Workflow visualization method and device, storage medium and terminal

Abstract

The application discloses a workflow visualization method and device, a storage medium and a terminal, wherein the method comprises the following steps: creating a preset canvas; forming a temporary auxiliary network on the preset canvas based on an original AOE network and a virtual task line in the original AOE network; obtaining a depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, dividing all the vertices of the temporary auxiliary network into multiple depth levels based on the depth value, and obtaining the widest depth level; obtaining the pre-position coordinates of each vertex in the widest depth level through a first coordinate obtaining mode; obtaining the pre-position coordinates of each vertex in other depth levels in the temporary auxiliary network through a second coordinate obtaining mode based on the pre-position coordinates of each vertex in the widest depth level; and adjusting the positions of each vertex in the temporary auxiliary network based on the pre-position coordinates corresponding to the vertices, so as to form an auxiliary network. The application provides a workflow visualization scheme which is simple to operate, clear in logic, convenient to draw, and easy to read and understand.

Description

Technical Field

[0001] This invention relates to the field of workflow scheme research technology, and in particular to a workflow visualization method and apparatus, storage medium and terminal. Background Technology

[0002] For heavy manufacturing industries such as shipbuilding, their production equipment often has numerous parts and complex relationships, resulting in highly complex and coupled workflows for commissioning and installation. To develop and optimize these workflows, the first step should be to analyze them to make them easier to read and understand. In the engineering field, graph theory techniques have already been applied to workflow analysis.

[0003] Workflow analysis can be performed using the AOE (Activity On Edge) network form in graph theory. This form abstracts complex workflows into a structure consisting of a task start point, a specific workflow, and a task sink. In this structure, each edge represents a task, and each vertex indicates the task status. A vertex can be connected to any number of other vertices via any number of edges. The workflow starts at the start point and ends at the sink. By calculating the earliest start time and latest start time of each vertex and edge based on task information and the relationships between tasks, the critical path of the workflow can be determined.

[0004] While existing AOE networks can effectively demonstrate the temporal relationships between different projects, they struggle to simultaneously present their logical and hierarchical relationships. Furthermore, readability deteriorates further with increasing project complexity. Therefore, transforming a known "working diagram" from a logical form into a readable graphical representation remains a challenge in this field. Summary of the Invention

[0005] The technical problem that this invention aims to solve is that existing AOE networks cannot simultaneously present the logical and hierarchical relationships in the engineering process. Furthermore, as the complexity of the project increases, existing AOE networks are even less able to be displayed in an easy-to-read image format, which is detrimental to the understanding and analysis of complex workflows, and consequently, makes it difficult for managers to streamline and optimize workflows.

[0006] To address the aforementioned technical problems, this invention provides a workflow visualization method, comprising:

[0007] Create a preset canvas;

[0008] Identify the virtual task lines in the original AOE network, and based on the original AOE network and the virtual task lines therein, form a temporary auxiliary network on the preset canvas;

[0009] The depth value of each vertex in the temporary auxiliary network is obtained based on the preset depth design scheme. Based on the depth value, all vertices in the temporary auxiliary network are divided into multiple depth levels, and the widest depth level is obtained.

[0010] The preposition coordinates of each vertex in the widest depth level are obtained using the first coordinate acquisition method;

[0011] Based on the pre-position coordinates of each vertex in the widest depth level, the pre-position coordinates of each vertex in other depth levels in the temporary auxiliary network are obtained through the second coordinate acquisition method.

[0012] The positions of each vertex in the temporary auxiliary network are adjusted based on its corresponding pre-position coordinates to form an auxiliary network.

[0013] In an optimized manner, the steps for creating a preset canvas include:

[0014] Construct a blank canvas, the length of which is positively correlated with the total duration of tasks in the original AOE network;

[0015] A two-dimensional planar coordinate system is constructed on the blank canvas, and the x-axis of the two-dimensional planar coordinate system is located at the exact center of the blank canvas.

[0016] Based on the starting point and sink point in the original AOE network, corresponding starting point and sink point are constructed on the x-axis.

[0017] Optimally, based on the original AOE network and its virtual task lines, forming a temporary auxiliary network on the preset canvas includes:

[0018] The original AOE network is copied onto the preset canvas to form an initial network;

[0019] All virtual task lines in the initial network are represented by the minimum length to form a replacement network;

[0020] Based on the minimum length, the time of all vertices and the time of all task lines in the replacement network are recalculated to obtain a temporary auxiliary network.

[0021] The task time of the virtual task line is zero, the time of the vertex includes the earliest start time and the latest start time of the vertex, and the time of the task line includes the earliest start time and the latest start time of the line.

[0022] Optimally, the minimum length is the shortest task time length among all non-virtual task lines in the original AOE network; or

[0023] The minimum length is

[0024] Among them, I max The earliest start time of the sink in the original AOE network is represented by m, the number of vertices in the original AOE network is represented by m, and K is a constant parameter.

[0025] Optimally, the steps of obtaining the depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, dividing all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and obtaining the widest depth level include:

[0026] The starting point in the temporary auxiliary network is set as the initial depth value, and depth values ​​are assigned to all vertices in the temporary auxiliary network based on a preset depth design scheme;

[0027] Based on different depth values, all vertices in the temporary auxiliary network are divided into multiple depth levels, and the depth level with the most vertices is taken as the widest depth level.

[0028] The preset depth design scheme is as follows:

[0029] All paths passing through the target vertex in the temporary auxiliary network are obtained as target paths. The temporary depth value of the target vertex in each target path is obtained. The minimum value among all temporary depth values ​​of the target vertex is selected as the depth value of the target vertex. The target vertex is any vertex in the temporary auxiliary network.

