Standardized Collaboration System and Method Based on the Whole Project Life Cycle

Abstract

The present invention discloses a standardized collaborative system and method based on the entire project life cycle, which relates to the technical field of project management. The present invention obtains the text data of real-time work orders by using text recognition technology; extracts historical projects from the project management platform to form a historical project set; extracts and marks the project feature data of each historical project; calculates the correlation degree value between the project feature data of the historical projects in the project feature set and the feature data of the first project; analyzes the association relationship between the historical project and the first project; constructs a project implementation fitting model according to the text data of the historical work orders; analyzes the task implementation situation corresponding to the work orders being implemented by the first project according to the project implementation fitting model, extracts abnormal work orders to generate a list of abnormal work orders, and sends them to the administrator. The accuracy of model fitting is improved, and the operation efficiency of the system is improved; the automated management of the entire project life cycle is realized, and the engineering implementation efficiency is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of project management, and specifically to a standardized collaborative system and method based on the full life cycle of a project. Background Art

[0002] With the rapid development of society and the continuous growth of the economy in our country, there have been obvious changes in people's living standards. Therefore, the demand for construction has also increased unprecedentedly. In order to better serve the needs of social development, it is necessary to build high-quality projects. Full life cycle management is a new concept that emerged in recent years. In the whole management process, effective technologies and organizational measures should be used to complete the full life cycle management, and optimize management in the true sense to achieve the goal of maximizing benefits.

[0003] However, in the existing project management, the project manager conducts long-term research on the project, and then generates specific management requirements and measures for the project; based on the management concept of a single person, there are prone to thinking loopholes, causing unnecessary losses. When there are multiple work orders implemented simultaneously in a project, it is easy to be ignored, reducing the overall project implementation efficiency.

[0004] Therefore, the present invention discloses a standardized collaborative system and method based on the full life cycle of a project to solve the above problems. Summary of the Invention

[0005] The purpose of the present invention is to provide a standardized collaborative system and method based on the full life cycle of a project to solve the problems raised in the prior art.

[0006] To achieve the above purpose, the present invention provides the following technical solution: A standardized collaborative method based on the full life cycle of a project, the method includes the following steps:

[0007] S1: Use text recognition technology to obtain the text data of real-time work orders; extract historical projects from the project management platform to form a historical project set; extract and mark the project feature data of each historical project to form a project feature set;

[0008] S2: Extract the feature data of the first project, and calculate the correlation degree value between the project feature data of the historical projects in the project feature set and the feature data of the first project; according to the correlation degree value, analyze the correlation relationship between the historical projects and the first project to form an associated project set;

[0009] S3: Extract the text data of the historical work orders of the historical projects in the associated project set, and construct a project implementation fitting model according to the text data of the historical work orders;

[0010] S4: Analyze the task implementation status of the work orders corresponding to the first project being implemented according to the project implementation fitting model, calculate the abnormality degree value of the work orders, identify and mark the abnormal work orders, extract the abnormal work orders to generate a list of abnormal work orders, and send it to the administrator.

[0011] According to the above solution, in S1, it includes the following content:

[0012] S101: Use text recognition technology to obtain the text data of real-time work orders. The text data includes the work order task name, the project name corresponding to the work order, the pre-consumed resources of the work order, the estimated engineering quantity of the work order, and the pre-consumed duration of the work order; Search for the project corresponding to the real-time work order in the project management platform, record the project corresponding to the real-time work order as the first project P0, and extract the project type of the first project.

[0013] S102: Extract historical projects with the same project type as the first project from the project management platform to form a historical project set; Number the historical projects in the historical project set uniformly, and record the i-th historical project as P i ; Extract the project feature data corresponding to each historical project in the historical project set, and generate a project feature set, denoted as PC = {PC i |i ∈ [1, I]}; where PC i represents the project feature data set of the i-th historical project P i , and I represents the total number of historical projects in the historical project set; The project feature data includes the total project duration, the total amount of resources, and the total amount of engineering; The total amount of resources includes the total cost, the total amount of materials, and the total amount of manpower.

[0014] Extract historical projects with the same project type as the first project from the project management platform to form a historical project set; Using the data of historical projects of the same type as the first project for subsequent analysis can more accurately analyze the subsequent implementation status of the first project and improve the accuracy of the system.

[0015] According to the above solution, in S2, it includes the following content:

[0016] S201: Extract the feature data of the first project, and record the feature data of the first project as PC0; According to the feature data of the first project and the project feature data of the historical projects in the historical project set, calculate the feature data correlation degree value:

[0017] FDA(0→i) = α1×(TT0 - TT i ) + α2×(TR0 - TR i ) + α3×(TQ0 - TQ i );

[0018] Among them, FDA(0→i) represents the degree of association value of feature data between the first project P0 and the historical project PC i ; α1, α2, and α3 represent the feature data correlation coefficients, and the feature data correlation coefficients are preset constants; TT0 represents the total duration of the first project P0; TT i represents the total duration of the historical project PC i ; TR0 represents the total amount of resources of the first project P0; TR i represents the total amount of resources of the historical project PC i ; TQ0 represents the total amount of engineering of the first project P0; TQ i represents the total amount of engineering of the historical project PC i ; The degree of association value of feature data is negative, zero, or positive;

[0019] S202: Set a threshold A for the degree of association value of feature data, where A is greater than zero; if the degree of association value of feature data FDA(0→i) between the first project P0 and the historical project PC i ∈[-A, A], it indicates that there is an association relationship between the first project P0 and the historical project PC i ; if the degree of association value of feature data FDA(0→i) between the first project P0 and the historical project PC i ∈(-∞, -A) ∩ (A, +∞), it indicates that there is no association relationship between the first project P0 and the historical project PC i ; Extract all historical projects that have an association relationship with the first project P0 to generate an associated project set.

