CN113760913A - Elastically extensible equipment cost acquisition method - Google Patents
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Abstract
The invention discloses an elastically extensible equipment expense acquisition method, which is used for constructing an equipment expense acquisition overall framework and setting an expense acquisition template by facing equipment component objects of different levels and a standardized expense decomposition structure; then establishing a structural data system of the multi-level equipment system, and automatically establishing a summary calculation relationship among data layers; setting a data acquisition item set on different levels of the expense decomposition structure, and defining an attribute set of the data acquisition item; and setting a data format, a content normal form and a verification rule of a data acquisition item according to the metadata and the data standard, performing data conversion processing on non-standard data, and detecting, extracting and marking illegal or abnormal data. The method can effectively solve the problems of structural management and evaluation analysis of the equipment multi-level multi-dimensional expense data, reduce the difficulty of the acquisition and compilation work of the equipment expense data by economic argumentation personnel, and improve the evaluation and analysis efficiency of the equipment economic data.
Description
Technical Field
The invention relates to a data acquisition method, in particular to an elastically extensible equipment expense acquisition method.
Background
Under the new technology revolution trend of equipment intelligent manufacturing, the digital cost management of the traditional equipment manufacturing process becomes a crucial link in the current industry upgrading and future industry 4.0 development process. In the traditional process of equipment manufacturing production, the equipment economic design is weak, an efficient technical means is lacked, the support economic analysis and design are matched with the digital production process, and the processes of investment management, cost control, expense management and the like of large-scale equipment are promoted to follow up with industrial development.
A set of universal and elastically extensible equipment expense data acquisition method is established, data resources under a long-term span can be integrated in a centralized manner, and the basic requirements of data resource development are met. Meanwhile, the method is suitable for compatibility and inclusion of data contents of different levels and different granularities, effectively solves the problems of difficulty in manual operation, low efficiency, single means and the like of the expense data acquisition service in a complex data environment, is already applied to a large-scale equipment economic analysis and evaluation software system, and realizes multi-mode data acquisition management in a heterogeneous cross-network environment.
Disclosure of Invention
The invention aims to solve the technical problem of providing a reasonable-design elastically-expandable equipment cost acquisition method aiming at the defects of the prior art. The method is based on a cost decomposition structure of a typical equipment type according to the acquisition management requirements of mass equipment cost data, and a generalized data acquisition method facing different types of equipment is constructed, so that flexible and extensible equipment cost data generalized acquisition process management and efficient support are realized.
In order to achieve the purpose, the invention adopts the following technical scheme:
an elastically extensible equipment expense acquisition method is characterized by comprising the following steps:
the method comprises the steps that firstly, equipment component objects of different levels in an equipment composition structure are oriented, a standardized cost decomposition structure is quoted based on equipment characteristics, an equipment cost collection overall framework is constructed, and cost collection templates of subsystems or components of all levels are set;
secondly, establishing an equipment composition structure to form a structural data system of a multi-level equipment system, and automatically establishing a summarizing calculation relation among data levels by the system;
thirdly, setting a data acquisition item set and defining an attribute set of the data acquisition items on different levels of the expense decomposition structure;
and fourthly, setting a data format, a content normal form and a verification rule of a data acquisition item according to the metadata and the data standard, performing data conversion processing on non-standard data, and detecting, extracting and marking illegal or abnormal data.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the first step, aiming at equipment component objects of different levels in an equipment composition structure, a standardized cost decomposition structure is quoted based on equipment characteristics, an equipment cost acquisition overall framework is constructed, and cost acquisition templates of subsystems or components of all levels are set, and the steps are as follows:
(1) matching standardized expense decomposition structure
Based on the composition structure and performance index of the equipment, system or equipment, extracting the characteristic information of the equipment, matching with the standardized cost decomposition structure of the equipment, and processing rules comprise the following contents:
a) extracting composition structure information of equipment, a system or equipment;
b) extracting performance index information of equipment, a system or equipment;
c) system composition information and performance index information are brought into a unified feature space, and equipment features are extracted;
d) and carrying out relevance search on the characteristic information of the equipment, the system or the equipment and the content of the standardized expense decomposition structure database to find a matching result.
