A benchmark model construction application method, device, equipment and storage medium

Abstract

The present invention discloses a benchmark model construction application method, device, equipment and storage medium, which relates to the field of digital technology. The method includes constructing a sub-model based on key variable parameters of each cost sub-item and coefficients corresponding to the key variable parameters, and obtaining a cost benchmark model according to the sub-model of each cost sub-item; dynamically adjusting key variable parameters and coefficients according to the actual scenario requirements of cost calculation, and maintaining the key variable parameters and coefficients; performing a cost benchmark model, and selecting key variable parameters and coefficients in the cost benchmark model sub-model, obtaining a new cost benchmark model and encapsulating it, and performing cost calculation based on the encapsulated new cost benchmark model. The present application can efficiently realize the automatic calculation of relevant costs in automobile production and application, and improve the efficiency and accuracy of cost calculation.

Description

Technical Field

[0001] The present application relates to the field of digital technology, and specifically to a benchmark model construction application method, device, equipment and storage medium. Background Art

[0002] In the field of automobile manufacturing and application, the calculation of various costs is generally carried out through manual calculation.

[0003] Costs are calculated manually, which makes it difficult to standardize cost calculations and update cost elements in a timely and accurate manner. Manual calculations also lead to a large workload and difficulty in improving measurement efficiency. Therefore, how to efficiently calculate costs related to automobile production and application is an issue that needs to be addressed urgently. Summary of the invention

[0004] The present application provides a benchmark model construction application method, device, equipment and storage medium, which can effectively realize the automatic calculation of relevant costs in automobile production and application, and improve the efficiency and accuracy of cost calculation.

[0005] In a first aspect, an embodiment of the present application provides a benchmark model construction application method, the benchmark model construction application method comprising:

[0006] Construct sub-models based on key variable parameters of each expense sub-item and the coefficients corresponding to the key variable parameters, and obtain the expense benchmark model based on the sub-model of each expense sub-item;

[0007] According to the actual scenario requirements of cost calculation, dynamically adjust key variable parameters and coefficients, and maintain key variable parameters and coefficients;

[0008] Conduct cost benchmarking model, and select key variable parameters and coefficients in the cost benchmarking model sub-model, obtain and encapsulate the new cost benchmarking model, and perform cost estimation based on the encapsulated new cost benchmarking model.

[0009] In combination with the first aspect, in one implementation,

[0010] The cost benchmark model includes a road test benchmark model, a bench test benchmark model, a trial production special parts procurement benchmark model and a quantity and price benchmark model, and each cost benchmark model includes at least one sub-model;

[0011] The cost sub-items corresponding to the road test benchmark model include fuel, site use, loading and unloading, labor commission, vehicle maintenance, road and bridge crossing, test commission, consumables, and kinetic energy;

[0012] The cost sub-items corresponding to the bench test benchmark model include fuel, consumables, kinetic energy, mold / tool / fixture depreciation, mold / tool / fixture maintenance, equipment depreciation, equipment maintenance, building depreciation, building maintenance, labor costs, management costs, financial costs, and test entrustment;

[0013] The cost sub-items corresponding to the benchmark model for the purchase of trial-produced special parts include 3D sand core casting, ABS CNC machining, body sheet metal, laser cutting, rubber tube crimping, nylon tube crimping, 3D printing, machining center, carbon dioxide shielded welding, spot welding, cathode electrophoresis, black paint, and heat treatment;

[0014] The cost sub-items corresponding to the quantity-price benchmarking model include departmental expenses.

[0015] In combination with the first aspect, in one implementation,

[0016] In the road test benchmark model and bench test benchmark model, the sub-model of the cost sub-item is specifically:

[0017] Fi=u*i+C

[0018] Among them, Fi represents the expense sub-item, that is, the expense calculation of the expense sub-item, i represents the key variable parameter used to determine Fi in the current expense sub-item, u is the coefficient of the corresponding key variable parameter, that is, the rate of the key variable parameter i, and C is a constant, which represents the fixed cost when the key variable parameter i is 0;

[0019] In the benchmark model for purchasing trial-production special parts, the sub-model of the cost sub-item is specifically as follows:

[0020] Fi=A n *X n +A n-1 *X n-1 +...+C

[0021] Among them, Fi represents the expense sub-item, X n Indicates the nth key variable parameter used to determine Fi in the current cost sub-item, A n represents the coefficient corresponding to the nth key variable parameter, and C is a constant;

[0022] In the quantity-price benchmark model, the sub-model of the expense sub-item is specifically as follows:

[0023] Fi=d*L 1 *L 2 *...L n

[0024] Among them, Fi represents the expense sub-item, L n It represents the nth key variable parameter in the cost sub-item, and d represents the coefficient.

[0025] In combination with the first aspect, in one implementation,

[0026] The key variable parameters include fixed parameters and random parameters;

[0027] The fixed parameters are individual parameters of the function CASE, and the fixed parameters are bound to the function CASE in a table form;

[0028] The random parameters are common parameters of the functional CASE, which can be randomly increased or decreased. When the key variable parameters and coefficients are dynamically adjusted, the key variable parameters corresponding to the random parameters and the corresponding coefficients are adjusted.

[0029] In combination with the first aspect, in one implementation, the cost benchmarking model is performed, and the key variable parameters and coefficients in the cost benchmarking model sub-model are selected to obtain a new cost benchmarking model and encapsulate it, specifically as follows:

[0030] Build a benchmark model calling interface and select the corresponding cost benchmark model based on cost estimation requirements;

[0031] Among all the function cases of the selected cost benchmark model, select the function cases with required fixed parameters and the function cases with random parameters, so as to determine the key variable parameters, and select and determine the corresponding coefficients of the key variable parameters;

[0032] Based on the determined key variable parameters and coefficients, a new cost benchmark model is encapsulated.

