JP2000331036A - Design support device, design information management device, design information editing method, design support system, and recording medium with design information editing program stored - Google Patents

Abstract

PROBLEM TO BE SOLVED: To easily realize sensitivity analysis of each design factor in an entire product and performance analysis of the product to efficiently design the product in a cooperative product design environment where design information is shared among plural users to design the product. SOLUTION: A design information editing part 1 which edits design information consisting of design restrictive formulas related to a design object and an analysis condition setting part 1 which sets an analysis condition for analysis of design information by making designers arbitrary design factors from a design factor group used in design restrictive formulas and making them input the attribute information of selected design factors are provided. Design restrictive formulas inputted by plural designers are simultaneously set up and are made into a mathematical model, and this model is subjected to behavior analysis in accordance with the analysis condition, and the analysis result is processed by a statistical technique like an experimental planning method to analysis the sensitivity of each design factor.

Description

DETAILED DESCRIPTION OF THE INVENTION

[0001]

The present invention relates to a design support device, a design information management device, a design information editing method, a design support system, and a recording medium for storing a design information editing program. In particular, in a collaborative product design environment where multiple users share design information to design products, by easily analyzing each design factor in the entire product,
The present invention relates to technology for realizing efficient product design.

[0002]

2. Description of the Related Art In recent years, the design of mechatronic product design and the like has been increasingly complicated. Mechatronic products have enormous design factors, and the relationship between these design factors is complicated. Therefore, in general, for example, designers having expertise in various fields such as mechanical, thermodynamics, and materials cooperate with each other to perform a composite design for one product.

In this so-called composite design, designers in various fields input various design constraints as design knowledge, and create an analysis model suitable for a tool used for analyzing each design factor in which the designer participates. Using these analysis models, analysis relating to one or more design factors has been individually performed. Through this analysis, design parameter values for each design factor that conforms to each characteristic value of the product have been obtained, and design data has been created.

On the other hand, a design manager who manages the entire design work selects a main design factor from design factors determined by each designer, sets a condition value of the design factor, and sets a condition value of the design factor. Conduct behavior analysis using various analysis tools. As a result of this behavior analysis, optimization of each design factor was achieved.

[0005]

However, the conventional composite design has the following problems.

As described above, the number of design factors is enormous, extends to other fields, and the relationship between design factors is complicated. Also, at the early stage of the design, it is unknown whether or not there is an interaction between these design factors. For this reason,
In practice, it is often not possible to verify the performance of a product with practical accuracy unless it is in the late stages of design. Therefore, re-designing (backtracking) frequently occurred.

[0007] That is, each designer can analyze the design factors in which he or she is involved by using a tool using, for example, a finite element method (hereinafter, referred to as “FEM”). However, it was difficult for each designer to perform a complex analysis such as a behavior analysis of the entire product at an early stage of design when design factors in other fields are unknown. Even if a designer creates a complex model for this complex analysis, the design constraints other than the design factors involved in the model are not known in detail. For this reason, the search space for analysis of this composite model is very large, and it has not been possible to perform analysis with practical accuracy in practical time.

[0008] On the other hand, the design manager experimented with enormous design factors that affect the performance of the product in order to analyze the behavior of the entire product.
Various tools that can be optimized for analysis and the like can be used. However, as described above, in mechatronics product design, the design factors are enormous and span many fields, and the relationships between the design factors are complicatedly intertwined. The design manager does not know in detail the design constraints of each of the enormous design factors and the presence or absence of interaction. For this reason, it has been difficult for a design manager to efficiently and comprehensively model a complex analysis target. In addition, even if the model can be modeled, at the time of various analyzes such as parameter analysis of the design factors, the design parameters are appropriately selected, and the analysis is performed by giving appropriate condition values (levels) to these design parameters. It took a lot of effort and time to optimize the design factors. For this reason,
It was more difficult to analyze the behavior and verify the performance of the entire product as it was designed for large-scale products.

[0009] More specifically, a designer, for example,
In order to perform analysis based on FEM with an analysis tool represented by I-DEAS of SDRC, USA, the shape information of a product is indispensable in principle of FEM. However, since the shape information of the product needs to be determined so as to satisfy various design constraints, it is often impossible to determine the shape information until late in the design.

Here, the input of the product shape data itself can be saved by using various CAE tools. However, in order to generate a finite element model called a mesh model composed of three-dimensional elements for FEM from the product shape data, appropriately define various constraint conditions and loads, and obtain analysis results, it is necessary to obtain analysis results in various fields. A lot of experience and engineering knowledge of the designer is required. In addition, the designer's experience and engineering knowledge are often used to read the obtained analysis results to judge the engineering meaning and to improve specific design information. For this reason, useful information is rarely obtained as an analysis result for much time required for the analysis. In addition, it is often the case that an important decision, such as selecting a design alternative, must be made in the early stages of design, when the product shape has not been determined. For this reason, even if the quantitative analysis accuracy is limited to a certain level, a method and environment that can easily perform sensitivity analysis of a large number of design factors in a practical time are required. However, it has been difficult for each designer to analyze the sensitivity of an enormous design factor over the entire product using individual tools.

[0011] Further, by networking the design environment, it is possible to share design information such as CAD data and chart files input by each designer. By sharing this design information, one designer could access an analysis model created by another designer.
However, it has been difficult for a designer or a design manager to analyze an analysis model created by another designer so as to conform to a unique analysis tool, and obtain a desired design factor condition value. Furthermore, it is difficult to grasp each design factor of an analysis model created by another designer and reflect this analysis model in order to reflect the condition value of the design factor involving the user.

As described above, according to the present invention, it is difficult to analyze the sensitivity of a large number of design factors for the entire product and the performance analysis of the product at an early stage of the design in the conventional complex design method. Therefore, it is made to solve the problem that the re-design has been frequently performed.

[0013] The purpose is to make each designer input design knowledge consciously of only the design factors that he or she is involved in and to mutually edit these design knowledge, thereby enabling early design stages. Accordingly, an object of the present invention is to provide a design support device, a design information management device, and a design support system that enable sensitivity analysis of each design factor in the entire product and performance analysis of the product.

