CN114493266A - Intelligent quality control method and system for engineering cost achievement - Google Patents
Intelligent quality control method and system for engineering cost achievement Download PDFInfo
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Abstract
The application relates to the technical field of engineering cost, in particular to an intelligent quality control method for engineering cost achievements, which comprises the following steps: building a data extraction comparison model by using the metadata; uploading the pricing file, and acquiring project management information data and project pricing information data in the pricing file by using a data extraction comparison model; building a comparison database; importing the data of the comparison database into a data extraction comparison model; comparing and checking the data in the comparison database and the extracted data in the pricing file; modifying and perfecting the marked data, and analyzing the auditing results; and classifying and summarizing the marked problems to form a quality control report, so that users can be prompted about the quality of the engineering cost achievement. The construction cost achievement file intelligent data error checking method and system comprehensively improve the quality control of the construction cost achievement.
Description
Technical Field
The application relates to the technical field of construction cost, in particular to an intelligent quality control method and system for construction cost achievements.
Background
The construction cost refers to the construction price of the project, and refers to the total sum of all the expenses expected or actually required for completing the construction of one project. The project cost is defined from the perspective of investors, and is the construction cost of a project, namely the investment cost of all fixed assets expected to be paid or actually paid for constructing a project.
At present, in the field of engineering cost, cost projects need cooperation of multiple persons, project flows are complex, time requirements are tight, cost achievement quality management is carried out only by manpower, and the problem of poor cost achievement quality is caused.
Disclosure of Invention
In order to comprehensively improve the quality control of the engineering cost achievement, the application provides an intelligent quality control method for the engineering cost achievement.
In a first aspect, the present application provides an intelligent quality control method for engineering cost achievements, which adopts the following technical scheme: the method comprises the following steps:
building a data extraction comparison model by using the metadata;
uploading the pricing file, and acquiring project management information data and project pricing information data in the pricing file by using a data extraction comparison model;
building a comparison database;
importing the data of the comparison database into a data extraction comparison model;
comparing and checking the data in the comparison database and the extracted data in the pricing file;
modifying and perfecting the marked data, and analyzing the auditing results;
and classifying and summarizing the marked problems to form a quality control report, so that users can be prompted about the quality of the engineering cost achievement.
By adopting the technical scheme, the project management information data and the project pricing information data in the pricing file are audited by utilizing the data extraction comparison model, the coverage of quality audit is improved, and comprehensive quality audit is promoted; by building a contrast database, the intelligent multi-angle multi-direction analysis of the frame file can be realized, and human errors are reduced.
Optionally, an item pricing information data extraction template and an item management information data extraction template are preset in the data extraction comparison model, the pricing file is uploaded, the data extraction comparison model is utilized to obtain item management information data and item pricing information data in the pricing file,
setting a pricing file analysis scheme and an interface document, and analyzing the uploaded pricing file according to the pricing file analysis scheme and the interface document;
importing the analyzed data of the pricing file into a data extraction comparison model;
according to a preset project pricing information data extraction template, comparing and extracting project pricing information data obtained through analysis;
and comparing and extracting the analyzed project management information data according to a preset project management information data extraction template.
By adopting the technical scheme, the data in the pricing file is converted into the character data which can be identified by a machine, so that the pricing information data and the project management information data of the project are extracted.
Optionally, the comparison database includes a project sub-library and a common cost problem sub-library, and both the project sub-library and the common cost problem sub-library can be checked and called by set screening conditions;
the project sub-library is provided with a plurality of sub-projects, and the sub-projects correspond to the project management information data extraction template;
an index sub-library is arranged in the sub-project and comprises a plurality of sub-indexes, and the sub-indexes correspond to project pricing information data extraction templates;
further comprising the steps of:
checking the reasonability of indexes in the pricing information data extraction template of the analysis project and checking the reasonability of project division in the management information data extraction template of the analysis project.
By adopting the technical scheme, the indexes and the sub-items set in the database are checked, called and compared according to the screening condition, the reasonability of the indexes in the pricing information data extraction template of the analysis item is judged, the reasonability of item division in the management information data extraction template of the analysis item is checked, and a scientific index data relationship is established.