And finally reading the equipment standardized cost decomposition structure obtained by matching into a user display interface.
(2) Set fee collecting template
Forming a hierarchical structure according to the equipment system, setting a cost acquisition template of each hierarchical subsystem or component, and constructing an equipment cost acquisition framework, wherein the processing rule mainly comprises the following contents:
a) traversing and setting cost acquisition templates of all subsystems and equipment step by step according to an equipment composition structure;
b) selecting a suitable expense subject set for the attributes of different systems;
c) and establishing a nested expense acquisition structure according to the hierarchical integration relation of equipment, a system and equipment to form a tree-shaped data acquisition framework.
And storing the processed tree-shaped data acquisition frame in a cost acquisition database, and performing unified management on data versions.
The technical problem to be solved by the invention can also be realized by the following technical scheme, in the second step, an equipment composition structure is established to form a multi-level equipment system structure data system, and the system automatically establishes a summarizing calculation relation between data layers:
(1) building multi-level equipment composition structure
On the basis of an equipment standardized cost decomposition structure, longitudinally thinning and transversely expanding equipment composition structures according to different types of equipment structure characteristics to form multi-level equipment composition structure data, and the method comprises the following steps:
a) based on a common equipment composition structure provided by a standardized expense decomposition structure, expanding and supplementing individual system units of equipment, and establishing tree structure information of a primary subsystem;
b) on the basis of the primary subsystem, a secondary system composition structure provided by a cost decomposition structure is combined, and secondary system structure information is longitudinally refined;
c) and further refining the three-level equipment-level structure information.
(2) Establishing a multi-level data summarization relationship
According to structural data formed by multi-level equipment, grouping upwards step by step to form a data summarizing calculation rule, and the method comprises the following steps:
a) traversing the subset data of the three-level system to form a collection calculation rule of the unit cost of the three-level system;
b) traversing all three-level subsystem data of the secondary system to form a collection calculation rule of unit cost of the secondary system;
c) traversing all secondary subsystem data of the primary system to form a collection calculation rule of the primary system unit cost;
d) and (4) collecting the cost of the system or equipment units of each level into a calculation formula, and binding the cost into the attribute data set of the corresponding data unit of the cost acquisition template.
The technical problem to be solved by the present invention can also be achieved by the following technical solution, in the third step, on different levels of the cost decomposition structure, a data acquisition item set is set, an attribute set of the data acquisition item is defined, and the processing steps are as follows:
(1) setting a set of data acquisition items
Based on the expense subject set selected by each device in the expense acquisition framework, configuring data acquisition items item by item, and supporting the expansion of the data acquisition items, wherein the processing rule mainly comprises the following contents:
a) setting data acquisition item contents of the expense departments item by item according to selected expense subject sets of different systems in the equipment expense decomposition structure;
b) loading default data acquisition item configuration information in the template according to different expense subject types;
c) extended supplementation of data acquisition items outside of the template is supported.
(2) Defining a collection of attributes for a data collection item
Aiming at the defined data acquisition items, defining the attribute information of the data acquisition items, and meeting the control requirement on the data quality in the acquisition process, wherein the processing rule mainly comprises the following contents:
a) loading a default data acquisition item attribute set in a template from metadata definition;
b) supporting the extension supplement or deletion of the data acquisition item attribute outside the template;
c) and editing or modifying the formula of the charge calculation process of the data acquisition item set.
The technical problem to be solved by the present invention can also be achieved by the following technical scheme, in the fourth step, according to metadata and data standards, a data format, a content normal form and a verification rule of a data acquisition item are set, data conversion processing is performed on non-standard data, detection, extraction and marking are performed on illegal or abnormal data, and the processing process is as follows:
(1) setting data rules for data acquisition items
Aiming at the defined data acquisition items, defining data rule information of the data acquisition items, and meeting the control requirement on the data quality in the acquisition process, wherein the processing rule mainly comprises the following contents:
a) loading a data rule set of default data acquisition items in the template from the metadata definition;
b) supporting extended supplement of data acquisition item rules outside the template;
c) the definition of the rule set of the data acquisition items comprises data types, length limitation, content formats, verification methods, required filling attributes and the like.
