CN107194609B - Product design system and method - Google Patents

Product design system and method Download PDF

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CN107194609B
CN107194609B CN201710452636.3A CN201710452636A CN107194609B CN 107194609 B CN107194609 B CN 107194609B CN 201710452636 A CN201710452636 A CN 201710452636A CN 107194609 B CN107194609 B CN 107194609B
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明振军
阎艳
王国新
韩海荣
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Beijing Institute of Technology BIT
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Abstract

The invention discloses a product design system and a method, which comprises a decision problem input unit, a database, a decision template packaging unit, a decision template library, a consistency check unit, a decision template execution unit, a design scheme analysis unit and a design scheme output unit; a decision problem input unit acquires problem information input by a user; the database stores data; the decision template packaging unit selects data and packages the data into a decision template; the decision template library stores and manages decision templates; the consistency checking unit is used for checking the consistency of the data packaged in the decision template; the decision template execution unit solves the decision templates which accord with the consistency to generate a design scheme; the design scheme analysis unit analyzes the design scheme to obtain an optimal design scheme; the design scheme output unit outputs an optimal design scheme. By adopting the system or the method, enterprises can be helped to obtain more comprehensive decision-making knowledge, the design efficiency is improved, and the requirements of the enterprises on different products are met.

Description

Product design system and method
Technical Field
The invention relates to the field of product design, in particular to a product design system and a product design method.
Background
The variable market environment requires that enterprises can rapidly design high-quality products meeting the demands at the lowest possible cost to gain an advantage in competition. The product design is a reduction process from a plurality of possible solutions to a final solution, and the decision is a key factor for promoting the resolution process. Therefore, accelerating the design decision process plays an important role in shortening the product design period and enhancing the core competitiveness of an enterprise.
Developing a computer-aided decision-making system is an effective way to accelerate the decision-making process of product design. At present, computer-aided decision systems applied to the field of product design are mainly classified into the following two categories:
(1) a product design system based on knowledge management. The knowledge base of the system organizes and manages various kinds of knowledge such as documents, calculation formulas, product models and the like related to the product design process, provides the required knowledge when designers are engaged in design tasks, and assists the designers in making decisions. The drawbacks of such systems are represented by: knowledge fragmentation, wherein the knowledge used for assisting the designer in decision making usually presents fragmentation and can not provide comprehensive decision support; the static knowledge, which is mostly descriptive static knowledge in the system, is only used as a reference, and cannot be quickly executed to generate the design result.
(2) A product design expert system. The system carries out knowledge modeling aiming at the design process of a specific product, can automatically deduce a design result after given input, and provides decision reference for designers. Although the system realizes quick decision-making through a solidified dynamic design reasoning process, the system has poor adaptability, a reasoning process knowledge model depends on a specific product, and decision support cannot be provided when the type of the product changes.
In summary, the existing computer aided design decision system lacks a comprehensive and rapid decision support means and lacks decision support capability for a wider range of product design problems.
Disclosure of Invention
The invention aims to provide a product design system and a product design method, which are used for helping enterprises obtain more comprehensive decision knowledge input, improving the design efficiency and meeting the requirements of the enterprises on different products.
In order to achieve the purpose, the invention provides the following scheme:
a product design system comprises a decision problem input unit, a database, a decision template packaging unit, a decision template base, a consistency check unit, a decision template execution unit, a design scheme analysis unit and a design scheme output unit;
the decision problem input unit is used for acquiring problem information input by a user;
the database is used for storing data, and the data comprises selection decision data and compromise decision data;
a decision template packaging unit for selecting the data in the database and packaging the selected data into a decision template;
a decision template library for storing and managing decision templates, the decision templates including the selection decision template and the compromise decision template;
the consistency check unit is used for checking the consistency of the data packaged in the decision template according to the consistency rule of the data;
the decision template execution unit is used for solving the decision template which accords with the consistency according to the problem information to generate a design scheme;
the design scheme analysis unit is used for analyzing the design scheme to obtain the sensitivity of the design scheme relative to parameter change and acquiring an optimal design scheme according to the sensitivity;
and the design scheme output unit is used for outputting the optimal design scheme.
