WO2006100712A1 - 設計支援装置、設計支援方法、設計支援プログラム - Google Patents
設計支援装置、設計支援方法、設計支援プログラム Download PDFInfo
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- WO2006100712A1 WO2006100712A1 PCT/JP2005/004918 JP2005004918W WO2006100712A1 WO 2006100712 A1 WO2006100712 A1 WO 2006100712A1 JP 2005004918 W JP2005004918 W JP 2005004918W WO 2006100712 A1 WO2006100712 A1 WO 2006100712A1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F30/00—Computer-aided design [CAD]
- G06F30/30—Circuit design
- G06F30/32—Circuit design at the digital level
- G06F30/33—Design verification, e.g. functional simulation or model checking
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F18/00—Pattern recognition
- G06F18/20—Analysing
- G06F18/23—Clustering techniques
Definitions
- Design support device design support method, design support program
- the present invention relates to a design support apparatus, a design support method, and a design support program for efficiently evaluating the relationship between design parameters and characteristics of a design object using quality engineering and simulation.
- CAE Computer Aided Engineering
- simulation-only evaluation can only confirm whether a specific design plan satisfies the required specifications. Therefore, the effects of certain design parameters on the characteristic values and the effects on the characteristic values when there is a change in certain design parameters are unknown. In order to analyze these effects, it is effective to execute a combination of quality engineering analysis and simulation.
- Patent Document 1 As a related art related to the present invention, for example, Patent Document 1 shown below is known.
- This equipment reliability design support device assigns design variables of equipment and parts to an orthogonal table based on Taguchi method, and analyzes the design analysis model or inverse problem analysis model based on this orthogonal table. Based on this analysis result, a response surface is obtained, and optimization design is performed using this response surface.
- Patent Document 1 JP 2001-125933 A
- the present invention has been made to solve the above-described problems, and a design support apparatus and a design support method for easily and accurately analyzing the relationship between design parameters and characteristics of a design object.
- the purpose is to provide a design support program.
- the present invention uses design parameters and characteristic values by using a simulation to obtain a characteristic value of a design target, which is a combination force of design parameter values such as control factors, error factors, and signal factors.
- a design support device that analyzes the relationship between the design parameter value and assigning the design parameter value to the orthogonal table, and the experiment design unit that selects the combination of the design parameter values, and the inner factors such as error factor and signal factor
- the orthogonal parameter By assigning the orthogonal parameter as a factor, the number of combinations of the design parameter values is reduced, and a simulation input creating unit that creates an input to the simulation and an input to the simulation are used to execute the simulation. Based on the simulation result and the simulation result Calculating a set of parameter values and characteristic values, in which a analyzing unit for analyzing.
- a response curved surface representing a relationship between the design parameter value and the characteristic value is further calculated using the design parameter value and the characteristic value obtained as a result of the simulation. It has a response surface calculation unit, and the analysis unit calculates an arbitrary set of design parameter values and characteristic values using the response surface and performs analysis.
- the design support apparatus further selects a set of characteristic values satisfying a predetermined criterion from the set of design parameter values and characteristic values, and selects the selected design parameter value and A clustering unit that classifies the selected set of design parameter values and characteristic values into clusters based on a distance between points represented by the characteristic value pairs, and the analysis unit includes the cluster Analysis is performed using a set of design parameter values and characteristic values for each.
- the present invention creates a necessary setting as a simulation input file for a simulation that obtains a characteristic value of a design target with respect to a combination force of design parameter values such as a control factor, an error factor, and a signal factor.
- a design support device which assigns design parameter values to an orthogonal table, prepares an experiment planning unit for selecting a combination of design parameter values, and associates a design parameter name with an identifier in advance.
- a simulation input template file which is a file in which design parameter values are described with identifiers, is prepared in advance, and for each combination of the design parameter values, the identifiers in the simulation input template file are converted into design parameter values according to the association.