Optionally, the data of the comparison database is imported into the data extraction comparison model,
importing the data of the comparison database into a data extraction comparison model;
and importing the data of the index sub-library in the comparison database into a preset project pricing information data extraction template.
By adopting the technical scheme, the data association relation is determined, the automatic matching of the comparison items is realized, and the extracted data is conveniently compared.
Optionally, the computing formula is called, the data in the imported project pricing information data extraction template is automatically computed, the computed data is compared with the preset data in the comparison database,
if the calculation result does not exceed the set standard reference value range of the deviation, corresponding data do not need to be marked;
if the calculation result exceeds the set standard reference value range of the deviation, the data exceeding the limit are automatically marked, and the problem point is positioned, so that the user can independently select and display the sub-indexes, and the comparison result can be exported in an EXCEL format. Items beyond the deviation range can be expanded to check detailed list composition and list details, and the deviation items are annotated with reasons;
the data extracted from the project management information data extraction template is automatically compared with the preset data in the database,
if the extracted project management information data does not correspond to data in a preset project management information data extraction template, marking the extracted project management information data, positioning problem points, and judging whether the extracted project management information data belongs to the existing problems in the problem library; if the problem does not belong to the problems in the problem database, the newly found problems are added into the comparison database;
if the extracted project management information data corresponds to data in the preset project management information data extraction template, the corresponding data does not need to be marked.
By adopting the technical scheme, abnormal indexes can be automatically positioned and problem sources can be automatically found, so that the manufacturing cost result file is intelligently checked for errors, and the quality of the result is comprehensively improved.
Optionally, judging whether the marked data belong to the existing problems in the question bank;
if the problem does not belong to the problems in the problem bank, the newly found problems are added into the comparison database.
By adopting the technical scheme, the data accumulation of the comparison database is completed, data sources are provided for a data center and a quality control database, quality control and data storage supplement each other, and virtuous circle development is established.
In a second aspect, the application provides an intelligent project cost achievement quality control system, which comprises a project management unit, an intelligent file batch analysis unit, a database unit, an intra-project comparison unit, a quality control report unit and a project warehousing unit; wherein the content of the first and second substances,
the project management unit is used for creating projects and managing the projects;
the file intelligent batch analysis unit is used for converting and analyzing the uploaded pricing file into logic which can be recognized by a machine, automatically extracting data according to a set template and sending the data to the project analysis unit;
the database unit is used for providing indexes and reference data of the indexes;
the in-project comparison unit is used for comparing the associated indexes under the appointed project of the uploaded files and automatically marking the data beyond the range of the reference data;
the quality control report unit is used for classifying and summarizing the problems analyzed by the item analysis unit to form a quality control report for viewing;
and the project warehousing unit is used for uploading and analyzing the invoicing result which is verified and modified completely, initiating a warehousing request and automatically classifying and warehousing according to the project classification.
By adopting the technical scheme, a scientific index data relation is established, an auditing content method system is configured, and index data are automatically extracted; by means of an intelligent analysis means, the coverage of quality audit is improved, and comprehensive quality audit is promoted.
Optionally, the project analysis unit includes an index library checking module, a project index analysis module, and a common problem screening module;
the system comprises a standard library checking module, a standard library searching module and a standard library searching module, wherein the standard library checking module is used for automatically screening similar projects of a project and comprehensively obtaining a reference index according to indexes of the similar projects;
the project index analysis module is used for analyzing and checking main project quantity indexes and main economic indexes in a project;
the common problem screening module is used for searching and analyzing problems in the data extracted by the file intelligent batch analysis module and marking the problems.
By adopting the technical scheme, when contrastive analysis between the same projects and different projects is carried out, the automatic matching of the contrastive projects, the automatic positioning of abnormal indexes and the back checking of problem sources can be carried out according to the principle setting of intelligent matching, the analysis breadth and the accuracy can be adjusted, and the purposes of intelligently checking data of construction cost achievement files and comprehensively improving the achievement quality can be achieved.
Drawings
FIG. 1 is a flow chart of the construction cost result quality intelligent quality control method of the present application;
FIG. 2 is a block diagram of a process for uploading a pricing file, and using a data extraction comparison model to obtain project management information data and project pricing information data in the pricing file;
FIG. 3 is a block diagram of a process for importing data from a comparison database into a data extraction comparison model according to the present application;
FIG. 4 is a block diagram of the process of comparing and verifying the data in the comparison database and the extracted pricing file according to the present application;
FIG. 5 is a block diagram of the module connection of the intelligent engineering cost result quality control system.