[0030] The temporary depth value of the target vertex in the target path is calculated as: initial depth value + i - 1, where i is the number of vertices in the target path where the target vertex is located.

[0031] Optimally, the steps for obtaining the pre-position coordinates of each vertex in the widest depth level using the first coordinate acquisition method include:

[0032] Calculate the minimum height h min ,

[0033] via y z,j =j*h min Calculate the y-value of the preposition coordinates of each vertex in the widest depth level, and take the earliest occurrence time of each vertex in the widest depth level as the x-value of the corresponding vertex preposition coordinates;

[0034] Where z represents the number of vertices in the widest depth level, w area The height of the preset canvas is represented by , and j represents the number of the j-th vertex in the widest depth level.

[0035] Optimally, the step of obtaining the pre-position coordinates of vertices in other depth levels of the temporary auxiliary network based on the pre-position coordinates of each vertex in the widest depth level through the second coordinate acquisition method includes:

[0036] Starting with the widest depth level as the base depth level, the pre-position coordinates of vertices at other depth levels in the temporary auxiliary network are sequentially calculated in the form of a calculation group. The calculation group includes adjacent base depth levels and depth levels to be calculated. The base depth level is the depth level where all pre-position coordinates of vertices have been calculated, and the depth level to be calculated is the depth level where all pre-position coordinates of vertices have not been calculated.

[0037] The process of obtaining the pre-position coordinates of vertices in the depth level to be determined in the determination group includes:

[0038] Determine whether the pre-position coordinates of the nth vertex in the depth level to be determined have not yet been obtained. If so, obtain the pre-position coordinates of the nth vertex in the depth level to be determined based on the first preset scheme, and perform preprocessing operation on the nth vertex. If it is determined that the pre-position coordinates of the nth vertex in the depth level to be determined have been obtained or the preprocessing operation on the nth vertex has been completed, increment n by 1, and determine whether n is greater than the number of vertices in the depth level to be determined. If so, determine that the pre-position coordinates of all vertices in the depth level to be determined in the determination group have been obtained. Otherwise, re-determine whether the pre-position coordinates of the nth vertex in the depth level to be determined have not yet been obtained, and implement the determination and preprocessing operation of the pre-position coordinates of the nth vertex in the depth level to be determined.

[0039] The initial value of n is 1.

[0040] Optimally, obtaining the pre-position coordinates of the vertex to be determined in the depth level to be determined based on the first preset scheme includes:

[0041] Obtain all relevant vertices of the vertex to be determined in the depth level to be determined;

[0042] The average y-value of all related vertices of the vertex to be determined is used as the y-value of the vertex to be determined, and the earliest occurrence time of the vertex to be determined is used as the x-value of the vertex to be determined.

[0043] Wherein, the vertex to be determined is any vertex in the depth level to be determined, and the related vertices of the vertex to be determined are the parent or child nodes of the vertex to be determined in its corresponding base depth level.

[0044] Optimally, preprocessing operations on prevertices include:

[0045] Determine whether the number of source vertices of the pre-vertex is greater than 1. If so, obtain the pre-position coordinates of all the source vertices of the pre-vertex using a calculation method, and perform preprocessing operations on all the source vertices of the pre-vertex in sequence. Otherwise, the preprocessing operation of the pre-vertex ends.

[0046] The method of obtaining the pre-position coordinates of the source vertex of the pre-vertex using the budget method includes:

[0047] Let the pre-position coordinates of the pre-vertex be p. a (x a ,y a If the y-value of the preposition coordinate of the i-th source vertex is: y i =y0+i*h min The x-value of the preposition coordinate of the i-th source vertex of the pre-vertex is the earliest occurrence time of the i-th source vertex of the pre-vertex;

[0048] Where y0=y a -(n father -1)*0.5*h min n father n is the number of source vertices of the pre-vertex. father The minimum height is defined as follows: the pre-vertex is any vertex in the temporary auxiliary network; the source vertex of the pre-vertex is either the parent or child node of the pre-vertex; and the source vertex of the pre-vertex is different from the related vertices of the pre-vertex.

[0049] Preferably, the workflow visualization method further includes:

[0050] Obtain the critical path in the original AOE network and highlight the critical path in the auxiliary network.

[0051] To address the aforementioned technical problems, the present invention also provides a workflow visualization device, comprising a canvas creation module, a temporary auxiliary network generation module, a maximum width and depth level acquisition module, a first pre-position coordinate acquisition module, a second pre-position coordinate acquisition module, and an auxiliary network acquisition module.

[0052] The canvas creation module is used to create a preset canvas;

[0053] The temporary auxiliary network generation module is used to determine the virtual task lines in the original AOE network, and form a temporary auxiliary network on the preset canvas based on the original AOE network and the virtual task lines therein.

[0054] The widest depth level acquisition module is used to acquire the depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, divide all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and acquire the widest depth level.

[0055] The first preposition coordinate acquisition module is used to acquire the preposition coordinates of each vertex in the widest depth level through a first coordinate acquisition method;

[0056] The second preposition coordinate acquisition module is used to acquire the preposition coordinates of each vertex in other depth levels of the temporary auxiliary network based on the preposition coordinates of each vertex in the widest depth level, through the second coordinate acquisition method.

[0057] The auxiliary network acquisition module is used to adjust the position of each vertex in the temporary auxiliary network based on its corresponding pre-position coordinates to form an auxiliary network.