[0020] Calculating the degree of association between the first project and the historical projects in the historical project set can more effectively narrow down the selection range of historical projects, select historical projects similar to the first project for model construction, further improve the accuracy of model fitting, reduce the computational amount of the system, and improve the operation efficiency of the system;

[0021] According to the above solution, in S3, it includes the following content:

[0022] S301: Extract all historical work orders of each historical project in the associated project set, arrange the historical work orders of the same historical project in the order of the start generation time, extract the task implementation situation of the historical work orders, and the task implementation situation includes the change of the remaining amount of work order resources and the remaining amount of work order engineering over the remaining time of the work order; generate the task implementation situation of the historical project according to the task implementation situation of all historical work orders; the jth historical project P in the associated project set jThe task implementation status is combined with the time variable and arranged in the order of the remaining time of the project to generate an associated project implementation set; the associated project implementation set includes an associated project resource implementation set and an associated project engineering implementation set; the associated project resource implementation set is denoted as PS j ={(ST j , SR j )|j ∈ [1, J]}, where ST j is the corresponding moment of the remaining project resource SR j ; J represents the total number of historical projects in the associated project set, J < I;

[0023] Extract the task implementation status of historical work orders, convert it into the task implementation status of historical projects according to the time nodes of the work orders, and perform the conversion of the time span, providing data support for subsequent model fitting;

[0024] S302: Use the associated project resource implementation set to establish an associated project resource implementation fitting model: y j 1 = B j 1 × x j 1 + C j 1 ; where B j 1 and C j 1 represent the fitting coefficients, x j 1 represents the independent variable of time, y j 1 represents the dependent variable of the remaining associated project resources. Use the least squares method to calculate and solve B j 1 and C j 1 in the project resource implementation fitting model; use the associated project engineering implementation set in the same way to establish an associated project engineering implementation fitting model;

[0025] S303: Construct the project resource implementation fitting model of the first project according to all associated project resource implementation fitting models: y = B × x + C; where B and C represent the fitting coefficients, x represents the independent variable of time, and y represents the dependent variable of the remaining project resources of the first project; the fitting coefficient B is equal to the average value of the fitting coefficients in the set {B1 1 , B2 1 , …, B J 1}; the fitting coefficient C is equal to the average value of the fitting coefficients in the set {C1 1 , C2 1 , …, C J 1The average value of the fitting coefficients; In the same way, a project implementation fitting model for the first project is established.

[0026] Using multiple related projects to participate in the construction of the model can avoid the errors caused by single-project simulation and further improve the accuracy of model fitting.

[0027] According to the above solution, in S4, it includes the following content:

[0028] S401: Extract the work orders being implemented for the first project, obtain the task implementation status at the current moment of the work orders being implemented, and analyze the remaining project resources and remaining project work according to the remaining work order resources and remaining work order work.

[0029] S402: Substitute the current moment into the project resource implementation fitting model and project work implementation fitting model of the first project to obtain the remaining fitting project resources and remaining fitting project work of the first project respectively.

[0030] S403: Calculate the work order anomaly degree value AD:

[0031] AD = (SR ÷ NSR) × (SG ÷ NSG);

[0032] Where SR represents the remaining project resources, NSR represents the remaining fitting project resources; SG represents the remaining project work, and NSG represents the remaining fitting project work.

[0033] Set a threshold for the work order anomaly degree value, mark the work orders being implemented with a work order anomaly degree value greater than the threshold as abnormal work orders, mark and extract all abnormal work orders to generate an abnormal work order list; calculate the proportion of abnormal work orders in the work orders being implemented. If the proportion is greater than the proportion threshold, mark the first project; if the proportion is not greater than the proportion threshold, no processing is done; send the abnormal work order list to the administrator.

[0034] Generating an abnormal work order list for the work orders with anomalies and sending the abnormal work order list to the administrator realizes the automated management of the entire project life cycle; it can discover the abnormal list as early as possible, remind the administrator to make adjustments, and effectively ensure the timeliness of the project.

[0035] Another aspect of the present application provides a standardized collaboration system based on the entire project life cycle. The system is applied to implement the above-mentioned standardized collaboration method based on the entire project life cycle. The system includes a data identification and acquisition module, a feature analysis and association module, a model construction module, and an anomaly analysis and prompt module.