Description of reference numerals: 1. a project management unit; 2. a file intelligent batch analysis unit; 3. a database unit; 31. an index library checking module; 32. a project index analysis module; 33. a common problem screening module; 4. an intra-item comparison unit; 5. a quality control report unit; 6. and an item warehousing unit.
Detailed Description
The present application is described in further detail below with reference to figures 1-5.
Example one
The embodiment of the application discloses an intelligent quality control method and system for engineering cost achievement, and the method and the system refer to fig. 1 and comprise the following steps:
step S1: and building a data extraction comparison model by using the metadata.
The data extraction comparison model is preset with an item pricing information data extraction template and an item management information data extraction template. The project pricing information data extraction template extracts pricing information data such as codes, characteristics, engineering quantities, unit prices, total prices and the like; the project management information data extraction template extracts management information data such as consignor, region, project type, preparation stage and project characteristics.
For example, an Oracle database model is built, and a project pricing information data extraction template and a project management information data extraction template are set as corresponding EXCEL extraction tables.
Step S2: uploading the pricing file, and acquiring the project management information data and the project pricing information data in the pricing file by using the data extraction comparison model, referring to fig. 2.
The formats of the pricing files comprise EXCEL files and XML files, and the construction data extraction comparison model using the metadata can support the import of EXCEL files and XML files.
The project management information data comprises consignor, region, project category, compiling stage and project characteristics; the project pricing information data includes codes, characteristics, engineering quantities, unit prices, and total prices.
And step S20, setting a pricing file analysis scheme and an interface document, and analyzing the uploaded pricing file according to the pricing file analysis scheme and the interface document.
Wherein, the pricing file analysis scheme is formulated by referring to 'construction engineering project amount list pricing standard' formulated by relevant departments of the country; the interface document is a reference standard for converting the pricing file parsing scheme into an interactive machine language, and is provided with a request method, a URL (uniform resource locator), request parameters and return parameters.
Step S21: and importing the analyzed data of the pricing file into a data extraction comparison model.
Step S22: and according to a preset project pricing information data extraction template, comparing and extracting the project pricing information data obtained by analysis.
Step S23: and comparing and extracting the analyzed project management information data according to a preset project management information data extraction template.
For example, firstly, importing the EXCEL Table of the analyzed pricing file into an ORCLE database to become a Table in the ORCLE database, named Table _ A, and marking the field needing to be captured and compared as AA;
another extraction template data Table needing comparison is called Table _ B, and a field needing comparison is called BB;
indexing a field AA in Table _ A;
indexing a field BB in Table _ B;
then executing the query;
and then, in Table _ A and Table _ B, the same contents of AA and BB are output one by one, thereby realizing the comparison and extraction of the data in the EXCEL Table of the pricing file.
Step S3: and (5) building a comparison database.
The comparison database comprises a project sub-library and a cost common problem sub-library, and the project sub-library and the cost common problem sub-library can be checked and called.
Furthermore, the generation condition of the project sub-library can be selected, the matched caliber and condition can be set for automatic generation, and the condition can also be manually selected. For example, the project sub-library is selected according to project regions and attributions, project time, project names, project characteristics and the like.
Firstly, a project sub-library is provided with a plurality of sub-projects; the sub-project corresponds to the project management information data extraction template, and the sub-project is a consignor, a region, a project type, a compilation stage and project characteristics.
For example, project sub-libraries include carrier entrustment, Henan and 5G construction, and so on.
Specifically, each of the plurality of sub-projects is provided with an index sub-library, the index sub-library comprises a plurality of sub-indexes, the sub-indexes correspond to the project pricing information data extraction template, the sub-indexes are codes, characteristics, engineering quantities, unit prices and total prices, and each sub-index is provided with a corresponding sub-project reference value range.
Further, by comparing the reference data in the similar items, the sub-item reference value range is obtained comprehensively.
Therefore, a certain type of unit single project can be designated for analysis through the sub-indexes, and the detailed list, the composition of the list and the work and material machine indexes of the project can be checked.