Optionally, the database includes a selection decision module and a compromise decision module; the selection decision module comprises a selection problem information module used for storing and managing selection problem information data; the alternative module is used for storing and managing alternative data of the selection decision; the attribute module is used for storing and managing scheme attribute data in the selection decision; the attribute weight module is used for storing and managing the relative weight of each attribute in the selection decision; the multi-attribute evaluation module is used for storing and managing evaluation data of a plurality of attribute influence selection decision relative weights; the compromise module comprises a compromise problem information module used for storing and managing compromise problem information data; the variable and parameter module is used for storing and managing variables and parameters in the compromise decision; a constraint and objective module for storing and managing constraints and objectives in the compromise decision; and the target preference module is used for storing and managing preference data of each design target in the compromise decision.
Optionally, the design scheme includes a selection decision design scheme and a compromise decision design scheme.
Optionally, the design solution analysis unit is configured to perform a solution ranking sensitivity analysis on the selected decision design solution; and carrying out multi-objective balance and design space visualization analysis on the compromise decision design scheme.
A product design method, comprising:
acquiring question information input by a user;
obtaining a decision template capable of solving the problem; the decision template is formed by data encapsulation in a database;
carrying out consistency check on the obtained data encapsulated in the decision template;
solving the decision template which accords with the consistency according to the problem to generate a design scheme;
analyzing the design scheme to obtain the sensitivity of the design scheme relative to parameter change;
evaluating the design scheme according to the sensitivity to obtain an optimal design scheme;
and outputting the optimal design scheme.
Optionally, the obtaining of the decision template capable of solving the problem specifically includes: according to the problem, searching a decision template capable of solving the problem from the design decision template library; if the decision template capable of solving the problem exists, judging whether the data packaged in the decision template needs to be modified; if the data needs to be modified, modifying the packaged data to obtain a modified decision template, and performing consistency check on the data packaged in the modified decision template; if the data does not need to be modified, performing consistency check on the data encapsulated in the acquired decision template; and if the decision template capable of solving the problem does not exist, updating the data in the database, packaging the updated data stored in the decision database to obtain a new decision template, and performing consistency check on the data packaged in the new decision template.
Optionally, the consistency check on the data encapsulated in the obtained decision template specifically includes: according to the consistency rule of the data, consistency check is carried out on the data packaged in the decision template, if the decision template accords with the consistency rule, the decision template which accords with the consistency rule is solved, and a design scheme is generated;
and if the decision template does not accord with the consistency rule, modifying the data which does not accord with the consistency rule in the decision template so as to enable the modified data to accord with the consistency rule.
The invention has the beneficial effects that: the system or the method forms comprehensive and systematized decision support by integrating discrete knowledge points stored in the database into one template, can help enterprises to obtain more comprehensive decision knowledge input, and generate a high-quality design scheme; the decision template comprises a selection decision template and an compromise decision template, the two decision types do not depend on specific products or specific design problems, the application range is wide, the expansion capability is strong, and the requirements of enterprises on different products can be met; by automatically carrying out decision calculation and solving, a design scheme is quickly generated, the design period is shortened, the complexity of solving a design decision problem is reduced, and the design efficiency can be greatly improved; the sensitivity of the design scheme relative to parameter change is obtained by analyzing the design scheme, and the optimal design scheme is obtained according to the sensitivity, so that the confidence coefficient of the design scheme is greatly improved.
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In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings needed in the embodiments will be briefly described below, and it is obvious that the drawings in the following description are only some embodiments of the present invention, and it is obvious for those skilled in the art to obtain other drawings without creative efforts.
FIG. 1 is a block diagram of a product design system of the present invention;
FIG. 2 is a diagram of a package structure of a decision template according to the present invention;
FIG. 3 is a schematic illustration of a selected decision template package according to the present invention;
FIG. 4 is a schematic diagram of a compromise decision template package according to the present invention;
FIG. 5 is a schematic diagram of a selected decision template execution solution and post-processing analysis of the present invention;
FIG. 6 is a schematic diagram of a compromise decision template instance execution solution and post-processing analysis in accordance with the present invention;
FIG. 7 is a flow chart of a product design method of 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. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The invention aims to provide a product design system and a product design method, which are used for helping enterprises obtain more comprehensive decision knowledge input, improving the design efficiency and meeting the requirements of the enterprises on different products.
In order to make the aforementioned objects, features and advantages of the present invention comprehensible, embodiments accompanied with figures are described in further detail below.
FIG. 1 is a block diagram of a product design system of the present invention; FIG. 2 is a package structure diagram of a decision template according to the present invention.
In a specific embodiment, as shown in fig. 1, the product design system includes a decision problem input unit 1, a database 2, a decision template packaging unit 3, a decision template library 4, a consistency check unit 5, a decision template execution unit 6, a design analysis unit 7, and a design output unit 8.
The decision problem input unit 1 is configured to obtain problem information input by a user, where the problem information includes a design object, a design target, and a function description.
The database 2 is configured to store data, where the data includes selection decision data and compromise decision data. As shown in fig. 2, the database 2 includes a selection decision module 21 and a compromise decision module 22; the selection decision module 21 is configured to store the selection decision data; the compromise decision module is used to store compromise decision data 22.
The selection decision module 21 includes a selection question information module 211, an alternative module 212, an attribute module 213, an attribute weight module 214, and a multi-attribute evaluation module 215.
And a selection question information module 211 for storing and managing selection question information data.
An alternatives module 212 for storing and managing alternatives data for selection decisions; the alternatives module 212 is organized in the form shown in table 1, including name, description, image, and solution attribute values. There may be multiple schema attribute values, each attribute value including an upper bound, a lower bound, and a probability distribution. In particular, the upper bound refers to the maximum value of the estimate, the lower bound refers to the minimum value of the estimate, and the probability distribution represents the distribution of the actual values between the upper and lower bounds, which is used to describe the uncertainty of the attribute.
Figure GDA0002583404380000051
Figure GDA0002583404380000061
TABLE 1
An attribute module 213 for storing and managing the recipe attribute data in the selection decision. The attribute module 213 is organized in the form shown in Table 2, including name, description, units, upper bound, lower bound, preference direction, ideal value, reason considered, utility function. Particularly, the preference direction refers to the expectation of attribute values in the decision making process and is divided into three conditions of maximum, minimum and approach to a specific numerical value; the reason for being considered refers to the reason that a certain attribute is considered in the decision process, and the attribute which has a large influence on the decision is considered; the utility function is used for measuring the value of the alternative scheme on a certain attribute, the larger the value of the utility function value of the scheme is, the larger the value of the scheme is, and the utility function can be expressed by using the function model and the parameters thereof.
Figure GDA0002583404380000062
TABLE 2
An attribute weight module 214 for storing and managing the relative weights of the attributes in the selection decision; the attribute weight module 214 is organized in the form described in table 3 as a numerical list of N rows.
Figure GDA0002583404380000071
TABLE 3
The multiple attribute evaluation module 214 is organized in the form shown in Table 4 and is a matrix of N × (2N-2), wherein N represents the number of attributes considered in a decision, and the matrix has N rows and 2N-2 columns, as shown in Table 3, two columns immediately adjacent to each other in the matrix represent a pair of equivalent schemes, the elements in the columns are the values of the attributes of the schemes, and the matrix has N-1 pairs of equivalent schemes
Figure GDA0002583404380000072
Representing a sum of weights of 1, KiRefers to the weight of the first attribute. The other N-1 linear equations are determined by the N-1 pair of equivalent schemes in a manner
Figure GDA0002583404380000073
Wherein
Figure GDA0002583404380000074
And
Figure GDA0002583404380000075
the attribute values of the p-th pair of equivalence schemes on the ith attribute are respectively, and p is the index p of the equivalence scheme which is N-1.
Figure GDA0002583404380000076
TABLE 4
The compromise module 22 includes a compromise question information module 221, a variables and parameters module 222, a constraints and objectives module 223, and an objectives preferences module 224.
The compromise question information module 221 is used for storing and managing the compromise question information data.
A variables and parameters module 222 for storing and managing variables and parameters in the compromise decision; the variables and parameters module 222 is organized in the form described in table 5, including name, description, type, symbol, unit, upper bound, lower bound, initial value. In particular, a type is used to identify whether a quantity belongs to a parameter or a variable in a compromise decision, a parameter if the quantity remains constant in the compromise decision, and a variable otherwise. Symbols are used to express the identity of a variable or parameter when used in a formula, and are expressed in english letters (or combinations of letters).
Figure GDA0002583404380000081
TABLE 5
A constraints and objectives module 223 for storing and managing constraints and objectives in the compromise decision; the constraint and target module 223 is organized in the form described in table 6, including name, description, type, expression, linear/non-linear, direction/polarity of value, boundary/target value. In particular, the type is used for identifying whether a certain function is used for expressing constraint or target in a compromise decision, if the value range of the function is limited, the function is used for expressing constraint, and if not, the function is used for expressing target; the expression is used for representing a symbolic representation form of a certain constraint or target, and a symbol in a variable/parameter module needs to be referred; linear/non-linear is used to express whether a constraint or target expression is linear or non-linear; the value direction/polarity is used to express the value direction of a certain constraint: including "≧" or "≦" or "═ or" or expressing the polarity of a certain target: "maximize" and "minimize"; boundary/target values are used to express boundary values for certain constraints, or target values for certain targets.
Figure GDA0002583404380000082
Figure GDA0002583404380000091
TABLE 6
A target preference module 224 for storing and managing preference data for each design target in the compromise decision. The goal preference module 224 is organized in the form described in Table 7, including goals, hierarchies, and weights. In particular, the hierarchy is used for expressing the priority hierarchy considered in the process of the compromise decision-making of a certain target, a plurality of targets can be arranged on the same hierarchy, and the higher the hierarchy is, the higher the priority is, the more will be satisfied in a limited way; the weights represent the relative weights between multiple objects at a certain level, the cumulative sum of which is 1.
Figure GDA0002583404380000092
TABLE 7
As shown in fig. 2, the decision template packaging unit 3 is configured to select data in the database 2 and package the selected data into a decision template.
The decision template library 4 is used for storing and managing decision templates, and the decision templates include the selection decision template 41 and the compromise decision template 42.
The consistency check unit 5 performs consistency check on the data encapsulated in the decision template according to a consistency rule of the data. Here, consistency means that modules in the template and their relationship with each other need to satisfy a certain rule, and the structure definition of the template is consistent. For example, the sum of the attribute weights in attribute weight module 214 must be 1, i.e.
Figure GDA0002583404380000093
Wherein KiRepresents the ith attribute; the upper and lower bounds of each parameter in the parameter and variables module 222 must satisfy: xu＝XlWherein X isuIs an upper bound, XlIs the lower bound. The consistency check unit 5 adopts a rule-based reasoning engine JESS (Java Expert System Shell) to realize the consistency check function, and the realization method comprises the following steps: firstly, a consistency rule is determined according to the structure definition of the template, then the JESS reasoning engine matches the templates in the selection decision template 41 and the compromise decision template 43 with the consistency rule one by one, and finally the JESS reasoning engine feeds back the instances which do not meet the consistency rule to the user and informs the user of the place where the inconsistency exists and the method for modifying. In particular, the consistency rule is defined using the following production rule form:
(defrule MAIN::rule_6(object(is-acDSPTemplate)(OBJECT？y))
＝>
(foreach？x(slot-get？y hasParameter)(if(neq(slot-get？x lowerBound)(slot-get？x upperBound))then(printout t WARNING_6 crlf))))
in the above rules, the cdsptelemplate represents a compromise decision template, the hasParameter represents a parameter module, the lowerBound represents a lower parameter bound, and the upperBound represents an upper parameter bound, and the logic expressed by the rules is as follows: when any instance in the parameter module has an unequal value between its upper and lower bounds, the inference engine pushes the inconsistency to the user and alerts him to the modification.
And the decision template execution unit 6 is used for solving the decision templates which accord with the consistency according to the problem information to generate a design scheme, wherein the design scheme comprises a selected decision design scheme and an compromise decision design scheme.
The selection decision template 41 is solved according to a mathematical model shown below to generate a selection decision design.
First, given a set of alternatives XiWherein i is 1.·, n;
second, determine the attribute AiWhere i 1.. m, and attribute uncertainty
Figure GDA0002583404380000101
Thirdly, evaluating a single-attribute utility function ui(x) Wherein i is 1, or a salt thereof,.., m, and a joint attribute utility function u (x) f (u)1(x),...,um(x))；
Fourthly, calculating the expected utility E (U) of each schemeiWherein i is 1.·, n;
fifthly, selecting the alternative scheme with the maximum expected utility value;
five parts of "giving", "determining", "evaluating", "calculating" and "selecting" are included in the selection decision problem mathematical model. Where the two parts "given" and "determined" are information related to a particular question, the encapsulation has been completed in the selection decision template 41, and the remaining three parts will be automatically completed by the computer. The completion method comprises the following steps: first, the relative weight K of each attribute is solved according to the data in the attribute evaluation matrix in the table 4iThen, the single-attribute expected utility E (u) of each scheme is calculated according to the data of the utility function in the table 2iAt KiAnd E (u)iCalculating the expected utility of the joint attribute of each scheme on the basis of
Figure GDA0002583404380000102
And finally, selecting the scheme with the highest expected utility E (U) of the joint attribute.
The compromise decision template 42 is solved according to a mathematical model shown below to generate a compromise decision design.
The method comprises the following steps that firstly, an alternative scheme to be optimized, parameters, boundary conditions, constraints, design targets and the like are given;
second, search for design variable XiWherein i 1, n, and a deviation variable
Figure GDA0002583404380000111
Wherein i 1.., m;
third, satisfy constraint Gi(X)＝0；i＝1,...,p、Gi(X) is not less than 0; i ═ p + 1., p + q, and target conditions
Figure GDA0002583404380000112
And boundary conditions
Figure GDA0002583404380000113
Fourth, minimizing the deviation function
Figure GDA0002583404380000114
The compromise decision problem mathematical model comprises four parts of "give", "search", "satisfy" and "minimize". The parameters, variables, constraints, objectives and objective preferences related to the specific problem in the four sections are defined by tables 5, 6 and 7, and are packaged in the compromise decision template 42, and the packaged template example is solved by simultaneously performing the three sections of searching, satisfying and minimizing, and the objective planning algorithm is adopted to realize the solution.
The design scheme analysis unit 7 is configured to analyze the design scheme to obtain sensitivity of the design scheme with respect to parameter changes, and obtain an optimal design scheme according to the sensitivity. And carrying out scheme ordering sensitivity analysis on the selected decision design scheme, namely analyzing whether the ordering of the design scheme can greatly fluctuate along with the change of the parameters, thereby enhancing the confidence of the first-ranked design scheme. And carrying out multi-objective balance and design space visualization analysis on the compromise decision design scheme, wherein the multi-objective balance analysis mainly determines the least sensitive weight combination by analyzing the influence of different weight combinations on the final target deviation. The design space visualization mainly shows the position of the optimal design scheme value corresponding to a certain weight combination in the design space in a visualization mode, and helps enterprises to know the distribution condition of the optimal design scheme so as to make rational decision.
And the design scheme output unit 8 is configured to output the optimal design scheme.
FIG. 3 is a schematic illustration of a selected decision template package according to the present invention; FIG. 4 is a schematic diagram of a compromise decision template package according to the present invention; FIG. 5 is a schematic diagram of a selected decision template execution solution and post-processing analysis of the present invention; FIG. 6 is a schematic diagram of a compromise decision template instance execution solution and post-processing analysis in accordance with the present invention.
Fig. 3 is a schematic interface diagram illustrating packaging of lamp switch cover rapid prototyping material-process selection issues as a selection decision template, as shown in fig. 3. The interface has 6 panels, which are respectively basic information, alternative schemes, attributes, multi-attribute equivalence evaluation and attribute weights. The basic information panel user needs to fill in the example name and the problem description, and the user can fill in the specific information of the rapid prototyping material-process selection problem, and the information is convenient for a designer to understand, search and reuse the template example. The alternative panel requires the user to set alternatives to the selection decision problem, which may be existing alternatives in the database 2 or newly created alternatives by the user, and double-clicking on an entry in the panel may edit detailed information of the alternative. The property panel requires the user to set the properties of the solution considered by the selection decision problem, which may also be from the properties already existing in the database 2, or the properties newly created by the user, and the detailed information of the properties can be edited by double-clicking the entry in the panel. The multi-attribute equivalence evaluation panel needs a user to set N-1 pairs of equivalence schemes, attribute values of the equivalence schemes are used as basic data for solving attribute weights, and the embodiment has 6 attributes in total, so that 5 pairs of equivalence schemes are set. And the weight of each attribute in the attribute weight panel is automatically generated after the data in the multi-attribute equivalent evaluation panel is filled. The lamp switch cover plate is packaged with the material for rapid prototyping-process selection problem and then stored in the selection decision template 41.
FIG. 4 illustrates an interface diagram of a multi-objective compromise decision problem packaging of a pressure vessel design into a compromise decision template. The interface has 6 panels, which are respectively basic information, variables, parameters, constraints, targets and preferences. Similar to the package interface for selecting the decision template instance, the basic information panel is filled by the user according to the specific information of the compromise decision problem, and the information of the rest panels can be selected from the database 2 or can be created by the user. The multi-objective compromise decision problem for the design of the electrical pressure vessel is packaged and stored in the compromise decision template 42.
The top panel of fig. 5 shows the packaged and published selection decision templates, including the material-process selection template, the barrel section selection template, and the barrel material selection template for the light switch cover plate. The user selects one of the templates (the embodiment selects the material-process selection template of the light switch cover plate), then clicks the 'operation' button, the system pops up a window for displaying the relevant parameters of the example, the window is divided into two parts of 'each scheme attribute value' and 'attribute weight', the user can modify the numerical values at the moment, and the system automatically executes solving on the example after modification. The results are shown in the "desired utility values for each case" panel and the "case ranking" histogram in the bottom half of fig. 5, the first case being the design to be selected.
The top panel of fig. 6 shows examples of encapsulated and released compromise decision templates, pressure vessel design templates, coil spring design templates, linear aluminum alloy material design templates, and data center cooling system design. The user selects one of the templates (the embodiment selects the pressure container design template), then clicks the 'operation' button, the system pops up a window for displaying the relevant parameters of the example, the window is divided into three parts of 'variable', 'parameter' and 'target weight', the user can modify the numerical values at the moment, and the system automatically solves the example after modification. The results are shown in the "variable value" and "target value" panels in the lower half of fig. 6, which are the final design.
Fig. 7 is a flowchart of a product design method of the present invention, and as shown in fig. 7, the method for designing a product by using the product design system described in embodiment 1 above includes the following steps:
s701, acquiring question information input by a user;
s702, obtaining a decision template capable of solving the problem;
specifically, the decision template is formed by selecting and encapsulating data in the database 2 by the decision template encapsulation unit 3; and the decision template is stored in a decision template library 4;
s703, carrying out consistency check on the obtained data encapsulated in the decision template;
specifically, the consistency check unit 5 performs consistency check on the data encapsulated in the decision template according to a consistency rule of the data;
s704, solving the decision template which accords with the consistency according to the problem to generate a design scheme;
s705, analyzing the design scheme to obtain the sensitivity of the design scheme relative to parameter change;
s706, evaluating the design scheme according to the sensitivity to obtain an optimal design scheme;
and S707, outputting the optimal design scheme.
Step S702 specifically includes, according to the problem, retrieving a decision template capable of solving the problem from the decision template library 4;
if the decision template capable of solving the problem exists, judging whether the data packaged in the decision template needs to be modified; if the data needs to be modified, modifying the packaged data to obtain a modified decision template, and performing consistency check on the data packaged in the modified decision template; if the data does not need to be modified, performing consistency check on the data encapsulated in the acquired decision template;
if the decision template capable of solving the problem does not exist, updating the data in the database 2, packaging the updated data stored in the database 2 to obtain a new decision template, and performing consistency check on the data packaged in the new decision template.
Step S703 specifically includes performing consistency check on the data encapsulated in the decision template according to a consistency rule of the data, and if the decision template meets the consistency rule, performing solution on the decision template meeting the consistency rule to generate a design scheme;
and if the decision template does not accord with the consistency rule, modifying the data which does not accord with the consistency rule in the decision template so as to enable the modified data to accord with the consistency rule.
The product design system and the design method can help enterprises to obtain more comprehensive decision knowledge input, improve the design efficiency and meet the requirements of the enterprises on different products.
The embodiments in the present description are described in a progressive manner, each embodiment focuses on differences from other embodiments, and the same and similar parts among the embodiments are referred to each other.
The principles and embodiments of the present invention have been described herein using specific examples, which are provided only to help understand the method and the core concept of the present invention; meanwhile, for a person skilled in the art, according to the idea of the present invention, the specific embodiments and the application range may be changed. In view of the above, the present disclosure should not be construed as limiting the invention.

Claims (7)

1. A product design system is characterized by comprising a decision problem input unit, a database, a decision template packaging unit, a decision template library, a consistency check unit, a decision template execution unit, a design scheme analysis unit and a design scheme output unit;
the decision problem input unit is used for acquiring problem information input by a user;
the database is used for storing data, and the data comprises selection decision data and compromise decision data;
the decision template packaging unit is used for selecting the data in the database and packaging the selected data into a decision template;
the decision template library is configured to store and manage decision templates, where the decision templates include the selection decision template and the compromise decision template, and the selection decision template is solved according to a mathematical model shown below to generate a selection decision design scheme, and specifically includes:
first, given a set of alternatives XiWherein i is 1..,n；
Second, determine the attribute AiWhere i 1.. m, and attribute uncertainty
Figure FDA0002610192460000011
Thirdly, evaluating a single-attribute utility function ui(x) Where i ═ 1.. said, m, and the joint attribute utility function u (x) ═ f (u)1(x),...,um(x))；
Fourthly, calculating the expected utility E (U) of each schemeiWherein i is 1.·, n;
fifthly, selecting the alternative scheme with the maximum expected utility value;
the compromise decision template is solved according to a mathematical model shown below to generate a compromise decision design scheme, which specifically includes:
the method comprises the following steps that firstly, an alternative scheme to be optimized, parameters, boundary conditions, constraints, design targets and the like are given;
second, search for design variable XiWherein i 1, n, and a deviation variable
Figure FDA0002610192460000012
Wherein i 1.., m;
third, satisfy constraint Gi(X)＝0；i＝1,...,p、Gi(X) is not less than 0; i ═ p + 1., p + q, and target conditions
Figure FDA0002610192460000021
And boundary conditions
Figure FDA0002610192460000022
Figure FDA0002610192460000023
Fourth, minimizing the deviation function
Figure FDA0002610192460000024
The consistency check unit is used for checking the consistency of the data packaged in the decision template according to the consistency rule of the data;
the decision template execution unit is used for solving the decision template which accords with the consistency according to the problem information to generate a design scheme;
the design scheme analysis unit is used for analyzing the design scheme to obtain the sensitivity of the design scheme relative to parameter change and acquiring an optimal design scheme according to the sensitivity;
and the design scheme output unit is used for outputting the optimal design scheme.
2. The system of claim 1, wherein the database comprises a selection decision module and a compromise decision module; the selection decision module is used for storing the selection decision data; the compromise decision module is used for storing compromise decision data;
the selection decision module comprises a selection problem information module used for storing and managing selection problem information data; the alternative module is used for storing and managing alternative data of the selection decision; the attribute module is used for storing and managing scheme attribute data in the selection decision; the attribute weight module is used for storing and managing the relative weight of each attribute in the selection decision; the multi-attribute evaluation module is used for storing and managing evaluation data of a plurality of attribute influence selection decision relative weights;
the compromise module comprises a compromise problem information module used for storing and managing compromise problem information data; the variable and parameter module is used for storing and managing variables and parameters in the compromise decision; a constraint and objective module for storing and managing constraints and objectives in the compromise decision; and the target preference module is used for storing and managing preference data of each design target in the compromise decision.
3. The system of claim 1, wherein the design solution comprises a selection decision design solution and a compromise decision design solution.
4. The system of claim 1, wherein the design analysis unit is configured to perform a solution ordering sensitivity analysis on the selected decision design; and carrying out multi-objective balance and design space visualization analysis on the compromise decision design scheme.
5. A method of product design, the method comprising:
acquiring question information input by a user;
obtaining a decision template capable of solving the problem, wherein the decision template comprises a selection decision template and an compromise decision template, and the selection decision template is solved according to a mathematical model shown as the following to generate a selection decision design scheme, which specifically comprises:
first, given a set of alternatives XiWherein i is 1.·, n;
second, determine the attribute AiWhere i 1.. m, and attribute uncertainty
Figure FDA0002610192460000031
Thirdly, evaluating a single-attribute utility function ui(x) Where i ═ 1.. said, m, and the joint attribute utility function u (x) ═ f (u)1(x),...,um(x))；
Fourthly, calculating the expected utility E (U) of each schemeiWherein i is 1.·, n;
and fifthly, selecting the alternative with the maximum expected utility value,
the compromise decision template is solved according to a mathematical model shown below to generate a compromise decision design scheme, which specifically includes:
the method comprises the following steps that firstly, an alternative scheme to be optimized, parameters, boundary conditions, constraints, design targets and the like are given;
second, search for design variable XiWherein i 1, n, and a deviation variable
Figure FDA0002610192460000032
Wherein i 1.., m;
third, satisfy constraint Gi(X)＝0；i＝1,...,p、Gi(X) is not less than 0; i ═ p + 1., p + q, and target conditions
Figure FDA0002610192460000033
And boundary conditions
Figure FDA0002610192460000034
Fourth, minimizing the deviation function
Figure FDA0002610192460000035
The decision template is formed by data encapsulation in a database;
carrying out consistency check on the obtained data encapsulated in the decision template;
solving the decision template which accords with the consistency according to the problem to generate a design scheme;
analyzing the design scheme to obtain the sensitivity of the design scheme relative to parameter change;
evaluating the design scheme according to the sensitivity to obtain an optimal design scheme;
and outputting the optimal design scheme.
6. The design method according to claim 5, wherein the obtaining of the decision template capable of solving the problem specifically includes:
according to the problem, searching a decision template capable of solving the problem from the design decision template library;
if the decision template capable of solving the problem exists, judging whether the data packaged in the decision template needs to be modified; if the data needs to be modified, modifying the packaged data to obtain a modified decision template, and performing consistency check on the data packaged in the modified decision template; if the data does not need to be modified, performing consistency check on the data encapsulated in the acquired decision template;
and if the decision template capable of solving the problem does not exist, updating the data in the database, packaging the updated data stored in the database to obtain a new decision template, and performing consistency check on the data packaged in the new decision template.
7. The design method according to claim 6, wherein the consistency check of the obtained data encapsulated in the decision template specifically includes:
according to the consistency rule of the data, consistency check is carried out on the data packaged in the decision template, if the decision template accords with the consistency rule, the decision template which accords with the consistency rule is solved, and a design scheme is generated;
and if the decision template does not accord with the consistency rule, modifying the data which does not accord with the consistency rule in the decision template so as to enable the modified data to accord with the consistency rule.
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