[0033] In conjunction with the first aspect, in one implementation, the cost benchmarking model further includes optimizing the corresponding coefficients of key variable parameters, specifically:

[0034] Collect data on project budget execution applications and build the first database containing all key variable parameters indexed by functional CASE and execution application number;

[0035] Collect data on project budget write-off applications and build a second database with details of write-off expenses indexed by function CASE and execution application number;

[0036] Specify the time range and key variable parameters to be analyzed, and associate the first database with the second database to obtain a third database;

[0037] Select key variable parameters to index in the third database, obtain the details of the written-off expenses within the specified time range, and generate a fourth database;

[0038] With the written-off expense details as the Y-axis and the selected key variable parameters as the X-axis, a coordinate system is established, and the data of the fourth database is plotted into the established coordinate system;

[0039] The trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated optimized coefficient corresponding to the key variable parameters.

[0040] In combination with the first aspect, in one implementation, the trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated optimized coefficient corresponding to the key variable parameter, specifically:

[0041] Determine the trend line based on the coordinate points in the coordinate system;

[0042] Remove the abnormal points on both sides of the trend line so that all the remaining coordinate points are evenly distributed on both sides of the trend line;

[0043] Based on the slope of the trend line after the outlier point is proposed, the updated and optimized coefficients corresponding to the key variable parameters are obtained.

[0044] In a second aspect, an embodiment of the present application provides a benchmark model construction application device, the benchmark model construction application device comprising:

[0045] A construction module, which is used to construct a sub-model based on the key variable parameters of each expense sub-item and the coefficients corresponding to the key variable parameters, and obtain the expense benchmark model according to the sub-model of each expense sub-item;

[0046] The maintenance module is used to dynamically adjust key variable parameters and coefficients according to the actual scenario requirements of cost calculation, and to maintain key variable parameters and coefficients;

[0047] The calculation module is used to carry out the cost benchmark model, and select the key variable parameters and coefficients in the cost benchmark model sub-model, obtain the new cost benchmark model and encapsulate it, and perform cost calculation based on the encapsulated new cost benchmark model.

[0048] In a third aspect, an embodiment of the present application provides a benchmark model building application device, which includes a processor, a memory, and a benchmark model building application stored in the memory and executable by the processor, wherein when the benchmark model building application is executed by the processor, the steps of the benchmark model building application method described above are implemented.

[0049] In a fourth aspect, an embodiment of the present application provides a computer-readable storage medium, on which a benchmark model building application is stored, wherein when the benchmark model building application is executed by a processor, the steps of the benchmark model building application method described above are implemented.

[0050] The beneficial effects brought by the technical solution provided in the embodiments of the present application include:

[0051] By constructing a sub-model based on the key variable parameters of each cost sub-item and the coefficients corresponding to the key variable parameters, and obtaining the cost benchmark model based on the sub-model of each cost sub-item, and then dynamically adjusting the key variable parameters and coefficients according to the actual scenario requirements of the cost measurement, the key variable parameters and coefficients are maintained, and finally the cost benchmark model and the key variable parameters and coefficients in the cost benchmark model sub-model are selected to obtain a new cost benchmark model and encapsulate it, and cost calculation is performed based on the encapsulated new cost benchmark model, thereby efficiently realizing the automatic calculation of relevant costs in automobile production and application, and improving the efficiency and accuracy of cost calculation. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] Figure 1 A flowchart of a benchmark model construction application method for this application;

[0053] Figure 2 A schematic diagram of a structure of a benchmark model construction application device for this application;

[0054] Figure 3 Schematic diagram of the hardware structure of the application equipment built for the benchmark model of this application. DETAILED DESCRIPTION

[0055] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of this application.

[0056] In order to make the objectives, technical solutions and advantages of the present application clearer, the implementation methods of the present application will be further described in detail below with reference to the accompanying drawings.

[0057] In a first aspect, an embodiment of the present application provides a benchmark model construction application method.

[0058] In one embodiment, referring to Figure 1 , Figure 1 The following is a flow chart of the application method of the benchmark model for this application. Figure 1 As shown in the figure, the benchmark model construction and application methods include:

[0059] S1: Construct a sub-model based on the key variable parameters of each expense sub-item and the coefficients corresponding to the key variable parameters, and obtain the expense benchmark model based on the sub-model of each expense sub-item;

[0060] It should be noted that the cost benchmark model includes a road test benchmark model, a bench test benchmark model, a trial special parts procurement benchmark model and a quantity and price benchmark model, and each cost benchmark model includes at least one sub-model. That is, for the cost benchmark model, when it includes multiple sub-models, the sum of the calculation results of each sub-model is the cost calculation result of the current cost benchmark model. When only one sub-model is included, the settlement result of the sub-model is the cost calculation result of the current cost benchmark model. For each cost sub-item, when it includes multiple key variable parameters, the sum of the results obtained after each key variable parameter and the corresponding coefficient are calculated is the calculation result of the sub-model corresponding to the current cost sub-item. When only one key variable parameter is included, the calculation result after the key variable parameter and the corresponding coefficient are calculated is the calculation result of the sub-model corresponding to the current cost sub-item. It can be understood that based on the calculation of the corresponding key variable parameters and coefficients, the corresponding cost sub-items are calculated.