Another object of the present invention is to allow each designer to easily set analysis conditions for an analysis engine for analyzing the sensitivity of a design factor that influences the performance of a product. The purpose of the present invention is to easily optimize the design factors by simply performing the sensitivity analysis in a practical time.

[0015]

A feature of the present invention for solving the above-mentioned problems is that the present invention is arranged on a network and allows a plurality of users to mutually edit design knowledge consisting of mathematical expressions of design constraints. Further, an analysis condition for analyzing a mathematical model derived from the mutually edited design knowledge is set in conjunction with the editing of the design knowledge.

A first feature of the present invention for realizing such a function is that a design information editing unit that edits design information composed of mathematical expressions that specify design conditions for a design object, and a design factor group used in the mathematical expressions And an analysis condition setting unit for setting an analysis condition for analyzing the design information by allowing the user to select an arbitrary design factor from and to input attribute information of the selected design factor. It is in providing a design support apparatus. The mathematical expression that defines the design conditions for the product to be designed is hereinafter referred to as a design constraint expression. The design factors include design variables and the like used in the design constraint equation.

According to the above configuration, the design constraint equations input by a plurality of designers are simultaneously converted into a mathematical model, and the behavior of the mathematical model is analyzed in accordance with the analysis conditions to analyze the sensitivity of each design factor. Can be. For this reason, it is possible to easily optimize the design factors of the entire product while easily understanding not only the design factors involved by each designer but also the design constraints input by other designers.

According to a second feature of the present invention, the design information editing unit further displays a list of at least one of another formula group already input and a design factor group used for the formula group. In that it has a design information display means.

According to the above configuration, it is possible to easily input and edit a new design constraint equation relating to a design factor involving the user in relation to a design constraint equation already input by another designer.

A third feature of the present invention is that the analysis condition setting unit selects the design factor based on the list of design factors displayed by the design information display means. is there.

According to the above configuration, it is possible to easily set analysis conditions for a desired design factor in conjunction with editing of design model information such as a design constraint equation and a design factor.

A fourth feature of the present invention is that the design information display means displays the design factor corresponding to a designated location from the group of formulas or design factors displayed in the list. The present invention is characterized in that display control means capable of switching and displaying the design factor description or the shortened design factor description indicating the contents of the design factor is provided.

According to the above configuration, the designer can input the design constraint formula and design factor contents already input as necessary, and the design factor names and design constraint formulas that show the contents of the design factors as necessary. And the abbreviated design factor names suitable for displaying
These contents can be grasped by appropriately displaying a simplified or detailed display.

According to a fifth feature of the present invention, the design information display means stores the design factor specified in the list of design factors in the input area with the new mathematical expression in an input area. An input assisting means for automatically inputting as a design factor to constitute is provided.

According to the above configuration, a designer can easily input a new design constraint equation by utilizing a design factor that has already been input.

Further, a sixth feature of the present invention is that the apparatus further comprises an analysis information presenting section for presenting numerical analysis result information relating to a design factor selected in the design information.

According to the above configuration, each designer can grasp the bottleneck of the design factor in which he / she is involved at an early stage and change the design.

A seventh feature of the present invention resides in that the design information further includes at least one of table information and chart information relating to a design target.

According to the above configuration, various data can be reflected in the analysis model in association with the rough design constraint mathematical formula that does not depend on the analysis tool.

According to an eighth feature of the present invention, the analysis condition setting unit allows a design factor to be analyzed and a level of the design factor to be input to the orthogonal array based on a design of experiment. The analysis condition is set by the following.

According to the above configuration, by converging the vast solution space of the product model and deriving the numerical tendency of each design factor, the sensitivity of the design factor can be easily and practically shortened even in the early stage of design. Can be analyzed.

A ninth feature of the present invention is that a design information storage unit that stores design information, which is stored by an external input and is composed of mathematical formulas that specify design conditions for a design object, includes a mathematical model based on the design information. Mathematical model generation unit for deriving the formula, and an analysis information control unit for generating design factors to be analyzed in the design information and attribute information of the design factors as analysis conditions for the derived mathematical model. A feature of the present invention is to provide a design information management device which is a feature.

According to the above-described configuration, the design constraint equations input by a plurality of designers are simultaneously converted into a mathematical model, and the mathematical model is subjected to behavior analysis according to the analysis conditions to analyze the sensitivity of each design factor. Can be. For this reason, it is possible to easily optimize the design factors of the entire product while easily understanding not only the design factors involved by each designer but also the design constraints input by other designers.

Further, a tenth feature of the present invention is that
An analysis unit that numerically analyzes the mathematical model according to the analysis conditions, and a design factor optimization unit that optimizes the design factors using an analysis result output by the analysis unit based on the analysis conditions. It is in.

According to the above configuration, the optimum design conditions can be easily derived based on the analysis result of the mathematical model.

An eleventh feature of the present invention is that the design information management device further comprises a model for converting the mathematical model derived by the mathematical model generation unit into an analysis model that can be analyzed by the analysis unit. And a conversion unit.

According to the above configuration, the generated mathematical model can be selectively analyzed by various analysis engines according to the purpose of analysis.

A twelfth feature of the present invention is that the analysis information control unit, based on an experiment design method, generates a predetermined orthogonal table holding design factors to be analyzed and levels of the design factors. The point is that it is set as an analysis condition.

According to the above configuration, the space of the enormous factor levels that can be taken by the product model is converged to a realistic number of combinations, and the numerical tendency of each design factor is derived, so that the design model can be used even in the early stages of design. The sensitivity of the design factors can be easily analyzed in a short time.

A thirteenth feature of the present invention is a design support system comprising a plurality of design information editing devices and a design information management device connected to the plurality of design information editing devices via a network. A design information editing unit that edits design information composed of mathematical formulas that specify design conditions for a design target; and a design factor editing unit that selects an arbitrary design factor from a design factor group used in the mathematical formula. An analysis condition setting unit for setting analysis conditions for analyzing the design information by inputting the attribute information of the design factors, wherein the design information management device receives the design information from the plurality of design information editing devices. A design information storage unit that is stored by mutual input and stores design information composed of the mathematical formula, and a mathematical model generation unit that derives a mathematical model from the design information An analysis information control unit that generates design factors to be analyzed in the design information and attribute information of the design factors as analysis conditions of the derived mathematical model, based on mutual input from the plurality of design information editing devices; A design support system characterized by comprising:

According to the above configuration, each design constraint equation input by a plurality of designers is simultaneously converted into a mathematical model, and the behavior of the mathematical model is analyzed in accordance with the analysis conditions to analyze the sensitivity of each design factor. Can be. For this reason, it is possible to easily optimize the design factors of the entire product while easily understanding not only the design factors involved by each designer but also the design constraints input by other designers.