- the replaced file is the simulation input file. If the error factor name in the design parameter matches the control factor name, the simulation input is created to replace the identifier corresponding to the error factor name with the control factor value plus the error factor value. It has a part.
- the simulation input creation unit assigns the number of combinations of the design parameter values by allocating inner factors such as error factors and signal factors to the orthogonal table as outer factors.
- Prepare the correspondence between design parameter names and identifiers in advance prepare simulation input template files, which are files describing design parameter values with identifiers for the simulation settings, and combine the design parameter values
- the error factor name in the design parameters matches the control factor name Includes an identifier corresponding to the error factor name. It is characterized in that to replace to a value obtained by adding the error factor value to the value.
- the present invention relates to the relationship between the design parameter value and the characteristic value by using a simulation that obtains the characteristic value of the design object for the combined force of the design parameter value such as the control factor, the error factor, and the signal factor.
- This is a design support method that performs analysis, and assigns design parameter values to an orthogonal table, thereby selecting an experimental design step that selects a combination of design parameter values, and an internal factor such as an error factor or signal factor as an external factor in the orthogonal table.
- a simulation input creating step for reducing the number of combinations of the design parameter values and creating an input to the simulation, and a simulation instruction step for instructing execution of the simulation using the input to the simulation.
- design parameters based on the simulation results.
- a set of parameter values and characteristic values is calculated and an analysis step for performing analysis is executed.
- the design parameter value and the characteristic value obtained as a result of the simulation are further used during the analysis step with the simulation instruction step.
- a response surface calculation step for calculating a response surface representing the relationship between the design parameter value and the characteristic value, and the analysis step calculates an arbitrary combination of the design parameter value and the characteristic value using the response surface. It is characterized by conducting an analysis.
- the characteristic value is determined from a set of the design parameter value and the characteristic value during the analysis step with the simulation instruction step.
- a clustering step for classifying the selected design parameter value / characteristic value pairs into clusters based on the distance between the points represented by the selected design parameter value / characteristic value pairs.
- the analysis step the analysis is performed using a set of design parameter values and characteristic values for each cluster.
- the present invention creates a necessary setting as a simulation input file for a simulation in which the combined force of design parameter values such as a control factor, an error factor, and a signal factor also obtains a characteristic value to be designed.
- a design support method in which design parameter values are assigned to an orthogonal table, whereby an experimental design step for selecting a combination of design parameter values and a correspondence between design parameter names and identifiers are prepared in advance, and the simulation input file Simulation, which is a file that describes design parameter values of an object using identifiers
- An input template file is prepared in advance, and for each combination of the design parameter values, the identifier in the simulation input template file replaced with the design parameter value according to the association is output as the simulation input file. If the error factor name in the data matches the control factor name, a simulation input creation step is performed to replace the identifier corresponding to the error factor name with a value obtained by adding the error factor value to the control factor value. It is something to execute.
- the simulation input creating step allocates the design parameter value by assigning an inner factor such as an error factor and a signal factor to the orthogonal table as an outer factor.
- an inner factor such as an error factor and a signal factor
- the correspondence between design parameter names and identifiers is prepared in advance, and a simulation input template file, which is a file describing design parameter values with identifiers for the simulation settings, is prepared in advance.
- the identifier in the simulation input template file replaced with the design parameter value according to the correspondence is output as a simulation input file, and the error factor name in the design parameter matches the control factor name. If it matches, the identifier corresponding to the error factor name is It is characterized by replacing the control factor value with the error factor value.
- the present invention relates to the relationship between the design parameter value and the characteristic value by using a simulation that obtains the characteristic value of the design object as well as the combined force of the design parameter value such as the control factor, error factor, and signal factor.
- a design support program that causes a computer to execute a design support method that performs analysis, and assigns design parameter values to an orthogonal table, thereby selecting an experiment design step for selecting a combination of design parameter values, error factors, signal factors, etc.