[0058] To address the aforementioned technical problems, the present invention also provides a storage medium storing a computer program that, when executed by a processor, implements the aforementioned workflow visualization method.

[0059] To address the aforementioned technical problems, the present invention also provides a terminal, comprising: a processor and a memory, wherein the memory and the processor are communicatively connected;

[0060] The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to enable the terminal to perform the workflow visualization method.

[0061] Compared with the prior art, one or more embodiments of the above solutions may have the following advantages or beneficial effects:

[0062] The workflow visualization method provided in this invention effectively solves the problem of overlapping vertices of virtual task lines in the auxiliary network by setting a minimum length to represent virtual task lines, making the logical relationships in the obtained auxiliary network engineering process clearer. By obtaining the widest depth level and prioritizing the setting of the position coordinates of each vertex in the widest depth level, and then calculating the positions of the remaining vertices in the auxiliary network based on the vertices already located in the widest depth level, the auxiliary network can be fully presented on the canvas. The obtained auxiliary network can simultaneously present the logical and hierarchical relationships in the engineering process, and as the complexity of the project increases, the auxiliary network can also be well displayed in an easy-to-read image format, improving the understanding and analysis capabilities of complex workflows, and thus facilitating managers to streamline and optimize workflows.

[0063] This invention provides a workflow visualization solution that is simple to operate, logically clear, easy to draw, and easy to read and understand, while retaining the information that traditional AOE networks can present. It displays the logical and hierarchical relationships between engineering projects in the form of a vivid and interactive AOE network diagram, which can be applied to different engineering project management processes and has good operability and applicability.

[0064] Other features and advantages of the invention will be set forth in the description which follows, and will be apparent in part from the description, or may be learned by practicing the invention. The objects and other advantages of the invention may be realized and obtained by means of the structures particularly pointed out in the description, claims, and drawings. Attached Figure Description

[0065] The accompanying drawings are provided to further illustrate the invention and form part of the specification. They are used in conjunction with the embodiments of the invention to explain the invention and do not constitute a limitation thereof. In the drawings:

[0066] Figure 1 A flowchart illustrating the workflow visualization method of Embodiment 1 of the present invention is shown;

[0067] Figure 2 This diagram illustrates the process of obtaining the depth values ​​of each vertex in the temporary auxiliary network according to Embodiment 1 of the present invention.

[0068] Figure 3 This diagram illustrates the process of calculating the pre-position coordinates of each vertex in the previous depth level from the widest depth level in Embodiment 1 of the present invention.

[0069] Figure 4 A flowchart illustrating the preprocessing operation in Embodiment 1 of the present invention is shown;

[0070] Figure 5 An example diagram of a temporary auxiliary network in Embodiment 1 of the present invention is shown;

[0071] Figure 6 A schematic diagram of the workflow visualization device according to Embodiment 2 of the present invention is shown;

[0072] Figure 7 A schematic diagram of the terminal structure of Embodiment 4 of the present invention is shown. Detailed Implementation

[0073] The embodiments of the present invention will be described in detail below with reference to the accompanying drawings and examples, so that the process of how the present invention uses technical means to solve technical problems and achieve technical effects can be fully understood and implemented accordingly. It should be noted that, as long as there is no conflict, the various embodiments and features in the various embodiments of the present invention can be combined with each other, and the resulting technical solutions are all within the protection scope of the present invention.

[0074] An AOE network, or Activity On Edge network, has one and only one source (starting point) and sink (ending point), representing the beginning and end of the workflow, respectively. Each vertex represents the completion status of an event, and each edge (task line) represents a specific task. An AOE network should have multiple vertices, correct connections, the ability to calculate the critical path, and each vertex should have its earliest start time (etv) and latest start time (ltv) calculated. Similarly, each edge should have its earliest start time (ete) and latest start time (lte) calculated. The task time of a virtual task line is zero, and tasks on the critical path in the workflow should satisfy lte = ete.

[0075] Example 1

[0076] To address the technical problems existing in the prior art, embodiments of the present invention provide a workflow visualization method.

[0077] Figure 1 A flowchart illustrating the workflow visualization method of Embodiment 1 of the present invention is shown; see reference. Figure 1 As shown, the workflow visualization method of this invention includes the following steps.

[0078] Step S101: Create a preset canvas.

[0079] Specifically, the canvas structure should be confirmed before drawing the engineering workflow. First, create a blank canvas, typically rectangular. The length of the blank canvas is positively correlated with the total task duration in the original AOE network, and the width can be determined by the monitor aspect ratio (e.g., 4:3). Then, construct a two-dimensional coordinate system on the blank canvas, with the x-axis centered on the blank canvas. Based on the start and sink points in the original AOE network, construct corresponding start and sink points on the x-axis, ensuring that the y-values ​​of the start and sink points on the canvas are both zero, thus forming the preset canvas.

[0080] Step S102: Determine the virtual task lines in the original AOE network, and form a temporary auxiliary network on the preset canvas based on the original AOE network and the virtual task lines therein.

[0081] In the actual rendering process of the auxiliary network, if the rendering is performed directly on the original AOE network, the problem of virtual connections (i.e., virtual task lines) may occur, causing two vertices to overlap during rendering, which greatly affects readability. Therefore, this embodiment sets up a temporary auxiliary network to solve the problem of overlapping virtual task line vertices.