Further, a fourteenth feature of the present invention is a design information editing method for editing design information, the design information editing step of editing design information consisting of mathematical expressions defining design conditions for a design object, By allowing the user to select an arbitrary design factor from the design factor group used in the formula and inputting the attribute information of the selected design factor,
An analysis condition setting step of setting analysis conditions for analyzing the design information is provided.

According to the above arrangement, each design constraint equation input by a plurality of designers is simultaneously converted into a mathematical model, and the mathematical model is subjected to behavior analysis according to the analysis conditions to analyze the sensitivity of each design factor. Can be. For this reason, it is possible to easily optimize the design factors of the entire product while easily understanding not only the design factors involved by each designer but also the design constraints input by other designers.

A fifteenth feature of the present invention is a computer-readable recording medium for storing a design information editing program for editing design information, the design information comprising a mathematical expression for defining design conditions for a design object. Analysis conditions for analyzing the design information by design information editing processing to be edited, and by selecting an arbitrary design factor from a design factor group used in the mathematical expression and inputting attribute information of the selected design factor. And a computer-readable recording medium that stores a design information editing program.

According to the above configuration, the respective design constraint equations input by a plurality of designers are simultaneously converted into a mathematical model, and the mathematical model is subjected to behavioral analysis in accordance with the analysis conditions to analyze the sensitivity of each design factor. Can be. For this reason, it is possible to easily optimize the design factors of the entire product while easily understanding not only the design factors involved by each designer but also the design constraints input by other designers.

[0046]

Embodiments of the present invention will be described below in detail with reference to the drawings. The present embodiment provides a function that allows a plurality of users to interactively edit analysis conditions for product design constraints and design factor analysis.

FIG. 1 is a block diagram showing a functional configuration of a design support device, a design information management device, and a design support system according to an embodiment of the present invention. As shown in FIG. 1, the design support system according to the present embodiment includes an editor unit 1 for editing design information, and is connected to each of the editor units 1 via a network 3, and the edited design information will be described later. Calculate the combination of the level (condition value) of each design factor in the analysis based on the experimental design method, perform numerical analysis of each design factor based on the obtained analysis conditions, perform factor-effect analysis of the factors and design parameters, and optimize The design information server 2 presents guidelines.

The design information server 2 further includes a design data storage unit 21, an analysis information control unit 23, a numerical analysis engine unit 24, a calculation procedure generation processing unit 25, and an optimization engine unit 26.

The editor unit 1 is arranged on the client side on the network and accesses the design information server 2 via, for example, WWW. The user uses the editor unit 1 to input various design data into the design data storage unit 21 as design knowledge. The design data input by the user is input as a simple mathematical expression-level design constraint expression independent of various tools. The design data may include table data and chart data. The editor unit 1 can appropriately present and edit the design data already edited to each user. Further, the editor unit 1 displays the analysis result output from the numerical analysis engine unit 24 via the analysis information control unit 23. Also, each editor unit 1 used by a user who is a designer in each field shares a design data storage unit 21 via a graphic user interface.
Can be edited. The editor unit 1 corresponds to a design support device including a design model information editing unit, an analysis condition setting unit, and an analysis information presenting unit in the claims.

The design data storage unit 21 stores design data input from a plurality of users as a database on the design information server side. The design data storage unit 21 maintains the consistency of the input design constraint data. In addition, the contents of the design data in the database are appropriately displayed to a plurality of client-side users to enable information sharing. The design constraint data input by the editor unit 1 is finally mathematically modeled as a simultaneous equation, and output to a numerical analysis engine unit 24 described later for performing performance prediction analysis. The design data storage unit 21 corresponds to a design model information storage unit and a mathematical model generation unit in the claims. Alternatively, the mathematical model generation process from the design constraint data performed by the mathematical model generation unit may be configured as a part of the numerical analysis engine unit 24 as needed.

The analysis information control unit 23 extracts each design factor input to the design data storage unit 21 and included in the generated mathematical model, and edits and manages the analysis conditions of the extracted design factor. The user inputs the design factor to be analyzed, the level value which is the condition value of the design factor, and, if necessary, the type of the design factor to the analysis information control unit 23 via the editor unit 1 as analysis conditions. Set. The analysis conditions are set based on, for example, a generally known experimental design method. Note that the analysis information control unit 23 includes the numerical analysis engine unit 2
4 functions as a pre-processor and a post-processor.

The experiment design method is a technique used for efficiently optimizing a number of factors that influence the performance of a product through experiments, analysis, and the like. The procedure for using the experimental design method is detailed in "Introduction to Experimental Design Method" (written by Yasutoshi Washio, published by the Japan Standards Association). "Ripses" developed by Ricoh Co., Ltd. and "Anova" released by the Japan Standards Association are known as software that supports the use of the experimental design method.

In the experimental design method, first, the user
From the respective design factors listed on the editor unit 1, a factor considered to be important in design is selected. A factor type such as a control factor, a signal factor, and an error factor is assigned to these selected factors. Control factors are subject to analysis,
It is a factor that the designer can control. On the other hand, the error factor is a factor for representing various environmental conditions and error factors in the analysis of control factors. The signal factor is an input factor when analyzing an output characteristic with respect to a change in input.