[0036] The data recognition and acquisition module is used to obtain the text data of real-time work orders by using text recognition technology; extract historical projects from the project management platform to form a historical project set; extract and mark the project feature data of each historical project to form a project feature set;

[0037] The feature analysis and association module is used to extract the feature data of the first project, calculate the association degree value between the project feature data of the historical projects in the project feature set and the feature data of the first project; analyze the association relationship between the historical projects and the first project according to the association degree value to form an associated project set;

[0038] The model construction module is used to extract the text data of the historical work orders of the historical projects in the associated project set and construct a project implementation fitting model according to the text data of the historical work orders;

[0039] The anomaly analysis and prompt module analyzes the task implementation situation corresponding to the work order of the first project being implemented according to the project implementation fitting model, calculates the anomaly degree value of the work order, identifies and marks the abnormal work orders, extracts the abnormal work orders to generate an abnormal work order list, and sends it to the administrator.

[0040] According to the above solution, the data recognition and acquisition module includes a work order data recognition unit and a feature extraction unit;

[0041] The work order data recognition unit obtains the text data of real-time work orders by using text recognition technology. The text data includes the work order task name, the project name corresponding to the work order, the pre-consumed resources of the work order, the pre-estimated engineering quantity of the work order, and the pre-consumed duration of the work order; search for the project corresponding to the real-time work order in the project management platform, record the project corresponding to the real-time work order as the first project, and extract the project type of the first project;

[0042] The feature extraction unit extracts historical projects with the same project type as the first project from the project management platform to form a historical project set; uniformly numbers the historical projects in the historical project set, extracts the project feature data corresponding to each historical project in the historical project set, and generates a project feature set. The project feature data includes the total project duration, the total resources, and the total engineering quantity; the total resources include the total cost, the total materials, and the total manpower.

[0043] According to the above solution, the feature analysis and association module includes an association degree value calculation unit and an association relationship analysis unit;

[0044] The association degree value calculation unit is used to extract the feature data of the first project and record the feature data of the first project as PC0; calculate the feature data association degree value according to the feature data of the first project and the project feature data of the historical projects in the historical project set. The feature data association degree value is negative, zero, or positive;

[0045] The associated relationship analysis unit is used to set a threshold A for the degree of association value of feature data, where A is greater than zero; if the degree of association value FDA(0→i) of the feature data between the first project P0 and the historical project PC i is in the range of [-A, A], it indicates that there is an associated relationship between the first project P0 and the historical project PC i ; if the degree of association value FDA(0→i) of the feature data between the first project P0 and the historical project PC i is in the range of (-∞, -A) ∩ (A, +∞), it indicates that there is no associated relationship between the first project P0 and the historical project PC i ; all historical projects associated with the first project P0 are extracted to generate an associated project set.

[0046] According to the above solution, the model construction module includes a task implementation analysis unit and a model fitting unit;

[0047] The task implementation analysis unit is used to extract all historical work orders of each historical project in the associated project set, arrange the historical work orders of the same historical project in the order of the start generation time, extract the task implementation status of the historical work orders, and the task implementation status includes the changes in the remaining work order resources and the remaining work order projects over the remaining work order time; generate the task implementation status of the historical project according to the task implementation status of all historical work orders; combine the task implementation status of the jth historical project P j in the associated project set with the time variable and arrange them in the order of the remaining project time to generate an associated project implementation set; the associated project implementation set includes an associated project resource implementation set and an associated project project implementation set;

[0048] The model fitting unit is used to establish an associated project resource implementation fitting model by using the associated project resource implementation set; establish an associated project project implementation fitting model by using the associated project project implementation set; construct a project resource implementation fitting model of the first project according to all associated project resource implementation fitting models; construct a project project implementation fitting model of the first project according to all associated project project implementation fitting models.

[0049] According to the above solution, the abnormal analysis and prompt module includes an implemented work order analysis unit and an abnormal work order processing unit;

[0050] The implemented work order analysis unit is used to extract the work orders being implemented for the first project, obtain the task implementation status at the current moment of the work orders being implemented, and analyze the remaining project resources and the remaining project projects based on the remaining work order resources and the remaining work order projects; substitute the current moment into the project resource implementation fitting model and the project project implementation fitting model of the first project to obtain the fitting remaining project resources and the fitting remaining project projects of the first project;

[0051] The abnormal work order processing unit is used to calculate the abnormal degree value of the work order; set a threshold for the abnormal degree value of the work order, record the work orders being implemented with the abnormal degree value greater than the threshold as abnormal work orders, mark and extract all abnormal work orders, and generate a list of abnormal work orders; calculate the proportion of abnormal work orders in the work orders being implemented. If the proportion is greater than the proportion threshold, mark the first project; if the proportion is not greater than the proportion threshold, no processing is performed; send the list of abnormal work orders to the administrator.

