Production plan scheduling method and device

Abstract

The invention discloses a production plan scheduling method and device, and the method comprises the steps: obtaining change information of N changes in a preset time period, the change information comprises change basic characteristic information, change implementation step information and change influence information, and N is a positive integer; according to the change information of the N changes, risk quantitative evaluation is carried out on the N changes from a change basic characteristic dimension, a change influence dimension and a change execution risk dimension, and a target risk value is obtained; and performing scheduling management on the production plan in a preset time period according to the target risk value. Therefore, the change risk in the production plan scheduling work can be comprehensively and quantitatively evaluated, and the reliability of production plan scheduling can be improved.

Description

Technical Field

[0001] The present invention relates to the field of computer technology, and in particular to a production planning and scheduling method and device. Background Art

[0002] As the core infrastructure department supporting the business operations of enterprises, the primary responsibility of the data center is to ensure the continuous stability and safe operation of the production environment. With the continuous expansion of business and the widespread application of cloud computing, distributed, big data and other technologies, the scale of data center operation and maintenance management systems is getting larger and larger, and the complexity of the architecture is also increasing. In this context, the production change tasks undertaken by the data center in daily operations are becoming increasingly heavy. The slightest negligence in the implementation of changes may lead to system abnormalities or service interruptions. How to avoid the impact of change implementation on the stable operation of production business has become one of the main challenges of data center work.

[0003] Production planning and scheduling play a core role in controlling change risks and ensuring smooth production. By implementing scientific and reasonable production planning and scheduling, enterprises can arrange various production tasks within daily and time windows in an orderly manner, effectively disperse and reduce risks, and properly handle potential conflicts and associated risks between different changes, thereby ensuring the efficiency and smoothness of the entire production process. The current production planning and scheduling only uses the number of changes implemented during the window as the basis for scheduling, and does not consider change risks. In the relevant technologies for controlling change risks, they often focus on independent assessments of the risks of implementing a certain change, and fail to fully consider the comprehensive risks that may be caused by the simultaneous implementation of multiple changes. Due to the lack of comprehensive quantitative assessment of change risks in production planning and scheduling, the reliability of production planning and scheduling will be affected. Summary of the invention

[0004] The embodiment of the present invention provides a production plan scheduling method and device, which are used to achieve a comprehensive quantitative evaluation of the change risk in the production plan scheduling work.

[0005] In a first aspect, an embodiment of the present invention provides a production plan scheduling method, comprising: obtaining change information of N changes within a preset time period, the change information including change basic characteristic information, change implementation step information and change impact information, where N is a positive integer; based on the change information of the N changes, performing risk quantification assessment on the N changes from the dimensions of basic characteristic of the changes, the dimensions of change impact and the dimensions of change execution risk, to obtain a target risk value; and based on the target risk value, scheduling and managing the production plan within the preset time period.

[0006] In the above technical scheme, by quantifying the change risk within a preset period from multiple key dimensions such as the basic characteristics of the change, the impact of the change, and the risk of the change execution, a comprehensive quantitative assessment of the change risk in the production planning and scheduling work is achieved, providing decision support for the production planning and scheduling, and helping to improve the reliability of the production planning and scheduling.

[0007] Optionally, the step of quantifying the risk of the N changes from the dimensions of basic characteristics of the changes, impact of the changes, and execution risk of the changes to obtain a target risk value includes:

[0008] For each of the N changes, execute:

[0009] According to the change information of the change, the risk of the change is quantified from the dimensions of basic characteristics of the change, the dimension of impact of the change and the dimension of execution risk of the change to obtain the risk value of the change; the target risk value includes the risk values ​​corresponding to the N changes respectively.

[0010] Optionally, the step of quantifying the risk of the change from a change basic characteristic dimension, a change impact dimension, and a change execution risk dimension according to the change information of the change to obtain a risk value of the change includes:

[0011] Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information;

[0012] The change blasting radius of the change and the associated impact set of the change are quantitatively evaluated respectively, and the change impact dimension quantization value of the change is determined according to the quantization results corresponding to the change blasting radius and the associated impact of the change, wherein the change blasting radius of the change is the application impact range generated by the implementation of the change, and the associated impact set of the change includes the change and other changes that have associated impacts with the change;

[0013] Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps;

[0014] The risk value of the change is determined according to the quantified value of the change basic characteristic dimension of the change, the quantified value of the change impact dimension of the change, and the quantified value of the change execution risk dimension of the change.

[0015] Optionally, the method further includes:

[0016] Determine other changes that have an associated impact on the change according to preset associated impact factors; wherein the preset associated impact factors include at least one of the following: affecting the same application as the change; having a version dependency relationship with the change; and having a system call relationship with the change;

[0017] According to the change and other changes having associated impacts with the change, a set of associated impacts of the change is determined.

[0018] Optionally, the step of quantifying the risk of the N changes from the dimensions of basic characteristics of the changes, impact of the changes, and execution risk of the changes to obtain a target risk value includes:

[0019] Dividing the change information of the N changes into a plurality of time windows;

[0020] For each time window in the multiple time windows, execute:

[0021] According to the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of the impact of the changes, and the dimensions of the execution risk of the changes, to obtain the overall risk value of the time window; the target risk value includes the overall risk values ​​corresponding to the multiple time windows respectively.

[0022] Optionally, before dividing the change information of the N changes into a plurality of time windows, the method further includes:

[0023] Divide the preset time period according to the window segmentation strategy to obtain the multiple time windows;

[0024] The window segmentation strategy includes: segmenting the preset time period into windows according to a fixed time period, or segmenting the preset time into windows according to a time window interval input by a user.