[0061] Key variable parameters include fixed parameters and random parameters. Fixed parameters are individual parameters of functional cases, and fixed parameters are bound to functional cases in a table format. Random parameters are common parameters of functional cases, which can be increased or decreased randomly. When dynamically adjusting key variable parameters and coefficients, the key variable parameters corresponding to the random parameters and the corresponding coefficients are adjusted. Functional cases are specific functional descriptions of key variable parameters.

[0062] S2: Dynamically adjust key variable parameters and coefficients according to actual cost calculation scenario requirements, and maintain key variable parameters and coefficients;

[0063] S3: Conduct cost benchmarking model, and select key variable parameters and coefficients in the cost benchmarking model sub-model, obtain a new cost benchmarking model and encapsulate it, and perform cost estimation based on the encapsulated new cost benchmarking model.

[0064] Furthermore, in one embodiment, the cost sub-items corresponding to the road test benchmark model include fuel, site use, loading and unloading, labor commission, vehicle maintenance, road and bridge crossing, test commission, consumables, and kinetic energy. In the cost benchmark model and bench test benchmark model, the sub-models of the cost sub-items are specifically:

[0065] Fi=u*i+C

[0066] Among them, Fi represents the expense sub-item, that is, the expense calculation of the expense sub-item, i represents the key variable parameter used to determine Fi in the current expense sub-item, u is the coefficient of the corresponding key variable parameter, that is, the rate of the key variable parameter i, and C is a constant, which represents the fixed cost when the key variable parameter i is 0;

[0067] That is, in the actual application process, the direct costs related to the research and development of vehicle road tests include 13 types of costs, such as fuel, site use, loading and unloading, labor commissions, vehicle maintenance, road and bridge crossings, test commissions, consumables, and kinetic energy. Each cost is a sub-model. For the sub-model of the cost sub-item, the variable i is the key variable parameter that determines Fi in the function CASE (example).

[0068] In the road test benchmark model, the functional CASE (key variable parameters) include the type of sample vehicle, the number of sample vehicle axles, the tonnage of the sample vehicle, the fuel type, the road condition BOM, the functional CASE operation standard, etc. The key variable parameters are divided into fixed parameters and random parameters.

[0069] Fixed parameters are individual parameters of the functional case, which may include road condition mileage, test category (four-level accounting subject), site rental time, test cycle, etc., and are bound to the functional case in a table. The test category records the four-level expense subject. Random parameters are common parameters of the functional case, including the type of sample vehicle, the number of axles of the sample vehicle, the tonnage of the sample vehicle, the fuel type, etc., which are randomly filled in the calling interface. Set random parameters to limit the number of derivatives of the functional case.

[0070] After the key variable parameters in the road test benchmark model are determined, it is also necessary to set the coefficient list of the key variable parameters. In the coefficient list, the row fields and column fields are key variable parameters and can be maintained. The coefficient list is divided into two categories: multiple coefficient lists and single coefficient lists. In a single coefficient list, the rates such as spare parts costs and performance site usage fees are constants, and the list is simplified to a single fixed parameter; the multiple coefficient list includes: a two-dimensional list of fuel consumption coefficients, a two-dimensional list of vehicle maintenance coefficients, a two-dimensional list of road and bridge coefficients, a two-dimensional list of site use coefficients, a one-dimensional list of loading and unloading coefficients, a one-dimensional list of driver rental coefficients, and a one-dimensional list of speed standard coefficients.

[0071] For the two-dimensional list of fuel consumption coefficients, the list row fields are set to fuel type + sample vehicle characteristics (sample vehicle category, number of axles, tonnage), and the list column fields are set to road condition BOM. As the values ​​of the list row fields and column fields change, the coefficients corresponding to the table cells change accordingly; for the two-dimensional list of vehicle maintenance coefficients and the two-dimensional list of road and bridge crossing coefficients, the list row fields are set to sample vehicle characteristics, and the list column fields are set to road condition BOM. As the values ​​of the list row fields and column fields change, the coefficients corresponding to the table cells change accordingly; for the two-dimensional list of site use coefficients, the list row fields are set to sample vehicle tonnage, and the list column fields are set to road condition BOM. As the values ​​of the list row fields and column fields change, the coefficients corresponding to the table cells change accordingly; for the one-dimensional list of loading and unloading coefficients, the list row fields are set to test category + sample vehicle category + sample vehicle axle number. As the values ​​of the list row fields change, the coefficients corresponding to the table cells change accordingly; for the one-dimensional list of driver rental coefficients and the one-dimensional list of speed standard coefficients, the list row fields are set to road condition BOM. As the road conditions change, the coefficients corresponding to the table cells change accordingly.

[0072] After determining the key variable parameters and the corresponding coefficients, the calculation logic of the cost sub-items and calibration function CASE can be encapsulated into a function package that can be called at any time, referred to as the road test benchmark model. This function package associates the cost sub-model into a whole through the key variable parameters in the function CASE, and at the same time presets the calling conditions of each coefficient list, and finally outputs the cost benchmark and cost items of the function CASE.

[0073] In this application, the cost sub-items corresponding to the bench test benchmark model include fuel, consumables, kinetic energy, mold / tool / fixture depreciation, mold / tool / fixture maintenance, equipment depreciation, equipment maintenance, house depreciation, house maintenance, labor costs, management costs, financial costs, and test commissions. That is, in the actual application process, the cost of R&D bench tests includes 13 items, including fuel, consumables, kinetic energy, mold / tool / fixture depreciation, mold / tool / fixture maintenance, equipment depreciation, equipment maintenance, house depreciation, house maintenance, labor costs, management costs, financial costs, and test commissions.

[0074] For the bench test benchmark model, the functional CASE (key variable parameters) includes test category, operating bench time, measurement and debugging bench time, prototype model, fuel type, functional CASE operation standard, etc.

[0075] First, we need to build the stage rate. The bench test has 9 stages: preparation-technical planning, preparation-installation, preparation-bench, operation, operation-measurement and debugging, closing-bench, closing-disassembly, closing-measurement, closing-report output. The number of samples (functional CASE operation standards used to calculate the stage rate) for calculating each stage rate is different. Except for the operation stage, the number of samples for the other 7 stages is one.

[0076] Then build auxiliary databases for consumables, equipment, fixtures, measuring tools, etc. Consumables library structure: consumables name, consumables unit price, etc.; equipment library structure: equipment name, equipment model, equipment original value, equipment host power, equipment compressed air, etc.; fixture library structure: fixture name, code, unit price, life unit, life, etc.; measuring tool library structure: measuring tool name, code, unit price, life unit, life, etc.

[0077] Then enter the samples of the non-operation stage. For the same type of test, 3 preparation stages and 4 finishing stages, a total of 7 samples are entered. For tests of different categories, if the operating standards of these 7 stages are similar, the samples are shared, otherwise, the samples are created separately. The sample name is composed of stage characteristics + test category characteristics. The sample content is entered in sequence according to the test steps. The fields of each record are: process name, operation time; consumable name, unit consumption of consumables; equipment name, working time; fixture name, quantity; measuring and inspection tool name, quantity; operator category, number of people, and energy ratio.

[0078] Then enter the operation phase samples. The number of operation phase samples depends on the weight of the total sample hours in the total annual hours of the test of this type. The initial weight is set to 80% and can be modified. The number of operation phase samples is different for different types of tests.

[0079] Then, the stage rate is constructed. First, for the first sample, the sub-model is used to calculate the detailed expenses incurred in each process; second, the detailed expenses of all processes of the same sample are summed up and the rates are calculated; third, the detailed expenses of all samples in this stage are weighted and summed up, and the rates are calculated; finally, the weighted rates of each detailed expense in this stage and the weighted total rate are recorded in the category rate association table.

[0080] Finally, a category-rate association table is constructed to record the rates and details of the nine stages of the test category. The rates of missing stages are recorded as 0; any change or replacement of any of the nine stages will generate a new test category.

[0081] The rates of each stage registered in the category rate association table of a bench test are combined with the key variable parameters of the functional case to calibrate the cost items and benchmarks of the test, and encapsulate them into a function package that can be called at any time, referred to as the bench test benchmark model. This function package associates the cost sub-model into a whole by the key variable parameters in the functional case, and presets the calling conditions of the rates of each stage at the same time, and finally outputs the cost benchmark and cost items of the functional case.

[0082] Further, in one embodiment, the cost sub-items corresponding to the benchmark model for trial-produced special parts procurement include 3D sand core casting, ABS CNC machining, body sheet metal, laser cutting, rubber tube crimping, nylon tube crimping, 3D printing, machining center, carbon dioxide shielded welding, spot welding, cathode electrophoresis, black paint, and heat treatment; in the benchmark model for trial-produced special parts procurement, the sub-models of the cost sub-items are specifically:

[0083] Fi=A n *X n +A n-1 *X n-1 +...+C

[0084] Among them, Fi represents the expense sub-item, X n Indicates the nth key variable parameter used to determine Fi in the current cost sub-item, A n represents the coefficient corresponding to the nth key variable parameter, and C is a constant;

[0085] That is, in the actual application process, for the trial production processes in the research and development process, including 3D sand core casting, ABS CNC machining, body sheet metal, laser cutting, rubber tube crimping, nylon tube crimping, 3D printing, machining center, carbon dioxide shielded welding, spot welding, cathode electrophoresis, black paint, heat treatment and more than 40 other types, the procurement cost (i.e. cost sub-item) of each trial production process is a sub-model. In the sub-model of the cost sub-item, X n is an independent variable.

[0086] For the benchmark model for trial-produced special parts procurement, the database structure corresponding to the function CASE (key variable parameters) includes independent variables, independent variable names, etc. The independent variable names include part net weight, material cost, part area, part volume, cutting circumference, pipe diameter, pipe thickness, pipe length, number of joints, etc.

[0087] For the construction of the database corresponding to the functional CASE (key variable parameters), first preset the trial production process sub-model interactive interface, and enter the fields: process category, mathematical model, accuracy coefficient, minimum value of independent variable, maximum value of independent variable, etc. The database is indexed by process category; then preset the procurement functional CASE entry interface, collect the functional CASE to be purchased, and enter the fields: functional CASE (material number), CASE name (material name), etc.

[0088] All trial production process sub-models are encapsulated into a function package that can be called at any time, called the trial production special parts procurement benchmark model. This function package indexes the sub-model through the process category, brings in the independent variables and performs logical operations according to the sub-model, and finally outputs the cost benchmark and cost account of the function CASE.

[0089] Furthermore, in one embodiment, the expense sub-items corresponding to the quantity-price benchmark model include department expenses. In the quantity-price benchmark model, the sub-models of the expense sub-items are specifically:

[0090] Fi=d*L 1 *L 2 *...L n

[0091] Among them, Fi represents the expense sub-item, L n It represents the nth key variable parameter in the cost sub-item, and d represents the coefficient.

[0092] For the construction of the quantity-price benchmark model, first preset the department expense number, and set the fields as: expense number, expense name, department, collection object (four-level accounting subject), auditor, approver, expense administrator, etc.; then preset the human-computer interaction interface, and when selecting the expense number, adding a functional case, checking the four-level accounting subject and the five-level accounting subject, the functional case creator can preset the "quantity*price benchmark model". Then select the composite measurement unit, such as yuan / (vehicle*hour), yuan / (vehicle*time), yuan / (trip*person), yuan / (person*month), yuan / (seat*module*time), yuan / (book*hour*person), etc., to construct the sub-model of the expense sub-item, L n are independent variables, and the independent variables are multiplied.

