task nodes in the set of issued task nodes, wherein the association relationship is determined according to support and confidence of an aggregated node pair in an aggregation result, the support representing a ratio of a number of overlapping values of two aggregated nodes in the aggregated node pair to a number of de-duplicated values of the two aggregated nodes, and the confidence representing a ratio of the number of overlapping values of the two aggregated nodes to a de-duplicated value of one of the two aggregated nodes; obtaining a to-be-issued task node; determining associated task nodes in the to-be-issued task node according to the to-be-issued task node and the association relationship; issuing the associated task nodes to a corresponding operation role.

2. The method of claim 1, wherein, The determining of the association relationship of the task nodes according to the description data of the task nodes in the set of issued task nodes comprises: determining the association relationship according to overlapping of the operation role and the issue time of the task nodes in the set of issued task nodes, wherein when the operation roles of two task nodes are the same and the issue times belong to the same time slice, it is considered that the operation roles and the issue times of the two task nodes overlap.

3. The method of claim 2, wherein, The description data of the task nodes comprises key-value pairs, the key comprising node identification of a corresponding task node, and the value comprising the operation role and the issue time of the corresponding task node, and the determining of the association relationship according to the overlapping of the operation role and the issue time of the task nodes in the set of issued task nodes comprises: aggregating the task nodes in the set of issued task nodes according to the key to obtain an aggregation result of the set of issued task nodes, the aggregation result comprising a plurality of aggregated nodes; determining the association relationship according to overlapping of the values of the aggregated nodes.

4. The method of claim 3, wherein, The determining of the association relationship according to the overlapping of the values of the aggregated nodes comprises: calculating the support and the confidence of the aggregated node pair in the aggregation result, merging the aggregated node pair according to the support and the confidence, and updating the aggregation result using the aggregated node obtained by the merging; repeating the merging and the updating for the updated aggregation result until the aggregated nodes in the updated aggregation result cannot be merged, to obtain a final aggregation result; determining the association relationship according to the merged aggregated node pair in the final aggregation result.

5. The method of claim 1, further comprising: after obtaining the to-be-issued task node, determining whether the to-be-issued task node has associated task nodes according to the association relationship, and if yes, waiting for a preset time period, and if the associated task nodes of the to-be-issued task node are received within the preset time period, issuing the to-be-issued task node and the associated task nodes to a corresponding operation role.

6. A discrete manufacturing task management method, comprising: display the to-be-issued task nodes and associated task nodes in the to-be-issued task nodes, wherein the associated task nodes are determined according to the to-be-issued task nodes and an association relationship, and the association relationship is determined according to a support degree and a confidence degree of an aggregated node pair in an aggregation result, the support degree representing a ratio of a number of values overlapped in the two aggregated nodes in the aggregated node pair to a number of values after deduplication of the two aggregated nodes, and the confidence degree representing a ratio of the number of values overlapped in the two aggregated nodes in the aggregated node pair to a number of deduplicated values of one of the two aggregated nodes; determining, according to a user input, the associated task nodes to be combined and issued; combining and issuing the associated task nodes to corresponding operation roles.

7. The method of claim 6, further comprising: displaying prompt information prompting the user to wait for the associated task nodes of the to-be-issued task nodes; after receiving the associated task nodes, displaying recommendation information recommending the associated task nodes that can be combined to the user.

8. The method of claim 6, wherein: the operation roles of the associated task nodes are the same; the associated task nodes are determined by the method of any one of claims 1-5.

9. An electronic device comprising a memory and a processor; wherein, the memory is configured to store one or more computer instructions, and the one or more computer instructions are executed by the processor to implement the method steps of any one of claims 1-8.

10. A readable storage medium having computer instructions stored thereon, and the computer instructions are executed by a processor to implement the method steps of any one of claims 1-8.

11. A computer program product comprising computer instructions, and the computer instructions are executed by a processor to implement the method steps of any one of claims 1-8.

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