(2) Data acquisition process based on data acquisition framework
For the defined data acquisition framework, data contents can be filled in item by item or imported in batch, and the processing rule mainly comprises the following contents:
a) when data are filled item by item, the legality and the compliance of the data are checked in real time;
b) for data contents which do not meet the standard, carrying out classification prompt according to the problem types;
c) when the batch data is imported, a hierarchical structure is formed based on the system, hierarchical relation matching is carried out on the batch data, batch verification is carried out on data contents, and problem data are displayed in batches in a classified mode.
(3) Non-standardized data conversion
Based on data standard definition, data perfection or conversion is carried out on non-standardized data, timely switching can be carried out in two strategies of human intervention and system autonomy, and the processing rule mainly comprises the following contents:
a) loading the metadata definition and the data standard of the data acquisition item from the metadata definition;
b) traversing all data items to find non-standard data;
c) for a clear data conversion rule in the data standard, the system automatically completes data format conversion;
and for undefined semantic-level data conversion, the conversion is carried out under the condition of human intervention.
Compared with the prior art, the invention has the following remarkable advantages:
(1) the innovation adopts a method based on equipment characteristic analysis and matching to quickly form a cost acquisition template;
(2) innovatively providing a data level summarizing calculation rule and a data cross-item association calculation rule, forming a complex data checking calculation rule, and meeting the calculation requirement of automatic cost;
(3) the data collection quality constraint is driven and the automatic conversion processing of non-compliant data is innovatively based on data attribute definition and data rule definition, the execution efficiency and quality of the data collection process are greatly improved, and the manual operation difficulty is greatly reduced.
Drawings
Fig. 1 is a schematic flow chart of the elastically extensible equipment cost collection method according to the present invention.
Detailed Description
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments.
Referring to fig. 1, a method for acquiring elastically extensible equipment expenses includes the following steps:
the method comprises the following steps of firstly, facing equipment component objects of different levels in an equipment composition structure, referring to a standardized cost decomposition structure based on equipment characteristics, constructing an equipment cost acquisition overall framework, and setting cost acquisition templates of subsystems or components of all levels, wherein the detailed processing steps are as follows:
(1) matching a standardized cost decomposition structure: based on the composition structure and performance index of the equipment, system or equipment, extracting the characteristic information of the equipment, and matching with the standardized expense decomposition structure of the equipment. Firstly, extracting the composition structure information of equipment, a system or equipment, and extracting the performance index information of the equipment, the system or the equipment; system composition information and performance index information are brought into a unified feature space, and equipment features are extracted; and carrying out relevance search on the characteristic information of the equipment, the system or the equipment and the content of the standardized expense decomposition structure database to find a matching result. And finally reading the equipment standardized cost decomposition structure obtained by matching into a user display interface.
(2) Setting a cost acquisition template: and forming a hierarchical structure according to the equipment system, setting a cost acquisition template of each hierarchical subsystem or component, and constructing an equipment cost acquisition framework. Firstly, the cost collection templates of all subsystems and equipment are set in a stepwise traversal mode according to an equipment composition structure, a proper cost subject set is selected for the attributes of different systems, and a nested cost collection structure is established according to the hierarchical integration relation of the equipment, the systems and the equipment. And storing the processed tree-shaped data acquisition frame in a cost acquisition database, and performing unified management on data versions.
Secondly, establishing an equipment composition structure to form a structural data system of the multi-level equipment system, and automatically establishing a summary calculation relationship among data levels by the system, wherein the detailed steps are as follows:
(1) establishing a multi-level equipment composition structure: on the basis of an equipment standardized cost decomposition structure, longitudinal refinement and transverse expansion are carried out on an equipment composition structure according to different types of equipment structure characteristics to form multi-level equipment composition structure data. Firstly, expanding and supplementing individual system units of equipment based on a common equipment composition structure provided by a standardized expense decomposition structure, and establishing tree structure information of a primary subsystem; on the basis of the primary subsystem, a secondary system composition structure provided by a cost decomposition structure is combined, and secondary system structure information is longitudinally refined; the tertiary device-level structure information is then further refined.