[0093] All function cases under the expense number are encapsulated into a function package that can be called at any time, called the quantity-price benchmark model, which is subdivided into the "standard-common" standard type. This function package specifies the quantity-price benchmark model through the function case, brings in the independent variables and performs logical operations according to the model, and finally outputs the cost benchmark and expense account of the function case.

[0094] Furthermore, in one embodiment, according to the actual scenario requirements of cost estimation, key variable parameters and coefficients are dynamically adjusted and maintained, that is, by constructing a maintenance interface for key variable parameters and coefficients, the scope of application of each cost benchmark model is expanded.

[0095] The maintenance of key variable parameters and coefficients in the road test benchmark model includes the following steps:

[0096] S501: Maintenance cost account interface. The direct cost of the R&D project is preset as variables, and the variable names are: fuel, site use, loading and unloading, labor commission, vehicle maintenance, road and bridge crossing, test commission, consumables, kinetic energy, etc., and the corresponding five-level accounting accounts are used to assign values ​​one by one.

[0097] S502: Interface for maintaining random parameters. Random parameters such as sample vehicle type, sample vehicle axle number, sample vehicle tonnage, fuel type, etc. are displayed in sub-tab pages, stored in the database, and can be deleted, modified, and added. Changes to random parameters will trigger synchronous changes to the column fields in the coefficient list.

[0098] Specifically, for the Tab page of the number of axles of the sample vehicle, in addition to recording the number of axles, it also binds related parameters such as the gross load mass, main vehicle equipment mass, and trailer equipment mass; for the Tab page of the sample vehicle category, in addition to maintaining the sample vehicle category - cargo, engineering, traction, electric, hybrid (oil-electric), natural gas, etc., it also binds related parameters such as the number of axles of the sample vehicle, the tonnage of the sample vehicle, and the fuel type.

[0099] S503: The interface for maintaining fixed parameters is also the interface for maintaining functional cases. Fixed parameters are fixed relative to a specific functional case, but are variable for different functional cases. For example, the mileage of road conditions is certain for a certain functional case, but different for another functional case. The road condition BOM is an independent Tab page, which is associated with the fixed parameter database structure and coefficient list structure bound to the functional case. The road condition BOM can be deleted, modified, and added, and the road condition position can also be swapped. Changes to the road condition BOM structure will trigger synchronous changes to the fixed parameter database structure and the column fields in the coefficient list.

[0100] S504: Interface for maintaining coefficient list. Each coefficient list is an independent Tab page, which can be maintained by the system authorized person or automatically updated by the system.

[0101] The maintenance of key variable parameters and coefficients in the bench test benchmark model includes the following steps:

[0102] S511: Construct the three-level maintenance interface of the expense sub-model. The first level maintenance is in the formula setting interface. Models involving life units are maintained in the "Models associated with life units" Tab page. Life units include: piece, time, day, month, year, etc., and the expense calculation model will also change accordingly; models not involving life units are maintained in the "Five-level expense account" Tab page. Each expense detail corresponds to a sub-model.

[0103] The second level of maintenance is in the list of equipment, fixtures, measuring tools, etc. When some equipment, fixtures / measurement and measurement have special requirements, the related kinetic energy, depreciation, and maintenance cost sub-models are bound to them and maintained separately. The third level of maintenance is in the audit interface. In the model audit process, the cost sub-model is modified by adjusting the precision coefficient. The precision coefficient, the system default value is 1. The interface of the maintenance cost account. The bench test costs are preset as variables, and the variable names are: fuel, consumables, kinetic energy, mold / tool / fixture depreciation, mold / tool / fixture maintenance, equipment depreciation, equipment maintenance, house depreciation, house maintenance, direct labor, administrative expenses, financial expenses, test commissions, etc., and they are assigned one by one with the corresponding five-level accounting accounts.

[0104] S512: Maintain parameters. Specifically, maintain random parameters. Random parameters such as prototype model and fuel type are displayed in sub-Tab pages, stored in the database, and can be deleted, modified and added. Prototype model Tab page: In addition to recording the engine model, it also binds related parameters such as engine rated power, performance consumption conversion rate, reliability consumption conversion rate, etc. Specifically, maintain fixed parameters, which is also the interface for maintaining functional CASE. While maintaining functional CASE, fixed parameters such as test category, operating bench time, and measurement and debugging bench time are also maintained.

[0105] S513: Maintenance phase rate. The interface for maintaining samples. The maintenance cycle of samples is set to one year. For samples with little change in process content, click on the original sample and make partial modifications. For samples with large changes in process content or samples that need to be replaced, delete the original sample before entering it, and then re-enter it. The interface for maintaining phase rates. Check the "status bar" of the phase rate interface to understand the maintenance tasks and progress. "Samples to be created": prompts that the samples for this phase have not been entered yet, and the samples need to be entered in the sample maintenance interface; "Formulas to be confirmed": prompts that the parameters for fuel consumption calculation need to be entered - check the test type, check the consumption conversion rate, enter the machine hours, etc.; "Submission for review": prompts that the review process needs to be triggered; "Pending review": prompts that the maintenance results are under review; "Available": prompts that the maintenance is complete.

[0106] Maintain the interface of the category rate association table, check the stage name with the "usable" status, update the 9 stages of the bench test, and redefine the category test.