- an inner factor to an orthogonal table as an outer factor, the number of combinations of the design parameter values is reduced, and a simulation input creating step for creating an input to the simulation and an input to the simulation are used.
- a simulation instruction step for instructing execution of the simulation; The simulation results based on calculating a set of design parameters and characteristics values, an analysis step for analyzing those to be executed by the combination Yuta.
- FIG. 1 is a block diagram showing an example of a configuration of a design support apparatus according to Embodiment 1.
- FIG. 2 is a flowchart showing an example of the operation of the design support apparatus according to the first embodiment.
- FIG. 3 is an orthogonal table showing an example of design parameter assignment in the first case according to the present invention.
- FIG. 4 is an orthogonal table showing an example of design parameter assignment in a second case according to the present invention.
- FIG. 5 is an orthogonal table showing an example of design parameter assignment in a third case according to the present invention.
- FIG. 6 is an orthogonal table showing an example of design parameter assignment in a fourth case according to the present invention.
- FIG. 7 is a diagram showing an example of an analysis pattern setting GUI in creating an orthogonal table according to the present invention.
- FIG. 8 is a diagram showing an example of a control factor setting GUI in orthogonal table creation according to the present invention.
- FIG. 9 is a diagram showing an example of a GUI for setting control factor combinations in orthogonal table creation according to the present invention.
- FIG. 10 is a diagram showing an example of an error factor setting GUI in orthogonal table creation according to the present invention.
- FIG. 11 is a table showing an example of correspondence between variable names and variable numbers according to the present invention.
- FIG. 12 is a table showing an example of a simulation input template file according to the present invention.
- FIG. 13 is a table showing an example of a simulation input file according to the present invention.
- FIG. 14 is a diagram showing an example of a GUI for referring to evaluation characteristic values according to the present invention.
- FIG. 15 is a flowchart showing an example of a first analysis method according to the first embodiment.
- FIG. 16 is a diagram showing an example of display of analysis results of a quality engineering analysis unit according to the present invention.
- FIG. 17 is a flowchart showing an example of a second analysis method according to the first embodiment.
- FIG. 18 is a diagram showing an example of an analysis result display setting GUI of the response surface calculation unit according to the present invention.
- FIG. 19 is a flowchart showing an example of a third analysis method according to the first embodiment.
- FIG. 20 is a flowchart showing an example of a fourth analysis method according to the first embodiment.
- FIG. 21 is a diagram showing an example of the operation of the clustering unit according to the present invention.
- FIG. 22 is a flowchart showing an example of a fifth analysis method according to the first embodiment.
- FIG. 23 is a flowchart showing an example of a sixth analysis method according to the first embodiment.
- FIG. 24 is a block diagram showing an example of a configuration of a design support apparatus according to Embodiment 2.
- FIG. 25 is a flowchart showing an example of the operation of the design support apparatus according to the second embodiment.
- FIG. 26 is an orthogonal table showing an example of allocation of error factors in normal quality engineering.
- FIG. 27 is an orthogonal table showing an example of allocation of error factors by the simulation input creation unit according to the second embodiment.
- FIG. 28 is a flowchart showing an example of a first analysis method according to the second embodiment.
- FIG. 29 is a flowchart showing an example of a second analysis method according to the second embodiment.
- FIG. 30 is a flowchart showing an example of a third analysis method according to the second embodiment.
- FIG. 31 is a flowchart showing an example of a fourth analysis method according to the second embodiment.
- FIG. 32 is a flowchart showing an example of a fifth analysis method according to the second embodiment.
- FIG. 1 is a block diagram showing an example of the configuration of the design support apparatus according to the first embodiment.
- the design support apparatus 1 includes an experiment planning unit 11, a simulation input creation unit 12, a simulation instruction unit 21, a simulation result extraction unit 22, an analysis unit 30, a design information DB (database) 50, and a display unit 51.