[0082] The process of obtaining the temporary auxiliary network includes: identifying all virtual task lines in the original AOE network (Object-Oriented Network), where each virtual task line has a task time of zero. Then, the original AOE network is copied onto a preset canvas. During the copying process, the start and sink points of the original AOE coincide with the start and sink points in the preset canvas, forming the initial network. All virtual task lines in the initial network are represented using the minimum length, forming a replacement network. Since the task time of the virtual task lines in the replacement network changes from zero to the minimum length, the time values ​​of each vertex and task line in the replacement network change. Then, based on the minimum length, the time values ​​of all vertices and all task lines in the replacement network are recalculated to obtain the temporary auxiliary network.

[0083] The vertex time includes the earliest start time and the latest start time of the vertex, and the task line time includes the earliest start time and the latest start time of the line. Furthermore, the minimum length in this embodiment can be set as the shortest task time length among all non-virtual task lines in the original AOE network. Alternatively, the minimum length can also be calculated using the following formula (1):

[0084]

[0085] Among them, I max This represents the earliest start time of the sink in the original AOE network, m represents the number of vertices in the original AOE network, and K represents a constant parameter, which can be selected as 0.3.

[0086] Step S103: Obtain the depth value of each vertex in the temporary auxiliary network based on the preset depth design scheme, divide all vertices of the temporary auxiliary network into multiple depth levels based on the depth values, and obtain the widest depth level.

[0087] Specifically, to fully represent the image on the canvas, the widest level and the width spacing between vertices at that level need to be determined in advance. To select the widest level in the temporary auxiliary network, this embodiment uses a preset depth design scheme to assign depth values ​​to each vertex in the temporary auxiliary network.

[0088] Obtaining the depth values ​​of each vertex in a temporary auxiliary network based on a preset depth design scheme includes: setting the starting vertex in the temporary auxiliary network as the initial depth value (usually 0), and designating the vertex to be assigned a depth value as the target vertex; then obtaining all paths in the temporary auxiliary network that pass through the target vertex, and designating these paths as the target paths of the target vertex; obtaining the temporary depth values ​​of the target vertex in each target path using a certain method; and finally selecting the minimum value among all temporary depth values ​​of the target vertex as the depth value of the target vertex. The target vertex can be any vertex in the temporary auxiliary network. Therefore, by repeating the above process, the depth values ​​of all vertices in the temporary auxiliary network can be obtained.

[0089] In the above process, the temporary depth value of the target vertex in a single target path is calculated as: initial depth value + i - 1, where i is the number of vertices in the target path.

[0090] Figure 2 This diagram illustrates the process of obtaining the depth values ​​of each vertex in a temporary auxiliary network according to Embodiment 1 of the present invention; see reference. Figure 2 As shown, the depth values ​​of each vertex in the temporary auxiliary network obtained based on the preset depth design scheme can also be obtained in the following form: Create a depth record, take the vertices of each execution level as the preparation list of the current layer, and set the temporary depth value of the vertex in the preparation list of the current layer to: the temporary depth value of its parent vertex of the path plus 1, and record it in the depth record. Repeat the above process until the temporary depth values ​​of all vertices in the temporary auxiliary network are obtained. Then, select the minimum value among all the corresponding temporary depth values ​​of each vertex as the depth value of the corresponding vertex.

[0091] Figure 5 An example diagram of a temporary auxiliary network in Embodiment 1 of the present invention is shown; combined with Figure 5 As shown, assuming the initial depth of vertex 'a' in the temporary auxiliary network is 0, the target path of vertex v5 includes path L1: a-v2-v5-z and path L2: a-v3-v5-z. Since the temporary depth of v5 in path L1 is 2, and the temporary depth of v5 in path L2 is also 2, the depth value of v5 is 2. Similarly, the depth values ​​of other vertices can be determined. The corresponding values ​​are then obtained. Figure 5 The corresponding depth table is as follows:

[0092] a 0 v2 1 v3 1 v4 1 v5 2 z 2

[0093] After obtaining the depth values ​​of all vertices in the temporary auxiliary network, the vertices can be sorted based on their depth values ​​to obtain multiple depth levels. For example, to obtain... Figure 5 The corresponding depth levels are listed below:

[0094] 0 a 1 v2 v3 v4 2 v5 z

[0095] The depth level with the most vertices among all depth levels is selected as the widest depth level; for example... Figure 5 The widest depth level in the temporary auxiliary network shown is the first depth level.

[0096] Step S104: Obtain the pre-position coordinates of each vertex in the widest depth level using the first coordinate acquisition method.

[0097] Specifically, after obtaining the widest depth level of the temporary auxiliary network, the pre-position coordinates of each vertex in the widest depth level can be obtained based on the first coordinate acquisition method. The further pre-position coordinate method for each vertex in the widest depth level is as follows: first, calculate the minimum height h based on formula (2). min ;

[0098]

[0099] Then through y z,j =j*h min Calculate the y-value of the preposition coordinates of each vertex in the widest depth level, and use the earliest occurrence time of each vertex in the widest depth level as the x-value of the corresponding vertex's preposition coordinates.

[0100] For example Figure 5 The height of each vertex in the widest depth level of the temporary auxiliary network shown is [50 100150].

[0101] Where z represents the number of vertices in the widest depth level, w area The value represents the height of the preset canvas, and j represents the number of the j-th vertex in the widest depth level.

[0102] Step S105: Based on the pre-position coordinates of each vertex in the widest depth level, obtain the pre-position coordinates of each vertex in other depth levels of the temporary auxiliary network through the second coordinate acquisition method.