For example, the sub-indexes include codes, characteristics, engineering quantities, unit prices and the like, wherein the codes correspond to 010101002003, the characteristics are that the depth of the foundation pit of the excavation pool is within 4m, the engineering quantities are 67.64, and the unit prices are 80 yuan.
And secondly, the sub-library of the common problems of the manufacturing cost comprises a project classification problem, an index name problem, an index data problem and a missing item problem.
The project classification problem is a problem occurring in consignor, area, project category, compilation stage and project characteristic information of the project; the index name problem is the problem of the names of the codes, the characteristics, the engineering quantity and the unit price of the sub-indexes; the index data problem is that the numerical ranges of the codes, the characteristics, the engineering quantity and the unit price of the sub-indexes are in question; the missing item problem is the occurrence of missing items in the project management information data and/or the project pricing information data.
Step S4: the data of the comparison database is imported into the data extraction comparison model, refer to fig. 4.
Step S40: and importing the data of the project sub-library in the comparison database into a preset project management information data extraction template.
Specifically, the extracted consignor, area, project category, compilation stage, project feature and the like are classified into a project sub-library.
For example, the extracted engineering address data corresponds to the sub-project database and is attributed to the index sub-database.
Step S41: and importing the data of the index sub-library in the comparison database into a preset project pricing information data extraction template.
Specifically, the extracted engineering quantity data corresponds to the sub-project reference value database and belongs to the sub-project reference value database.
For example: and classifying the extracted engineering quantity data, the extracted money amount data, the extracted single-component cost data and the like into an index sub-library.
Step S5: and comparing and checking the data in the comparison database and the data in the extracted pricing file, and referring to fig. 4.
Step S50: and a calculation formula is built in a calculation mode of the reference pricing file.
Step S51: and calling a calculation formula, automatically calculating the data in the imported project pricing information data extraction template, and comparing the calculated data with the preset data in the comparison database.
If the calculation result does not exceed the set standard reference value range of the deviation, the corresponding data does not need to be marked.
If the calculation result exceeds the set standard reference value range of the deviation, the data exceeding the limit are automatically marked, and the problem point is positioned, so that the user can independently select and display the sub-indexes, and the comparison result can be exported in an EXCEL format. Items beyond the deviation range can be expanded to check detailed list composition and list details, and the deviation items are annotated with reasons.
Further, it is judged whether the marked data belongs to a problem already existing in the problem bank.
If the problem does not belong to the problems in the problem bank, the newly found problems are added into the comparison database.
Step S52: and automatically comparing the extracted data in the project management information data extraction template with the preset data in the database.
If the extracted project management information data does not correspond to data in a preset project management information data extraction template, marking the extracted project management information data, positioning problem points, and judging whether the extracted project management information data belongs to the existing problems in the problem library; if the problem does not belong to the problems in the problem bank, the newly found problems are added into the comparison database.
If the extracted project management information data corresponds to data in the preset project management information data extraction template, the corresponding data does not need to be marked.
Step S6: and modifying and perfecting the marked data, and analyzing the auditing results.
Step S7: and classifying and summarizing the marked problems to form a quality control report.
Wherein, the quality control report can be checked on line or exported.
Step S8: and automatically classifying and warehousing the items after the examination and modification are finished according to different items.
Example two
The difference between the embodiment of the present application and the first embodiment is that the method further includes step S10:
checking the reasonability of indexes in the analysis project pricing information data extraction template, and checking the reasonability of project division in the analysis project management information data extraction template.
EXAMPLE III
The embodiment of the present application is different from the second embodiment in that the method further includes step S24:
and if the data in the pricing file fails to be extracted, prompting that the imported pricing file is in an unsupported file format.
Example four
The present embodiment differs from the above-described embodiment in step S5 in that:
and automatically searching and analyzing the imported project management information data and project pricing information data based on the common cost problem sub-library set by the comparison database, and marking problems.
The implementation principle is as follows: extracting the uploaded pricing file through a data extraction comparison model, extracting project pricing information data and project management information data in the pricing file, comparing the project management information data with a project sub-library preset in a comparison database, and determining whether the project classification in the pricing file has problems; the project pricing information data is compared with preset sub-indexes in a comparison database, whether the indexes in the pricing files have problems or not is determined, the pricing files are analyzed intelligently in a multi-angle and multi-direction mode, human errors are reduced, problems are clear and traceable, and experience is convenient to copy and utilize. The existing problems are sorted and labeled and are additionally recorded in the comparison database, so that the comprehensiveness of subsequent comparison and check is improved.