[0025] Optionally, the step of performing an overall risk quantitative assessment on all changes in the time window from the dimensions of basic characteristics of changes, impact of changes, and execution risk of changes, respectively, based on the change information of all changes in the time window, to obtain an overall risk value of the time window includes:

[0026] quantifying a plurality of overall associated change sets formed by all changes included in the time window respectively, and determining a first impact dimension quantization value corresponding to the time window according to the quantization results respectively corresponding to the plurality of overall associated change sets;

[0027] For each change within the time window, execute:

[0028] Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information;

[0029] Performing a quantitative evaluation on the change blasting radius of the change, and determining a quantitative value of a first impact dimension of the change according to a quantitative result corresponding to the change blasting radius, wherein the change blasting radius of the change is an application impact range generated by the implementation of the change;

[0030] Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps;

[0031] The overall risk value of the time window is determined based on the quantified value of the first impact dimension corresponding to the time window, the quantified values ​​of the basic characteristic dimension of changes corresponding to all changes within the time window, the quantified values ​​of the first impact dimension corresponding to all changes within the time window, and the quantified values ​​of the change execution risk dimension corresponding to all changes within the time window.

[0032] Optionally, the quantifying respectively a plurality of overall associated change sets formed by all changes included in the time window includes:

[0033] For each of the plurality of overall association change sets, executing:

[0034] Determining weights of respective association links included in the overall association change set, wherein each association link is an association link formed between two different changes having an associated impact in the overall association change set;

[0035] The sum of the weights of the associated links included in the overall association change set is determined as the quantization result corresponding to the overall association change set.

[0036] Optionally, the method further includes:

[0037] The target risk value is displayed in a display interface; wherein the target risk value includes at least one of the following:

[0038] The risk values ​​corresponding to the N changes respectively;

[0039] The overall risk value corresponding to each time window within the preset period;

[0040] The overall risk value of the preset time period; wherein the overall risk value of the preset time period is determined according to the overall risk values ​​corresponding to all time windows included in the preset time period.

[0041] In a second aspect, an embodiment of the present invention provides a production planning and scheduling device, including:

[0042] An acquisition module, used to acquire change information of N changes within a preset period, wherein the change information includes change basic characteristic information, change implementation step information, and change impact information, where N is a positive integer;

[0043] A processing module, configured to perform risk quantitative assessment on the N changes from the dimensions of basic characteristics of the changes, impact of the changes, and execution risk of the changes, respectively, according to the change information of the N changes, to obtain a target risk value;

[0044] The scheduling module is used to schedule and manage the production plan within a preset time period according to the target risk value.

[0045] In a third aspect, an embodiment of the present invention further provides a computer device, including:

[0046] A memory for storing program instructions;

[0047] The processor is used to call the program instructions stored in the memory and execute the above-mentioned production plan scheduling method according to the obtained program.

[0048] In a fourth aspect, an embodiment of the present invention further provides a computer-readable storage medium, wherein the computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned production planning and scheduling method. BRIEF DESCRIPTION OF THE DRAWINGS

[0049] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0050] Figure 1 A schematic diagram of a system architecture provided for an embodiment of the present application;

[0051] Figure 2 A schematic diagram of change risks in three dimensions provided in an embodiment of the present application;

[0052] Figure 3 A flowchart of a production planning and scheduling method provided in an embodiment of the present application;

[0053] Figure 4 A schematic diagram of an associated impact set of a network change 1 provided in an embodiment of the present application;

[0054] Figure 5 A schematic diagram of time window segmentation provided in an embodiment of the present application;

[0055] Figure 6 A schematic diagram of the overall association influence set provided in the embodiment of the present application;

[0056] Figure 7 A schematic diagram of the structure of a production planning and scheduling device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0057] In order to make the purpose, technical solutions and advantages of the present application clearer, the present application will be further described in detail below in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present application, rather than all the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0058] It should be noted that the term "and / or" herein is merely a description of the association relationship of associated objects, indicating that three relationships may exist. For example, A and / or B may represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " herein, unless otherwise specified, generally indicates that the associated objects before and after are in an "or" relationship. And in the description of the embodiments of the present application, words such as "first" and "second" are only used to distinguish the purpose of description, and cannot be understood as indicating or implying relative importance, nor can they be understood as indicating or implying order. In the description of the present application, unless otherwise specified, the meaning of "multiple" is two or more.

[0059] refer to Figure 1 , which is a system architecture diagram applicable to an embodiment of the present application, wherein the system architecture includes a production planning and scheduling device and an associated platform.

[0060] The production planning and scheduling device includes a data acquisition module, a data processing module, a risk calculation module, and a monitoring and scheduling module. The associated platform includes a change module, a CMDB, a publishing platform, and an event module. The following mainly introduces the functions of each module in the production planning and scheduling device.

[0061] (1) The data acquisition module is mainly used to obtain the necessary information for change risk assessment, where the necessary information includes change basic information, change step information, change impact information, etc. The changes involved in the embodiments of the present application are not limited to changes in a single field, but may involve changes in various fields of the data center, such as application systems, IT infrastructure, management tool platforms, etc.

[0062] The basic change information is the core attribute information recorded during change plan registration and planning, including but not limited to change type, change plan, implementation strategy, test and verification status, inspection and verification arrangements, rollback operations, etc.

[0063] Change implementation step information includes the manual and automated steps required for each change. The information involved includes the planned start and end time of the step implementation, as well as the associated operational risk level, etc.

[0064] Change impact information relies on the existing digital change impact assessment capabilities of the data center, including three types of key impact information: First, the change blasting radius, that is, the direct impact range of the change on the application service, based on the change implementation operation configuration items, and combined with the topological relationship between the configuration items in the Configuration Management Database (CMDB) for short. Objectively identify. Second, the call impact between applications, analyzing the potential impact of a certain application change on other applications. Third, the correlation impact between application versions, considering the interdependence of different version launch plans, etc.

[0065] (2) The data processing module is mainly responsible for in-depth processing and handling of various types of information collected by the data acquisition module. Its core functions include: change window (also called time window) segmentation function and correlation impact calculation function.

[0066] The following is an introduction to the time window segmentation function.