[0103] Specifically, starting with the widest depth level as the base depth level, and deriving forward and backward from the widest depth level respectively, in the form of a calculation group, the pre-position coordinates of vertices at other depth levels in the temporary auxiliary network are calculated until the starting point and sink point are calculated.

[0104] Furthermore, based on the pre-position coordinates of each vertex in the widest depth level, the pre-position coordinates of each vertex in each depth level before the widest depth level are calculated sequentially using a set of coordinates. Similarly, based on the pre-position coordinates of each vertex in the widest depth level, the pre-position coordinates of each vertex in each depth level after the widest depth level are calculated sequentially using a set of coordinates. The forward and backward calculation methods are similar, differing only in the direction of calculation. Figure 3 This diagram illustrates the process of calculating the pre-position coordinates of each vertex in the previous depth level from the widest depth level in Embodiment 1 of the present invention.

[0105] Each depth group consists of a base depth level and a depth level to be determined. The base depth level and the depth level to be determined are adjacent depth levels in the temporary auxiliary network. The base depth level is the depth level for which the pre-position coordinates of all vertices have been determined, while the depth level to be determined is the depth level for which the pre-position coordinates of all vertices have not been determined.

[0106] For example, assuming the widest depth level is the w-th depth level, the w-th depth level can form a calculation group with the (w-1)-th depth level. In this group, the w-th depth level serves as the base depth level, and the (w-1)-th depth level serves as the depth level to be calculated. After calculating the pre-position coordinates of each vertex in the depth level to be calculated based on the pre-position coordinates of each vertex in the base depth level, the (w-1)-th depth level can be used as the base depth level, and the (w-2)-th depth level as the depth level to be calculated, forming a new calculation group. The pre-position coordinates of each vertex in the (w-2)-th depth level are then calculated, and so on, to deduce the pre-position coordinates of each vertex in all depth levels before the widest depth level. Similarly, the pre-position coordinates of each vertex in all depth levels after the widest depth level can also be calculated.

[0107] The above process of obtaining the preposition coordinates of vertices in the depth level to be determined in the determination group includes: judging whether the preposition coordinates of the nth vertex in the depth level to be determined have not yet been obtained; if so, obtaining the preposition coordinates of the nth vertex in the depth level to be determined based on the first preset scheme, and performing preprocessing operations on the nth vertex; if it is determined that the preposition coordinates of the nth vertex in the depth level to be determined have been obtained or the preprocessing operations on the nth vertex have been completed, then n is incremented by 1, and it is judged whether n is greater than the number of vertices in the depth level to be determined; if so, it means that the preposition coordinates of each vertex in the depth level to be determined in the current determination group have been obtained; otherwise, it is necessary to judge whether the preposition coordinates of the next vertex in the depth level to be determined have not yet been obtained, and to implement the process of obtaining and preprocessing the preposition coordinates of the nth vertex (i.e., the next vertex) in the depth level to be determined; repeating the above process until the preposition coordinates of all vertices in the depth level to be determined in the determination group are obtained. The initial value of n is 1.

[0108] The process of obtaining the pre-position coordinates of vertices in the desired depth level based on the first preset scheme includes: selecting the vertex in the desired depth level whose pre-position coordinates are to be obtained as the vertex to be determined; selecting all related vertices of the vertex to be determined in the base depth level corresponding to the desired depth level; then summing and averaging the y-values ​​of all related vertices of the vertex to be determined, and using the calculated average as the y-value of the pre-position coordinates of the vertex to be determined; simultaneously, using the earliest occurrence time of the vertex to be determined as the x-value of the pre-position coordinates of the vertex to be determined. At this point, the pre-position coordinates of the vertex to be determined are obtained. The vertex to be determined can be any vertex in the desired depth level; therefore, repeating the above process will obtain the pre-position coordinates of all vertices in the desired depth level.

[0109] It should be noted that the y-value of a vertex is the same as its y-value in a two-dimensional plane coordinate system. Furthermore, the related vertices of the vertex to be determined are its parent or child nodes in its corresponding base depth level. For example, if the w-th depth level and the (w-1)-th depth level are combined into a determination group, with the w-th depth level as the base depth level and the (w-1)-th depth level as the depth level to be determined, then the related vertices of the vertex to be determined in the (w-1)-th depth level are the child nodes of that vertex in the w-th depth level. If the w-th depth level and the (w+1)-th depth level are combined into a determination group, then the related vertices of the vertex to be determined in the (w+1)-th depth level are the parent nodes of that vertex in the w-th depth level.

[0110] Figure 4 A flowchart illustrating the preprocessing operation in Embodiment 1 of the present invention is shown; see reference. Figure 4 As shown, the preprocessing operation for a vertex includes: setting the vertex to be preprocessed as the pre-vertex; determining whether the number of source vertices of the pre-vertex is greater than 1; if so, obtaining the pre-position coordinates of all source vertices of the pre-vertex using a calculation method, and performing preprocessing operations on all source vertices of the pre-vertex sequentially; if the preprocessing operations on all source vertices of the pre-vertex and the source vertices of the source vertices of the source vertices have been completed, or if the number of source vertices of the pre-vertex is 1 or 0, then the preprocessing operation for the current pre-vertex is considered complete. The source vertex of the pre-vertex is either its parent node or child node, and the source vertex of the pre-vertex is different from its related vertices. For example, if a related vertex of the pre-vertex is its parent node, then its source node is its child node.