The application also discloses an engineering cost achievement quality intelligent product control system, which refers to fig. 5 and comprises a project management unit 1, a file intelligent batch analysis unit 2, a database unit 3, an intra-project comparison unit 4, a quality control report unit 5 and a project warehousing unit 6.
The project management unit 1 is used for creating projects and managing the projects according to project classification, preparation stages and project site information;
the file intelligent batch analysis unit 2 is used for converting and analyzing the uploaded pricing files into logic which can be recognized by a machine, automatically extracting data according to a set template and sending the data to the project analysis unit;
the database unit 3 is used for providing indexes and reference data of the indexes;
the in-project comparison unit 4 is used for comparing the uploaded files with the associated indexes under the designated project, automatically marking the data beyond the range of the reference data, enabling the user to select the display indexes independently, and exporting the comparison result in the EXCEL format. Items beyond the deviation range can be expanded to view detailed list composition and list details and to note reasons for the deviation items.
And the quality control report unit 5 is used for classifying and summarizing the problems analyzed by the item analysis unit to form a quality control report, and the quality control report can be checked on line or can be exported and checked.
And the project warehousing unit 6 is used for uploading and analyzing the invoicing results which are verified and modified completely, initiating warehousing requests, and automatically classifying and warehousing according to different consignors, regions, project types, compiling stages, project characteristics and the like.
Referring to fig. 1, the project management unit 1 includes a system background management unit, and the system background management unit is configured to configure a system account, a role, a file format template of a principal and a maintenance list, so as to meet requirements of different index file templates under different principal.
Referring to fig. 5, the database unit 3 includes an index library checking module 31, a project index analyzing module 32, and a common problem screening module 33;
the system comprises a standard library checking module, a standard library searching module and a standard library searching module, wherein the standard library checking module is used for automatically screening similar projects of a project and comprehensively obtaining a reference index according to indexes of the similar projects;
the project index analysis module 32 is used for analyzing and checking main project quantity indexes and main economic indexes in projects, analyzing single projects of a specified type of units in the projects, and checking detailed lists, list composition and work and material machine indexes of partial project projects.
The common problem screening module 33 is used for searching, analyzing and labeling problems in the data extracted by the file intelligent batch analysis module.
The above embodiments are preferred embodiments of the present application, and the protection scope of the present application is not limited by the above embodiments, so: all equivalent changes made according to the structure, shape and principle of the present application shall be covered by the protection scope of the present application.
Claims (10)
1. An intelligent quality control method for engineering cost achievements is characterized by comprising the following steps: the method comprises the following steps:
building a data extraction comparison model by using the metadata;
uploading the pricing file, and acquiring project management information data and project pricing information data in the pricing file by using a data extraction comparison model;
building a comparison database;
importing the data of the comparison database into a data extraction comparison model;
comparing and checking the data in the comparison database and the extracted data in the pricing file;
modifying and perfecting the marked data, and analyzing the auditing results;
and classifying and summarizing the marked problems to form a quality control report, so that users can be prompted about the quality of the engineering cost achievement.
2. The intelligent engineering cost result quality control method according to claim 1, characterized in that: the data extraction and comparison model is preset with an item pricing information data extraction template and an item management information data extraction template, the pricing file is uploaded, the data extraction and comparison model is utilized to obtain the item management information data and the item pricing information data in the pricing file,
setting a pricing file analysis scheme and an interface document, and analyzing the uploaded pricing file according to the pricing file analysis scheme and the interface document;
importing the analyzed data of the pricing file into a data extraction comparison model;
according to a preset project pricing information data extraction template, comparing and extracting project pricing information data obtained through analysis;
and comparing and extracting the analyzed project management information data according to a preset project management information data extraction template.
