Process simulation playback method based on statistical activity weight

Abstract

The invention relates to the technical field of process simulation, in particular to a process simulation playback method based on statistical activity weights. The method comprises the following steps: firstly, collecting flow data from multiple data sources of an enterprise, obtaining flow overview information through cleaning, activity identification and attribute statistics, then constructing a flow chart and determining frame duration in sequence, counting an activity frame index based on the duration, then aggregating statistical data in an activity frame index range and calculating a weight, and finally obtaining the flow chart. And finally, packaging and transmitting the real time length, the aggregation statistical result and the weight to a playback program, playing back according to the flow chart and the real time length, and reading and displaying the activity weight in each frame to list the load. The method can comprehensively and accurately process flow data, accurately reflect the activity load, improve the flow analysis capability and assist enterprises in flow optimization, and has important significance and practical value in the field of enterprise flow management.

Description

Technical Field

[0001] The invention relates to the technical field of process simulation, and in particular to a process simulation playback method based on statistical activity weights. Background Art

[0002] In today's digital age, business operations are highly dependent on various business processes. The efficiency and optimization of these processes directly affect the competitiveness and benefits of enterprises. Process mining technology has emerged to extract valuable process knowledge from the large amount of event log data recorded in enterprise information systems to help enterprises understand, analyze and improve their business processes.

[0003] As the scale of enterprises continues to expand and the complexity of business continues to increase, business processes are becoming increasingly complex. Traditional process analysis methods often have difficulty coping with massive amounts of process data and are unable to deeply explore the rules and problems hidden in the process. As an important part of process mining, process simulation playback provides enterprises with an intuitive and effective process analysis method by simulating the actual operation of the process.

[0004] However, existing process simulation and playback methods face many challenges. On the one hand, in the data processing link, due to the large number of data sources and diverse data formats, data collection and integration are difficult. At the same time, errors, duplications, and incomplete information in the data seriously affect the accuracy of subsequent analysis, and existing data cleaning technologies often do not work well when processing data in complex business scenarios. On the other hand, during the simulation playback process, the characterization of activity load conditions is not accurate enough. Most methods simply consider the execution time or resource consumption of the activity, and fail to comprehensively evaluate the importance and impact of the activity in the process by comprehensively considering multiple factors, resulting in deviations in the analysis results, making it difficult to effectively guide enterprises to make process optimization decisions. Summary of the invention

[0005] The purpose of the present invention is to propose a process simulation playback method based on statistical activity weights, which can deeply analyze process mining data, accurately count process overview information, construct a flowchart containing accurate activity load representation, and realize efficient and realistic process simulation playback, so as to provide strong support for enterprise process optimization.

[0006] The technical solution of the present invention is as follows:

[0007] A process simulation playback method based on statistical activity weights, comprising:

[0008] Collect enterprise process data, identify activities in the data, and provide process overview information based on process data and activities;

[0009] Build a flowchart based on the sequence and attribute relationship between activities in the process overview information, and play back the actual duration of each frame;

[0010] Count the frame index of all activities based on the real duration;

[0011] Based on the activity, as well as the activity start frame index and the activity end frame index in the frame index, the activity data is aggregated and counted and the weight is calculated;

[0012] The real duration, activity data aggregation statistics and weight are packaged and handed over to the process simulation playback program for playback according to the flowchart. The playback program reads the weight of each activity in a certain frame and represents the load with the size of the weight on the current activity.

[0013] According to a process simulation playback method based on statistical activity weights, in a possible implementation manner, the statistical process overview information based on process data and activities further includes:

[0014] Collect process data from various data sources across the enterprise;

[0015] Clean the collected data to remove erroneous data, duplicate data and incomplete data. Identify activities in the data based on business rules and process knowledge.

[0016] The attributes of each identified activity are counted, and the attributes of the counted activities constitute the process overview information.

[0017] According to a process simulation playback method based on statistical activity weights, in a possible implementation, the actual duration is determined by analyzing the total execution time T of the process and the expected playback fluency f, and the calculation formula is:

[0018]

[0019] Among them, Δt is the frame duration, that is, the real duration.