[0052] Compared with the prior art, the beneficial effects of the present invention are as follows: Historical projects with the same project type as the first project are extracted from the project management platform to form a set of historical projects; using the data of historical projects of the same type as the first project for subsequent analysis can more accurately analyze the subsequent implementation situation of the first project and improve the accuracy of the system; calculating the correlation degree between the first project and the historical projects in the set of historical projects can more effectively narrow the selection range of historical projects, select similar historical projects to the first project for model construction, further improve the accuracy of model fitting, reduce the calculation amount of the system, and improve the operation efficiency of the system; extract the task implementation situation of historical work orders, convert it into the task implementation situation of historical projects according to the time nodes of the work orders, and perform the conversion of the time span, providing data support for subsequent model fitting; using multiple associated projects to participate in the construction of the model can avoid errors caused by single-project simulation and further improve the accuracy of model fitting; generate a list of abnormal work orders for the work orders with abnormalities, and send the list of abnormal work orders to the administrator, realizing the automated management of the entire project life cycle; can discover the abnormal list as early as possible, remind the administrator to make adjustments, effectively guarantee the timeliness of the project, and improve the engineering implementation efficiency. Description of the Drawings

[0053] The drawings are used to provide a further understanding of the present invention, and constitute a part of the specification. They are used together with the embodiments of the present invention to explain the present invention, and do not constitute a limitation to the present invention. In the drawings:

[0054] Figure 1 It is a schematic flow chart of the standardized collaboration method based on the entire project life cycle of the present invention;

[0055] Figure 2 It is a schematic structural diagram of the standardized collaboration system based on the entire project life cycle of the present invention. Detailed Embodiments

[0056] The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0057] Please refer to Figure 1 , the present invention provides a technical solution: a standardized collaboration method based on the entire project life cycle, and the method includes the following steps:

[0058] S1: Obtain the text data of the real-time work order by using text recognition technology; extract historical projects from the project management platform to form a historical project set; extract and mark the project feature data of each historical project to form a project feature set;

[0059] In S1, it includes the following content:

[0060] S101: Obtain the text data of the real-time work order by using text recognition technology. The text data includes the work order task name, the project name corresponding to the work order, the pre-consumed resources of the work order, the estimated engineering quantity of the work order, and the pre-consumed duration of the work order; search for the project corresponding to the real-time work order in the project management platform, denote the project corresponding to the real-time work order as the first project P0, and extract the project type of the first project;

[0061] S102: Extract historical projects with the same project type as the first project from the project management platform to form a historical project set; uniformly number the historical projects in the historical project set, and denote the i-th historical project as P i ; extract the project feature data corresponding to each historical project in the historical project set and generate a project feature set, denoted as PC = {PC i |i ∈ [1, I]}; where PC i represents the project feature data set of the i-th historical project P i , I represents the total number of historical projects in the historical project set; the project feature data includes the total project duration, the total amount of resources, and the total amount of engineering; the total amount of resources includes the total cost, the total amount of materials, and the total amount of manpower.

[0062] Embodiment 1: In this embodiment, the calculation formula for the total amount of resources is as follows:

[0063] TR i = D1 × TC i + D2 × TAM i + D3 × TM i ;

[0064] Among them, D1, D2, and D3 represent resource coefficients, and the resource coefficients are preset constants; TC i represents the total cost; TAM i represents the total amount of materials; TM i represents the total amount of human resources;

[0065] S2: Extract the feature data of the first project, calculate the correlation degree value between the project feature data of the historical projects in the project feature set and the feature data of the first project; according to the correlation degree value, analyze the correlation relationship between the historical project and the first project, and form a set of associated projects;

[0066] In S2, the following contents are included:

[0067] S201: Extract the feature data of the first project, and record the feature data of the first project as PC0; according to the feature data of the first project and the project feature data of the historical projects in the historical project set, calculate the feature data correlation degree value:

[0068] FDA(0→i) = α1×(TT0 - TT i ) + α2×(TR0 - TR i ) + α3×(TQ0 - TQ i );

[0069] Among them, FDA(0→i) represents the feature data correlation degree value between the first project P0 and the historical project PC i ; α1, α2, and α3 represent feature data correlation coefficients, and the feature data correlation coefficients are preset constants; TT0 represents the total project duration of the first project P0; TT i represents the total project duration of the historical project PC i ; TR0 represents the total amount of resources of the first project P0; TR i represents the total amount of resources of the historical project PC i ; TQ0 represents the total amount of engineering of the first project P0; TQ i represents the total amount of engineering of the historical project PC i ; the feature data correlation degree value is negative, zero, or positive;

[0070] S202: Set a threshold A for the feature data correlation degree value, and A is greater than zero; if the feature data correlation degree value FDA(0→i) between the first project P0 and the historical project PC i ∈[-A, A], it indicates that there is a correlation relationship between the first project P0 and the historical project PC i ; if the feature data correlation degree value FDA(0→i) between the first project P0 and the historical project PC i ∈(-∞, -A) ∩ (A, +∞), it indicates that the first project P0 and the historical project PCi There is no association relationship; extract all historical items that have an association relationship with the first item P0, and generate an associated item set.

[0071] S3: Extract the text data of the historical work orders of the historical items in the associated item set, and construct a project implementation fitting model based on the text data of the historical work orders;

[0072] In S3, it includes the following content:

[0073] S301: Extract all historical work orders of each historical item in the associated item set, arrange the historical work orders of the same historical item in the order of the start generation time, and extract the task implementation status of the historical work orders. The task implementation status includes the situation of the remaining work order resources and the remaining work order project quantity changing with the remaining work order time; generate the task implementation status of the historical item based on the task implementation status of all historical work orders; combine the task implementation status of the j-th historical item P j in the associated item set with the time variable, and arrange it in the order of the remaining project time to generate an associated project implementation set; the associated project implementation set includes an associated project resource implementation set and an associated project engineering implementation set; denote the associated project resource implementation set as PS j ={(ST j , SR j )|j∈[1, J]}, where ST j is the corresponding moment of the remaining project resource SR j ; J represents the total number of historical items in the associated item set, and J < I;

[0074] S302: Use the associated project resource implementation set to establish an associated project resource implementation fitting model: y j 1 =B j 1 ×x j 1 +C j 1 ; where B j 1 and C j 1 represent the fitting coefficients, x j 1 represents the independent variable of time, y j 1 represents the dependent variable of the remaining associated project resources, and use the least squares method to calculate and solve B j 1 and C j 1 in the project resource implementation fitting model; use the associated project engineering implementation set in the same way to establish an associated project engineering implementation fitting model;

[0075] S303: Implement the fitting model for the project resources of the first project according to all associated project resources: y = B × x + C; where B and C represent fitting coefficients, x represents the independent variable of time, and y represents the dependent variable of the remaining project resources of the first project; the fitting coefficient B is equal to the average value of the fitting coefficients in the set {B1 1 , B2 1 , …, B J 1}; the fitting coefficient C is equal to the average value of the fitting coefficients in the set {C1 1 , C2 1 , …, C J 1}; in the same way, establish the fitting model for the project implementation of the first project.

[0076] S4: Analyze the task implementation situation corresponding to the work orders being implemented for the first project according to the project implementation fitting model, calculate the abnormality degree value of the work orders, identify and mark the abnormal work orders, extract the abnormal work orders to generate a list of abnormal work orders, and send it to the administrator.

[0077] In S4, it includes the following content:

[0078] S401: Extract the work orders being implemented for the first project, obtain the task implementation situation at the current moment of the work orders being implemented, and analyze the remaining project resources and the remaining project engineering quantity based on the remaining work order resources and the remaining work order engineering quantity;

[0079] S402: Substitute the current moment into the project resource implementation fitting model and the project engineering implementation fitting model of the first project to obtain the remaining fitting project resources and the remaining fitting project engineering quantity of the first project respectively;

[0080] S403: Calculate the work order abnormality degree value AD:

[0081] AD = (SR ÷ NSR) × (SG ÷ NSG);

[0082] where SR represents the remaining project resources, NSR represents the remaining fitting project resources; SG represents the remaining project engineering quantity, NSG represents the remaining fitting project engineering quantity;

[0083] Example 2: In this example, SR is 15, NSR is 10; SG is 12, NSG is 10;

[0084] Therefore, AD = (SR ÷ NSR) × (SG ÷ NSG) = (15 ÷ 10) × (12 ÷ 10) = 1.8;

[0085] Set the threshold value of the work order exception degree to 1.5; therefore, the work order being implemented in this embodiment is an abnormal work order.

[0086] Mark and extract all abnormal work orders to generate a list of abnormal work orders; calculate the proportion of abnormal work orders in the work orders being implemented. If the proportion is greater than the proportion threshold, mark the first project; if the proportion is not greater than the proportion threshold, no processing is performed; send the list of abnormal work orders to the administrator.

[0087] Please refer to Figure 2 , the present invention provides a technical solution: in another aspect of the present application, a standardized collaboration system based on the entire project life cycle is provided. The system is applied to implement the above-mentioned standardized collaboration method based on the entire project life cycle. The system includes a data identification and acquisition module, a feature analysis and association module, a model construction module, and an abnormal analysis and prompt module;

[0088] The data identification and acquisition module is used to obtain the text data of real-time work orders by using text recognition technology; extract historical projects from the project management platform to form a set of historical projects; extract and mark the project feature data of each historical project to form a set of project feature data;

[0089] The feature analysis and association module is used to extract the feature data of the first project, calculate the association degree value between the project feature data of the historical projects in the project feature set and the feature data of the first project; according to the association degree value, analyze the association relationship between the historical projects and the first project to form a set of associated projects;

[0090] The model construction module is used to extract the text data of the historical work orders of the historical projects in the set of associated projects, and construct a project implementation fitting model according to the text data of the historical work orders;

[0091] The abnormal analysis and prompt module analyzes the task implementation situation corresponding to the work orders being implemented for the first project according to the project implementation fitting model, calculates the abnormal degree value of the work orders, identifies and marks the abnormal work orders, extracts the abnormal work orders to generate a list of abnormal work orders, and sends it to the administrator.

[0092] The data identification and acquisition module includes a work order data identification unit and a feature extraction unit;

[0093] The work order data identification unit obtains the text data of real-time work orders by using text recognition technology. The text data includes the work order task name, the project name corresponding to the work order, the pre-consumed resources of the work order, the estimated engineering quantity of the work order, and the pre-consumed duration of the work order; search for the project corresponding to the real-time work order in the project management platform, record the project corresponding to the real-time work order as the first project, and extract the project type of the first project;

[0094] The feature extraction unit extracts historical projects with the same project type as the first project from the project management platform to form a historical project set; numbers the historical projects in the historical project set uniformly, extracts the project feature data corresponding to each historical project in the historical project set, and generates a project feature set. The project feature data includes the total project duration, total resources, and total project volume. The total resources include the total cost, total materials, and total manpower.