- the analysis unit 30 includes a response surface calculation unit 31, a quality engineering analysis unit 32, and a clustering unit 41.
- the simulation server 2 performs a simulation related to the design object according to the simulation input file received from the simulation instruction unit 21 and transmits the simulation result to the simulation result extraction unit 22. This simulation is performed by using the design parameter values included in the simulation input file to calculate the characteristic values of the design target and include them in the simulation results as evaluation characteristic values. I will.
- FIG. 2 is a flowchart showing an example of the operation of the design support apparatus according to the first embodiment.
- the experiment design unit 11 receives the design parameters of control factors, error factors, and signal factors, the number of levels of each variable, and the level value by GUI (Graphical User Interface) input or file input from the user. Get (Sl l).
- the experiment design unit 11 creates a simulation input by selecting an appropriate combination of design parameter values by creating an orthogonal table corresponding to the type of design parameter, the number of variables, and the number of levels. Pass to part 12 (S 12).
- the experiment design unit 11 selects a combination of design parameter values by automatically selecting an appropriate orthogonal table and assigning design parameter values to the orthogonal table.
- the orthogonal table creation method according to the design parameters corresponds to the following four cases.
- the first case is a case where control factors are assigned to an appropriate orthogonal table, all combinations of error factors are performed, and no signal factors are included.
- FIG. 3 is an orthogonal table showing an example of design parameter assignment in the first case according to the present invention.
- the control factors are A, B, C, and D
- the error factors are X and Y.
- the second case is a case where control factors and error factors are assigned to an appropriate orthogonal table, a direct product experiment is performed, and no signal factors are included.
- FIG. 4 is an orthogonal table showing an example of design parameter assignment in the second case according to the present invention.
- the control factors are A, B, C, D
- the error factors are X, Y, Z, W.
- the third case is a case where control factors are allocated to an appropriate orthogonal table, error factors are mixed, the conditions are unified into 2-3 conditions, and no signal factors are included.
- FIG. 5 is an orthogonal table showing an example of design parameter assignment in the third case according to the present invention.
- the control factors are A, B, C, D
- the error factors are X, Y, Z, W
- the conditions are Nl, N2.
- the fourth case is a case where the control factors are assigned to an appropriate orthogonal table and the dynamic characteristics include signal factors. All combinations of the error factor assignment methods shown in the first to third cases can be executed.
- FIG. 6 is an orthogonal table showing an example of design parameter assignment in the fourth case according to the present invention.
- the control factors are A, B, C, D, and the signal factor Is Ml, M2, M3, and conditions are Nl, N2.
- FIG. 7 is a diagram showing an example of an analysis pattern setting GUI in creating an orthogonal table according to the present invention.
- the user sets the number of combinations of inner factors and outer factors.
- FIG. 8 is a diagram showing an example of a GUI for setting control factors in creating an orthogonal table according to the present invention.
- the user sets the orthogonal table type, control factor variable name, and level value.
- FIG. 9 is a diagram showing an example of a GUI for setting a combination of control factors in creating an orthogonal table according to the present invention.
- the user sets the combination of control factors based on the orthogonal table.
- FIG. 10 is a diagram showing an example of a GUI for setting an error factor in creating an orthogonal table according to the present invention.
- the user sets the variable name and level value of the error factor, and also the error factor formulation.
- the simulation input creation unit 12 creates a simulation input file for each combination of design parameters using the combination of design parameters obtained in the experiment planning unit 11 and a simulation input template file prepared in advance. Then, it is passed to the simulation instruction unit 21 (S13).
- the simulation input file is a file describing settings to be input to the simulation.
- the simulation input template file is a file that describes the basic settings that form the basis of the simulation input file. Variables are indicated by variable numbers with "$".
- FIG. 11 is a table showing an example of correspondence between variable names and variable numbers according to the present invention.
- FIG. 12 is a table showing an example of a simulation input template file according to the present invention.
