Method and system for realizing refined control of full cost of operation and maintenance projects based on digitalization

Abstract

The present invention discloses a method and system for realizing refined control of the entire cost of operation and maintenance projects based on digitization. The present invention relates to the field of digital technology for operation and maintenance projects, and solves the problem that abnormal data needs to be manually identified in the process of digital management of cost data. The present invention classifies the cost data of different digital operation and maintenance projects, performs relevant numerical control and analysis on the data after different classifications, and performs relevant confirmation on the abnormal costs generated in each different project. The relevant abnormal cost data can be quickly and effectively identified for different operation and maintenance projects, thereby completing the refined control effect of operation and maintenance costs, achieving better data management effects, and facilitating relevant personnel to promptly understand the abnormal data that has occurred and perform relevant processing.

Description

Technical Field

[0001] The present invention relates to the technical field of digitalization of operation and maintenance projects, and specifically to a method and system for realizing refined control of the entire cost of operation and maintenance projects based on digitalization. Background Art

[0002] In recent years, in the application for innovation results of improving the management capacity of metallurgical enterprise management modernization, information management accounts for about 30% of the first and second class results of information management innovation. The further increase in the number of information management projects fully demonstrates that the new generation of information and digital technology is profoundly affecting all aspects of production, operation and management of steel enterprises. Some steel enterprises have responded quickly and actively integrated advanced information and digital technology with traditional production and operation, and achieved remarkable results. Among the innovation results of metallurgical enterprise management modernization in recent years, the proportion of first and second class results related to digitalization has continued to rise. The new generation of information technology and digital technology has developed rapidly, and has been continuously integrated into production and life, changing the traditional production and lifestyle, and constantly creating new industrial forms and business models. Many enterprises have accelerated the digital transformation and upgrading of the manufacturing industry.

[0003] Some steel companies have actively explored and made full use of advanced information and digital technologies such as 5G, big data, and artificial intelligence to carry out management innovation, such as exploring smart marketing management, intelligent quality management, integrated operations, building smart factories and smart mines, and accelerating the pace of digital transformation.

[0004] Nowadays, digital management has run through the entire process of enterprise development. Improving efficiency and reducing costs are the goals pursued by all enterprises, and digital transformation has become the focus of operating enterprises.

[0005] Realizing cost control of operation and maintenance projects and reducing operating costs are the foundation for all enterprises in the current context. In order to improve the efficiency of full cost control of operation projects, it is of great significance to combine digital management and realize refined control of the full cost of operation and maintenance projects. Summary of the invention

[0006] In view of the deficiencies in the prior art, the present invention provides a method and system for realizing refined control of the entire cost of operation and maintenance projects based on digitalization, which solves the problem that abnormal data needs to be manually identified during the digital management of cost data.

[0007] To achieve the above objectives, the present invention is implemented through the following technical solutions: a method for realizing refined control of the full cost of operation and maintenance projects based on digitalization, comprising the following steps:

[0008] Step 1: Collect several groups of project cost data generated within the set period, and classify the collected different types of project cost data, and classify the project cost data belonging to the same category into different management and control zones. The specific method is as follows:

[0009] S11, determining a set period T, where T is a preset value;

[0010] S12, classifying the several groups of project cost data collected within the set period T according to the set classification table, distinguishing the project cost data of different types one by one, and storing the classified project cost data of the same classification in the same control partition, wherein the classification table is a preset table;

[0011] Step 2: Perform numerical analysis on the project cost data managed in each control zone, prioritize sorting different cost values, determine the numerical sorting sequence, and then determine relatively concentrated values ​​from the numerical sorting sequence to determine the set of values ​​with the same characteristics. The specific sub-steps are:

[0012] S21, determining the cost values ​​from different project cost data, and sorting the confirmed cost value groups from small to large values ​​to determine the value sorting sequence. If there are identical cost values, they are randomly arranged in the front and back order;

[0013] S22, randomly select a set of cost values ​​C from the numerical sorting sequence i , whose cost value cannot be the first cost value or the last cost value in the numerical sorting sequence, where i represents the different cost values ​​selected. Based on the selected cost value C i , determine its variation range [C i -(Y1×B), C i +(Y1×B)], where Y1 is a preset value, where B represents a change stage, and B=1, 2, ..., n, when B is 1, it represents the first change stage, and when B is 2, it represents the second change stage;

[0014] Identify the number of cost values ​​G contained in the change interval corresponding to the first change stage, and then confirm the value length C of this change interval, where C is the specific length of the value range within the change interval, which is the value difference between the maximum and minimum values ​​of the change interval. Use C÷G=P to confirm the value density of this change stage, and compare P with the preset value Y2, where Y2 is the preset value:

[0015] If P≤Y2, then enter the second change phase to identify whether P of this change node still satisfies:

[0016] If P≤Y2, if it is satisfied, then enter the third change stage, and so on, until P>Y2 corresponding to the determined corresponding change stage, and then stop, and divide the cost values ​​included in the previous stage of the corresponding change stage into a set of values ​​with the same characteristics;

[0017] If P>Y2, the cost values ​​included in the first change node are divided into sets of values ​​with the same characteristics, and other cost values ​​are reselected for related processing, and the corresponding sets of values ​​with the same characteristics are determined;

[0018] If P>Y2, reselect other cost values ​​C i and perform such numerical processing;

[0019] S23. For each different cost value C i , confirm that it is different C i The corresponding numerical value set with the same characteristic is marked as the set with the largest number of values ​​in the numerical value set with the same characteristic. If there are multiple numerical value sets with the largest number of values ​​in the numerical value set with the same characteristic, the numerical value set with the same characteristic is randomly selected as the final set;

[0020] Step 3: Based on the same characteristic value set determined in the corresponding control zone, other cost values ​​that do not belong to the same characteristic value set in the control zone are judged as abnormal, and the abnormal cost value is determined. The specific sub-steps are:

[0021] S31. Determine the corresponding set of values ​​with the same characteristics in the control zone, mark other cost values ​​that do not belong to the same set of values ​​with the same characteristics in the corresponding control zone as pending values, and mark them as SZ k , where k represents different undetermined values;

[0022] S32, determine the mean of the set of numerical values ​​with the same characteristics and mark it as Jz, and set the undetermined value SZ k Compare with the mean Jz of the same characteristic value set: If |SZ k -Jz|<Y3, where Y3 is the preset standard value, and this undetermined value is calibrated as the abnormal cost value, otherwise, no calibration is performed;

[0023] Step 4: Based on the different abnormal cost values ​​determined in different set periods, determine the control zone to which the abnormal cost value belongs. If there are more than 10 groups of abnormal cost values ​​in the corresponding control zone, mark such control zone as an abnormal zone and display it.

[0024] Preferably, it includes:

[0025] The cost data collection and classification unit collects several groups of project cost data generated within a set period, and classifies the collected different types of project cost data, and classifies the project cost data belonging to the same classification into different control zones;

[0026] The value set determination unit performs a value analysis on the project cost data managed in each control zone, prioritizes the different cost values, determines the value sorting sequence, and then determines relatively concentrated values ​​from the value sorting sequence to determine the value set with the same characteristics;

[0027] The abnormal cost value determination unit determines the abnormal cost value based on the same characteristic value set determined in the corresponding control zone, and determines the abnormal cost value for other cost values ​​in the control zone that do not belong to the same characteristic value set;

[0028] The recording unit monitors the specific total number of abnormal cost values ​​that appear in different set periods. When the specific total number exceeds 10 groups, the corresponding control partition will be marked as an abnormal partition and displayed.

[0029] The present invention provides a method and system for realizing refined control of the full cost of operation and maintenance projects based on digitalization. Compared with the prior art, it has the following beneficial effects:

[0030] The present invention classifies the cost data of different digital operation and maintenance projects, performs relevant numerical control and analysis on the classified data, and confirms the abnormal costs generated in each different project. It can quickly and effectively identify the relevant abnormal cost data for different operation and maintenance projects, thereby completing the refined control effect of operation and maintenance costs, achieving better data management effects, and facilitating relevant personnel to timely understand the abnormal data that has occurred and perform relevant processing;

[0031] The full cost control method of operation and maintenance projects includes pre-sales control, project cost control management, cost statistics analysis, and cost budget rolling control. The full cost control system of operation and maintenance projects is based on the network function platform, user portal and full cost database of operation and maintenance projects. It creates multiple core function modules according to the enterprise's managed operating cost data, and constructs the core functions into multiple function platforms according to the enterprise's full cost management requirements. It builds a user portal according to the enterprise's business division of labor categories, sets user portal permissions by user responsibilities, and establishes a corresponding database based on the data of the core function modules; the full cost control system of operation and maintenance projects includes operation and maintenance project establishment management, team management, full cost budget management, full cost performance management, procurement application management, report management, project closure management and other functions. The present invention solves the existing method of cost control of operation and maintenance projects, and realizes the online refined control of costs in a digital way. BRIEF DESCRIPTION OF THE DRAWINGS

[0032] Figure 1 It is a schematic diagram of the process of the present invention;

[0033] Figure 2 It is a schematic diagram of the principle framework of the present invention. DETAILED DESCRIPTION

[0034] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0035] Example 1

[0036] See also Figure 1 , this application provides a method for realizing refined control of the full cost of operation and maintenance projects based on digitalization, including the following steps:

[0037] Step 1: Collect several groups of project cost data generated within a set period, and classify the collected different types of project cost data, and classify the project cost data belonging to the same category into different management and control zones. The specific method of classification is:

[0038] S11, determine a set period T, where T is a preset value, the specific value of which is determined by the operator based on experience, and is generally 30 days;

[0039] S12. Classify several groups of project cost data collected within the set period T according to the set classification table, distinguish project cost data belonging to different types one by one, and store the classified project cost data belonging to the same classification in the same type of control partition, wherein the classification table is a preset table, which is prepared in advance by the operator, and there are multiple different classifications in the classification table, each of which is also prepared in advance by the relevant operator, such as production cost, maintenance cost, equipment cost, energy medium cost, management fee, technical transformation cost and others, and each different project cost data has a related header, based on the corresponding header, the category to which the project cost data belongs can be quickly identified;

[0040] Step 2: Perform numerical analysis on the project cost data managed in each control zone, prioritize sorting different cost values, determine the numerical sorting sequence, and then determine relatively concentrated values ​​from the numerical sorting sequence to determine the same characteristic numerical set. For example, the project cost data includes the corresponding cost values, and the relevant values ​​for numerical analysis are the corresponding cost values. The specific sub-steps for determination are:

[0041] S21, determining the cost values ​​from different project cost data, and sorting the confirmed cost value groups from small to large values ​​to determine the value sorting sequence. If there are identical cost values, they are randomly arranged in the front and back order;

[0042] S22, randomly select a set of cost values ​​C from the numerical sorting sequence i , whose cost value cannot be the first cost value or the last cost value in the numerical sorting sequence, where i represents the different cost values ​​selected. Based on the selected cost value C i , determine its variation range [C i -(Y1×B), C i +(Y1×B)], where Y1 is a preset value, which is prepared in advance by relevant operators based on experience, where B represents the change stage, and B=1, 2, ..., n, when B is 1, it represents the first change stage, and when B is 2, it represents the second change stage;

[0043] Identify the number of cost values ​​G contained in the change interval corresponding to the first change stage, and then confirm the value length C of this change interval, where C is the specific length of the value range within the change interval, which is the value difference between the maximum and minimum values ​​of the change interval. Use C÷G=P to confirm the value density of this change stage, and compare P with the preset value Y2, where Y2 is a preset value, and its specific value is determined by the operator based on experience:

[0044] If P≤Y2, then enter the second change phase to identify whether P of this change node still satisfies:

[0045] If P≤Y2, if it is satisfied, then enter the third change stage, and so on, until P>Y2 corresponding to the determined corresponding change stage, and then stop, and divide the cost values ​​included in the previous stage of the corresponding change stage into a set of values ​​with the same characteristics;

[0046] If P>Y2, the cost values ​​included in the first change node are divided into sets of values ​​with the same characteristics, and other cost values ​​are reselected for related processing, and the corresponding sets of values ​​with the same characteristics are determined;

[0047] If P>Y2, reselect other cost values ​​C i and perform such numerical processing;

[0048] S23. For each different cost value C i , confirm that it is different C i The corresponding numerical set with the same characteristics is marked as the set with the largest number of values ​​in the numerical set with the same characteristics as the final numerical set with the same characteristics. If there are multiple sets with the largest number of values, they are randomly selected;

[0049] Specifically, the content here is explained with an example: the proposed numerical sorting sequence after sorting is: 10, 12, 14, 15, 16, 17, 19, 20, 22, 24, where Y1 takes the value of 1, and 14 is selected as the selected cost value. The change interval of the first stage is confirmed, and its B is 1, and Y1 is also 1, then the determined change interval of the first stage is [13, 15], and the values ​​belonging to 13 and 15 are 14 and 15, so it contains two groups of values. At this time, the confirmed G is 2, and the value length of this change interval is 2, then the determined P=C(2)÷G(2)=1, where Y2 takes the value of 1, then P=1, and the second stage processing process is executed:

[0050] In the second stage, B takes the value of 2, so the change interval of the second stage is [12, 16], the length of the interval range C is 4, and the number of values ​​contained in this interval is also 4, so the determined P = 1, then the evaluation conditions are met, and the processing process of the third stage is executed:

[0051] In the third stage, B takes the value 3, and the confirmed change interval of the third stage is [11, 17]. The range length of the interval is 6, and the values ​​included are 12, 14, 15, 16, and 17, of which there are only 5. Therefore, the confirmed P = 6 ÷ 5 > 1, so the third stage does not meet the corresponding evaluation process, and the values ​​included in the second stage belong to the same characteristic value set {12, 14, 15, 16}

[0052] After 14 is selected, 15 is selected as the cost value for related processing, and the corresponding value set with the same characteristics is confirmed. Similarly, other values ​​are selected one by one, and the value sets with the same characteristics corresponding to different values ​​are confirmed one by one.

[0053] Step 3: Based on the same characteristic value set determined in the corresponding control zone, other cost values ​​that do not belong to the same characteristic value set in the control zone are judged as abnormal, and the abnormal cost value is determined, wherein the specific sub-steps of determination are:

[0054] S31. Determine the corresponding set of values ​​with the same characteristics in the control zone, mark other cost values ​​that do not belong to the same set of values ​​with the same characteristics in the corresponding control zone as pending values, and mark them as SZ k , where k represents different undetermined values;

[0055] S32, determine the mean of the set of numerical values ​​with the same characteristics and mark it as Jz, and set the undetermined value SZ k Compare with the mean Jz of the same characteristic value set: If |SZ k-Jz|<Y3, where Y3 is a preset standard value, which is prepared in advance by relevant operators. This undetermined value is calibrated as the abnormal cost value. Otherwise, no calibration is performed;

[0056] Step 4: Based on the different abnormal cost values ​​determined in different set periods, determine the control partition (that is, different projects) to which the abnormal cost value belongs. If there are more than 10 groups of abnormal cost values ​​in the corresponding control partition, mark such control partition as an abnormal partition and display it.

[0057] Specifically, the corresponding items have calibrated abnormal cost values ​​in different set periods, and the abnormal cost values ​​exceed 10 groups in different set periods, that is, there are two groups in some set periods, and there are 3 groups, 4 groups and 6 groups respectively in other set periods. Then there are relevant problems with the cost values ​​of such items, and it is necessary to calibrate and display the abnormal items.

[0058] Example 2

[0059] See also Figure 2 , based on digitalization, a refined management and control system for the entire cost of operation and maintenance projects is implemented, including:

[0060] The cost data collection and classification unit collects several groups of project cost data generated within a set period, and classifies the collected different types of project cost data, and classifies the project cost data belonging to the same classification into different control zones;

[0061] The value set determination unit performs a value analysis on the project cost data managed in each control zone, prioritizes the different cost values, determines the value sorting sequence, and then determines relatively concentrated values ​​from the value sorting sequence to determine the value set with the same characteristics;

[0062] The abnormal cost value determination unit determines the abnormal cost value based on the same characteristic value set determined in the corresponding control zone, and determines the abnormal cost value for other cost values ​​in the control zone that do not belong to the same characteristic value set;

[0063] The recording unit monitors the specific total number of abnormal cost values ​​that appear in different set periods. When the specific total number exceeds 10 groups, the corresponding control partition will be marked as an abnormal partition and displayed.

[0064] The system is based on a network function platform, a user portal and a full-cost database for operation and maintenance projects. It creates multiple core function modules based on the enterprise's managed operating cost data, constructs core functions into multiple function platforms based on the enterprise's full-cost management requirements, builds a user portal based on the enterprise's business division of labor categories, sets user portal permissions based on user responsibilities, and establishes a corresponding database based on the data of the core function modules; the full-cost management and control system for operation and maintenance projects is characterized in that the system includes functions such as operation and maintenance project establishment management, team management, full-cost budget management, full-cost performance management, procurement application management, report management, and project closure management; the procurement application management is characterized in that the procurement application fee control is subject to the full-cost budget limit, and the procurement expenses incurred shall not exceed the cost budget; the report management is characterized in that it includes full-cost budget reports, full-cost performance reports, and full-cost analysis reports.

[0065] Example 3

[0066] The specific implementation process of this embodiment includes the entire implementation process of the above two groups of embodiments.

[0067] Some of the data in the above formulas are dimensionless and numerically calculated. Meanwhile, the contents not described in detail in this specification belong to the prior art known to those skilled in the art.

[0068] The above embodiments are only used to illustrate the technical method of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical method of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical method of the present invention.

Claims

1. A method for realizing refined control of the full cost of operation and maintenance projects based on digitalization, characterized in that: The following steps are involved: Step 1: Collect several groups of project cost data generated within a set period, classify different types of collected project cost data, and classify project cost data belonging to the same category into different control zones; Step 2: Perform numerical analysis on the project cost data managed in each control zone, prioritize sorting different cost values, determine the numerical sorting sequence, and then determine relatively concentrated values ​​from the numerical sorting sequence to determine a set of values ​​with the same characteristics; Step 3: Based on the same characteristic value set determined in the corresponding control zone, other cost values ​​in the control zone that do not belong to the same characteristic value set are judged as abnormal, and the abnormal cost value is determined; Step 4: Based on the different abnormal cost values ​​determined in different set periods, determine the control zone to which the abnormal cost value belongs. If there are more than 10 groups of abnormal cost values ​​in the corresponding control zone, mark such control zone as an abnormal zone and display it.

2. The method for realizing refined control of the full cost of operation and maintenance projects based on digitalization according to claim 1 is characterized in that: In step 1, the specific method of classifying the collected project cost data is as follows: S11, determining a set period T, where T is a preset value; S12. Classify the several groups of project cost data collected within the set period T according to the set classification table, distinguish the project cost data of different types one by one, and store the project cost data of the same classification after classification into the same type of management and control partition, where the classification table is a preset table.

3. The method for realizing refined control of the full cost of operation and maintenance projects based on digitalization according to claim 2 is characterized in that: In step 2, the specific sub-steps for determining the same characteristic value set are: S21, determining the cost values ​​from different project cost data, and sorting the confirmed cost value groups from small to large values ​​to determine the value sorting sequence. If there are identical cost values, they are randomly arranged in the front and back order; S22, randomly select a set of cost values ​​C from the numerical sorting sequence i , whose cost value cannot be the first cost value or the last cost value in the numerical sorting sequence, where i represents the different cost values ​​selected. Based on the selected cost value C i , determine its variation range [C i -(Y1×B), C i +(Y1×B)], where Y1 is a preset value, where B represents a change stage, and B=1, 2, ..., n, when B is 1, it represents the first change stage, and when B is 2, it represents the second change stage; Identify the number of cost values ​​G contained in the change interval corresponding to the first change stage, and then confirm the value length C of this change interval, where C is the specific length of the value range within the change interval, which is the value difference between the maximum and minimum values ​​of the change interval. Use C÷G=P to confirm the value density of this change stage, and compare P with the preset value Y2, where Y2 is the preset value: If P≤Y2, then enter the second change phase to identify whether P of this change node still satisfies: If P≤Y2, if it is satisfied, then enter the third change stage, and so on, until P>Y2 corresponding to the determined corresponding change stage, and then stop, and divide the cost values ​​included in the previous stage of the corresponding change stage into a set of values ​​with the same characteristics; If P>Y2, the cost values ​​included in the first change node are divided into sets of values ​​with the same characteristics, and other cost values ​​are reselected for related processing, and the corresponding sets of values ​​with the same characteristics are determined; If P>Y2, reselect other cost values ​​C i and perform such numerical processing; S23. For each different cost value C i , confirm that it is different C i The corresponding same-feature numerical value set is marked as the set with the largest number of values ​​within the same-feature numerical value set as the final determined same-feature numerical value set.

4. The method for realizing refined control of the full cost of operation and maintenance projects based on digitalization according to claim 3 is characterized in that: In S23, if there are multiple sets of numerical values ​​with the largest number of values ​​and the same characteristic, the set of numerical values ​​with the same characteristic is randomly selected as the final determined set.

5. The method for realizing refined control of the full cost of operation and maintenance projects based on digitalization according to claim 3 is characterized in that: In step 3, the specific sub-steps for determining the abnormal cost value are: S31. Determine the corresponding set of values ​​with the same characteristics in the control zone, mark other cost values ​​that do not belong to the same set of values ​​with the same characteristics in the corresponding control zone as pending values, and mark them as SZ k , where k represents different undetermined values; S32, determine the mean of the set of numerical values ​​with the same characteristics and mark it as Jz, and set the undetermined value SZ k Compare with the mean Jz of the same characteristic value set: If |SZ k -Jz|<Y3, where Y3 is the preset standard value, and this undetermined value is calibrated as the abnormal cost value. Otherwise, no calibration is performed.

6. A system for realizing refined control of the full cost of operation and maintenance projects based on digitalization, the control system is operated according to the method for realizing refined control of the full cost of operation and maintenance projects based on digitalization according to any one of claims 1 to 5, characterized in that: include: The cost data collection and classification unit collects several groups of project cost data generated within a set period, and classifies the collected different types of project cost data, and classifies the project cost data belonging to the same classification into different control zones; The value set determination unit performs a value analysis on the project cost data managed in each control zone, prioritizes the different cost values, determines the value sorting sequence, and then determines relatively concentrated values ​​from the value sorting sequence to determine the value set with the same characteristics; The abnormal cost value determination unit determines the abnormal cost value based on the same characteristic value set determined in the corresponding control zone, and determines the abnormal cost value for other cost values ​​in the control zone that do not belong to the same characteristic value set; The recording unit monitors the specific total number of abnormal cost values ​​that appear in different set periods. When the specific total number exceeds 10 groups, the corresponding control partition will be marked as an abnormal partition and displayed.

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