[0111] For example, suppose that the w-th depth level and the (w-1)-th depth level form a search group, and the pre-position coordinates of the n-th vertex in the depth level to be searched have been obtained based on the first preset scheme. At this time, the n-th vertex in the depth level to be searched is taken as a pre-vertex and preprocessed. If, during the preprocessing operation of the n-th vertex, it is found that the number of source vertices of the h-th source vertex of the n-th vertex is greater than 1, then the h-th source vertex of the n-th vertex needs to be taken as a pre-vertex and preprocessed. Repeat the above process until all source vertices of the pre-vertex and the source vertices of the source vertices have been preprocessed. At this time, it means that the preprocessing operation of the pre-vertex is over.

[0112] Furthermore, the process of obtaining the preposition coordinates of a single source vertex using the budget method includes: assuming the preposition coordinates of the prevertices are set to p a (x a ,y a If the y-value of the preposition coordinate of the i-th source vertex is: y i =y0+i*h min The x-value of the preposition coordinate of the i-th source vertex of the pre-vertex is the earliest occurrence time of the i-th source vertex of the pre-vertex. Where y0 = y a -(n father -1)*0.5*h min n father h is the number of source vertices of the pre-vertices. min This is the minimum height. Repeating the above process will yield the pre-position coordinates of all source vertices for the pre-vertex.

[0113] Step S106: Adjust the position of each vertex in the temporary auxiliary network based on its corresponding pre-position coordinates, that is, replace the position coordinates of each vertex in the temporary network with its corresponding pre-position coordinates, thus forming the auxiliary network.

[0114] Step S107: Obtain the critical path in the original AOE network and highlight the critical path in the auxiliary network.

[0115] Specifically, in the auxiliary network, to improve readability of the rendering results, the length of all dummy task lines is set to the minimum length, causing a discrepancy between the calculated critical path and the actual situation. Therefore, it is necessary to obtain the critical path from the original AOE network and, after the auxiliary network is generated, represent it using different colored lines or by thickening the lines to highlight the critical path in the auxiliary network.

[0116] The workflow visualization method provided in this invention effectively solves the problem of overlapping vertices of virtual task lines in the auxiliary network by setting a minimum length to represent virtual task lines, making the logical relationships in the obtained auxiliary network engineering process clearer. By obtaining the widest depth level and prioritizing the setting of the position coordinates of each vertex in the widest depth level, and then calculating the positions of the remaining vertices in the auxiliary network based on the vertices already located in the widest depth level, the auxiliary network can be fully presented on the canvas. The obtained auxiliary network can simultaneously present the logical and hierarchical relationships in the engineering process, and as the complexity of the project increases, the auxiliary network can also be well displayed in an easy-to-read image format, improving the understanding and analysis ability of complex workflows, and thus facilitating managers to streamline and optimize workflows.

[0117] This invention provides a workflow visualization solution that is simple to operate, logically clear, easy to draw, and easy to read and understand, while retaining the information that traditional AOE networks can present. It displays the logical and hierarchical relationships between engineering projects in the form of a vivid and interactive AOE network diagram, which can be applied to different engineering project management processes and has good operability and applicability.

[0118] Example 2

[0119] To address the aforementioned technical problems in the prior art, embodiments of the present invention also provide a workflow visualization device.

[0120] Figure 6 A schematic diagram of the workflow visualization device according to Embodiment 2 of the present invention is shown; Reference Figure 6 As shown, the workflow visualization device of this embodiment includes a canvas creation module, a temporary auxiliary network generation module, a maximum depth level acquisition module, a first pre-position coordinate acquisition module, a second pre-position coordinate acquisition module, and an auxiliary network acquisition module.

[0121] The canvas creation module is used to create preset canvases.

[0122] The temporary auxiliary network generation module is used to determine the virtual task lines in the original AOE network and form a temporary auxiliary network on the preset canvas based on the original AOE network and the virtual task lines therein.

[0123] The widest depth level acquisition module is used to obtain the depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, divide all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and obtain the widest depth level.

[0124] The first preposition coordinate acquisition module is used to acquire the preposition coordinates of each vertex in the widest depth level through the first coordinate acquisition method.

[0125] The second preposition coordinate acquisition module is used to acquire the preposition coordinates of vertices in other depth levels of the temporary auxiliary network based on the preposition coordinates of each vertex in the widest depth level, using the second coordinate acquisition method.

[0126] The auxiliary network acquisition module is used to adjust the position of each vertex in the temporary auxiliary network based on its corresponding pre-position coordinates to form the auxiliary network.

[0127] The workflow visualization device provided in this invention effectively solves the problem of overlapping vertices of virtual task lines in the auxiliary network by setting a minimum length to represent virtual task lines, making the logical relationships in the obtained auxiliary network engineering process clearer. By obtaining the widest depth level and prioritizing the setting of the position coordinates of each vertex in the widest depth level, and then calculating the positions of the remaining vertices in the auxiliary network based on the vertices already located in the widest depth level, the auxiliary network can be fully presented on the canvas. The obtained auxiliary network can simultaneously present the logical and hierarchical relationships in the engineering process, and as the complexity of the project increases, the auxiliary network can also be well displayed in an easy-to-read image format, improving the understanding and analysis ability of complex workflows, and thus facilitating managers to streamline and optimize workflows.

[0128] The device of this invention, while retaining the information that can be presented by traditional AOE networks, provides a workflow visualization solution that is simple to operate, logically clear, easy to draw, and easy to read and understand. It presents the logical and hierarchical relationships between engineering projects in the form of a vivid and interactive AOE network diagram, which can be applied to different engineering project management processes and has good operability and applicability.