Next, the user assigns each factor to the given orthogonal table. As shown in FIG. 3, for example, the orthogonal table is a table that describes a pattern of a combination of level values that are possible condition values of each factor. In this orthogonal table, for each level of a certain factor, a combination of each level value of another factor is always defined by the same number of times. For this reason, it is possible to analyze the factor effects (main effects and interaction effects) specific to each factor defined in the orthogonal array, using the property that the effects of other factors work homogeneously on the factor to be analyzed. it can. Originally, in factor analysis, factors to be evaluated are taken at the same time,
All combinations of all levels of these factors need to be analyzed to assess the factorial effect of each factor. This orthogonal table can be used to reduce analysis patterns in this factor analysis and narrow the search space. still,
Although the level effect of one factor may differ depending on the level of another factor, a combination effect that specifically occurs for a combination of levels between these factors is called an interaction. The main effect is that
The average effect of each factor level.

[0055] the orthogonal ^{_{table, L 18 (6 1 × 3}} 6), L 18 (2
¹ × 3 ⁷ ), L ₈ (2 ⁷ ), L ₁₆ (2 ¹⁵ ), L ₂₇ (3 ¹³ ),
There are certain types of experimental designs such as L ₃₆ (2 ¹¹ × 3 ¹² ). The user selects an orthogonal table from these orthogonal tables that is appropriate for the analysis of the desired design factors, such as the number of factors, the number of levels, and whether to perform factor effect analysis or robustness evaluation by parameter design. Select in consideration of type, etc. Alternatively, based on analysis conditions such as the number, type, and level value of design factors input to the analysis information control unit 23 by the user, the analysis condition control unit 23 selects an optimal orthogonal table and presents it to the user. Is also good.

The combination of the levels of the factors at the time of executing the analysis a predetermined number of times is determined from the orthogonal table. For example, in the orthogonal table of L ₁₈ (6 ¹ × 3 ⁶ ), the combination of the levels of the factors is determined by a combination of one type of the maximum of six levels and six types of the three levels of the factors. To simply experiment or analyze all of the combinations, 6 ¹ × 3 ⁶ = 437
Analysis of four combinations will be performed. On the other hand, by using the orthogonal table of L ₁₈ the perspective that ignores the interaction evaluate ^{(6 1} × 3 6) between each factor, each factor trial experiments or analysis of 18 types factors Analysis becomes possible. Alternatively, even in the case of performing analysis in consideration of robustness to noise including interaction, it is possible to perform factor analysis and parameter design of each factor through (18 × the number of error factor levels) experiments or analysis trials. Therefore, the influence of each factor on the design can be efficiently and quantitatively evaluated in a short period.

The numerical analysis engine unit 24 includes the editor unit 1
Obtains a mathematical model without any tool dependence constructed based on input of design constraint data from
This is a mathematical engine that analyzes the behavior of the mathematical model using the levels of the factors determined in 3 as analysis conditions.

As a pattern of design constraints that frequently appear in product design, a constant equation of the second order is used as a basic equation, and each constant of the equation has various nonlinearities, and its characteristics are given in the form of a mathematical expression or a table. Is often done. The design information on these designs is collected and centralized by the editor unit 1 and is mathematically modeled.

The numerical analysis engine unit 24 converts the mathematical model into a numerical analysis engine unit 24 such as simultaneous equations and interpolation functions.
Convert to a format that can be handled by and analyze the behavior of this mathematical model. In general, there are two types of analysis: an algebraic solution that simplifies mathematical expressions algebraically, and a numerical solution that divides the analysis time into minute periods and numerically repeats integration to obtain a numerical solution. It is normal that the analysis is performed while performing. However, a numerical solution method is often more suitable for a complicated model including complicated non-linearity and conditional branching such as design information. The numerical analysis engine unit 24 easily derives the relative numerical tendency of each design factor. Therefore, the user can obtain an engineeringly sufficient amount of information as a product design guide. Note that the numerical analysis engine unit 24 corresponds to an analysis unit in the claims.

The calculation procedure generation processing unit 25 converts the obtained mathematical model into an analysis model that conforms to specific rules such as syntax used by the numerical analysis engine unit 24, types of operations that can be handled, and algorithm of the procedure as necessary. Convert.
The calculation procedure generation processing unit 25 corresponds to a model conversion unit in the claims.

The optimization engine unit 26 calculates an optimal design factor value based on the characteristic value of the product based on the analysis result obtained by the numerical analysis engine unit 24. By optimizing the design factors, a user can obtain an optimal design guideline at an early stage of design. The optimization engine unit 26
Corresponds to the design factor optimizing unit in the claims.

Next, the hardware configuration of the design support device and the design information management device according to the present embodiment will be described.
The design support device and the design information management device according to the present invention,
It is mounted on various computers such as a workstation, a general-purpose computer, a PC, and various portable information terminals. Note that the design support apparatus according to the present invention forms an editor unit 1 arranged on the client side in FIG. On the other hand, the design information management device forms the design information server 2 in FIG. These client and server form a design support system via the network 3.

Each computer has a CPU, a data memory, a program memory, a hard disk, an external disk drive, a communication interface, and an input / output unit. The CPU realizes the present embodiment by controlling and executing software for realizing the design support device and the design information management device.

It should be noted that programs for implementing various processes of design support and design information management according to the present invention can be stored in various recording media. The present invention is implemented by reading out such a recording medium by a CPU of a computer having the above hardware and executing this program. Here, the recording medium is, for example, a semiconductor memory, a magnetic disk (floppy disk, hard disk), an optical disk (CD-ROM, DVD, etc.),
Includes all devices that can record programs. Further, the program may be distributed through various communication means such as a network.

The present embodiment is configured as described above, and the flow of the processing will be described below in order with reference to FIGS.

First, a user such as a designer or an expert involved in the design uses the editor unit 1 to input various kinds of information and technical knowledge on a product to be designed as design data (design information) (S10). . At the time of this input, the editor unit 1 switches and displays a plurality of screens using, for example, an Internet browser. The user inputs design data and the like to these screens, or browses and edits design data input by other users. Specifically, each user on the client side communicates with the design information server 2 via an Internet browser, for example.
Connect to Next, the user enters HTML (Hyper Text M).
arkup Language) or CGI (Common Gateway Interface)
e) Design data is input from a keyboard on the client side to a dialog box provided on a graphic screen provided using a technique such as e). Alternatively, electronic files such as documents and charts relating to the design are uploaded to the design information server 2.