[0107] The maintenance of key variable parameters and coefficients in the benchmark model for trial production of special parts procurement includes the following steps:

[0108] S521: Interface for maintaining expense accounts. Preset the trial production special parts purchase as a variable, the variable name is: parts purchase, and assign values ​​with the corresponding five-level accounting accounts.

[0109] S522: Interface for maintaining independent variables. Add: enter the sub-model to add new requirement variables; Modify: change the independent variables; Delete: discard the original definition.

[0110] S523: Interface for maintaining the trial production process sub-model. The sub-model is a mathematical model, which is entered according to the general principles of Excel. Except for the independent variables defined in the independent variable library, the rest are treated as constants.

[0111] S524: Interface for maintaining the purchase function CASE. All parts included in the standard function CASE management scope are entered through this interface.

[0112] Furthermore, in one embodiment, the cost benchmarking model and the selection of key variable parameters and coefficients in the cost benchmarking model sub-model are performed to obtain a new cost benchmarking model and encapsulate it, specifically:

[0113] S301: construct a benchmark model calling interface, and select a corresponding cost benchmark model based on cost calculation requirements;

[0114] S302: Selecting the required fixed parameter function cases and random parameter function cases from all the function cases of the selected cost benchmark model, thereby determining key variable parameters, and selecting and determining the corresponding coefficients of the key variable parameters;

[0115] S303: Based on the determined key variable parameters and coefficients, a new cost benchmark model is encapsulated.

[0116] The above process is explained below using the road test benchmark model as an example.

[0117] Build the model calling interface and set up three layers of picture-in-picture: the first layer, check the "road test benchmark model" and the "standard type" of the model subdivision; the second layer, check the functional case; the third layer, check the random parameters of the functional case. After checking, the packaged functional package of the road test benchmark model will calibrate the detailed expenses and expense items of the selected functional case.

[0118] Furthermore, in one embodiment, the cost benchmarking model further includes optimizing the corresponding coefficients of key variable parameters, specifically:

[0119] S401: Collect data of project budget execution application, and construct a first database containing all key variable parameters with function CASE and execution application number as index;

[0120] S402: Collect data on project budget write-off applications, and construct a second database containing details of write-off expenses indexed by function CASE and execution application number;

[0121] S403: specifying the time range and key variable parameters to be analyzed, and associating the first database with the second database to obtain a third database;

[0122] S404: Select key variable parameters to index in the third database, obtain the details of the written-off expenses within the specified time range, and generate a fourth database;

[0123] S405: establishing a coordinate system with the written-off expense details as the Y-axis and the selected key variable parameter as the X-axis, and plotting the data of the fourth database into the established coordinate system;

[0124] S406: Determine a trend line according to the coordinate points in the coordinate system, and the slope of the trend line is the updated optimized coefficient corresponding to the key variable parameter.

[0125] In this application, the trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated and optimized coefficient corresponding to the key variable parameters, specifically:

[0126] S4061: Determine the trend line according to the coordinate points in the coordinate system;

[0127] S4062: Remove the abnormal points on both sides of the trend line so that all the remaining coordinate points are evenly distributed on both sides of the trend line; that is, click to remove the points far from both sides of the trend line so that all analysis points are evenly distributed on both sides of the trend line. Abnormal points are the manifestation of business abnormalities.

[0128] S4063: Based on the slope of the trend line after the outlier point is proposed, the updated and optimized coefficients corresponding to the key variable parameters are obtained.

[0129] The benchmark model construction application method of the embodiment of the present application constructs a sub-model based on the key variable parameters of each cost sub-item and the coefficients corresponding to the key variable parameters, and obtains the cost benchmark model based on the sub-model of each cost sub-item, and then dynamically adjusts the key variable parameters and coefficients according to the actual scenario requirements of the cost measurement, and maintains the key variable parameters and coefficients. Finally, the cost benchmark model and the key variable parameters and coefficients in the cost benchmark model sub-model are selected to obtain a new cost benchmark model and encapsulate it, and cost measurement is performed based on the encapsulated new cost benchmark model, thereby efficiently realizing the automatic calculation of relevant costs in automobile production and application, and improving the efficiency and accuracy of cost measurement.

[0130] In a second aspect, an embodiment of the present application also provides a benchmark model construction application device.

[0131] In one embodiment, referring to Figure 2 , Figure 2 The functional module diagram of the application device constructed for the benchmark model of this application. Figure 2As shown, the benchmark model construction application device includes a construction module, a maintenance module and a measurement module.

[0132] The construction module is used to construct a sub-model based on the key variable parameters of each expense sub-item and the coefficients corresponding to the key variable parameters, and obtain the expense benchmark model based on the sub-model of each expense sub-item; the maintenance module is used to dynamically adjust the key variable parameters and coefficients according to the actual scenario requirements of the expense measurement, and to maintain the key variable parameters and coefficients; the calculation module is used to perform the expense benchmark model, as well as the selection of key variable parameters and coefficients in the expense benchmark model sub-model, obtain the new expense benchmark model and encapsulate it, and perform expense measurement based on the encapsulated new expense benchmark model.

[0133] On the third aspect, an embodiment of the present application provides a benchmark model construction application device, which can be a personal computer (PC), a laptop computer, a server, or other device with data processing capabilities.

[0134] Reference Figure 3 , Figure 3 The hardware structure diagram of the benchmark model construction application device involved in the embodiment of the present application is shown in FIG. In the embodiment of the present application, the benchmark model construction application device may include a processor, a memory, a communication interface, and a communication bus.

[0135] The communication bus may be of any type and is used to interconnect the processor, the memory, and the communication interface.

[0136] The communication interface includes input / output (I / O) interface, physical interface and logical interface, etc., which are used to realize the interconnection of devices inside the benchmark model construction application device, and the interface used to realize the interconnection between the benchmark model construction application device and other devices (such as other computing devices or user devices). The physical interface can be an Ethernet interface, a fiber optic interface, an ATM interface, etc.; the user device can be a display, a keyboard, etc.

[0137] The memory can be various types of storage media, such as random access memory (RAM), read-only memory (ROM), non-volatile RAM (NVRAM), flash memory, optical storage, hard disk, programmable ROM (PROM), erasable PROM (EPROM), electrically erasable PROM (EEPROM), etc.

[0138] The processor may be a general-purpose processor, which may call the benchmark model construction application stored in the memory and execute the benchmark model construction application method provided in the embodiment of the present application. For example, the general-purpose processor may be a central processing unit (CPU). The method executed when the benchmark model construction application is called may refer to the various embodiments of the benchmark model construction application method of the present application, which will not be repeated here.

[0139] Those skilled in the art will understand that Figure 3 The hardware structure shown in the figure does not constitute a limitation on the present application, and may include more or less components than shown in the figure, or combine certain components, or arrange the components differently.

[0140] In a fourth aspect, an embodiment of the present application also provides a computer-readable storage medium.

[0141] The computer-readable storage medium of the present application stores a benchmark model construction application, wherein when the benchmark model construction application is executed by a processor, the steps of the benchmark model construction application method as described above are implemented.

[0142] Among them, the method implemented when the benchmark model construction application is executed can refer to the various embodiments of the benchmark model construction application method of this application, and will not be repeated here.

[0143] It should be noted that the serial numbers of the above-mentioned embodiments of the present application are only for description and do not represent the advantages or disadvantages of the embodiments.

[0144] The terms "including" and "having" and any variations thereof in the specification and claims of this application and the above-mentioned drawings are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not limited to the listed steps or units, but optionally includes steps or units that are not listed, or optionally includes other steps or units inherent to these processes, methods, products or devices. The terms "first", "second" and "third" are used to distinguish different objects, etc., and do not represent a sequence, nor do they limit "first", "second" and "third" to different types.

[0145] In the description of the embodiments of the present application, "exemplary", "for example" or "for example" are used to indicate examples, illustrations or descriptions. Any embodiment or design described as "exemplary", "for example" or "for example" in the embodiments of the present application should not be interpreted as being more preferred or more advantageous than other embodiments or designs. Specifically, the use of words such as "exemplary", "for example" or "for example" is intended to present related concepts in a specific way.

[0146] In the description of the embodiments of the present application, unless otherwise specified, “ / ” means or, for example, A / B can mean A or B; the “and / or” in the text is merely a description of the association relationship of associated objects, indicating that three relationships may exist, for example, A and / or B can mean: A exists alone, A and B exist at the same time, and B exists alone. In addition, in the description of the embodiments of the present application, “multiple” refers to two or more than two.

[0147] In some processes described in the embodiments of the present application, multiple operations or steps that appear in a specific order are included, but it should be understood that these operations or steps may not be executed in the order in which they appear in the embodiments of the present application or in parallel, and the sequence number of the operation is only used to distinguish the different operations, and the sequence number itself does not represent any execution order. In addition, these processes may include more or fewer operations, and these operations or steps may be executed in sequence or in parallel, and these operations or steps may be combined.

[0148] Through the description of the above implementation methods, those skilled in the art can clearly understand that the above-mentioned embodiment methods can be implemented by means of software plus a necessary general hardware platform, and of course by hardware, but in many cases the former is a better implementation method. Based on such an understanding, the technical solution of the present application is essentially or the part that contributes to the prior art can be embodied in the form of a software product, which is stored in a storage medium (such as ROM / RAM, disk, CD) as described above, and includes a number of instructions for a terminal device to execute the methods described in each embodiment of the present application.

[0149] The above are only preferred embodiments of the present application, and are not intended to limit the patent scope of the present application. Any equivalent structure or equivalent process transformation made using the contents of the present application specification and drawings, or directly or indirectly applied in other related technical fields, are also included in the patent protection scope of the present application.

Claims

1. A benchmark model construction application method, characterized in that: The benchmark model construction and application method comprises: Construct sub-models based on key variable parameters of each expense sub-item and coefficients corresponding to the key variable parameters, and obtain expense benchmark models based on the sub-models of each expense sub-item; According to the actual scenario requirements of cost calculation, dynamically adjust key variable parameters and coefficients, and maintain key variable parameters and coefficients; Conduct cost benchmarking model, and select key variable parameters and coefficients in the cost benchmarking model sub-model, obtain and encapsulate the new cost benchmarking model, and perform cost estimation based on the encapsulated new cost benchmarking model; Among them, for the cost benchmark model, it also includes the optimization of the corresponding coefficients of key variable parameters, specifically: Collect data on project budget execution applications and build the first database containing all key variable parameters indexed by functional CASE and execution application number; Collect data on project budget write-off applications and build a second database containing details of write-off expenses indexed by function CASE and execution application number; Specify the time range and key variable parameters to be analyzed, and associate the first database with the second database to obtain a third database; Select key variable parameters to index in the third database, obtain the details of the written-off expenses within the specified time range, and generate a fourth database; With the written-off expense details as the Y-axis and the selected key variable parameters as the X-axis, a coordinate system is established, and the data of the fourth database is plotted into the established coordinate system; The trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated optimized coefficient corresponding to the key variable parameters.

2. A benchmark model construction application method according to claim 1, characterized in that: The cost benchmark model includes a road test benchmark model, a bench test benchmark model, a trial production special parts procurement benchmark model and a quantity and price benchmark model, and each cost benchmark model includes at least one sub-model; The cost sub-items corresponding to the road test benchmark model include fuel, site use, loading and unloading, labor commission, vehicle maintenance, road and bridge crossing, test commission, consumables, and kinetic energy; The cost sub-items corresponding to the bench test benchmark model include fuel, consumables, kinetic energy, mold / tool / fixture depreciation, mold / tool / fixture maintenance, equipment depreciation, equipment maintenance, building depreciation, building maintenance, labor costs, management costs, financial costs, and test entrustment; The cost sub-items corresponding to the benchmark model for the purchase of trial-produced special parts include 3D sand core casting, ABS CNC machining, body sheet metal, laser cutting, rubber tube crimping, nylon tube crimping, 3D printing, machining center, carbon dioxide shielded welding, spot welding, cathode electrophoresis, black paint, and heat treatment; The cost sub-items corresponding to the quantity-price benchmarking model include departmental expenses.

3. A benchmark model construction application method as claimed in claim 2, characterized in that: In the road test benchmark model and bench test benchmark model, the sub-model of the cost sub-item is specifically: Fi=u*i+C Among them, Fi represents the expense sub-item, that is, the expense calculation of the expense sub-item, i represents the key variable parameter used to determine Fi in the current expense sub-item, u is the coefficient of the corresponding key variable parameter, that is, the rate of the key variable parameter i, and C is a constant, which represents the fixed cost when the key variable parameter i is 0; In the benchmark model for purchasing trial-production special parts, the sub-model of the cost sub-item is specifically as follows: Be=A n *X n +A n-1 *X n-1 +...+C Among them, Fi represents the expense sub-item, X n Indicates the nth key variable parameter used to determine Fi in the current cost sub-item, A n represents the coefficient corresponding to the nth key variable parameter, and C is a constant; In the quantity-price benchmark model, the sub-model of the expense sub-item is specifically as follows: <h2 style=";text-align:left;direction:ltr">Fi = d*L1*L2*...L<h2 style=";text-align:left;direction:ltr"> n Among them, Fi represents the expense sub-item, L n It represents the nth key variable parameter in the cost sub-item, and d represents the coefficient.

4. A benchmark model construction application method as claimed in claim 3, characterized in that: The key variable parameters include fixed parameters and random parameters; The fixed parameters are individual parameters of the function CASE, and the fixed parameters are bound to the function CASE in a table form; The random parameters are common parameters of the functional CASE, which can be randomly increased or decreased. When the key variable parameters and coefficients are dynamically adjusted, the key variable parameters corresponding to the random parameters and the corresponding coefficients are adjusted.

5. A benchmark model construction application method as claimed in claim 4, characterized in that: The cost benchmark model is developed, and the key variable parameters and coefficients in the cost benchmark model sub-model are selected to obtain a new cost benchmark model and encapsulate it, specifically: Build a benchmark model calling interface and select the corresponding cost benchmark model based on cost estimation requirements; Among all the function cases of the selected cost benchmark model, select the function cases with required fixed parameters and the function cases with random parameters, so as to determine the key variable parameters, and select and determine the corresponding coefficients of the key variable parameters; Based on the determined key variable parameters and coefficients, a new cost benchmark model is encapsulated.

6. A benchmark model construction application method according to claim 1, characterized in that: The trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated and optimized coefficient corresponding to the key variable parameter, specifically: Determine the trend line based on the coordinate points in the coordinate system; Remove the abnormal points on both sides of the trend line so that all the remaining coordinate points are evenly distributed on both sides of the trend line; Based on the slope of the trend line after the outlier point is proposed, the updated and optimized coefficients corresponding to the key variable parameters are obtained.

7. A benchmark model construction application device, characterized in that: The benchmark model construction application device comprises: A construction module, which is used to construct a sub-model based on the key variable parameters of each expense sub-item and the coefficients corresponding to the key variable parameters, and obtain the expense benchmark model according to the sub-model of each expense sub-item; The maintenance module is used to dynamically adjust key variable parameters and coefficients according to the actual scenario requirements of cost calculation, and to maintain key variable parameters and coefficients; The calculation module is used to carry out the cost benchmark model, and select the key variable parameters and coefficients in the sub-model of the cost benchmark model, obtain the new cost benchmark model and encapsulate it, and perform cost calculation based on the encapsulated new cost benchmark model; Among them, for the cost benchmark model, it also includes the optimization of the corresponding coefficients of key variable parameters, specifically: Collect data on project budget execution applications and build the first database containing all key variable parameters indexed by functional CASE and execution application number; Collect data on project budget write-off applications and build a second database containing details of write-off expenses indexed by function CASE and execution application number; Specify the time range and key variable parameters to be analyzed, and associate the first database with the second database to obtain a third database; Select key variable parameters to index in the third database, obtain the details of the written-off expenses within the specified time range, and generate a fourth database; With the written-off expense details as the Y-axis and the selected key variable parameters as the X-axis, a coordinate system is established, and the data of the fourth database is plotted into the established coordinate system; The trend line is determined according to the coordinate points in the coordinate system, and the slope of the trend line is the updated optimized coefficient corresponding to the key variable parameters.

8. A benchmark model construction application device, characterized in that: The benchmark model building application device includes a processor, a memory, and a benchmark model building application stored in the memory and executable by the processor, wherein when the benchmark model building application is executed by the processor, the steps of the benchmark model building application method as described in any one of claims 1 to 6 are implemented.

9. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a benchmark model building application, wherein when the benchmark model building application is executed by a processor, the steps of the benchmark model building application method according to any one of claims 1 to 6 are implemented.

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