(2) Establishing a multi-level data summarization relation: and forming structural data according to the multi-level equipment, and gradually collecting upwards to form a data summarizing and calculating rule. Firstly, traversing subset data of a three-level system to form a collection calculation rule of unit cost of the three-level system; traversing all three-level subsystem data of the secondary system to form a collection calculation rule of unit cost of the secondary system; and traversing all the secondary subsystem data of the primary system to form a collection calculation rule of the primary system unit cost. And (4) collecting the cost of the system or equipment units of each level into a calculation formula, and binding the cost into the attribute data set of the corresponding data unit of the cost acquisition template.
Thirdly, setting a data acquisition item set and defining an attribute set of the data acquisition items on different levels of the expense decomposition structure, wherein the detailed steps are as follows:
(1) setting a data acquisition item set: and configuring data acquisition items item by item based on the expense subject set selected by each device in the expense acquisition framework, and supporting the expansion of the data acquisition items. Setting data acquisition item contents of the expense departments item by item according to selected expense subject sets of different systems in the equipment expense decomposition structure; loading default data acquisition item configuration information in the template according to different expense subject types; and simultaneously supports the extension supplement of data acquisition items outside the template.
(2) Defining a set of attributes for a data collection item: and aiming at the defined data acquisition items, defining the attribute information of the data acquisition items and meeting the control requirement on the data quality in the acquisition process. Loading a default data acquisition item attribute set in a template from metadata definition; supporting the extension supplement or deletion of the data acquisition item attribute outside the template; and editing or modifying the formula of the charge calculation process of the data acquisition item set.
Fourthly, setting a data format, a content normal form and a verification rule of a data acquisition item according to the metadata and the data standard, performing data conversion processing on non-standard data, and detecting, extracting and marking illegal or abnormal data, wherein the detailed steps are as follows:
(1) setting data rules of the data acquisition items: and aiming at the defined data acquisition items, defining data rule information of the data acquisition items, and meeting the control requirement on the data quality in the acquisition process. Loading a data rule set of default data acquisition items in the template from the metadata definition; supporting extended supplement of data acquisition item rules outside the template; the definition of the rule set of the data acquisition items comprises data types, length limitation, content formats, verification methods, required filling attributes and the like.
(2) The data acquisition process based on the data acquisition framework comprises the following steps: for the defined data acquisition framework, the data content can be filled in item by item or imported in batch. When data are filled item by item, the legality and the compliance of the data are checked in real time; for data contents which do not meet the standard, carrying out classification prompt according to the problem types; when the batch data is imported, a hierarchical structure is formed based on the system, hierarchical relation matching is carried out on the batch data, batch verification is carried out on data contents, and problem data are displayed in batches in a classified mode.
(3) Non-normalized data conversion: based on the data standard definition, the non-standardized data is subjected to data perfection or conversion, and timely switching can be performed in two strategies of human intervention and system autonomy. Loading the metadata definition and the data standard of the data acquisition item from the metadata definition; traversing all data items to find non-standard data; for a clear data conversion rule in the data standard, the system automatically completes data format conversion; and for undefined semantic-level data conversion, the conversion is carried out under the condition of human intervention.
The method provided by the invention is used for constructing the generalized data acquisition method for different types of equipment based on the cost decomposition structure of a typical equipment type according to the acquisition management requirements of mass equipment cost data. The method comprises the steps of establishing an equipment cost collection overall framework facing equipment component objects and standardized cost decomposition structures of different levels, setting a cost collection template, establishing a multi-level equipment system structural data system, automatically establishing a summarizing calculation relation among data levels, setting a data collection item and an attribute set, setting a data rule according to metadata and data standards, detecting, extracting and marking the data, automatically collecting and summarizing cost data, and forming a multi-level cost summarizing report. The elastically extensible equipment cost collection method can be widely applied to economic analysis and cost management of various types of equipment, effectively solves the problem of structural management and evaluation analysis of multi-level and multi-dimensional cost data of the equipment, greatly reduces the difficulty of collection and compilation work of the equipment cost data by economic argumentation personnel, and greatly improves the evaluation and analysis efficiency of the equipment economic data.