The design data information is transmitted to the design data storage unit 2 and constructed as a database (S2).
0). Here, the design data is composed of a design constraint equation / table relating to the performance of the product. The user adds and edits the design data as appropriate while viewing the design data such as the design constraint equation already input by another user. Specifically, for example, it is assumed that the mechanism designer has already input the equation of motion of the product. Next, a thermal analysis expert will add a thermodynamic equation for the temperature dependence of the spring constant used in this equation of motion. At this time, the thermal analysis expert can easily browse the already input equation of motion from the editor unit 1. For this reason, a thermal analysis expert can add a thermodynamic equation while keeping in mind the uniformity of variable names used in the equation of motion including the spring constant.

According to the above procedure, a plurality of experts cooperate to input and supplement design data, and a mathematical model capable of predicting product behavior from final design information is obtained from the design data storage unit 21. It is generated by background processing or the like (S30). For example, if the mathematical model consists of simultaneous equations centered on differential equations on the time axis,
By performing a numerical analysis by integrating and solving the simultaneous equations of the mathematical model on the time axis, the time axis response of the product can be known. Thereby, the product behavior can be easily evaluated.

Here, the procedure for inputting the design information shown in step S10 of the flowchart of FIG. 2 performed by the design information editing method according to the present embodiment will be described in detail with reference to the screens of FIGS.

FIG. 4 shows a GUI (Graphic User Interface) provided by the editor unit 1 of the design support apparatus according to this embodiment.
ce) is shown below. In FIG. 4, another user has already entered the mathematical expression list (F9) in the mathematical expression list (F9).
2, F3) has already been entered. In the variable list (F10) located at the bottom of the mathematical expression list, the variables used in these three mathematical expressions are listed together with the definitions of the variables (F4 to F8).

A part or all of the list of formulas and the list of variables are designated by clicking a shortened display / detailed display switching icon at the upper right of each box (hereinafter, simply referred to as “click”). ,
Short display / detailed display can be arbitrarily switched and displayed.

In the mathematical expression list of FIG. 4, since the abbreviated display is selected, the meaning of the variable of each mathematical expression is not displayed. On the other hand, in the variable list of FIG. 4, since the detailed display is selected, the definition of the variable is displayed together with each variable. Similarly, in the input box (dialog box) of FIG. 6, since the detailed display is selected (F20),
The equation F = i × B × l is decoded (F2
1). Therefore, the meaning of the equation can be easily grasped.

Next, a procedure in which a user who is a designer in another field adds a mathematical expression as a new design constraint will be described.
First, the user accesses the design information server 2 with an Internet browser (web browser), and selects G in FIG.
The UI is opened by the editor unit 1 on the client machine. By appropriately browsing the formula list and the variable list in FIG. 4, the user can confirm whether or not information related to the design formula that he or she wants to input has already been input. Here, the user recognizes that his or her own expression is an expression related to the defined expression (F1) regarding F with reference to the expression list in FIG. In this case, as shown in FIG. 5, the designer selects (F11) by clicking F from the variable list (F10), and then clicks the reference icon on the right side of the variable list. By these operations, the system copies the variable F to the input box as shown in FIG. 5 (F13). Alternatively, by dragging and dropping F from the variable list (F10) to the input box, the variable F is similarly copied to the input box by the system.

Next, as shown in FIG. 7, the designer can edit the expression relating to F in the input box. At the time of editing this formula, the designer can easily edit the formula with the same operation as a scientific calculator, by using various function icons arranged at the top of the GUI.

Each mathematical expression can have a logical expression or the like as an application condition. As shown in FIG. 8, in the case of these logical expressions, when the designer clicks the application condition icon (F23) at the upper right of the input box, a new input box is opened in the input box (F24). As shown in FIG.
The user inputs a conditional expression in this new input box (F25). By appropriately using icons (F26) such as "IF", "ELSE", "AND", and "OR" at the upper right in the figure for inputting these conditional expressions, the input of the conditional expressions becomes easy. As shown in FIG. 10, after inputting the application condition, the user inputs a registration icon (F28) on the left of the input box.
By clicking, the entered mathematical expression with a conditional expression is registered in the mathematical expression list (F27).

Here, not only mathematical formulas but also table data and chart data are input to the design data storage section 21 as design data. In the list of equations in FIG.
The Young's modulus E (F29) is, for example, the file “Resin 12” of spreadsheet software “EXCEL” of Microsoft Corporation.
34 Young's modulus.xls ”(F30) is referred to as a data table. That is, the expression of the Young's modulus E compares the argument temp of the Young's modulus E with the value in the first column (F31) and, if necessary, It is defined so that the value of the Young's modulus (F32) in the second column at the matching temperature is substituted for E by using both interpolation and extrapolation.
By selecting “Young's modulus.xls” by, for example, an operation such as double-clicking, the system starts up “EXCEL” and displays the file content of the selected file name.
The user can browse the contents of the file as another window on the same screen.

Next, following the above-mentioned database construction (S20), the user analyzes the design optimization using the design data stored in the design data storage unit 21 through the editor unit 1. Specifically, first, the user calls an editing screen presented by the analysis information control unit 23 via the editor unit 1. On the editing screen for setting the analysis conditions, the user browses the design data input to the design data storage unit 21, particularly a list of variables that are design factors to be optimized. From among the variables displayed in the list, the user selects variables to be subjected to a combination calculation of factors, which are input for analysis based on the above-described design of experiment, as factors to be evaluated (S40). Selection criteria for this variable include, for example, variables that are expected to have a large effect on product performance, or that it is particularly difficult to make changes in the later stages of the design. A certain variable or the like may be preferentially selected. Note that the number of factors and their levels that can be assigned by the experimental design method vary depending on the orthogonal table used. This orthogonal table may be selected by the user, or may be selected in step S40.
The design support apparatus according to the present embodiment may automatically select an optimal orthogonal table and present it to the user based on the evaluation target design factors and the number of levels determined in (1). Next, the user assigns a level to the selected orthogonal table (S50).