- This simulation input template file contains variable numbers with "$".
- the variable number with "$" is used, but other identifiers may be used.
- the simulation input creation unit 12 replaces the variable number in the simulation input template file with the variable value for each combination of design parameters obtained in the experiment planning unit 11 according to the correspondence between the variable name and the variable number. Created as a simulation input file.
- the error factor name does not match the control factor name
- the above replacement is performed as it is, but if the error factor name matches the control factor name, the error factor name Is recognized as an error variable name for the control factor, and then the above-described replacement is performed.
- error factor A is treated as error factor ⁇ A because it has the same variable name as control factor A.
- FIG. 13 is a table showing an example of a simulation input file according to the present invention.
- the variable number in the simulation input template file in Fig. 12 is replaced with the variable value.
- This simulation input creation unit 12 makes it easy to create a large number of simulation input files just by making one simulation input template file easy, and even if the error factor name matches the control factor name, it is appropriate. Processing can be performed.
- the simulation instruction unit 21 transmits a simulation input file to the simulation server 2 and instructs execution of the simulation (S21).
- the simulation result extraction unit 22 receives the simulation result from the simulation server 2 (S22)
- the simulation result force also extracts an evaluation characteristic value necessary for the analysis, and a combination of the design parameter value and the evaluation characteristic value for each simulation.
- the extracted evaluation characteristic value can be referred to.
- FIG. 14 is a diagram showing an example of an evaluation characteristic value reference GUI according to the present invention. Here, an evaluation characteristic value for each simulation is displayed.
- the analysis unit 30 performs analysis according to the analysis method designated by the user power, and stores the analysis result in the design information database 50 (S31).
- the display unit 51 displays the analysis result (S32) and ends this flow.
- the analysis unit 30 performs analysis using the analysis method selected by the user. Here, six types of analysis methods are described.
- FIG. 15 is a flowchart showing an example of the first analysis method according to the first embodiment.
- the quality engineering analysis unit 32 calculates the degree of influence of the control factor on the evaluation characteristic value from the set of the input design parameter value and evaluation characteristic value set, and the design information database as the analysis result. (S41), and this flow ends.
- Influence The degree is, for example, an SN ratio.
- the degree of influence, which is the analysis result, can be displayed on the display unit 51.
- FIG. 16 is a diagram showing an example of the display of the analysis result of the quality engineering analysis unit according to the present invention. The example in this figure is the case where 10 control factors of 2 levels are analyzed, and the change of the signal-to-noise ratio [dB] with respect to the change of the level value of each control factor is shown. For example, it can be seen that when the level of control factor A changes from A1 to A2, the SN ratio changes by about 5 dB.
- FIG. 17 is a flowchart showing an example of the second analysis method according to the first embodiment.
- the response surface calculation unit 31 is an approximate expression that represents the relationship between the design parameter value and the evaluation characteristic value by using the least square method from the set of the set of the input design parameter value and the evaluation characteristic value.
- a response surface is calculated and stored in the design information database as an analysis result (S51), and this flow is terminated.
- FIG. 18 is a diagram showing an example of a display setting screen for the analysis result of the response surface calculation unit according to the present invention. When the display setting is made on this screen and the “graph output” button is clicked, a response surface dull as an analysis result is displayed on the display unit 51.
- FIG. 19 is a flowchart showing an example of the third analysis method according to the first embodiment.
- the response surface calculation unit 31 calculates the response surface in the same manner as the processing S51, and outputs it to the quality engineering analysis unit 32 (S61).
- the quality engineering analysis unit 32 uses the response surface obtained from the response surface calculation unit 31 to calculate the degree of influence of the control factor on the characteristic value with an arbitrary value of the control factor. Store in the design information database (S62), and end this flow.
- FIG. 20 is a flowchart showing an example of the fourth analysis method according to the first embodiment.