[0020] According to a process simulation playback method based on statistical activity weights, in a possible implementation, the frame indexing of all activities based on real duration statistics includes converting the activity start time into a frame index and converting the activity end time into a frame index.

[0021] According to a process simulation playback method based on statistical activity weights, in a possible implementation manner, the calculation formula for converting the activity start time into a frame index is:

[0022]

[0023] Among them, s i For each activity A iThe start time, Δt is the frame duration, f istart The frame index for the start time of the activity.

[0024] According to a process simulation playback method based on statistical activity weights, in a possible implementation manner, the calculation formula for converting the activity end time into a frame index is:

[0025]

[0026] Among them, e i For each activity A i The start and end time of the frame, Δt is the frame length, f iend The frame index of the activity end time.

[0027] According to a process simulation playback method based on statistical activity weights, in a possible implementation manner, the activity data aggregation statistics are as follows:

[0028] For each activity A i , at its starting frame index f istart To the end frame index f iend Within the range of , aggregate statistics of activity data, assuming that the activity data sequence is r i1 ,r i2 ,...,r im , where m = f iend -f istart +1, is the number of data points within the frame range, then the activity data aggregation statistics are:

[0029]

[0030] Among them, R i It is the aggregated statistical result of activity data.

[0031] According to a process simulation playback method based on statistical activity weights, in a possible implementation, a method for calculating activity weights based on the activity data aggregation statistical results includes:

[0032] Determine the factors used to calculate the weights and their importance coefficients α i , where α1+α2+...+α n =1, n is each activity A i Factor X in i the number of

[0033] The weight of the activity is calculated based on the aggregated statistical results of the activity data and the importance coefficient. The calculation formula is:

[0034]

[0035] Among them, ωi is the weight of the activity, R i Aggregate statistics for activity data, R imax The maximum value of the activity data aggregation statistics.

[0036] According to a process simulation playback method based on statistical activity weights, in a possible implementation manner, the real duration, activity data aggregation statistics and weight packaging are packaged in the form of a structure array, and the packaged data in the form of a structure array is passed to a process simulation playback program, and the time interval between each frame is set according to the calculated real duration. During the playback of each frame, the weight information of each activity is read from the structure array, and the display effect of the activity in the flowchart is adjusted according to the obtained weight value to represent the load.

[0037] The beneficial effects of the present invention are:

[0038] Through data preprocessing and aggregate statistical compression, the amount of data is reduced and the complexity of data processing is reduced. For example, in the complex business processes of large enterprises, the original data may contain a large amount of transaction records and operation logs. After the data processing of the present invention, only key statistical information and weight data are retained, which greatly improves the data reading and processing speed of the playback program, avoids the jamming phenomenon, and makes the playback smoother.

[0039] The weight calculation method based on multiple factors comprehensively considers the performance of activities in terms of resource consumption, time occupation and quality impact. In the production process, not only the execution time of processing activities is paid attention to, but also the use of raw materials and product quality are comprehensively considered, so that the weight can accurately describe the actual load of activities in the process, providing a more scientific and reliable basis for process optimization decisions.

[0040] The generated flowchart combined with the simulation playback with weights provides analysts with an intuitive and comprehensive process view. Through the visual weight display, it is possible to quickly locate activities with high or low loads, deeply understand the bottlenecks and advantages of the process, and help discover hidden problems in the process, such as unreasonable resource allocation, improper activity execution sequence, etc., so as to carry out targeted process improvement and optimization. BRIEF DESCRIPTION OF THE DRAWINGS

[0041] Figure 1 It is the overall flow chart of the present invention;

[0042] Figure 2 is a flowchart of method S100;

[0043] Figure 3 is a flow chart of method S200;

[0044] Figure 4is a flow chart of method S300;

[0045] Figure 5 is a flow chart of method S400;

[0046] Figure 6 is a flow chart of method S500. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0048] See also Figure 1 , which shows a process simulation playback method based on statistical activity weights provided by an embodiment of the present invention, including:

[0049] S100: Collect enterprise process data, identify activities in the data, and compile process overview information based on process data and activities.