[0129] Example 3

[0130] To address the aforementioned technical problems in the prior art, this embodiment of the invention also provides a storage medium storing a computer program that, when executed by a processor, can implement all the steps in the workflow visualization method of Embodiment 1.

[0131] The specific steps of the workflow visualization method and the beneficial effects obtained by applying the readable storage medium provided in this embodiment are the same as in Embodiment 1, and will not be repeated here.

[0132] It should be noted that storage media include various media that can store program code, such as ROM, RAM, magnetic disks, or optical disks.

[0133] Example 4

[0134] To address the aforementioned technical problems in the prior art, embodiments of the present invention also provide a terminal.

[0135] Figure 7 A schematic diagram of the terminal structure of Embodiment 4 of the present invention is shown, with reference to... Figure 7 In this embodiment, the terminal includes a processor and a memory that are interconnected. The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory, so that when the terminal is executed, it can implement all the steps of the workflow visualization method described in Embodiment 1.

[0136] The specific steps of the workflow visualization method and the beneficial effects obtained by applying the terminal provided in this embodiment of the invention are the same as in Embodiment 1, and will not be repeated here.

[0137] It should be noted that the memory may include random access memory (RAM) and may also include non-volatile memory, such as at least one disk storage device. Similarly, the processor can be a general-purpose processor, including a central processing unit (CPU), a network processor (NP), etc.; it can also be a digital signal processor (DSP), an application-specific integrated circuit (ASIC), a field-programmable gate array (FPGA), or other programmable logic devices, discrete gate or transistor logic devices, or discrete hardware components.

[0138] While the embodiments disclosed in this invention are as described above, the content is merely for the purpose of facilitating understanding of the invention and is not intended to limit the invention. Any person skilled in the art to which this invention pertains may make any modifications and changes in form and detail of the implementation without departing from the spirit and scope disclosed herein; however, the scope of protection of this invention shall still be determined by the scope defined in the appended claims.

Claims

1. A workflow visualization method, comprising: Create a preset canvas; Identify the virtual task lines in the original AOE network, and based on the original AOE network and the virtual task lines therein, form a temporary auxiliary network on the preset canvas; Based on the original AOE network and its virtual task lines, forming a temporary auxiliary network on the preset canvas includes: copying the original AOE network onto the preset canvas to form an initial network; representing all virtual task lines in the initial network with a minimum length to form a replacement network; and recalculating the time values ​​of all vertices and all task lines in the replacement network based on the minimum length to obtain a temporary auxiliary network; wherein the task time of each virtual task line is zero, the time value of each vertex includes the earliest start time and the latest start time of the vertex, and the time value of each task line includes the earliest start time and the latest start time of the line. The steps of obtaining the depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, dividing all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and obtaining the widest depth level include: setting the starting point in the temporary auxiliary network as the initial depth value, assigning depth values ​​to all vertices in the temporary auxiliary network based on the preset depth design scheme, dividing all vertices in the temporary auxiliary network into multiple depth levels based on different depth values, and taking the depth level with the most vertices as the widest depth level; The preposition coordinates of each vertex in the widest depth level are obtained using the first coordinate acquisition method; Based on the pre-position coordinates of each vertex in the widest depth level, the pre-position coordinates of each vertex in other depth levels in the temporary auxiliary network are obtained through the second coordinate acquisition method. The positions of each vertex in the temporary auxiliary network are adjusted based on its corresponding pre-position coordinates to form an auxiliary network.

2. The method according to claim 1, characterized in that, The steps to create a preset canvas include: Construct a blank canvas, the length of which is positively correlated with the total duration of tasks in the original AOE network; A two-dimensional planar coordinate system is constructed on the blank canvas, with the x-axis of the two-dimensional planar coordinate system located at the exact center of the blank canvas; Based on the starting point and sink point in the original AOE network, corresponding starting point and sink point are constructed on the x-axis.

3. The method according to claim 1, characterized in that, The minimum length is the shortest task time length among all non-virtual task lines in the original AOE network; or The minimum length is ; in, The earliest start time of the sink in the original AOE network is represented by m, the number of vertices in the original AOE network is represented by m, and K is a constant parameter.

4. The method according to claim 1, characterized in that, The preset depth design scheme is as follows: All paths passing through the target vertex in the temporary auxiliary network are obtained as target paths. The temporary depth value of the target vertex in each target path is obtained. The minimum value among all temporary depth values ​​of the target vertex is selected as the depth value of the target vertex. The target vertex is any vertex in the temporary auxiliary network. The temporary depth value of the target vertex in the target path is calculated as: initial depth value + i - 1, where i is the number of vertices in the target path where the target vertex is located.

5. The method according to claim 1, characterized in that, The steps for obtaining the pre-position coordinates of each vertex in the widest depth level using the first coordinate acquisition method include: Calculate minimum height , ; pass Calculate the y-value of the preposition coordinates of each vertex in the widest depth level, and take the earliest occurrence time of each vertex in the widest depth level as the x-value of the corresponding vertex preposition coordinates; Where z represents the number of vertices in the widest depth level. The height of the preset canvas is represented by , and j represents the number of the j-th vertex in the widest depth level.