- the clustering unit 41 selects a set having an evaluation characteristic value that is equal to or greater than a preset design allowable value from the set of input design parameters and evaluation characteristic values.
- the evaluation characteristic value is equal to or greater than the design allowable value, it is determined that the evaluation characteristic value can be designed.
- clustering is performed to classify the selected set into clusters, and a set of design parameter values and evaluation characteristic values for each cluster is output to the quality engineering analysis unit 32 (S71).
- the Euclidean distance or Mahalanobis distance which is the distance between the points represented by the set of design parameter values and evaluation characteristic values, is calculated, and nearby points based on the distance are used as clusters. Clustering is performed by putting them together.
- the quality engineering analysis unit 32 calculates the degree of influence for each cluster in the same manner as the processing S41, stores it in the design information database as the analysis result for each cluster (S72), and ends this flow. .
- FIG. 21 is a diagram showing an example of the operation of the clustering unit according to the present invention.
- the horizontal axis is 1 variable, 17-level control factor X, and the vertical axis is the evaluation characteristic value Y.
- a line indicating the design tolerance of Y is drawn.
- a solution with a Y value exceeding the design tolerance is a designable solution.
- it is classified into three clusters of point power consisting of X and Y pairs that can be designed.
- the degree of influence of the solution control factor X on the evaluation characteristic value Y differs for each cluster. For example, even if X changes greatly in cluster 1, Y does not change so much.
- cluster 2 and cluster 3 the change in Y with respect to the change in X is large. In this way, it is possible to perform highly accurate analysis by classifying into clusters and performing individual analysis.
- FIG. 22 is a flowchart showing an example of the fifth analysis method according to the first embodiment.
- the clustering unit 41 performs clustering in the same manner as in the processing S71, and outputs a set of design parameter values and evaluation characteristic values for each cluster to the response surface calculation unit 31 (S8 Do)
- the unit 31 calculates a response surface for each cluster in the same manner as the processing S51, stores it in the design information database as an analysis result for each cluster (S82), and ends this flow.
- FIG. 23 is a flowchart showing an example of the sixth analysis method according to the first embodiment.
- the clustering unit 41 performs clustering in the same manner as the processing S71, and outputs a set of design parameter values and evaluation characteristic values for each cluster to the response surface calculation unit 31 (S9 Do)
- the unit 31 calculates a response surface for each cluster in the same manner as the processing S51 and outputs the response surface to the quality engineering analysis unit 32 (S92)
- the quality engineering analysis unit 32 calculates the response surface for each cluster. Using the response surface obtained from part 31, the degree of influence of the control factor on the characteristic value is calculated with an arbitrary value of the control factor based on the center of gravity of the cluster, and the analysis result for each cluster is sent to the design information database. Store (S93) and end this flow.
- FIG. 24 is a block diagram showing an example of the configuration of the design support apparatus according to the second embodiment. 24, the same reference numerals as those in FIG. 1 denote the same or corresponding parts as those in FIG. 1, and the description thereof is omitted here.
- FIG. 24 includes a design support apparatus 101 instead of the design support apparatus 1.
- the design support apparatus 101 to be compared with the design support apparatus 1 includes a simulation input generation unit 112 instead of the simulation input generation unit 12 and an analysis unit 130 instead of the analysis unit 30.
- the analysis unit 130 includes a response surface calculation unit 131 instead of the response surface calculation unit 31, a quality engineering analysis unit 132 instead of the quality engineering analysis unit 32, and clustering instead of the clustering unit 41. Part 141 is provided.
- FIG. 25 is a flowchart showing an example of the operation of the design support apparatus according to the second embodiment.
- the same reference numerals as those in FIG. 2 indicate the same or equivalent processes as those in FIG. 2, and the description thereof is omitted here.
- process S113 is executed instead of process S13
- process S131 is executed instead of process S31.
- Fig. 26 is an orthogonal table showing an example of error factor assignment in normal quality engineering.