After the method is realized, data analysis personnel can flexibly operate and develop equipment expense data acquisition operation, the requirement of individualized and elastically expanded equipment expense data acquisition under different service scenes is met, the method can adapt to the compatibility and the inclusion of data contents of different levels and different granularities, and the problems of difficult manual operation, low efficiency, single means and the like of expense data acquisition services under complex data environments are effectively solved. The data resource preparation and data conversion integration work is automatically processed by a system background, and the whole data processing process is visual, traceable and controllable, so that the overall requirements of the intelligent manufacturing field of equipment and the comprehension and standardization of economic data are met. The elastically extensible equipment expense acquisition method can be applied to application software such as price reporting compilation, economic analysis, cost evaluation, cost control, investment evaluation and the like in the equipment manufacturing industry after being modified and expanded appropriately.
The above description is only for the preferred embodiment of the present invention, but the scope of the present invention is not limited thereto, and any person skilled in the art should be considered to be within the technical scope of the present invention, and the technical solutions and the inventive concepts thereof according to the present invention should be equivalent or changed within the scope of the present invention.
Claims (5)
1. An elastically extensible equipment cost acquisition method is characterized by comprising the following steps:
the method comprises the steps that firstly, equipment component objects of different levels in an equipment composition structure are oriented, a standardized cost decomposition structure is quoted based on equipment characteristics, an equipment cost collection overall framework is constructed, and cost collection templates of subsystems or components of all levels are set;
firstly, establishing an equipment composition structure to form a structural data system of a multi-level equipment system, and automatically establishing a summary calculation relationship among data levels by the system;
firstly, setting a data acquisition item set and defining an attribute set of the data acquisition items on different levels of a cost decomposition structure;
firstly, setting a data format, a content normal form and a verification rule of a data acquisition item according to metadata and a data standard, performing data conversion processing on non-standard data, and detecting, extracting and marking illegal or abnormal data.
2. The method for acquiring the elastically extensible equipment cost according to claim 1, wherein in the first step, the equipment cost acquisition overall framework is constructed by referring to the standardized cost decomposition structure based on the equipment features facing to the equipment component objects of different levels in the equipment composition structure, and the cost acquisition templates of all level subsystems or components are set, and the method comprises the following steps:
(1) matching standardized expense decomposition structure
Based on the composition structure and performance index of the equipment, system or equipment, extracting the characteristic information of the equipment, matching with the standardized cost decomposition structure of the equipment, and processing rules comprise the following contents:
extracting composition structure information of equipment, a system or equipment;
extracting performance index information of equipment, a system or equipment;
the composition structure information and the performance index information are brought into a unified feature space, and equipment features are extracted;
carrying out relevance search on the equipment characteristics and the contents of the standardized expense decomposition structure database, and searching for a matching result;
finally, reading the matched equipment standardized cost decomposition structure into a user display interface;
(2) set fee collecting template
Forming a hierarchical structure according to the equipment system, setting a cost acquisition template of each hierarchical subsystem or component, and constructing an equipment cost acquisition framework, wherein the processing rule mainly comprises the following contents:
traversing and setting cost acquisition templates of all subsystems and equipment step by step according to an equipment composition structure;
selecting corresponding expense subject sets for the attributes of different systems;
establishing a nested expense acquisition structure according to the hierarchical integration relation of equipment, a system and equipment to form a tree-shaped data acquisition framework;
and storing the processed tree-shaped data acquisition frame in a cost acquisition database, and performing unified management on data versions.