3. The intelligent engineering cost result quality control method according to claim 2, characterized in that:
the comparison database comprises a project sub-library and a cost common problem sub-library, and the project sub-library and the cost common problem sub-library can be checked and called by set screening conditions;
the project sub-library is provided with a plurality of sub-projects, and the sub-projects correspond to the project management information data extraction template;
an index sub-library is arranged in the sub-project and comprises a plurality of sub-indexes, and the sub-indexes correspond to project pricing information data extraction templates;
further comprising the steps of:
checking the reasonability of indexes in the pricing information data extraction template of the analysis project and checking the reasonability of project division in the management information data extraction template of the analysis project.
4. The intelligent engineering cost result quality control method according to claim 3, characterized in that: the data of the comparison database is imported into a data extraction comparison model,
importing the data of the comparison database into a data extraction comparison model;
and importing the data of the index sub-library in the comparison database into a preset project pricing information data extraction template.
5. The intelligent engineering cost result quality control method according to claim 4, characterized in that: in the comparison and verification of the data in the comparison database and the extracted data in the pricing file,
a calculation formula is built in a calculation mode of a reference pricing file;
calling a calculation formula, automatically calculating data in the imported project pricing information data extraction template, and comparing the calculated data with preset data in a comparison database;
and automatically comparing the data extracted from the project management information data extraction template with the preset data in the database.
6. The intelligent engineering cost result quality control method according to claim 5, characterized in that: the calculation formula is called, the data in the imported project pricing information data extraction template is automatically calculated, the data obtained through calculation is compared with the preset data in the comparison database,
if the calculation result does not exceed the set standard reference value range of the deviation, corresponding data do not need to be marked;
if the calculation result exceeds the set standard reference value range of the deviation, the data exceeding the limit are automatically marked, and the problem point is positioned, so that the user can independently select and display the sub-indexes, and the comparison result can be exported in an EXCEL format. Items beyond the deviation range can be expanded to check detailed list composition and list details, and the deviation items are annotated with reasons;
the data extracted from the project management information data extraction template is automatically compared with the preset data in the database,
if the extracted project management information data does not correspond to data in a preset project management information data extraction template, marking the extracted project management information data, positioning problem points, and judging whether the extracted project management information data belongs to the existing problems in the problem library; if the problem does not belong to the problems in the problem database, the newly found problems are added into the comparison database;
if the extracted project management information data corresponds to data in the preset project management information data extraction template, the corresponding data does not need to be marked.
7. The intelligent engineering cost result quality control method and system according to claim 6, wherein:
judging whether the marked data belong to the existing problems in the question bank;
if the problem does not belong to the problems in the problem bank, the newly found problems are added into the comparison database.
8. The intelligent engineering cost result quality control method and system according to claim 1, wherein: further comprising the steps of:
and if the data in the pricing file fails to be extracted, prompting that the imported pricing file is in an unsupported file format.
9. An intelligent engineering cost result quality control system based on any one of claims 1-8, characterized in that: the system comprises a project management unit (1), a file intelligent batch analysis unit (2), a database unit (3), an in-project comparison unit (4), a quality control report unit (5) and a project warehousing unit (6); wherein the content of the first and second substances,
the project management unit (1) is used for creating projects and managing the projects;
the file intelligent batch analysis unit (2) is used for converting and analyzing the uploaded pricing file into logic which can be recognized by a machine, automatically extracting data according to a set template and sending the data to the project analysis unit;
the database unit (3) is used for providing indexes and reference data of the indexes;
the in-item comparison unit (4) is used for comparing the related indexes under the appointed item of the uploaded files and automatically marking the data beyond the range of the reference data;
the quality control report unit (5) is used for classifying and summarizing the problems analyzed by the item analysis unit to form a quality control report for viewing;
and the project warehousing unit (6) is used for uploading and analyzing the invoicing results which are verified and modified completely, initiating a warehousing request and automatically classifying and warehousing according to the project classification.
10. The intelligent project cost result quality control system according to claim 8, characterized in that: the project analysis unit comprises an index library checking module (31), a project index analysis module (32) and a common problem screening module (33);
the system comprises a standard library checking module, a standard library searching module and a standard library searching module, wherein the standard library checking module is used for automatically screening similar projects of a project and comprehensively obtaining a reference index according to indexes of the similar projects;
the project index analysis module (32) is used for analyzing and checking main project quantity indexes and main economic indexes in a project;
the common problem screening module (33) is used for searching and analyzing problems in the data extracted by the file intelligent batch analysis module and labeling the problems.
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