Referring to FIG. 3, the level assignment to this orthogonal table will be specifically described using an example using an orthogonal table called L ₁₈ (2 ¹ × 3 ⁷ ). Here, the notation L ₁₈ (2 ¹ × 3 ⁷ ) determines a combination of factor levels in the analysis for 18 times by combining a maximum of one set of two levels and a maximum of seven sets of three levels in this orthogonal table. Means that
In addition to this combination, there are a method of reducing the number of levels of a specific factor, a method of using an orthogonal table of L ₁₈ (2 ¹ × 3 ⁷ ) as L ₁₈ (6 ¹ × 3 ⁶ ) by a predetermined method, and the like. It is established in the experimental design method, and by using these methods, the flexibility of determining the combination of factors can be expanded, but the description is omitted here.

For example, as shown in FIG. 1 (variable name A)
Is given two levels. As shown in FIG. Analysis No. 1 For 1-9, 2
One (“1”) of the level values determined as described above is assigned. On the other hand, analysis No. The other level value ("2") is assigned to 10 to 18. Other factor Nos. 2
８8 are given level values determined in three ways. These factor Nos. Values of three levels are respectively assigned to 2 to 8 as analysis conditions according to an orthogonal table.

As described above, when the level values are assigned to the factors in accordance with the orthogonal table, the factor effects unique to each factor with respect to a certain characteristic value can be statistically extracted. Therefore, a relative sensitivity analysis of each design factor in the product design data can be performed.
Therefore, a design factor that becomes a bottleneck can be corrected at an early stage of design.

For each of the 18 sets of analysis numbers in FIG. 3, for example, two types of error factors are prepared and combined with each of the 18 sets, so that a total of 18 × 2 = 36 kinds of analysis can be performed. it can. By further analyzing the combination with the error factor, a so-called parameter design can be performed. The parameter design is a method for evaluating the sensitivity to the error of each design factor, that is, the robustness, for stabilizing product performance.

Here, the procedure for setting the analysis conditions for performing the factor-effect analysis based on the experimental design method of the mathematical model shown in steps S40 and S50 of the flowchart of FIG. 2 performed by the design information editing method according to the present embodiment is as follows. This will be described in detail with reference to the screens of FIGS.

FIG. 12 shows an example of the orthogonal table allocation menu screen. The designer clicks a menu screen switching icon (not shown) of the editor unit 1. By this click, the analysis information control unit 23 outputs the orthogonal table allocation menu screen shown in FIG.
Note that FIGS. 4 to 13 described above are, for example, child screens of the Windows application, and the menu screen switching icons are arranged in the main screen window.

In FIG. 12, first, the user needs to select the type of orthogonal table. The selection of this orthogonal table is determined by the number of factors to be subjected to the sensitivity analysis and the number of levels of each factor. When the orthogonal table to be selected by the user is obvious, the user may select the target orthogonal table directly from the selection box (F40). On the other hand, if not, the user sets the number of factors to be subjected to the sensitivity analysis (F43) and the number of factor levels (F4) in the automatic selection box (F41).
2) and click on the automatic selection icon (F44). From the input number of factors (F43) and the number of levels of factors (F42), the analysis condition control unit 23 automatically selects an optimal or closest orthogonal table. Alternatively, if a unique optimal orthogonal table cannot be selected, an error message is displayed to prompt the user to re-enter.

When the type of orthogonal table is selected by any of the above means, the analysis information control unit 23 displays an orthogonal table for assigning analysis conditions as shown in the upper right of FIG. 12 (F45). In the example of FIG. 12, according to the input of four 2-level factors and one 3-level factor in the automatic selection box (F41), L ₈ (2 ⁴ ×) which is an application of L ₈ (2 ⁷ ) is input.
4 ¹ ) is selected as the closest orthogonal table. Next, the designer performs a dummy (pseudo-level) position setting (F46) necessary for assigning the three-level factor to the factor for the four-level factor included in L ₈ (2 ⁴ × 4 ¹ ). In FIG. 12, from 1 to 4 which were originally in the item of the factor name A of L ₈ (2 ⁴ × 4 ¹ ).
(F4) where a 1-2-3-2 type dummy position setting in which level 2 is assigned instead of level 4
7). The setting of the dummy position is performed as necessary in order to adapt the selected analysis target factor / level number to the selected orthogonal table.

Next, the user selects a factor to be assigned to the orthogonal table. Specifically, a variable m (F48) is selected from the variable selection box (F49) and sent to the level value input box (F50). The user inputs a factor number A so that the variable m is assigned to the factor A in the orthogonal array (F
51). By inputting this factor number, the analysis information control unit 2
3 automatically opens three levels of input boxes (F5
2, F53, F54). Users can use these levels 1-3
In the input boxes of 0.005 and 0.0, respectively.
Input to assign 055 and 0.006.

After these inputs, as shown in FIG.
When the designer clicks the “input to orthogonal table” icon (F55), the analysis information control unit 23 assigns the variable m to the factor A in the upper right orthogonal table.

By repeating the above operation for the factors B to E, the assignment to the orthogonal table is completed. When the assignment to the orthogonal array is completed, the user clicks the “orthogonal array allocation completed” icon (F56) at the lower right of FIG. With the above procedure, the processing of steps S40 and S50 in FIG. 2 is completed.

Returning to FIG. 2, the 18 sets of factor levels determined in this way are substituted into the mathematical model constructed in step S30 (S60). The numerical analysis engine unit 24 calculates the number of input factor levels for each of the 18 factor level sets.
The numerical analysis is repeatedly executed sequentially (S60 to S10)
0).

In performing this numerical analysis, there is a case where the numerical analysis cannot be directly performed by the numerical analysis engine unit 24 simply by substituting the values of the factors into the simultaneous differential equations as the mathematical model. This is because there is a difference unique to each numerical analysis engine in the syntax of the numerical analysis engine, types of operations that can be handled, procedures, and the like. Calculation procedure generation processing unit 2
5 eliminates the difference unique to each numerical analysis engine.
The calculation procedure generation processing unit 25 includes the design data storage unit 2
When the mathematical model is transferred from 1 to the numerical analysis engine unit 24, the mathematical model is converted into an input expression that can be processed by the numerical analysis engine unit 24.