3. The elastically extensible equipment cost collection method as claimed in claim 1, wherein in the second step, an equipment composition structure is established to form a multi-level equipment system structure data system, and the system automatically establishes a summary calculation relationship between data levels:
(1) building multi-level equipment composition structure
On the basis of an equipment standardized cost decomposition structure, longitudinally thinning and transversely expanding equipment composition structures according to different types of equipment structure characteristics to form multi-level equipment composition structure data, and the method comprises the following steps:
based on a common equipment composition structure provided by a standardized expense decomposition structure, expanding and supplementing individual system units of equipment, and establishing tree structure information of a primary subsystem;
on the basis of the primary subsystem, a secondary system composition structure provided by a cost decomposition structure is combined, and secondary system structure information is longitudinally refined;
further refining the three-level equipment level structure information;
(2) establishing a multi-level data summarization relationship
According to structural data formed by multi-level equipment, grouping upwards step by step to form a data summarizing calculation rule, and the method comprises the following steps:
traversing the subset data of the three-level system to form a collection calculation rule of the unit cost of the three-level system;
traversing all three-level subsystem data of the secondary system to form a collection calculation rule of unit cost of the secondary system;
traversing all secondary subsystem data of the primary system to form a collection calculation rule of the primary system unit cost;
and binding the fee collection calculation rule of the system or equipment units of each level into the attribute data set of the corresponding data unit of the fee collection template.
4. The method of claim 1, wherein in the third step, a set of data collection items is set at different levels of the cost decomposition structure, and a set of attributes of the data collection items is defined, and the processing steps are as follows:
(1) setting a set of data acquisition items
Based on the expense subject set selected by each device in the expense acquisition framework, configuring data acquisition items item by item, and supporting the expansion of the data acquisition items, wherein the processing rule mainly comprises the following contents:
setting data acquisition item contents of the expense departments item by item according to selected expense subject sets of different systems in the equipment expense decomposition structure;
loading default data acquisition item configuration information in the template according to different expense subject types;
supporting extended supplement of data acquisition items outside the template;
(2) defining a collection of attributes for a data collection item
Aiming at the defined data acquisition items, defining the attribute information of the data acquisition items, and meeting the control requirement on the data quality in the acquisition process, wherein the processing rule mainly comprises the following contents:
loading a default data acquisition item attribute set in a template from metadata definition;
supporting the extension supplement or deletion of the data acquisition item attribute outside the template;
and editing or modifying the formula of the charge calculation process of the data acquisition item set.
5. The elastically extensible equipment cost collection method according to claim 1, wherein in the fourth step, the data format, the content paradigm and the verification rule of the data collection items are set according to the metadata and the data standards, the data conversion processing is performed on the non-standard data, and the detection, extraction and marking are performed on the illegal or abnormal data, and the processing procedures are as follows:
(1) setting data rules for data acquisition items
Aiming at the defined data acquisition items, defining data rule information of the data acquisition items, and meeting the control requirement on the data quality in the acquisition process, wherein the processing rule mainly comprises the following contents:
loading a data rule set of default data acquisition items in the template from the metadata definition;
supporting extended supplement of data acquisition item rules outside the template;
the definition of the data acquisition item rule set comprises data type, length limit, content format, verification method and mandatory fill attribute;
(2) data acquisition process based on data acquisition framework
For a defined data acquisition framework, filling data contents item by item or importing data contents in batch, wherein the processing rule mainly comprises the following contents:
when data are filled item by item, the legality and the compliance of the data are checked in real time;
for data contents which do not meet the standard, carrying out classification prompt according to the problem types;
when batch data is imported, hierarchical relation matching is carried out on the batch data based on a system composition hierarchical structure, batch verification is carried out on data contents, and problem data are displayed in a classified and batch mode;
(3) non-standardized data conversion
Based on data standard definition, performing data perfection or conversion on non-standardized data, and timely switching between human intervention strategies and system autonomous strategies, wherein the processing rules mainly comprise the following contents:
loading the metadata definition and the data standard of the data acquisition item from the metadata definition;
traversing all data items to find non-standard data;
for a clear data conversion rule in the data standard, the system automatically completes data format conversion;
and for undefined semantic-level data conversion, the conversion is carried out under the condition of human intervention.
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Citations (4)
| Publication number | Priority date | Publication date | Assignee | Title |
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| WO2012094017A1 (en) * | 2011-01-07 | 2012-07-12 | Co-Exprise, Inc. | Total cost management system, method, and apparatus |
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