- 1 error factor (X) is 3 levels and 2 control factors (A, B) are 3 levels, it is necessary to perform 27 cases (C1-C27) simulation in normal quality engineering .
- the simulation input creation unit 112 reduces the number of combinations of design parameters used in the simulation by assigning error factors or the like, which are usually outside factors in quality engineering, to appropriate orthogonal tables as inside factors.
- FIG. 27 is an orthogonal table showing an example of allocation of error factors by the simulation input creation unit according to the second embodiment. According to the simulation instruction unit 61, FIG. 26 and FIG. As shown in the example of 27, the time required for simulation can be reduced to 1Z3 from 27 cases (C1 to C27) to 9 cases (D1 to D9).
- simulation input creation unit 112 creates a simulation input file in the same manner as the simulation input creation unit 12.
- a set of reduced design parameter values and evaluation characteristic values is input from the simulation result extraction unit 22 to the analysis unit 130.
- Analysis Department Thus, by first calculating the combined force response surface from which the response surface calculation unit 131 has been reduced, the response surface force can be obtained as an evaluation characteristic value for an arbitrary value of the control factor. Therefore, although combinations are reduced by the simulation input creation unit 112, combinations used for analysis can be arbitrarily selected.
- the analysis unit 130 performs analysis using the analysis method selected by the user. Here, five types of analysis methods are described.
- FIG. 28 is a flowchart showing an example of the first analysis method according to the second embodiment.
- the response surface is calculated in the same manner as in step S51 (S151), and this flow is terminated.
- FIG. 29 is a flowchart showing an example of the second analysis method according to the second embodiment.
- the response surface calculation unit 131 calculates a response surface in the same manner as the processing S51 and outputs it to the quality engineering analysis unit 132 (S161).
- the quality engineering analysis unit 132 calculates an arbitrary set of control factor values and characteristic values using the response surface obtained from the response surface calculation unit 131, and calculates the influence of the control factors on the characteristic values.
- the analysis result is stored in the design information database (S162), and this flow ends.
- FIG. 30 is a flowchart showing an example of the third analysis method according to the second embodiment.
- the response surface calculation unit 131 calculates the response surface described above and outputs it to the clustering unit 141 (S170).
- the clustering unit 141 calculates a set of arbitrary design parameter values and evaluation characteristic values using the response surface obtained from the response surface calculation unit 131 and compares it with a preset design allowable value. To select a set of design parameter values and evaluation characteristic values corresponding to the characteristic values that can be designed.
- clustering is performed to classify the selected set into clusters in the same way as in process S71, and design for each cluster
- a set of pairs of parameter values and evaluation characteristic values is output to the quality engineering analysis unit 132 (S171).
- the quality engineering analysis unit 132 calculates the degree of influence for each cluster in the same manner as the processing S41, stores it in the design information database as the analysis result for each cluster (S172), and ends this flow. .
- FIG. 31 is a flowchart showing an example of the fourth analysis method according to the second embodiment.
- the response surface calculation unit 131 calculates a response surface in the same manner as the processing S170 and outputs the response surface to the clustering unit 141 (S180).
- the clustering unit 141 performs clustering in the same manner as the processing S171, and outputs a set of design parameter values and evaluation characteristic values for each cluster to the response surface calculation unit 131 (S181).
- the response surface calculation unit 131 calculates the response surface for each cluster in the same manner as the processing S51, stores it in the design information database as the analysis result for each cluster (S182), and ends this flow. .
- FIG. 32 is a flowchart showing an example of the fifth analysis method according to the second embodiment.
- the response surface calculation unit 131 calculates a response surface in the same manner as the processing S170 and outputs the response surface to the clustering unit 141 (S190).
- the clustering unit 141 performs clustering in the same manner as the processing S171, and outputs a set of design parameter values and evaluation characteristic values for each cluster to the response surface calculation unit 131 (S191).
- the response surface calculation unit 131 calculates the response surface described above for each cluster and outputs the response surface to the quality engineering analysis unit 132 (S192).
- the quality engineering analysis unit 132 uses the response surface for each cluster obtained from the response surface calculation unit 131 to influence the control factor on the characteristic value with an arbitrary value of the control factor based on the center of gravity of the cluster. The degree is calculated and stored in the design information database as an analysis result for each cluster (S193), and this flow ends.
- a program that causes a computer constituting the design support apparatus to execute the above steps can be provided as a design support program.
- the above-described program can be executed by a computer constituting the design support apparatus by storing the program in a computer-readable recording medium.
- the recording medium readable by the computer includes an internal storage device such as a ROM and a RAM, a portable storage such as a CD-ROM, a flexible disk, a DVD disk, a magneto-optical disk, and an IC card.
- the analysis unit corresponds to the response surface calculation unit, the quality engineering analysis unit, and the clustering unit in the embodiment.
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JP2007509067A JP4648386B2 (ja) | 2005-03-18 | 2005-03-18 | 設計支援装置、設計支援方法、設計支援プログラム |
US11/857,136 US20080004855A1 (en) | 2005-03-18 | 2007-09-18 | Design support apparatus, design support method, and design support program |
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US11/857,136 Continuation US20080004855A1 (en) | 2005-03-18 | 2007-09-18 | Design support apparatus, design support method, and design support program |
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JP2007087098A (ja) * | 2005-09-22 | 2007-04-05 | Nissan Motor Co Ltd | 最適化システム、最適化方法、最適化プログラム、及びプログラム媒体 |
KR100887187B1 (ko) * | 2005-12-15 | 2009-03-10 | 인터내셔널 비지네스 머신즈 코포레이션 | 실험 고안 정보 지정 방법, 기계 액세스 가능 매체, 데이터 프로세싱 컴퓨터 시스템 및 실험 고안 정보 분석 방법 |
WO2009044850A1 (ja) * | 2007-10-04 | 2009-04-09 | Ihi Corporation | 製品設計支援システム及び方法 |
JP2009288785A (ja) * | 2008-05-01 | 2009-12-10 | Ricoh Co Ltd | 組合せレンズ装置の評価方法、プログラム及び記憶媒体 |
KR101246185B1 (ko) | 2012-01-20 | 2013-03-25 | 삼성중공업 주식회사 | 곡형 부재의 가공 완성도 평가 방법 및 그 시스템 |
WO2014132885A1 (ja) * | 2013-02-27 | 2014-09-04 | 三菱レイヨン株式会社 | ゴルフ用具フィッティングシステム、及びゴルフ用具フィッティングプログラム |
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EP2932091B1 (en) | 2012-12-12 | 2016-07-27 | Repsol, S.A. | Energy converters and energy conversion systems |
JP7496497B2 (ja) * | 2020-08-27 | 2024-06-07 | パナソニックIpマネジメント株式会社 | 情報処理方法、プログラム、および情報処理装置 |
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JP2007087098A (ja) * | 2005-09-22 | 2007-04-05 | Nissan Motor Co Ltd | 最適化システム、最適化方法、最適化プログラム、及びプログラム媒体 |
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JP2009288785A (ja) * | 2008-05-01 | 2009-12-10 | Ricoh Co Ltd | 組合せレンズ装置の評価方法、プログラム及び記憶媒体 |
KR101246185B1 (ko) | 2012-01-20 | 2013-03-25 | 삼성중공업 주식회사 | 곡형 부재의 가공 완성도 평가 방법 및 그 시스템 |
WO2014132885A1 (ja) * | 2013-02-27 | 2014-09-04 | 三菱レイヨン株式会社 | ゴルフ用具フィッティングシステム、及びゴルフ用具フィッティングプログラム |
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US20080004855A1 (en) | 2008-01-03 |
JPWO2006100712A1 (ja) | 2008-08-28 |
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