[0067] Given that a change implementation plan may span multiple time periods of a day, or even extend over multiple days. In order to more accurately quantify and assess the risks brought about by the implementation of changes, this application adopts a window segmentation strategy, which divides the change implementation steps into different time windows, and quantitatively assesses the change risks within each window. Based on this time window segmentation, it is possible to specifically obtain the change implementation steps within each time window, the operational risk level associated with the change steps, and the possible impact information of the implementation steps.

[0068] The following is an introduction to the association impact calculation function.

[0069] The association impact calculation function mainly includes two parts: the first part is to calculate the risk of a single change. The second part is to calculate the overall change risk, such as calculating the overall change risk within a change window, or calculating the overall change risk within a preset period, where the preset period includes multiple change windows.

[0070] (3) The risk calculation module is the core part of the entire risk assessment and dynamic monitoring device, covering the quantitative calculation of individual change risks, the quantitative calculation of overall change risks, and the dynamic quantitative calculation of risks during the change implementation process.

[0071] (4) The monitoring and scheduling module is used to visually present individual change risks and overall change risks, and to implement dynamic risk monitoring. At the same time, it schedules production changes as needed. It covers two sub-modules: display and monitoring, and production plan scheduling.

[0072] The display and monitoring submodule is mainly used to: display the change risks in three dimensions, such as Figure 2 The diagram shows the daily overall change risk, the change risk in each time window, and the individual change risks; the daily overall change risk is the accumulation of the overall change risk in each time window of the day. The display and monitoring submodule also supports custom multi-dimensional threshold parameters. Once the change risk in a certain dimension reaches the corresponding dimension threshold, an early warning is triggered.

[0073] During the risk assessment phase of the change plan, the display and monitoring submodule is used to obtain the daily change risk value. If the warning line is reached, the data center is prompted to review the change plan for the day and consider whether to schedule the production plan to disperse the change risk. At the same time, the risk details can be viewed in depth through windows and individual change dimensions. Entering the change implementation phase, the display and monitoring submodule displays the risk changes through dynamic curves. Under normal circumstances, as the change implementation progresses, the overall risk curve should gradually decrease; if an abnormality occurs, such as a sudden increase in risk at a certain point in the overall risk curve, an immediate warning will be issued to prompt the change coordinator to quickly coordinate and intervene, such as adjusting related changes through the change scheduling function to reduce systemic risks.

[0074] The production plan scheduling submodule is mainly used to schedule and manage production plans efficiently and accurately. Based on the quantitative risk display and monitoring of changes, when the production plan needs to be scheduled to disperse the overall risk of the change, the scheduling module can be used to directly select the change to be scheduled for scheduling. After scheduling, the production plan scheduling device will recalculate the change risk.

[0075] It should be noted that the above Figure 1The system architecture shown is only an example, and any multiple modules in the production planning and scheduling device can be combined into one module, or any module can be split into multiple sub-modules, which is not limited in the embodiments of the present application.

[0076] Based on the above description, Figure 3 A flow chart of a production planning and scheduling method provided in an embodiment of the present application is exemplarily shown, and the flow chart can be executed by a production planning and scheduling device.

[0077] like Figure 3 As shown in the figure, the process specifically includes:

[0078] Step 301, obtaining change information of N changes within a preset time period, the change information includes change basic characteristic information, change implementation step information and change impact information, and N is a positive integer.

[0079] Among them, changing the basic characteristic information can change the core attribute information recorded during plan registration and planning, including but not limited to change type, change plan, implementation strategy, test verification status, inspection and verification arrangements, rollback operations, etc.

[0080] The above preset time period can be set according to actual needs, such as one day, three days, one week, one month, or even longer, and this application does not impose any restrictions on this.

[0081] Optionally, step 301 may be performed by Figure 1 The data acquisition module in is executed.

[0082] Step 302 , based on the change information of the N changes, risk quantitative assessment is performed on the N changes from the dimensions of basic characteristics of the changes, impact of the changes, and execution risk of the changes to obtain a target risk value.

[0083] The target risk value may include but is not limited to at least one of the following:

[0084] (1) The risk values ​​corresponding to the N changes;

[0085] (2) The overall risk value corresponding to each time window within the preset period;

[0086] (3) An overall risk value for a preset period of time, wherein the overall risk value for the preset period of time is determined based on the overall risk values ​​corresponding to all time windows included in the preset period of time. For example, if the preset period of time includes M time windows, the overall risk value for the preset period of time may be the sum of the overall risk values ​​corresponding to the M time windows.

[0087] Step 303: Schedule and manage the production plan within a preset period according to the target risk value.

[0088] In the embodiment of the present application, by quantifying the change risk within a preset time period from multiple key dimensions such as the dimension of basic characteristics of the change, the dimension of the impact of the change, and the dimension of the risk of change execution, a comprehensive quantitative assessment of the change risk in the production planning and scheduling work is achieved, providing decision support for production planning and scheduling, and helping decision makers to fully grasp and effectively control the risk of change implementation.

[0089] There are many possible implementations of the above step 302, and possible implementations 1 to 3 are provided below.

[0090] In the first implementation mode, for each of the N changes, the following steps are performed: risk quantification of the change is performed from the change basic characteristic dimension, the change impact dimension, and the change execution risk dimension according to the change information of the change, to obtain a risk value of the change. In the first implementation mode, the target risk value in the above step 302 may include the risk values ​​corresponding to the N changes respectively.

[0091] In a possible implementation, each changed risk value can be implemented by following the steps S11 to S14:

[0092] S11, quantitatively evaluating each item of attribute information included in the change basic characteristic information of the change, and determining a quantized value of a change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information.

[0093] For different data centers, the specific content of the basic characteristic information of the change that needs to be quantitatively assessed for the change risk can be determined based on the actual situation. Taking the basic characteristic information of the change including the attribute information such as the change type, change plan, implementation strategy, test verification, inspection verification, and rollback operation as an example, each attribute information such as the change type, change plan, implementation strategy, test verification, inspection verification, and rollback operation can be quantitatively assessed separately to obtain the quantitative results corresponding to each attribute information.