[0050] S200: Generate a flowchart based on the activity information and the statistical process overview information, and play back the actual duration corresponding to each frame of the data.

[0051] S300: Counting frame indexes of all activities based on real duration.

[0052] S400: performing activity data aggregation statistics and calculating weights based on the activity and the activity start frame index and the activity end frame index in the frame index.

[0053] S500: The real duration, activity data aggregation statistics and weight are packaged and handed over to the process simulation playback program for playback according to the flowchart. The playback program reads the weight of each activity in a certain frame and represents the load with the size of the weight on the current activity.

[0054] S100 collects process data from a wide range of enterprise data sources, identifies and classifies activities based on business rules, and counts various attributes of activities to obtain process overview information and provide basic data support for subsequent process simulation playback. Its data sources cover enterprise resource planning, customer relationship management, workflow management and other systems. It focuses on data accuracy and standardization during data processing, and the statistics of activity attributes are comprehensive and detailed, laying a solid foundation for overall process analysis.

[0055] Please refer to Figure 2, which shows a flowchart of an exemplary process simulation playback method S100 based on statistical activity weights of the present application, and its contents include:

[0056] S110: Collect process data from various data sources of the enterprise.

[0057] The data sources of process data include but are not limited to enterprise resource planning (ERP) systems, customer relationship management (CRM) systems, workflow management systems, etc.

[0058] For example, in a manufacturing enterprise, raw material procurement process data is collected, and procurement order information is obtained from the ERP system, including supplier, procurement quantity, procurement time, etc.; each link and execution time in the procurement approval process is obtained from the workflow management system.

[0059] S120: Clean the collected data to remove erroneous data, duplicate data, and incomplete data.

[0060] For example, if the price field in the purchase order contains abnormal values, such as negative numbers or values ​​far beyond the reasonable market range, it will be corrected or deleted according to the data distribution and business rules. At the same time, the data format is unified, and the time format, quantity format, etc. in different systems are converted into a standard format for subsequent processing.

[0061] S130: Identify activities in the data based on business rules and process knowledge.

[0062] For example, in the procurement process, "submitting a purchase application", "supplier selection", "contract signing", "goods acceptance" and so on are identified as different activities. Then, they are classified according to the nature and function of the activities, such as decision-making activities such as supplier selection and operational activities such as goods acceptance.

[0063] S140: Counting the attributes of each identified activity, and the attributes of the counted activities constitute process overview information.

[0064] For each identified activity, its attributes such as the number of occurrences, average execution time, longest execution time, and shortest execution time are counted, and the counted attributes constitute the process overview information.

[0065] S200: Build a flowchart based on the process overview information to clearly present the sequential relationship between activities. At the same time, deeply analyze the total execution time of the process and the expected playback smoothness, accurately calculate the actual duration corresponding to a frame, fully consider the logical relationship of activities when building the flowchart, and take into account both process characteristics and playback requirements when calculating the frame duration, to ensure that the flowchart can intuitively display the process structure and the frame duration is reasonably selected, so as to provide guarantee for the accuracy and smoothness of subsequent simulation playback.

[0066] Please refer to Figure 3 , which shows a flowchart of an exemplary process simulation playback method S200 based on statistical activity weights of the present application, and its contents include:

[0067] S210: Construct a flowchart according to the sequence and attribute relationship between activities in the process overview information.

[0068] Taking the procurement process as an example, after "submitting a procurement application", it is usually followed by "department approval". After "department approval", it enters the "supplier selection" and other links. In this order, nodes are used to represent activities, and directed edges are used to represent the sequential relationship between activities to draw a flow chart.

[0069] S220: Analyze the total execution time of the process and the expected playback smoothness to determine the actual duration corresponding to one frame.

[0070] The total execution time T of the analysis process and the expected playback smoothness f are used to determine the actual duration corresponding to a frame, that is, the frame duration Δt. The calculation formula is:

[0071]

[0072] For example, if the total time of the purchase process from start to finish is 1000 seconds and it is expected to play back 20 frames per second, then At the same time, the distribution of activity execution time in the process needs to be considered to ensure that the frame duration can reasonably display the execution process of the activity and avoid the situation where the activity is completed instantly within one frame or the span is too large.

[0073] S300: Using the determined real duration, the start time and end time of each activity are converted into frame indexes respectively, and the time range of the activity in the simulation playback is clarified through calculation and rounding by a specific formula, so as to determine the time dimension positioning for subsequent data processing. The calculation process is strictly based on the formula, and the conversion result is accurate and reliable, providing a key time reference for activity data processing and weight calculation, so that the entire simulation playback process can proceed in an orderly manner in the time dimension.

[0074] Please refer to Figure 4 , which shows a flowchart of an exemplary process simulation playback method S300 based on statistical activity weights of the present application, and its contents include:

[0075] S310: Convert the activity start time into a frame index.

[0076] For each activity A i , its starting time s is known i , calculate the starting frame index f according to the frame duration Δt istart , the calculation formula is:

[0077]

[0078] Round the calculated value.

[0079] For example, if the start time of an activity is 250 milliseconds and the frame length is 50 milliseconds, the start frame index is

[0080] S320: Convert the activity end time into a frame index.

[0081] For each activity A i , its end time e is known i , calculate the end frame index f according to the frame duration Δt iend , the calculation formula is:

[0082]

[0083] Round the calculated value.

[0084] For example, if the start time of an activity is 450 milliseconds and the frame length is 50 milliseconds, the start frame index is

[0085] By converting the activity start time into frame number and the activity end time into frame number, the frame number range of each activity in the simulation playback is determined, providing the time dimension positioning for subsequent data processing.

[0086] S400: For each activity, data aggregation statistics are performed within the frame index range, and a variety of factors and their importance coefficients are comprehensively considered. The activity weight is calculated using a scientific formula to comprehensively and accurately reflect the load of the activity in the process. The data aggregation statistics cover all types of activity-related data. The importance coefficient setting is in line with the actual needs of the enterprise. The weight calculation method is scientific and reasonable, providing a strong basis for the importance evaluation of activities in the process and facilitating in-depth analysis of the process operation status.

[0087] Please refer to Figure 5 , which shows a flowchart of an exemplary process simulation playback method S400 based on statistical activity weights of the present application, and its contents include:

[0088] S410: For each activity, aggregate statistics are performed on the activity data within the range from the start frame index to the end frame index.

[0089] For each activity A i , at its starting frame index f istart To the end frame index f iend Within the range of , aggregate statistics of activity data, assuming that the activity data sequence is r i1 ,r i2 ,...,rim , where m = f iend -f istart +1 is the number of data points within the frame range. The aggregate statistics of the activity data are:

[0090]

[0091] Among them, R i It is the aggregated statistical result of activity data.

[0092] S420: Calculate the weight of the activity according to the aggregated statistical results of the activity data.

[0093] First, determine the factors used to calculate the weight and their importance coefficients. For each activity A i Factor X in i , assigning importance coefficient α i , where α1+α2+...+α n = 1. Importance coefficient α i It is set according to the company's production goals and management priorities.

[0094] The weight of the activity is calculated based on the aggregated statistical results of the activity data and the importance coefficient. The calculation formula is:

[0095]

[0096] Among them, ω i is the weight of the activity, R i Aggregate statistics for activity data, R imax The maximum value of the activity data aggregation statistics.

[0097] S500: The calculated real duration, activity data aggregation statistics and weights are carefully packaged in the form of a structure array and passed to the playback program. The playback speed is strictly controlled according to the real duration. The activity weight information is accurately read and intuitively displayed in a variety of ways during each frame playback to clearly represent the activity load. The data packaging structure is reasonably designed, data transmission is accurate and efficient, playback speed control is precise and stable, and weight display methods are diverse and intuitive, which effectively helps analysts understand the process load and promotes the smooth implementation of process optimization work.

[0098] Please refer to Figure 6 , which shows a flowchart of an exemplary process simulation playback method S500 based on statistical activity weights of the present application, and its contents include:

[0099] S510: Aggregate the calculated real duration Δt and the activity data of each activity into statistical results R i , weight ω i Packed in the form of structure array.

[0100] First, define a structure to store the relevant information of each activity. The structure contains the following members:

[0101] Activity Name (activityName): used to identify the activity, such as "purchase application submission", "raw material processing", etc., and the type is string (string).

[0102] Real time: stores the real time corresponding to one frame of the activity in the process. The type is a floating point number (float) or a double precision number (double) to ensure that the time interval can be accurately represented.

[0103] Aggregate statistics (statistics): This is a structure or class containing multiple data items, used to store the aggregate statistics of activity data. For example, it can contain the total raw material consumption (rawMaterialConsumption), the total equipment running time (equipmentRunningTime), the number of operations (operationCount), etc. The types of these data items depend on the actual statistical data type.

[0104] Weight: stores the calculated activity weight, which is a floating point number and indicates the relative importance and load of the activity in the process.

[0105] Next, create an array of structures whose size is equal to the number of activities in the process.

[0106] After the structure array is filled, the structure array contains the relevant information of all activities, and the real duration, aggregated statistical results and weights are packaged in the form of a structure array. The packaged structure array is passed to the process simulation playback program.

[0107] S520: The packaged data is passed to the playback program, and the playback speed is controlled according to the flowchart and the actual duration. During the playback of each frame, the weight information of each activity is read and displayed, and the load is represented by the size of the weight on the current activity.

[0108] Pass the packed data in the form of structure array to the process simulation playback program.

[0109] Set the time interval between each frame based on the calculated real time. For example, if the real time is 0.1 seconds / frame, then in the playback program, use a timer or delay function to ensure that the playback interval between each frame is seconds. To ensure the accuracy of the playback speed, perform synchronization and calibration operations. Before the playback starts, record the current system time as the start time, and then when each frame is played, calculate whether the playback time of the next frame has been reached based on the current time, start time and frame number. If the playback is delayed due to reasons such as system load, adjustments need to be made, such as skipping some unnecessary calculations or display update operations to keep the playback speed as stable as possible.

[0110] During the playback of each frame, the weight information of each activity is read from the structure array. According to the time range corresponding to the current frame, it is determined which activities are in the execution state in the current frame, and then the weight values ​​of these activities are obtained.

[0111] The activity display in the flowchart is adjusted based on the obtained weight value to represent the load.

[0112] The above technology can accurately pass the packaged data to the playback program and smoothly play it back according to the actual duration. At the same time, the weight information of each activity is intuitively displayed in each frame, helping analysts to better understand the load of activities during the process operation, thereby providing strong support for process optimization.

[0113] The basic principles of the present application are described above in conjunction with specific embodiments. However, it should be noted that the advantages, strengths, effects, etc. mentioned in the present application are only examples and not limitations, and it cannot be considered that these advantages, strengths, effects, etc. are required by each embodiment of the present application. In addition, the specific details disclosed above are only for the purpose of illustration and ease of understanding, not for limitation, and the above details do not limit the present application to being implemented by adopting the above specific details.

[0114] The block diagrams of the devices, apparatuses, equipment, and systems involved in this application are only illustrative examples and are not intended to require or imply that they must be connected, arranged, and configured in the manner shown in the block diagram. As will be appreciated by those skilled in the art, these devices, apparatuses, equipment, and systems can be connected, arranged, and configured in any manner. Words such as "including", "comprising", "having", etc. are open words, referring to "including but not limited to", and can be used interchangeably with them. The words "or" and "and" used here refer to the words "and / or" and can be used interchangeably with them, unless the context clearly indicates otherwise. The words "such as" used here refer to the phrase "such as but not limited to", and can be used interchangeably with them.

[0115] It should also be noted that in the apparatus, device and method of the present application, each component or each step can be decomposed and / or recombined. Such decomposition and / or recombination should be regarded as equivalent solutions of the present application.

[0116] The above description of the disclosed aspects is provided to enable any person skilled in the art to make or use the present application. Various modifications to these aspects will be readily apparent to those skilled in the art, and the general principles defined herein may be applied to other aspects without departing from the scope of the present application. Therefore, the present application is not intended to be limited to the aspects shown herein, but rather to the widest scope consistent with the principles and novel features of the present invention.

[0117] The above description is only a preferred embodiment of the present application and is not intended to limit the present application. Any modifications, equivalent substitutions, etc. made within the spirit and principles of the present application shall be included in the protection scope of the present application.

Claims

1. A process simulation playback method based on statistical activity weights, characterized in that: include: Collect enterprise process data, identify activities in the data, and provide process overview information based on process data and activities; Build a flowchart based on the sequence and attribute relationship between activities in the process overview information, and play back the actual duration of each frame; Count the frame index of all activities based on the real duration; Based on the activity, as well as the activity start frame index and the activity end frame index in the frame index, the activity data is aggregated and counted and the weight is calculated; The real duration, activity data aggregation statistics and weight are packaged and handed over to the process simulation playback program for playback according to the flowchart. The playback program reads the weight of each activity in a certain frame and represents the load with the size of the weight on the current activity.

2. A process simulation playback method based on statistical activity weights according to claim 1, characterized in that: The process overview information based on process data and activity statistics also includes: Collect process data from various data sources across the enterprise; Clean the collected data to remove erroneous data, duplicate data and incomplete data. Identify activities in the data based on business rules and process knowledge. The attributes of each identified activity are counted, and the attributes of the counted activities constitute the process overview information.

3. A process simulation playback method based on statistical activity weights according to claim 1, characterized in that: The actual duration is determined by analyzing the total execution time T of the process and the expected playback smoothness f, and the calculation formula is: Among them, Δt is the frame duration, that is, the real duration.

4. A process simulation playback method based on statistical activity weights according to claim 1, characterized in that: The counting of frame indexes of all activities based on the real duration includes converting the activity start time into a frame index and converting the activity end time into a frame index.

5. A process simulation playback method based on statistical activity weights according to claim 4, characterized in that: The calculation formula for converting the activity start time into a frame index is: Among them, s i For each activity A i The start time, Δt is the frame length, f istart The frame index for the start time of the activity.

6. A process simulation playback method based on statistical activity weights according to claim 4, characterized in that: The calculation formula for converting the activity end time into a frame index is: Among them, e i For each activity A i The start and end time of the frame, Δt is the frame length, f iend The frame index of the activity end time.

7. A process simulation playback method based on statistical activity weights according to claim 1, characterized in that: The activity data aggregation and statistical method is as follows: For each activity A i , at its starting frame index f istart To the end frame index f iend Within the range of , aggregate statistics of activity data, assuming that the activity data sequence is r i1 ,r i2 ,...,r im , where m = f iend -f istart +1, is the number of data points within the frame range, then the activity data aggregation statistics are: Among them, R i It is the aggregated statistical result of activity data.

8. A process simulation playback method based on statistical activity weights according to claim 7, characterized in that: The method for calculating the weight of an activity according to the aggregated statistical result of the activity data includes: Determine the factors used to calculate the weights and their importance coefficients α i , where α1+α2+...+α n =1, n is each activity A i Factor X in i the number of The weight of the activity is calculated based on the aggregated statistical results of the activity data and the importance coefficient. The calculation formula is: Among them, ω i is the weight of the activity, R i Aggregate statistics for activity data, R imax The maximum value of the activity data aggregation statistics.

9. A process simulation playback method based on statistical activity weights according to claim 1, characterized in that: The real duration, activity data aggregation statistics and weight packaging method are packaged in the form of a structure array, and the packaged data in the form of a structure array is passed to the process simulation playback program. The time interval between each frame is set according to the calculated real duration. During the playback of each frame, the weight information of each activity is read from the structure array, and the display effect of the activity in the flowchart is adjusted according to the obtained weight value to represent the load.

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