[0095] The feature analysis and association module includes an association degree value calculation unit and an association relationship analysis unit;

[0096] The association degree value calculation unit is used to extract the feature data of the first project, and denote the feature data of the first project as PC0; calculate the feature data association degree value according to the feature data of the first project and the project feature data of the historical projects in the historical project set. The feature data association degree value is negative, zero, or positive;

[0097] The association relationship analysis unit is used to set a threshold A for the feature data association degree value, where A>0; if the feature data association degree value FDA(0→i) between the first project P0 and the historical project PC i is in [-A, A], it indicates that there is an association relationship between the first project P0 and the historical project PC i ; if the feature data association degree value FDA(0→i) between the first project P0 and the historical project PC i is in (-∞, -A) ∩ (A, +∞), it indicates that there is no association relationship between the first project P0 and the historical project PC i ; extracts all historical projects that have an association relationship with the first project P0 to generate an associated project set.

[0098] The model construction module includes a task implementation analysis unit and a model fitting unit;

[0099] The task implementation analysis unit is used to extract all historical work orders of each historical project in the associated project set, arrange the historical work orders of the same historical project in the order of the start generation time, and extract the task implementation situation of the historical work orders. The task implementation situation includes the change of the remaining work order resources and the remaining work order project volume with the remaining work order time; generates the task implementation situation of the historical project according to the task implementation situation of all historical work orders; combines the task implementation situation of the jth historical project P j in the associated project set with the time variable and arranges them in the order of the remaining project time to generate an associated project implementation set; the associated project implementation set includes an associated project resource implementation set and an associated project project implementation set;

[0100] The model fitting unit is used to establish an implementation fitting model of associated project resources by using the implementation set of associated project resources; establish an implementation fitting model of associated project works by using the implementation set of associated project works; construct an implementation fitting model of project resources of the first project according to all the implementation fitting models of associated project resources; and construct an implementation fitting model of project works of the first project according to all the implementation fitting models of associated project works.

[0101] The exception analysis and prompt module includes an implementation work order analysis unit and an exception work order processing unit;

[0102] The implementation work order analysis unit is used to extract the work orders being implemented for the first project, obtain the task implementation status of the work orders being implemented at the current moment, and analyze the remaining project resources and the remaining project works based on the remaining work order resources and the remaining work order works; substitute the current moment into the implementation fitting model of project resources and the implementation fitting model of project works of the first project to obtain the remaining fitting project resources and the remaining fitting project works of the first project respectively;

[0103] The exception work order processing unit is used to calculate the work order exception degree value; set a threshold for the work order exception degree value, mark the work orders being implemented with a work order exception degree value greater than the threshold as exception work orders, mark and extract all the exception work orders to generate an exception work order list; calculate the proportion of the exception work orders in the work orders being implemented, if the proportion is greater than the proportion threshold, mark the first project; if the proportion is not greater than the proportion threshold, no processing is performed; and send the exception work order list to the administrator.

[0104] It should be noted that in this article, relational terms such as first and second are only used to distinguish one entity or operation from another entity or operation, and do not necessarily require or imply any actual relationship or order between these entities or operations. Moreover, the term "comprises", "comprising" or any other variation thereof is intended to cover a non-exclusive inclusion, such that a process, method, article or device comprising a series of elements includes not only those elements but also other elements not expressly listed, or elements inherent to such process, method, article or device.

[0105] For those skilled in the art, it is obvious that the present invention is not limited to the details of the above exemplary embodiments, and can be implemented in other specific forms without departing from the spirit or basic characteristics of the present invention. Therefore, in any aspect, the embodiments should be regarded as exemplary and non-restrictive. The scope of the present invention is defined by the appended claims rather than the above description. Therefore, all changes falling within the meaning and scope of the equivalent elements of the claims are intended to be included in the present invention. Any reference signs in the claims should not be regarded as limiting the claims involved.

Claims

1. A standardized collaborative approach based on the entire project life cycle, characterized by: The method comprises the following steps: S1: Use text recognition technology to obtain text data of real-time work orders; extract historical projects from the project management platform to form a historical project set; extract and mark the project feature data of each historical project to form a project feature set; S2: extracting feature data of the first project, calculating the correlation degree between the project feature data of the historical project and the feature data of the first project in the project feature set; analyzing the correlation relationship between the historical project and the first project according to the correlation degree value, and forming a correlation project set; S3: extract the text data of historical work orders of historical projects in the associated project set, and build a project implementation fitting model based on the text data of the historical work orders; S4: analyzing the implementation status of tasks corresponding to the work orders being implemented in the first project according to the project implementation fitting model, calculating the abnormality degree value of the work orders, identifying and marking abnormal work orders, extracting abnormal work orders to generate an abnormal work order list, and sending it to the administrator; In S1, the following are included: S101: using text recognition technology to obtain text data of a real-time work order, the text data including a work order task name, a project name corresponding to the work order, a pre-consumed resource amount of the work order, a predicted engineering amount of the work order, and a pre-consumed duration of the work order; searching for a project corresponding to the real-time work order in a project management platform, recording the project corresponding to the real-time work order as a first project P0, and extracting a project type of the first project; S102: extract historical projects of the same project type as the first project from the project management platform to form a historical project set; uniformly number the historical projects in the historical project set, and record the i-th historical project as P i ; Extract the project feature data corresponding to each historical project in the historical project set, and generate a project feature set, denoted as PC={PC i |i∈[1,I]}; where PC i represents the i-th historical item P i A set of project characteristic data, where I represents the total number of historical projects in the historical project set; the project characteristic data includes the total duration of the project, the total amount of resources and the total amount of engineering; the total amount of resources includes the total amount of expenses, the total amount of materials and the total amount of manpower; In S2, the following are included: S201: extracting feature data of the first project, recording the feature data of the first project as PC0; calculating a feature data association degree value based on the feature data of the first project and the project feature data of the historical project in the historical project set: FDA(0→i)=α1×(TT0-TT i )+α2×(TR0-TR i )+α3×(TQ0-TQ i ); Among them, FDA (0→i) represents the first item P0 and the historical item PC i α1, α2 and α3 represent the characteristic data association coefficients, which are preset constants; TT0 represents the total duration of the first project P0; TT i Indicates historical project PC i The total duration of the project; TR0 represents the total amount of resources of the first project P0; TR i Indicates historical project PC i The total amount of resources; TQ0 represents the total amount of engineering work for the first project P0; TQ i Indicates historical project PC i The total amount of engineering; the characteristic data correlation degree value is negative, zero or positive; S202: Setting a threshold value A of the feature data association degree value, A is greater than zero; if the first item P0 and the historical item PC i The feature data association degree value FDA(0→i)∈[-A, A] indicates that the first item P0 and the historical item PC i There is an association relationship between the first item P0 and the historical item PC i The characteristic data association degree value FDA(0→i)∈(-∞,-A)∩(A,+∞) between the first item P0 and the historical item PC i There is no association relationship between them; extract all historical projects that have an association relationship with the first project P0 to generate a set of associated projects; In S3, include the following: S301: extract all historical work orders of each historical project in the associated project set, arrange the historical work orders of the same historical project in the order of the start time of generation, extract the task implementation status of the historical work orders, and the task implementation status includes the change of the remaining amount of work order resources and the remaining amount of work order engineering with the remaining time of the work order; generate the task implementation status of the historical project according to the task implementation status of all historical work orders; and j The task implementation status is combined with the time variable, and the associated project implementation set is generated according to the order of the remaining time of the project; the associated project implementation set includes the associated project resource implementation set and the associated project engineering implementation set; the associated project resource implementation set is recorded as PS j ={(ST j , SR j )|j∈[1,J]}, where ST j SR for remaining resources of the project j The corresponding moment; J represents the total number of historical items in the associated item set, J<I; S302: Using the associated project resource implementation set, establish an associated project resource implementation fitting model: j 1 =B j 1 × j 1 +C j 1 ; Among them B j 1 and C j 1 represents the fitting coefficient, x j 1 The independent variable representing time, y j 1 The dependent variable represents the remaining resources of the associated project, and the B in the fitting model is implemented using the least squares method to fit the project resources. j 1 and C j 1 Perform calculation and solution; use the related project engineering implementation set in the same way to establish the related project engineering implementation fitting model; S303: Construct a project resource implementation fitting model for the first project based on all associated project resource implementation fitting models: y=B×x+C; where B and C represent fitting coefficients, x represents the independent variable of time, and y represents the dependent variable of the remaining project resources of the first project; the fitting coefficient B is equal to the set {B1 1 , B2 1 , …, B J 1 The average value of the fitting coefficients in the set {C1 1 , C2 1 , …, C J 1 }; Using the same method, establish the project engineering implementation fitting model of the first project; In S4, the following are included: S401: extracting the work orders being implemented for the first project, obtaining the current task implementation status of the work orders being implemented, and obtaining the project resource remaining amount and the project engineering remaining amount according to the work order resource remaining amount and the work order engineering remaining amount; S402: Substituting the current moment into the project resource implementation fitting model and the project engineering implementation fitting model of the first project, respectively obtaining the fitted project resource remaining amount and the fitted project engineering remaining amount of the first project; S403: Calculate the abnormality degree value AD of the work order: AD=(SR÷NSR)×(SG÷NSG); Among them, SR represents the remaining amount of project resources, and NSR represents the remaining amount of fitting project resources; SG represents the remaining amount of project engineering, and NSG represents the remaining amount of fitting project engineering; Set a threshold for the abnormality level of the work order, record the ongoing work orders whose abnormality level is greater than the threshold as abnormal work orders, mark and extract all abnormal work orders, and generate a list of abnormal work orders; calculate the proportion of abnormal work orders in the ongoing work orders, if the proportion is greater than the proportion threshold, mark the first item; if the proportion is not greater than the proportion threshold, do not process it; send the list of abnormal work orders to the administrator.

2. A standardized collaborative system based on the entire life cycle of a project, the system being applied to the implementation of a standardized collaborative method based on the entire life cycle of a project as described in any one of claim 1, characterized in that: The system includes a data identification and acquisition module, a feature analysis and association module, a model building module and an abnormal analysis and prompting module; The data recognition and acquisition module is used to acquire text data of real-time work orders using text recognition technology; extract historical projects from the project management platform to form a historical project set; extract and mark project feature data of each historical project to form a project feature set; The feature analysis and association module is used to extract feature data of the first project, calculate the correlation degree value between the project feature data of the historical project and the feature data of the first project in the project feature set; analyze the correlation relationship between the historical project and the first project according to the correlation degree value, and form a set of associated projects; The model building module is used to extract text data of historical work orders of historical projects in the associated project set, and build a project implementation fitting model based on the text data of the historical work orders; The abnormal analysis prompt module analyzes the task implementation status corresponding to the work order being implemented in the first project according to the project implementation fitting model, calculates the abnormality degree value of the work order, identifies and marks the abnormal work order, extracts the abnormal work order to generate an abnormal work order list, and sends it to the administrator.

3. The standardized collaborative system based on the entire project life cycle according to claim 2 is characterized in that: The data identification and acquisition module includes a work order data identification unit and a feature extraction unit; The work order data recognition unit uses text recognition technology to obtain text data of the real-time work order, wherein the text data includes the work order task name, the project name corresponding to the work order, the estimated resource consumption of the work order, the estimated engineering quantity of the work order, and the estimated duration of the work order; searches for the project corresponding to the real-time work order in the project management platform, records the project corresponding to the real-time work order as the first project, and extracts the project type of the first project; The feature extraction unit extracts historical projects of the same project type as the first project from the project management platform to form a historical project set; uniformly number the historical projects in the historical project set, extract the project feature data corresponding to each historical project in the historical project set, and generate a project feature set, wherein the project feature data includes the total duration of the project, the total amount of resources and the total amount of engineering; the total amount of resources includes the total amount of expenses, the total amount of materials and the total amount of manpower.

4. The standardized collaborative system based on the entire project life cycle according to claim 2 is characterized by: The feature analysis association module includes an association degree value calculation unit and an association relationship analysis unit; The association degree value calculation unit is used to extract the feature data of the first project, and record the feature data of the first project as PC0; calculate the feature data association degree value according to the feature data of the first project and the project feature data of the historical project in the historical project set, and the feature data association degree value is negative, zero or positive; The association relationship analysis unit is used to set a threshold value A of the feature data association degree value, A is greater than zero; if the first item P0 and the historical item PC i The feature data association degree value FDA(0→i)∈[-A, A] indicates that the first item P0 and the historical item PC i There is an association relationship between the first item P0 and the historical item PC i The characteristic data association degree value FDA(0→i)∈(-∞,-A)∩(A,+∞) between the first item P0 and the historical item PC i There is no association relationship between them; extract all historical projects that have an association relationship with the first project P0 to generate a set of associated projects.

5. The standardized collaborative system based on the entire project life cycle according to claim 2 is characterized in that: The model building module includes a task implementation analysis unit and a model fitting unit; The task implementation analysis unit is used to extract all historical work orders of each historical project in the associated project set, arrange the historical work orders of the same historical project in the order of the start generation time, extract the task implementation status of the historical work orders, and the task implementation status includes the change of the remaining amount of work order resources and the remaining amount of work order engineering with the remaining time of the work order; generate the task implementation status of the historical project according to the task implementation status of all historical work orders; and assign the jth historical project P in the associated project set to the task implementation status of the historical project; j The task implementation status is combined with the time variable, and the associated project implementation set is generated according to the order of the remaining time of the project; the associated project implementation set includes the associated project resource implementation set and the associated project engineering implementation set; The model fitting unit is used to use the associated project resource implementation set to establish an associated project resource implementation fitting model; use the associated project engineering implementation set to establish an associated project engineering implementation fitting model; construct a project resource implementation fitting model for the first project based on all associated project resource implementation fitting models; and construct a project engineering implementation fitting model for the first project based on all associated project engineering implementation fitting models.

6. The standardized collaborative system based on the entire project life cycle according to claim 2 is characterized by: The abnormal analysis prompt module includes a work order analysis unit and an abnormal work order processing unit; The implementation work order analysis unit is used to extract the work orders being implemented for the first project, obtain the current task implementation status of the work orders being implemented, and obtain the project resource remaining amount and the project engineering remaining amount according to the work order resource remaining amount and the work order engineering remaining amount; bring the current moment into the project resource implementation fitting model and the project engineering implementation fitting model of the first project, and obtain the fitted project resource remaining amount and the fitted project engineering remaining amount of the first project respectively; The abnormal work order processing unit is used to calculate the abnormality degree value of the work order; Set a threshold for the abnormality level of the work order, record the ongoing work orders whose abnormality level is greater than the threshold as abnormal work orders, mark and extract all abnormal work orders, and generate an abnormal work order list; Calculate the proportion of abnormal work orders in the work orders being implemented. If the proportion is greater than the proportion threshold, mark the first item; if the proportion is not greater than the proportion threshold, do not process it; send the abnormal work order list to the administrator.

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