For example, suppose that the designer unknowingly inputs left side = right side. However, depending on the numerical analysis engine, for the so-called mathematical expression "=", a. Assign the right side to the left side b. Verify that the left and right sides are equal c. Sometimes it is necessary for the user to explicitly indicate the distinction, such as a function definition, to the numerical analysis engine. In order to distinguish between these, the numerical analysis engine unit 24 includes: a. , B. , C. For each: a. = B. == c. It is assumed that the notation is distinguished and defined like: =. In such a case, it is necessary to determine the intention of the input person and to assign an appropriate notation. Here, when the engineering numerical analysis has a main use as in the present embodiment, the user often describes the equal sign as ": =" at the stage of describing the design constraint. On the other hand, at the stage of substituting the level value into the mathematical model in step S60, it can be clearly determined that “=” should be used.

Alternatively, when the mathematical model is composed of a large number of simultaneous equations, the numerical analysis succeeds unless the mathematical model is once subjected to a process of eliminating algebraically redundant variables and then input to the numerical analysis engine unit 24. Or the processing efficiency may decrease.

The calculation procedure generation processing unit 25 converts a mathematical model so as to conform to the specific rules used in the numerical analysis engine unit 24. As a result, the types and scales of mathematical models that can be analyzed are expanded. When the type of the numerical analysis engine unit 24 is changed, it is only necessary to change the calculation procedure generation processing unit 25 to one corresponding to the new numerical analysis engine unit 24, and other components may be changed. There is no. Therefore, the numerical analysis engine unit 24 can be quickly replaced with the minimum effort according to the desired analysis characteristics.

If the mathematical model conversion process cannot be automatically determined by the calculation procedure generation processing unit 25, an algorithm that prompts the user to select an option by, for example, displaying options on the editor unit 1 is used. May be provided.

Next, the above-described steps S10 to S10
Since 0 results in 18 analysis results, these analysis results are statistically processed based on the experimental design (S1).
10). In the present embodiment, the sensitivity (main effect) of each factor on the characteristic value is analyzed. Alternatively, when the above-described parameter design is performed, the robustness to the error factor is evaluated as the S / N ratio in step S110.

The characteristic value used to evaluate the analysis result is classified as a desired characteristic when the characteristic value is larger as it is larger than a negative value. On the other hand, the characteristic value is classified as a desired small characteristic when it is preferable that the characteristic value is as small as possible without taking a negative value. Note that S for evaluating robustness when performing parameter design is used.
The method of calculating the / N ratio is different for each of the three methods. Therefore, when performing parameter design, the user instructs the division of the characteristic value through the editor unit 1. The subsequent actual statistical processing such as the analysis of variance test is widely known as an experimental design method, particularly the Taguchi method, and thus detailed description thereof is omitted.

Since the main effects of each factor can be obtained quantitatively by the processing up to step S110, the optimization engine unit 26 evaluates an optimal design guideline using these analysis results (S120). . The optimization engine unit 26
For example, when the characteristic value is the maximum characteristic, the factor level at which the characteristic value increases for all the factors may be selected.
On the other hand, there is a case where the level of a certain factor is 3 or more and the tendency is not uniquely determined, that is, there is a case where the factor has a complicated characteristic having a maximum or a minimum. In such a case, the optimization engine unit 26 can derive a design optimization guideline by approximating the obtained factor effect to, for example, a spline curve and numerically analyzing the maximum or minimum value. Many other existing mathematical methods can be used, but they are not described in detail here. This optimized set of design factors is displayed as appropriate in the editor unit 1 via the analysis information control unit 23 as analysis result data.

According to the present embodiment, the following effects can be obtained.

The design data storage unit 21 collects and shares design data, which is design knowledge of each designer, via the editor unit 1. These design data are interactively edited by each user via the network, and are stored in the design data storage unit 21 as a lumped constant model having no tool dependence.

The analysis information control unit 23 interactively sets analysis information by assigning factors to the orthogonal table of each designer via the editor unit 1. The analysis information control unit 2
3 optimizes design factors using the optimization engine unit 26 based on the analysis result from the numerical analysis engine unit 24.

For this reason, each designer can seamlessly exchange design data input by other designers without having detailed knowledge of design factors involved by other designers, and can only transmit design data that he or she is involved in. Instead, it is possible to easily analyze the sensitivity of the design factor in each product as a whole, while being conscious of the design constraints input by other designers. Therefore, even at an early stage of design where not all the design parameters have quantitative values, it is possible to evaluate the relative importance of each design factor and recognize the bottleneck design factor at an early stage. it can.

Further, each designer cooperates with each other to add and edit design data, and to input these when detailed analysis results by FEM or the like and experimental data by prototype are obtained. Accordingly, as the amount of design information added to the design database increases, the accuracy of the mathematical model improves. Further, even if a certain design factor is corrected based on the result of the sensitivity analysis, it is sufficient to reflect this correction in the expression of the design factor in the lumped mathematical model (mathematical model). Therefore, the designer in charge of other design factors does not need to be aware of this, and the efficiency at the time of design change is greatly improved.

Further, the design manager can easily carry out behavior analysis and performance analysis of the entire product without grasping various design constraints in detail.

[0104]

As described above, according to the present invention,
The following effects are obtained.

That is, the present invention allows each designer to easily edit the design constraint equations while easily understanding not only the design factors involved by himself / herself but also the design constraints inputted by other designers. To provide a function to make lumped mathematical model by combining In addition, a function is provided in which each designer interactively sets analysis conditions for sensitivity analysis of a design factor involving his or herself in the analysis engine in conjunction with design constraint equation editing. Therefore, in the early stage of product design, sensitivity analysis of each design factor in the entire product and performance analysis of the product can be easily performed in a practical time using a rough mathematical model.

Therefore, so-called distributed cooperative design is promoted even between geographically dispersed design teams by collecting and sharing design information on a network. Also, by directly integrating the information input from the editor with the analysis information controller and the numerical analysis engine, modeling of the analysis target, which required complicated procedures in the past, factor analysis and parameter design by experiment design method The design optimization work at the early stage of design can be largely labor-saving.