6. The method according to claim 1, characterized in that, Based on the pre-position coordinates of each vertex in the widest depth level, the steps for obtaining the pre-position coordinates of each vertex in other depth levels of the temporary auxiliary network using the second coordinate acquisition method include: Starting with the widest depth level as the base depth level, the pre-position coordinates of vertices at other depth levels in the temporary auxiliary network are sequentially calculated in the form of a calculation group. The calculation group includes adjacent base depth levels and depth levels to be calculated. The base depth level is the depth level where all pre-position coordinates of vertices have been calculated, and the depth level to be calculated is the depth level where all pre-position coordinates of vertices have not been calculated. The process of obtaining the pre-position coordinates of vertices in the depth level to be determined in the determination group includes: Determine whether the pre-position coordinates of the nth vertex in the depth level to be determined have not yet been obtained. If so, obtain the pre-position coordinates of the nth vertex in the depth level to be determined based on the first preset scheme, and perform preprocessing operation on the nth vertex. If it is determined that the pre-position coordinates of the nth vertex in the depth level to be determined have been obtained or the preprocessing operation on the nth vertex has been completed, increment n by 1, and determine whether n is greater than the number of vertices in the depth level to be determined. If so, determine that the pre-position coordinates of all vertices in the depth level to be determined in the determination group have been obtained. Otherwise, re-determine whether the pre-position coordinates of the nth vertex in the depth level to be determined have not yet been obtained, and implement the determination and preprocessing operation of the pre-position coordinates of the nth vertex in the depth level to be determined. The initial value of n is 1.

7. The method according to claim 6, characterized in that, Obtaining the pre-position coordinates of the vertex to be determined in the depth level to be determined based on the first preset scheme includes: Obtain all relevant vertices of the vertex to be determined in the depth level to be determined; The average y-value of all related vertices of the vertex to be determined is used as the y-value of the vertex to be determined, and the earliest occurrence time of the vertex to be determined is used as the x-value of the vertex to be determined. Wherein, the vertex to be determined is any vertex in the depth level to be determined, and the related vertices of the vertex to be determined are the parent or child nodes of the vertex to be determined in its corresponding base depth level.

8. The method according to claim 7, characterized in that, Preprocessing operations on prevertices include: Determine whether the number of source vertices of the pre-vertex is greater than 1. If so, obtain the pre-position coordinates of all the source vertices of the pre-vertex using a calculation method, and perform preprocessing operations on all the source vertices of the pre-vertex in sequence. Otherwise, the preprocessing operation of the pre-vertex ends. The method of obtaining the pre-position coordinates of the source vertex of the pre-vertex using the budget method includes: The preposition coordinates of the pre-vertex are set as follows: Then, the y-value of the preposition coordinate of the i-th source vertex is: The x-value of the preposition coordinate of the i-th source vertex of the pre-vertex is the earliest occurrence time of the i-th source vertex of the pre-vertex; in, , The number of source vertices of the pre-vertex. The minimum height is defined as follows: the pre-vertex is any vertex in the temporary auxiliary network; the source vertex of the pre-vertex is either the parent or child node of the pre-vertex; and the source vertex of the pre-vertex is different from the related vertices of the pre-vertex.

9. The method according to claim 1, characterized in that, Also includes: Obtain the critical path in the original AOE network and highlight the critical path in the auxiliary network.

10. A workflow visualization device, characterized in that, It includes a canvas creation module, a temporary auxiliary network generation module, a maximum width and depth level acquisition module, a first pre-position coordinate acquisition module, a second pre-position coordinate acquisition module, and an auxiliary network acquisition module; The canvas creation module is used to create a preset canvas; The temporary auxiliary network generation module is used to determine the virtual task lines in the original AOE network, and form a temporary auxiliary network on the preset canvas based on the original AOE network and the virtual task lines therein. Based on the original AOE network and its virtual task lines, forming a temporary auxiliary network on the preset canvas includes: copying the original AOE network onto the preset canvas to form an initial network; representing all virtual task lines in the initial network with a minimum length to form a replacement network; and recalculating the time values ​​of all vertices and all task lines in the replacement network based on the minimum length to obtain a temporary auxiliary network; wherein the task time of each virtual task line is zero, the time value of each vertex includes the earliest start time and the latest start time of the vertex, and the time value of each task line includes the earliest start time and the latest start time of the line. The widest depth level acquisition module is used to acquire the depth value of each vertex in the temporary auxiliary network based on a preset depth design scheme, divide all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and acquire the widest depth level. The steps of acquiring the depth value of each vertex in the temporary auxiliary network based on the preset depth design scheme, dividing all vertices in the temporary auxiliary network into multiple depth levels based on the depth values, and acquiring the widest depth level include: setting the starting point in the temporary auxiliary network as the initial depth value, assigning depth values ​​to all vertices in the temporary auxiliary network based on the preset depth design scheme; dividing all vertices in the temporary auxiliary network into multiple depth levels based on different depth values, and taking the depth level with the most vertices as the widest depth level. The first preposition coordinate acquisition module is used to acquire the preposition coordinates of each vertex in the widest depth level through a first coordinate acquisition method; The second preposition coordinate acquisition module is used to acquire the preposition coordinates of each vertex in other depth levels of the temporary auxiliary network based on the preposition coordinates of each vertex in the widest depth level, through the second coordinate acquisition method. The auxiliary network acquisition module is used to adjust the position of each vertex in the temporary auxiliary network based on its corresponding pre-position coordinates to form an auxiliary network.

11. A storage medium having a computer program stored thereon, characterized in that, When the program is executed by the processor, it implements the workflow visualization method as described in any one of claims 1 to 9.

12. A terminal, characterized in that, include: A processor and a memory, wherein the memory and the processor are communicatively connected; The memory is used to store computer programs, and the processor is used to execute the computer programs stored in the memory to enable the terminal to perform the workflow visualization method as described in any one of claims 1 to 9.

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