[0094] The quantitative evaluation is performed on each item of attribute information in the changed basic characteristic information. Specifically, the quantitative evaluation may be performed on the corresponding attribute information according to the association relationship between the preset attribute information and the quantitative value.

[0095] The following introduces the quantitative evaluation of the change types in the basic characteristic information of the change.

[0096] For example, the preset change types include major, medium, small, and standard. Corresponding quantitative values ​​can be set for different preset change types. Assuming that the change type is B1, the quantitative values ​​corresponding to different change types are shown in Table 1 below.

[0097] Table 1: Quantitative values ​​of change types

[0098] Change Type B1 quantization value major 5 medium 3 Small 2 standard 0

[0099] For the change type included in the basic characteristic information of the change, for example, medium, then the quantization value corresponding to the change type is determined from Table 1, for example, the quantization value B1 corresponding to medium is 3.

[0100] The following introduces the quantitative evaluation of the change plan in the change basic characteristic information.

[0101] For example, the preset change plans include the first implementation in the production environment, multiple implementations in the production environment with implementation anomalies, and multiple implementations in the production environment with normal implementation. Corresponding quantitative values ​​can be set for different preset change plans. Assuming that the change plan attribute is B2, the quantitative values ​​corresponding to different change plan attributes are shown in Table 2 below.

[0102] Table 2 Quantitative values ​​of change plan

[0103] Change plan B2 quantization value First implementation in production environment 3 The production environment has been implemented multiple times and there are implementation anomalies 2 The production environment has been implemented multiple times and all have been normal 1

[0104] For the change plan included in the change basic characteristic information, for example, it is implemented multiple times in the production environment and all are implemented normally. Then, the quantitative value corresponding to the change plan is determined from Table 2, and B2 is 1.

[0105] The following introduces the quantitative evaluation of the implementation strategy in the basic characteristic information of the change.

[0106] For example, the preset implementation strategies include the first window or batch, and the non-first window or batch. The corresponding quantitative values ​​can be set for the different preset implementation strategies. Assuming that the implementation strategy attribute is B3, the quantitative values ​​corresponding to different implementation strategy attributes are shown in Table 3 below.

[0107] Table 3 Quantitative values ​​of implementation strategies

[0108] Implementation strategy B3 Quantization Value First window or batch 2 Not the first window or batch 1

[0109] The following introduces the quantitative evaluation of the test verification in the basic feature information of the change.

[0110] For example, the preset test verification includes no test conditions, partial test pass, and test pass. Corresponding quantitative values ​​can be set for different preset test verifications. Assuming that the test verification attribute is B4, the quantitative values ​​corresponding to different test verification attributes are shown in Table 4 below.

[0111] Table 4 Test verification quantization values

[0112] Test verification B4 Quantization Value No test conditions 2 Test Partially Passed 1 Test passed 0.5

[0113] The following introduces the quantitative evaluation of the inspection and verification in the basic characteristic information of the change.

[0114] For example, the preset inspection and verification include no immediate verification conditions after the change and immediate inspection and verification after the change. Corresponding quantitative values ​​can be set for different preset inspection and verification. Assuming that the inspection and verification attribute is B5, the quantitative values ​​corresponding to different inspection and verification attributes are shown in Table 5 below.

[0115] Table 5: Check and verify the quantitative values

[0116] Check and Verify B5 Quantization Value No immediate verification conditions after the change 2 Changes can be checked and verified immediately 1

[0117] The following introduces the quantitative evaluation of the rollback operation in the change basic feature information.

[0118] For example, the preset fallback operations include non-direct fallback and the emergency plan has been verified, non-direct fallback and the emergency plan has been successfully implemented, and direct fallback. Corresponding quantitative values ​​can be set for different preset fallback operations. Assuming that the fallback operation attribute is B6, the quantitative values ​​corresponding to different fallback operation attributes are shown in Table 6 below.

[0119] Table 6 Quantization values ​​of fallback operation

[0120] Rollback Operation B6 Quantization Value Cannot be returned directly, emergency plan has been verified 2 Cannot be rolled back directly, the emergency plan has been successfully implemented 1.5 Can be rolled back directly 1

[0121] The quantized value of the changed basic characteristic dimension in the above step S11 can be obtained by summing the quantized values ​​corresponding to the above attribute information, that is, the quantized value of the changed basic characteristic dimension is calculated by the following formula:

[0122] Q1=B1+B2+B3+B4+B5+B6+…+Bn.

[0123] The embodiment of the present application is described with n being 6. In actual situations, other attributes may be selected for quantization.

[0124] S12, quantitatively evaluate the change blasting radius of the change and the associated impact set of the change respectively, and determine the quantitative value of the change impact dimension of the change according to the quantitative results corresponding to the change blasting radius of the change and the quantitative results corresponding to the change associated impact of the change, wherein the change blasting radius of the change is the application impact range caused by the implementation of the change, and the associated impact set of the change includes the change and other changes that have associated impacts with the change.

[0125] The change blasting radius of the change can be calculated based on the change operation configuration items and combined with the topological association relationship between various configuration items in the CMDB.

[0126] The following is an example. Assuming the blasting radius is changed to I1, the quantitative calculation formula is as follows:

[0127]

[0128] Among them, n is the number of affected applications, and the application j impact weight factor is the weight factor corresponding to the affected application. The weight quantization method can be determined according to the actual situation. In this example, the value is simply quantized according to the gear information corresponding to the application. For example, the application gear is divided into six gears, where the first gear is the highest and the sixth gear is the lowest. The weights corresponding to each gear are shown in Table 7.

[0129] Table 7 Application weights of different gears

[0130] Application gear Quantization of weight factors First gear 1 Second gear 0.5 Third gear 0.4 Four gears 0.3 Five gears 0.2 Sixth gear 0.1

[0131] The following describes the associated impact set for each change.

[0132] In a possible implementation, other changes that have an associated impact on the change are determined based on preset associated impact factors; then, based on the change and the other changes that have an associated impact on the change, an associated impact set of the change is determined.

[0133] The preset correlation influencing factors include at least one of the following:

[0134] (1) The change affects the same application;

[0135] (2) There is a version dependency with the change;

[0136] (3) There is a system call relationship with the change.

[0137] The following takes network change 1 as an example to illustrate the process of determining the associated impact set of network change 1.

[0138] For example, network change 1 affects three applications, namely application A, application B, and application C. In the same change window, network change 2 affects application A and application B, system change 1 affects application B and application C, application A change 1 affects application A, and application C version change 1 affects application C. As different changes affect the same application, network change 2, system change 1, application A change 1, and application C version change 1 are associated.

[0139] In the same time window, application D version change 1 and application C version change 1 have a sequential dependency relationship, application F calls application A, and application E calls application C, and both have changes, which has potential impact.

[0140] Combining the above-mentioned correlation factors, a set of correlation impacts of network change 1 is formed, such as Figure 4 shown.

[0141] In fact, the degree of correlation impact of different factors may be different, and it is necessary to comprehensively consider whether to include them in the correlation impact calculation based on the actual situation of the data center. For example, for network change 1, network change 2, system change 1, application F change 1, application E change 1, and application D version change 1 are not very correlated. In the specific calculation, the calculation weight can be used to control whether to include them in the calculation. However, application A change 1 and application C version change directly affect application A and application C respectively, and have a greater correlation impact with network change 1, so they need to be included in the correlation impact calculation. In this example, for simplicity, for changes in IT infrastructure such as networks and systems, the correlation impact set calculation mainly considers including changes in application fields associated with the same application in the calculation, that is, Figure 4 The network change 1, application A change 1 and application C version change 1 that implement the connection are used. For application changes, the calculation of the associated impact set mainly considers the associated version changes and calling system changes associated with it. For example, the associated set for application C version change 1 is application C version change 1, application E change 1 and application D version change 1.

[0142] In an example, assuming that the change-related impact is I2, its quantitative calculation formula is as follows:

[0143]

[0144] Among them, m is the number of association links in a single change association impact set, and different association links can be set with different weights. For example, the weight of the association link between IT infrastructure and application class changes is 1, the weight of the association link between application association version changes is 2, and the weight of the association link between application call changes is 1.

[0145] In the above step S12, the quantization result corresponding to the change explosion radius of the change is I1, and the quantization result corresponding to the change association impact of the change is I2. Then the quantization value of the change impact dimension of the change can be calculated by the following formula:

[0146] Q2=I1+I2.

[0147] S13, quantitatively assessing the operational risk levels corresponding to the respective change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the respective change implementation steps.

[0148] The change execution risk dimension is mainly quantitatively evaluated based on the operational risk level corresponding to the change implementation steps. In the embodiment of the present application, the production operation risk level associated with the change step is divided into four levels, from high to low: A, B, C, and D. The assessment of the risk level comprehensively considers multiple factors such as the potential impact on business or external services, the number of applications involved, and the availability and reliability of IT equipment. The data center can establish an operational risk ledger based on actual production operations and associate various types of change operations with it. Assuming that the production operation risk attribute is OP, the quantitative calculation formula is:

[0149]

[0150] Among them, k is the number of steps of a single change, and the operational risk factors associated with the change steps are quantified according to the operational risk level, as shown in Table 8.

[0151] Table 8 Operation execution risk quantification

[0152]

[0153] In the above step S13, the quantitative value of the change execution risk dimension of the change can be calculated by the following formula:

[0154] Q3=OP.

[0155] It should be understood that the present application does not limit the execution order of the above steps S11 to S13.

[0156] S14, determining a risk value of the change according to the quantified value of the change basic characteristic dimension of the change, the quantified value of the change impact dimension of the change, and the quantified value of the change execution risk dimension of the change.

[0157] For change i, the quantitative value of the basic characteristic dimension of change i is Q1 i Indicates that the change i’s impact dimension is quantified by Q2 i Indicates that the change execution risk dimension quantification value of change i is Q3 i Indicates that the risk value Ri of the change i can be calculated by the following formula:

[0158] Ri=Q1 i +Q2 i +Q3 i .

[0159] The overall change risk is calculated based on the quantification of individual change risks, but it does not directly add up the individual change risks. The overall associated risk of the change needs to be considered.

[0160] In the second implementation mode, the change information of the N changes may be divided into multiple time windows; then, for each of the multiple time windows, the following is performed: based on the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes, to obtain the overall risk value of the time window. In the first implementation mode, the target risk value in the above step 302 may include the overall risk values ​​corresponding to the multiple time windows respectively.

[0161] Before dividing the change information of the N changes into a plurality of time windows, the preset time period may be divided according to a window division strategy to obtain the plurality of time windows; wherein the window division strategy includes:

[0162] The first one is to divide the preset time period into windows according to a fixed time period.

[0163] For example, the fixed time period is 3 hours, that is, every 3 hours is divided into a window, for example, Figure 5 In the fixed cycle mode, enter the starting time 9:00 and the fixed cycle 3, that is, the time windows are 9:00-12:00, 12:00-15:00, 15:00-18:00, 18:00-21:00, etc.

[0164] The second method is to divide the preset time into windows according to the time window interval input by the user.

[0165] For example, you can customize the settings based on the actual change window range of the data center, such as Figure 5 In the personalized mode, set the starting time 18:00 and the intervals 5 and 6 corresponding to different time windows, that is, the time windows are 18:00-23:00, 23:00-05:00, etc.

[0166] In a possible implementation, for each time window, based on the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of the impact of the changes, and the dimensions of the execution risk of the changes, to obtain an overall risk value of the time window, which can be achieved by the following steps S21 to S24:

[0167] S21, quantizing a plurality of overall associated change sets formed by all changes included in the time window respectively, and determining a first impact dimension quantization value corresponding to the time window according to the quantization results respectively corresponding to the plurality of overall associated change sets.

[0168] Each overall association impact set is introduced below.

[0169] The overall correlation impact set needs to integrate each individual change correlation set to form a more complex correlation system. For a data center, a change window usually involves a large number of changes, so it is likely to form multiple such overall correlation impact sets. In the overall correlation impact set, different from a single change set, each change may have its own correlation impact set.

[0170] like Figure 5 As shown in the figure, a schematic diagram of an overall associated impact set is shown. Network change 1, network change 2, system change 1, system change 2, application A change 1, application C version change 1, application F change 1, and application D version change 1 all have their own associated impact sets, thus forming a complex overall associated impact set.

[0171] Similar to the single change association impact set, in the overall association impact set, each data center can also consider which relationships need to be included in the calculation according to the actual situation. For example, the relationship between IT infrastructure changes is not included, the relationship between IT infrastructure and application changes is included, and the relationship between application changes is included. Based on this assumption, Figure 6 There is no association between network change 1 and network change 2, no association between network change 1 and system change 1, associations are established between network change 1 and application A change 1 and application C version change 1, associations are established between network change 2 and application A change 1, associations are established between system change 1 and application C version change 1, associations are established between application F change 1 and system change 2, and associations are established between system change 2 and application D version change 1.

[0172] In addition, in the overall association impact link, different association weights can be set for the association links according to actual conditions. For example, the weight of the association link between IT infrastructure and application class changes is 1, the weight of the association link between application association version changes is 2, and the weight of the association link between application call changes is 1.

[0173] An implementation method that can realize the quantization of multiple overall associated change sets formed by all changes included in the time window in step S21, and for each overall associated change set in the multiple overall associated change sets, executing: determining the weights of each associated link included in the overall associated change set, wherein each associated link is an associated link formed between two different changes with associated impact in the overall associated change set; and determining the sum of the weights of each associated link included in the overall associated change set as the quantization result corresponding to the overall associated change set.

[0174] Exemplary, a single holistic association change set quantitative calculation formula:

[0175]

[0176] Where s is the number of association links in a single holistic association impact set, and different weights can be set for different association links. I3p represents the quantitative risk of the pth holistic association impact set in the time window.

[0177] S22, for each change within the time window, execute the following steps S221 to S224:

[0178] S221, quantitatively evaluate each attribute information included in the change basic characteristic information of the change, and determine the quantitative value of the change basic characteristic dimension of the change according to the quantitative results corresponding to each attribute information. The specific implementation of step S221 can refer to the relevant description of the above step S11, which will not be repeated here.

[0179] S222, quantitatively evaluate the change blasting radius of the change, and determine the quantitative value of the first impact dimension of the change according to the quantitative result corresponding to the change blasting radius, wherein the change blasting radius of the change is the application impact range generated by the implementation of the change. The specific implementation of step S222 can refer to the relevant description of the aforementioned step S12, which will not be repeated here.

[0180] S223, quantitatively evaluate the operational risk level corresponding to each change implementation step of the change, and determine the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk level corresponding to each change implementation step. The specific implementation of step S223 can refer to the relevant description of the aforementioned step S13, which will not be repeated here.

[0181] S224, determines the overall risk value of the time window based on the quantified value of the first impact dimension corresponding to the time window, the quantified values ​​of the basic characteristic dimension of changes corresponding to all changes in the time window, the quantified values ​​of the first impact dimension corresponding to all changes in the time window, and the quantified values ​​of the change execution risk dimension corresponding to all changes in the time window.

[0182] In an example, the overall change risk quantification formula for a time window is as follows:

[0183]

[0184] Among them, Rt is the overall change risk in a single time window, l is the number of changes involved in the change window, Q1 j I1 represents the quantitative risk value of the basic characteristic dimension of the jth change, j Quantify the risk value of the blast radius for the jth change, Q3 j The risk value of the j-th change operation execution risk dimension is quantified, and q is the number of associated change sets formed in the change window.

[0185] Implementation method three, the above target risk value includes the risk values ​​corresponding to the N changes and the overall risk values ​​corresponding to the multiple time windows, or the target risk value includes the overall risk value of the preset period and any one of the following: the risk values ​​corresponding to the N changes; the overall risk values ​​corresponding to the multiple time windows. The overall risk value of the preset period is determined based on the overall risk values ​​corresponding to all the time windows included in the preset period.

[0186] Based on any of the above implementations, the target risk value may also be displayed on the display interface in the embodiment of the present application.

[0187] For the change plan within each change window, the risk of individual changes and overall changes are quantified to provide support for risk control work such as change scheduling. However, given the continuous evolution of risk conditions during the change implementation process, it is necessary to be able to dynamically monitor the change risks to ensure that risks can be continuously evaluated and effectively managed throughout the change cycle. Through dynamic monitoring, on the one hand, the overall change risk within the change window can be controlled, and on the other hand, when the risk fluctuates abnormally, it can be quickly identified and targeted intervention measures can be taken.

[0188] In order to realize dynamic calculation of change implementation risk, the following three key factors are comprehensively considered in the embodiment of the present application:

[0189] The first key element is to dynamically remove the completed change steps

[0190] During the change implementation process, for the change steps that have been successfully executed and completed, the corresponding risk assessment items are dynamically eliminated from the risk quantification model, which mainly involves dynamic quantitative calculations of the change impact dimension and the change operation execution risk dimension.

[0191] The second key element is to quantify the impact of changes when they are implemented abnormally

[0192] When an abnormality occurs in the implementation of a change, the weight of the associated link in the associated impact set related to the abnormal change will be increased. The specific increase ratio can be flexibly set according to the actual situation, for example, it can be increased to N times the default weight, or a fixed weight, to fully reflect the impact of the abnormal change on the overall risk of the associated link.

[0193] The third key element is integrated analysis with the event module

[0194] In order to more comprehensively capture and respond to risk changes during the implementation of changes, the production planning and scheduling device in the embodiment of the present application is tightly integrated with the event management module. During the implementation of changes, if an impact event associated with the changed operation configuration item or the affected configuration item occurs, an additional event-related risk value is added to the risk quantification model, and the specific added weight can be set according to the event level to reflect the immediate impact of the event on the overall risk pattern.

[0195] Combining the above three key factors, the dynamic risk quantification calculation formula for a single change is as follows:

[0196]

[0197] Among them, Q1 i Quantify the risk value for the static basic characteristic dimension, To eliminate the change impact dimension that is recalculated after the change steps have been completed, dynamically quantify the risk value. In order to eliminate the dynamic quantitative risk value of the operation execution risk dimension after the change steps have been completed, ΔR is the event-related risk value.

[0198] The quantitative calculation formula for the overall change dynamic risk in a single time window is:

[0199]

[0200] in, Quantify the risk value of the basic characteristic dimension of the jth change, Dynamically quantify the risk value of the j-th changed blast radius dimension, The dynamic quantitative risk value of the risk dimension of the j-th changed operation execution, is the dynamic quantitative risk value of the pth holistic associated impact set, and ΔR is the associated risk value of a single event.

[0201] Based on the same technical concept, a structural diagram of a production planning and scheduling device provided in an embodiment of the present application is as follows: Figure 7 As shown, the device 700 includes:

[0202] The acquisition module 701 is used to acquire change information of N changes within a preset period, wherein the change information includes change basic characteristic information, change implementation step information and change impact information, and N is a positive integer;

[0203] The processing module 702 is used to perform risk quantitative assessment on the N changes from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes according to the change information of the N changes, so as to obtain a target risk value;

[0204] The scheduling module 703 is used to schedule and manage the production plan within a preset time period according to the target risk value.

[0205] Optionally, the processing module 702 is used to:

[0206] For each of the N changes, execute:

[0207] According to the change information of the change, the risk of the change is quantified from the dimensions of basic characteristics of the change, the dimension of impact of the change and the dimension of execution risk of the change to obtain the risk value of the change; the target risk value includes the risk values ​​corresponding to the N changes respectively.

[0208] Optionally, the processing module 702 is used to:

[0209] Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information;

[0210] The change blasting radius of the change and the associated impact set of the change are quantitatively evaluated respectively, and the change impact dimension quantization value of the change is determined according to the quantization results corresponding to the change blasting radius and the associated impact of the change, wherein the change blasting radius of the change is the application impact range generated by the implementation of the change, and the associated impact set of the change includes the change and other changes that have associated impacts with the change;

[0211] Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps;

[0212] The risk value of the change is determined according to the quantified value of the change basic characteristic dimension of the change, the quantified value of the change impact dimension of the change, and the quantified value of the change execution risk dimension of the change.

[0213] Optionally, the processing module 702 is further configured to:

[0214] Determine other changes that have an associated impact on the change according to preset associated impact factors; wherein the preset associated impact factors include at least one of the following: affecting the same application as the change; having a version dependency relationship with the change; and having a system call relationship with the change;

[0215] According to the change and other changes having associated impacts with the change, a set of associated impacts of the change is determined.

[0216] Optionally, the processing module 702 is specifically configured to:

[0217] Dividing the change information of the N changes into a plurality of time windows;

[0218] For each time window in the multiple time windows, execute:

[0219] According to the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of the impact of the changes, and the dimensions of the execution risk of the changes, to obtain the overall risk value of the time window; the target risk value includes the overall risk values ​​corresponding to the multiple time windows respectively.

[0220] Optionally, the processing module 702 is further configured to:

[0221] Divide the preset time period according to the window segmentation strategy to obtain the multiple time windows;

[0222] The window segmentation strategy includes: segmenting the preset time period into windows according to a fixed time period, or segmenting the preset time into windows according to a time window interval input by a user.

[0223] Optionally, the processing module 702 is specifically configured to:

[0224] quantifying a plurality of overall associated change sets formed by all changes included in the time window respectively, and determining a first impact dimension quantization value corresponding to the time window according to the quantization results respectively corresponding to the plurality of overall associated change sets;

[0225] For each change within the time window, execute:

[0226] Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information;

[0227] Performing a quantitative evaluation on the change blasting radius of the change, and determining a quantitative value of a first impact dimension of the change according to a quantitative result corresponding to the change blasting radius, wherein the change blasting radius of the change is an application impact range generated by the implementation of the change;

[0228] Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps;

[0229] The overall risk value of the time window is determined based on the quantified value of the first impact dimension corresponding to the time window, the quantified values ​​of the basic characteristic dimension of changes corresponding to all changes within the time window, the quantified values ​​of the first impact dimension corresponding to all changes within the time window, and the quantified values ​​of the change execution risk dimension corresponding to all changes within the time window.

[0230] Optionally, the processing module 702 is specifically configured to:

[0231] For each of the plurality of overall association change sets, executing:

[0232] Determining weights of respective association links included in the overall association change set, wherein each association link is an association link formed between two different changes having an associated impact in the overall association change set;

[0233] The sum of the weights of the associated links included in the overall association change set is determined as the quantization result corresponding to the overall association change set.

[0234] The device also includes a display module 704, which is used to: display the target risk value in a display interface; wherein the target risk value includes at least one of the following:

[0235] The risk values ​​corresponding to the N changes respectively;

[0236] The overall risk value corresponding to each time window within the preset period;

[0237] The overall risk value of the preset time period; wherein the overall risk value of the preset time period is determined according to the overall risk values ​​corresponding to all time windows included in the preset time period.

[0238] Based on the same technical concept, the embodiment of the present application also provides a computer device, including:

[0239] A memory for storing program instructions;

[0240] The processor is used to call the program instructions stored in the memory and execute the above-mentioned production plan scheduling method according to the obtained program.

[0241] Based on the same technical concept, an embodiment of the present application also provides a computer-readable storage medium, which stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the above-mentioned production planning and scheduling method.

[0242] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems, or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented in one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that include computer-usable program code.

[0243] The present application is described with reference to the flowcharts and / or block diagrams of the methods, devices (systems), and computer program products according to the present application. It should be understood that each process and / or box in the flowchart and / or block diagram, as well as the combination of the processes and / or boxes in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0244] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0245] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0246] Obviously, those skilled in the art can make various changes and modifications to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalents, the present application is also intended to include these modifications and variations.

Claims

1. A production planning and scheduling method, characterized in that: include: Obtain change information of N changes within a preset period, wherein the change information includes change basic characteristic information, change implementation step information, and change impact information, where N is a positive integer; According to the change information of the N changes, respectively, a risk quantitative assessment is performed on the N changes from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes to obtain a target risk value; According to the target risk value, the production plan within the preset time period is scheduled and managed.

2. The method according to claim 1, characterized in that According to the change information of the N changes, risk quantification of the N changes is performed from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes to obtain a target risk value, including: For each of the N changes, execute: According to the change information of the change, the risk of the change is quantified from the dimensions of basic characteristics of the change, the dimension of impact of the change and the dimension of execution risk of the change to obtain the risk value of the change; the target risk value includes the risk values ​​corresponding to the N changes respectively.

3. The method according to claim 2, characterized in that The step of quantifying the risk of the change from the dimensions of basic characteristics of the change, the dimension of impact of the change, and the dimension of execution risk of the change according to the change information of the change to obtain the risk value of the change includes: Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information; The change blasting radius of the change and the associated impact set of the change are quantitatively evaluated respectively, and the change impact dimension quantization value of the change is determined according to the quantization results corresponding to the change blasting radius and the associated impact of the change, wherein the change blasting radius of the change is the application impact range generated by the implementation of the change, and the associated impact set of the change includes the change and other changes that have associated impacts with the change; Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps; The risk value of the change is determined according to the quantified value of the change basic characteristic dimension of the change, the quantified value of the change impact dimension of the change, and the quantified value of the change execution risk dimension of the change.

4. The method according to claim 3, characterized in that The method further comprises: Determine other changes that have an associated impact on the change according to preset associated impact factors; wherein the preset associated impact factors include at least one of the following: affecting the same application as the change; having a version dependency relationship with the change; and having a system call relationship with the change; According to the change and other changes having associated impacts with the change, a set of associated impacts of the change is determined.

5. The method according to claim 1, characterized in that According to the change information of the N changes, risk quantification of the N changes is performed from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes to obtain a target risk value, including: Dividing the change information of the N changes into a plurality of time windows; For each time window in the multiple time windows, execute: According to the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of the impact of the changes, and the dimensions of the execution risk of the changes, to obtain the overall risk value of the time window; the target risk value includes the overall risk values ​​corresponding to the multiple time windows respectively.

6. The method according to claim 5, characterized in that Before dividing the change information of the N changes into a plurality of time windows, the method further includes: Divide the preset time period according to the window segmentation strategy to obtain the multiple time windows; The window segmentation strategy includes: segmenting the preset time period into windows according to a fixed time period, or segmenting the preset time into windows according to a time window interval input by a user.

7. The method according to claim 5, characterized in that According to the change information of all changes in the time window, an overall risk quantitative assessment is performed on all changes in the time window from the dimensions of basic characteristics of the changes, the dimensions of impact of the changes, and the dimensions of execution risk of the changes, to obtain an overall risk value of the time window, including: quantifying a plurality of overall associated change sets formed by all changes included in the time window respectively, and determining a first impact dimension quantization value corresponding to the time window according to the quantization results respectively corresponding to the plurality of overall associated change sets; For each change within the time window, execute: Quantitatively evaluate each item of attribute information included in the change basic characteristic information of the change, and determine the quantized value of the change basic characteristic dimension of the change according to the quantized results corresponding to each item of attribute information; Performing a quantitative evaluation on the change blasting radius of the change, and determining a quantitative value of a first impact dimension of the change according to a quantitative result corresponding to the change blasting radius, wherein the change blasting radius of the change is an application impact range generated by the implementation of the change; Conducting quantitative assessment on the operational risk levels corresponding to the various change implementation steps of the change, and determining the quantitative value of the change execution risk dimension of the change according to the quantitative results of the operational risk levels corresponding to the various change implementation steps; The overall risk value of the time window is determined based on the quantified value of the first impact dimension corresponding to the time window, the quantified values ​​of the basic characteristic dimension of changes corresponding to all changes within the time window, the quantified values ​​of the first impact dimension corresponding to all changes within the time window, and the quantified values ​​of the change execution risk dimension corresponding to all changes within the time window.

8. The method according to claim 7, characterized in that The quantifying of the plurality of overall associated change sets formed by all the changes included in the time window comprises: For each of the plurality of overall association change sets, executing: Determining weights of respective association links included in the overall association change set, wherein each association link is an association link formed between two different changes having an associated impact in the overall association change set; The sum of the weights of the associated links included in the overall association change set is determined as the quantization result corresponding to the overall association change set.

9. The method according to claim 1, characterized in that The method further comprises: The target risk value is displayed in a display interface; wherein the target risk value includes at least one of the following: The risk values ​​corresponding to the N changes respectively; The overall risk value corresponding to each time window within the preset period; The overall risk value of the preset time period; wherein the overall risk value of the preset time period is determined according to the overall risk values ​​corresponding to all time windows included in the preset time period.

10. A production planning and scheduling device, characterized in that: include: An acquisition module, used to acquire change information of N changes within a preset period, wherein the change information includes change basic characteristic information, change implementation step information, and change impact information, where N is a positive integer; A processing module, configured to perform risk quantitative assessment on the N changes from the dimensions of basic characteristics of the changes, impact of the changes, and execution risk of the changes according to the change information of the N changes, to obtain a target risk value; The scheduling module is used to schedule and manage the production plan within a preset time period according to the target risk value.

11. A computer device, characterized in that: include: A memory for storing program instructions; A processor, configured to call the program instructions stored in the memory, and execute the method according to any one of claims 1 to 9 according to the obtained program.

12. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores computer-executable instructions, and the computer-executable instructions are used to enable a computer to execute the method according to any one of claims 1 to 9.

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