As described above, according to the present invention, it is possible to perform sensitivity analysis by factor analysis of each factor even at an early stage of design in which quantitative values are not obtained for all design factors. Therefore, backtracking is eliminated by early verification of design factors that are bottlenecks in design, thereby shortening the design period and reducing product development costs.

[Brief description of the drawings]

FIG. 1 is a block diagram illustrating a functional configuration of a design support device, a design information management device, and a design support system according to an embodiment of the present invention.

FIG. 2 is a flowchart showing a procedure of a design model analysis process of the design support device, the design information management device, and the design support system according to the embodiment of the present invention.

FIG. 3 is a diagram illustrating an example of an orthogonal table in which an analysis information control unit 23 assigns factors and levels.

FIG. 4 Graphic User Interfa presented by the editor unit 1
It is a figure showing an example of a screen of ce (GUI).

5 is a diagram illustrating an operation of copying a variable “F” to a dialog box on the screen of FIG.

FIG. 6 is a diagram illustrating an operation of switching between abbreviated display and detailed display in a dialog box.

FIG. 7 is a diagram illustrating a screen when a short display of a dialog box is selected on the screen of FIG. 6;

FIG. 8 is a diagram illustrating an input operation of an application condition of a mathematical expression on the screen of FIG. 7;

FIG. 9 is a diagram illustrating an operation of copying variables from a variable list display when inputting the application conditions in FIG. 8;

10 is a diagram illustrating an operation of registering input contents in the dialog box of FIG. 9 in a mathematical expression list.

FIG. 11 is a diagram illustrating a link operation to an external file defining a table when a table is referred to in a mathematical expression.

FIG. 12 is a diagram illustrating an example of an orthogonal table allocation menu output by an analysis information control unit 23;

13 is a diagram illustrating an input operation to an orthogonal table from the orthogonal table allocation menu in FIG. 12;

[Explanation of symbols]

 DESCRIPTION OF SYMBOLS 1 Editor part 2 Design information server 3 Network 21 Design data storage part 23 Analysis information control part 24 Numerical analysis engine part 25 Calculation procedure processing part 26 Optimization engine part

Claims (15)

[Claims] A design information editing unit that edits design information consisting of a mathematical expression defining a design condition relating to a design object; and an arbitrary design factor selected from a design factor group used in the mathematical expression, and the selected design factor. A design condition setting unit for setting analysis conditions for analyzing the design information by inputting the attribute information of the design information. 2. The design information editing unit further includes a design information display unit for displaying a list of at least one of another already input mathematical formula group and a design factor group used in the mathematical formula group. The design support apparatus according to claim 1, wherein: 3. The method according to claim 1, wherein the analysis condition setting unit selects the design factor based on the design factor group displayed in the list displayed by the design information display unit. The design support device described in the above. 4. The design information display means includes: a group of formulas or a group of design factors displayed in the list;
4. The display device according to claim 2, further comprising a display control unit capable of switching and displaying the design factor corresponding to the designated location to a design factor description indicating the contents of the design factor or a shortened design factor description. The design support device described in the above. 5. An input for automatically inputting any of the design factors designated from the list of design factors as design factors constituting the new mathematical formula into an input area. 5. The design support apparatus according to claim 2, further comprising auxiliary means. 6. The design support apparatus according to claim 1, further comprising: an analysis information presenting unit that presents numerical analysis result information on a design factor selected in the design information. The design support apparatus according to claim 1, 2, 3, 4, or 5, wherein: 7. The design according to claim 1, wherein the design information further includes at least one of table information and chart information relating to a design target. Support equipment. 8. The analysis condition setting unit sets the analysis condition by inputting a design factor to be analyzed and a level of the design factor to an orthogonal array based on an experiment design method. The design support apparatus according to claim 1, 2, 3, 4, 5, 6, or 7. 9. A design information storage unit that stores design information that is accumulated by an external input and includes mathematical formulas that define design conditions for a design object; a mathematical model generation unit that derives a mathematical model from the design information; A design information management device, comprising: an analysis information control unit that generates a design factor to be analyzed in the design information and attribute information of the design factor as analysis conditions of the derived mathematical model. 10. The design information management device according to claim 9, further comprising: an analysis unit that numerically analyzes the mathematical model according to the analysis conditions; and an analysis result output by the analysis unit based on the analysis conditions. The design information management device according to claim 9, further comprising: a design factor optimization unit that optimizes the design factor by using the design factor optimization unit. 11. The design information management device according to claim 9, further comprising: a model conversion unit that converts the mathematical model derived by the mathematical model generation unit into an analysis model that can be analyzed by the analysis unit. The design information management device according to claim 9, further comprising: 12. The analysis information control unit sets a predetermined orthogonal table holding design factors to be analyzed and a level of the design factors as the analysis condition based on an experiment design method. The design information management device according to claim 9, 10 or 11, 13. A design support system comprising: a plurality of design information editing devices; and a design information management device connected to the plurality of design information editing devices via a network, wherein the design information editing device comprises: A design information editing unit that edits design information composed of a mathematical expression that defines a design condition for an object; and selects an arbitrary design factor from a design factor group used in the mathematical expression and inputs attribute information of the selected design factor. An analysis condition setting unit for setting an analysis condition for analyzing the design information, wherein the design information management device is stored by mutual input from the plurality of design information editing devices, and A design information storage unit that stores design information that includes: a mathematical model generation unit that derives a mathematical model from the design information; An analysis information control unit that generates design factors to be analyzed in the design information and attribute information of the design factors as analysis conditions of the derived mathematical model based on mutual input from the device. Characteristic design support system. 14. A design information editing method for editing design information, comprising: a design information editing step of editing design information consisting of a mathematical expression defining a design condition relating to a design object; An analysis condition setting step of setting analysis conditions for analyzing the design information by allowing the user to select design factors and inputting attribute information of the selected design factors. Method. 15. A computer-readable recording medium storing a design information editing program for editing design information, comprising: a design information editing process for editing design information consisting of mathematical expressions defining design conditions for a design target; An analysis condition setting process for setting analysis conditions for analyzing the design information by allowing an arbitrary design factor to be selected from a design factor group used in the mathematical formula and inputting attribute information of the selected design factor. A computer-readable recording medium for storing a design information editing program, characterized by comprising: