JP3597153B2 - Cutting tool performance evaluation system and cutting tool design method - Google Patents

Description

[0001]
TECHNICAL FIELD OF THE INVENTION
The present invention relates to a cutting tool performance evaluation system and a cutting tool design method that reflect the needs of many users.
[0002]
[Prior art]
Conventionally, the design of cutting tools has traditionally been based on daily business activities that capture user requirements, and the designer determines the tool shape, material, etc. to satisfy them, and implements the process of tool prototype, test machining / evaluation, and redesign. The developed product obtained as a result is repeatedly provided to the user, and the final performance is confirmed and commercialized.
[0003]
However, there are various performance standards of cutting tools such as wear resistance, chipping resistance, processing power, processing accuracy, and finished surface gloss, and many of them have a trade-off relationship. In addition, there are some things that are difficult to judge in general, such as chip controllability. Generally, it is not sufficient that only some of these performance criteria are satisfied, and therefore, respective weights are necessary.However, there are few cases where each user has a quantitative criterion for weighting, and each user needs Performance criteria will be implicit. For this reason, conventionally, a designer has set a design target by estimating a user's evaluation criterion based on indirect information from a sales representative.
[0004]
Also, the process of evaluating prototypes by actual processing takes time, and it is difficult to evaluate many prototypes. For this purpose, attempts have been made to improve efficiency by executing a cutting process in a virtual space using a computer simulation.
[0005]
U.S. Pat. No. 5,377,116 entitled "Method and System for Designing Cutting Tools" discloses a simulation-based performance prediction and knowledge-based inference such as an expert system for some parameters representing a tool shape. Using the mechanism, the tool shape is automatically optimized. However, in the case of three-dimensional tools that are frequently used in actual machining, that is, tools in which the rake surface cross-sectional shape in the direction perpendicular to the cutting edge is not uniform, the rake surface shape must be defined by several parameters. Therefore, even if the required performance is clear, it is impossible to optimize the tool shape by the same method. That is, even when cutting performance is predicted by experiment or simulation for a tool shape in the course of design, there is no clear standard for a method of changing the design shape, and it actually depends on the intuition and experience of the designer in charge.
[0006]
[Problems to be solved by the invention]
As described above, the conventional method is mainly designed and evaluated by the designer of the supplier, and the needs of the user are only reflected indirectly. In order to solve such a problem, it is conceivable that a user directly evaluates a prototype in the design process. This would allow the design of cutting tools to meet the needs of specific users, but it is necessary to increase the overall evaluation of not only specific users but also multiple users in mass-produced cutting tools. . Further, regarding the correction of the tool shape, it is necessary to generate a solution candidate group that is not biased to a specific tendency and is diverse and is considered to have a certain performance because the efficiency is not extremely reduced.
[0007]
Accordingly, a main object of the present invention is to provide a cutting tool evaluation system in which a plurality of users can participate in a cutting tool design process in designing a cutting tool, and can accurately capture the needs and knowledge of the cutting tool. is there.
[0008]
Another object of the present invention is to provide a method for designing a cutting tool with a high degree of satisfaction that sufficiently reflects the needs and knowledge of the user.
[0009]
[Means for Solving the Problems]
According to the present invention, both a tool supplier and a user use a virtual machining system (hereinafter, referred to as VMS) to predict the performance of a tool model in a cutting process by simulation using a virtual machining system (hereinafter, referred to as VMS), and perform cutting based on the prediction result. The above objectives are achieved by performing tool performance evaluation and design.
[0010]
That is, the cutting tool performance evaluation system of the present invention includes a tool design information database for registering information on a tool model, information on a tool model extracted from the tool design information database by a user via a communication network, and setting by the user. A means for simulating the chip generation process when using a tool model based on the cutting conditions and predicting the performance item results, a calculation result database storing the prediction results obtained by the prediction means, and a user communicating An evaluation information database for registering evaluation results for prediction results extracted from a calculation result database via a network, and a means for totalizing the evaluation results are provided.
[0011]
The method of designing a cutting tool according to the present invention includes the steps of: registering information of a tool model presented by a model provider in a tool design information database; and extracting a tool model information from a tool design information database by a user. Simulating the chip generation process when using the tool model with the cutting conditions set by the user and predicting the performance item results, storing the prediction results in a calculation result database, Registering the evaluation result for the prediction result extracted from the calculation result database in the evaluation information database; totalizing the evaluation result of the user; and, based on the total result, the model provider changing the information of the tool model. And adding the changed tool model to the tool design information database. .
[0012]
In this way, the supplier and the user evaluate the efficient tool model using the VMS, and reflect the results in the design of the tool, so that a highly satisfactory cutting tool that sufficiently reflects the needs of the user can be obtained. Can be designed. Further, it is possible to reflect opinions of a sales person or the like who has not been involved in the conventional design.
[0013]
Also, by summing up the evaluations of a plurality of users, the evaluation tendency of a specific user is not biased, so that a product that satisfies the needs of many users can be designed.
[0014]
In particular, in the system of the present invention, the evaluator can know which performance item the tool is being purchased with emphasis on by purchasing the tool by using a method described later in the method of summing up the prediction results. More optimal parameters can be extracted as indices. Therefore, the performance items that are valued by the evaluator can be improved, and for each performance item, an optimal parameter can be used as an evaluation index, and a cutting tool with higher user satisfaction can be designed.
[0015]
Hereinafter, the system of the present invention and a design method using the same will be described in more detail.
First, the definitions of suppliers, users, users, and model providers will be described.
Supplier: A person who manufactures and sells tools.
User: A person who purchases and uses tools.
Model provider: A person who registers a tool model in the tool performance evaluation system, which may be a supplier or a user.
User: A person who uses the tool performance evaluation system, and includes all of suppliers, users, and model providers.
As is clear from this definition, the system of the present invention can be used not only when a supplier provides a tool model and the user evaluates the model, but also when the user himself becomes a provider of the tool model and converts the model into another model. Any type of usage is possible, such as when the user or supplier evaluates or when the model provider evaluates itself. In particular, by evaluating a tool model by a plurality of users, it is possible to obtain a tool with a higher degree of satisfaction reflecting needs.
[0016]
A tool model is registered in the tool information database. The tool model includes a tool shape and a tool material type. Most commonly, suppliers create and register tool models. Not only a supplier but also a user may create and register a tool model. In other words, the designer of the supplier or the like registers the information of the tool model, and the user performs the evaluation of the tool model, as well as the user registers the information of the tool model. It is also possible for the user to do this. As a result, not only the supplier but also the user can carry out the design directly, and the tool reflecting the user's needs can be easily designed.
[0017]
The registration of the tool model is performed using a file transfer service server such as an FTP server via a communication network such as the Internet. The registered tool model can be browsed using a document browse server such as a WWW server via a communication network. At that time, it is preferable to provide an authentication means for authenticating the user.
[0018]
The tool model is browsed using a WWW server or the like, and the performance of the tool model in the cutting process is simulated and predicted by VMS. This simulation requires setting of cutting conditions in addition to the tool model. Generally, a user who browses a tool model sets a cutting condition desired by the user and performs a simulation. Of course, it is also possible for the supplier itself to simulate to perform a self-evaluation of the tool model. The cutting conditions include a cutting speed, a feed, a depth of cut, a work material type, and the like. The performance items predicted by the simulation include a plurality of items such as a chip shape, a tool stress, and a tool temperature, and these are processed to obtain a wear rate, a chipping probability, a cutting force, and the like.
[0019]
The prediction result of each performance item obtained by the calculation is accumulated in the calculation result database. A user (supplier / user) can access the calculation result database using a WWW server or the like via a communication network and browse the prediction result.
[0020]
Browse the prediction results and evaluate the tool model for each performance item. In general, it is preferable that the evaluation be performed by scoring. At the same time, the degree of desired use of the tool model is scored. This evaluation is stored in the evaluation information database.
[0021]
Then, the prediction result and the evaluation result of the user are totaled. In this tabulation, for example, the average of the evaluation scores performed by a plurality of evaluators is obtained. The designer of the tool model repeats the process of changing the tool shape and the like for the tool with a high evaluation and executing the simulation again by the user to make the prediction result and the evaluation result viewable.
[0022]
Evaluation of a plurality of types of tool models is obtained by changing the tool model, and a more preferable tool model can be clarified by ranking the average value for each tool model. This ranking result can also be browsed by a user using a WWW server or the like via a communication network. It goes without saying that the tool model designer designs the tool such that the evaluation of a plurality of users is enhanced through the above-described iterative process. Then, the supplier's designer performs a detailed design for the tool with the highest evaluation among these.
[0023]
The above-mentioned ranking is preferably performed by classifying at least one of the use of the tool model, the use form of the tool, and the type of business of the tool user. Tool model categories (applications) include general-purpose, high-speed machining, finishing, and difficult-to-cut materials. Tool usage forms include automatic line production and small-lot production. It is preferable to use a cutting condition database in which cutting conditions are registered for use determination of the tool model. In the cutting condition database, a range of cutting conditions corresponding to each category such as general-purpose, high-speed machining, finishing, and difficult-to-cut materials is registered. Then, the cutting conditions set by the user are compared with the range of each cutting condition. For example, if the cutting speed set by the user is equal to or more than the lower limit of the cutting condition range for high-speed machining, the feed / cutting is performed for high-speed machining. If it is less than or equal to the upper limit of the range of cutting conditions for finishing, it is determined to be for finishing. The usage form of the tool and the type of tool user are determined from the user registration information. Further, it is also preferable that typical conditions in the range of the registered cutting conditions are defined as standard cutting conditions so that simulation can be performed under the standard cutting conditions.
[0024]
In particular, the evaluation of each performance item and the evaluation of the desired use of the tool model are numerically stored in the evaluation information database, and the absolute value of the difference between the evaluation of each performance item and the evaluation of the desired use is obtained by means of summing up. It is possible to determine the performance item that the user emphasizes on the basis of the result of the aggregation. For example, a difference between a score for each performance item issued by each user and a desired use degree is made into a histogram, and the histogram can be viewed by a supplier, thereby extracting a performance item that the user regards as important when purchasing a tool.
[0025]
In addition, among the performance items, for items such as the chip shape and the temperature distribution shape of the tool rake face, for which the optimal numerical parameters are not sufficiently determined as the evaluation index of each user, the correlation analysis is performed as follows. By doing so, it is also possible to determine which evaluation parameter is optimal. That is, the prediction result of the performance item is indexed by a plurality of evaluation index parameters by the cutting performance prediction means. Further, the counting means obtains a correlation between the evaluation index parameter and the evaluation of the prediction result for each performance item, and determines a suitable evaluation index parameter based on the correlation. For example, a supplier designer sets temporary evaluation parameters, creates a correlation diagram between each parameter and a score average value for each performance item issued by the user, and enables the designer to browse the results. Thus, it is understood that a parameter having a strong correlation with the user's evaluation is a more preferable evaluation parameter.
[0026]
BEST MODE FOR CARRYING OUT THE INVENTION
Hereinafter, embodiments of the present invention will be described with reference to the drawings.
[0027]
<System configuration>
FIG. 1 is a schematic diagram of the cutting tool performance evaluation system of the present invention. A designer (tool supplier) and a user (tool user) connect to a tool performance evaluation system 1 (hereinafter, an evaluation server) from their own clients via the Internet. Here, a designer presents a tool model, and for this tool model, the user A performs performance item prediction by cutting simulation and evaluates the prediction result. Similarly to the user A, the other user B also predicts performance items by simulation and evaluates the prediction result. Then, the designer and users A and B can browse these prediction results and evaluations with each other using a browser.
[0028]
The evaluation server is broadly divided as shown in FIG. 2 and includes a user interface 10, a tool information providing system 20, a VMS 30, an evaluation support system 40, and a general information database 50. Each system has the following configuration. ing.
[0029]
(Tool information providing system)
The tool information providing system 20 stores the design information of the tool model, that is, the tool design information database 21 for registering the tool shape and the material type of the tool, and the provided design information of the tool model in a format suitable for accumulation in this database. And an information format inspection unit 22 for determining whether or not there is any information. An individual tool number is assigned to each piece of design information. When browsing a tool shape or executing a simulation, the design information is called based on the tool number. As data necessary for the tool shape, at least data on a tool rake face necessary for simulation may be used.
[0030]
(VMS)
The VMS 30 is a simulation system that simulates a chip generation process when using a tool model based on information of a tool model extracted from a tool design information database and cutting conditions set by a user, and predicts a performance item result. is there.
[0031]
The VMS 30 includes a work material characteristic database 31 which stores work material characteristics (physical values such as material type, flow stress characteristics, elastic modulus, and heat conduction characteristics) necessary for simulation, and tool material characteristics (material type, elasticity). Tool information characteristic database 32 in which physical property values such as rate, heat conduction characteristics, and rake face friction characteristics) are stored. The mesh creating unit 33 creates an FE (Finite Element) model of the work material and the tool for the finite element method. To the mesh creating unit 33, via the control unit 34, a command to extract a physical property value of a tool model and a tool material type corresponding to a tool number selected by a user, a command to extract a physical property value of a work material type, In addition, cutting conditions necessary for creating the FE model of the work material are transmitted.
[0032]
Further, with respect to the input of the work material, the initial coordinates of the tool, the boundary conditions, the physical property values, and the like created by the mesh creation unit 33, the coordinates, displacement, nodal force, temperature, A calculation unit 35 for calculating stress, strain, and the like at each element integration point is provided. The calculation result in the calculation unit 35 is output together with the calculation result number.
[0033]
(Evaluation support system)
The evaluation support system 40 creates and registers information for the user to evaluate the tool based on the calculation result of the simulation. From the calculation results output from the VMS 30, the calculation result processing unit 41 calculates the cutting force, tool surface wear rate distribution, and the like, calculates various parameters, and creates browsing image information. This calculation result is stored in the calculation result database 42, and can be viewed by the user as a prediction result for each performance item using a WWW browser. The user can evaluate the prediction result for each performance item viewed. The user's evaluation information is registered in the evaluation information database 43. The calculation result of the calculation result database 42 and the evaluation result of the evaluation information database 43 are totaled by the browsing information creating unit 44, and browsing information is created so that the totaling result can be browsed through the WWW server. Regarding the calculation result and the evaluation result, a calculation result number and an evaluation result number are individually assigned to each tool. Further, a cutting condition database 45 for storing cutting conditions is also provided. In this cutting condition database 45, a range of cutting conditions corresponding to each category such as general-purpose, high-speed machining, finishing, and difficult-to-cut materials is registered.
[0034]
(General information database)
Correspondence between tool number and designer information, calculation result number and evaluation result number, design / evaluation history information, user address / name / company name / email address, business type, tool usage (automatic line or small amount General information such as correspondence between user information (for production) and the like is stored in the general information database 50.
[0035]
(User interface)
A user interface 10 for the user to exchange information with each of these units 20, 30, 40, and 50 includes an FTP server 11 for registering tool information, a WWW for receiving a simulation execution instruction, a result browsing, an evaluation registration, and the like. It comprises a server 12 and an SMTP server 13 for notifying various information by e-mail to the user. Further, an authentication unit 14 for issuing a user ID to a user who accesses the FTP server 11 or the WWW server 12 or performing authentication is provided. Further, a notification information creation unit 15 for creating various information notified by e-mail is provided.
[0036]
(Other)
Each user needs only a WWW browser when only browsing simulation instructions and results and registering evaluations, and a tool designer needs a CAD calculation system and FTP client software in addition.
[0037]
If the designer is inside the supplier, the evaluation server and the CAD calculation system may be realized on the same computer. Further, since the object of the shape design is only the tool rake face as described above, the CAD calculation system may be a general system or a simple system dedicated for each cutting mode.
[0038]
<Tool performance prediction flow>
FIG. 3 shows a flow until the user performs tool performance prediction. In advance, the user who participates in the evaluation registers the user, registers information such as the company name, the type of business, and the use form of the tool (for automatic line or small-quantity production) and receives a user ID. The designer of the supplier also receives the user ID.
[0039]
First, a designer inside a supplier designs a tool using a CAD calculation system. The designer registers this design information (rake face shape and material) in the evaluation server. In the case where the CAD calculation system is a designer on a different computer from the evaluation server, the design information is registered by a file transfer service such as FTP via the intranet or the Internet. At this time, the user ID of the designer is authenticated by the authentication unit. The fact that the registration of the tool model has been performed and the problem with the format of the design information have been sent to the notification information creation unit 15, and the mail address of the designer (model provider) is read from the general information database, Will be notified. When a supplier registers a tool model, this notification is sent only to the supplier's designer. When the CAD calculation system is on the same computer as the evaluation server (when not passing through the FTP server), this notification is not performed without needing to be notified by e-mail.
[0040]
Next, the user accesses the evaluation server 1 from the client through a WWW browser to check the cutting performance when the tool model is used. The tool designer himself may also make the evaluation.
[0041]
The WWW server 12 is configured to be able to select and browse each document page such as general reception, virtual cutting instruction reception, tool shape / calculation result viewing, result evaluation / impression reception, price information reception, and the like. The user inputs a user ID from the client, and performs authentication in the authentication unit through “general reception” of the evaluation server. The authentication unit 14 performs authentication by comparing the input user ID with data on the user ID in the general information database 50.
[0042]
When the authentication is completed, the user issues a command to read out the tool shape data to the tool design information database 21 from “Browse tool shape / calculation result” and browses the tool shape to be evaluated.
[0043]
Next, for the tool shape to be evaluated from the “virtual cutting command reception”, the registered tool number, cutting speed, feed, cutting, and the kind of the work material are inputted, and a command is issued to perform a simulation. At that time, the cutting condition set by the user is compared with the range of the cutting condition for each application in the cutting condition database 45, and, for example, if the cutting speed set by the user is equal to or more than the lower limit of the high-speed cutting condition, For high-speed machining, if the feed / cut is equal to or less than the upper limit of the finish machining cutting conditions, it is determined to be for finish machining, and if the work material is difficult to machine such as Ti alloy, it is determined to be for difficult-to-cut materials.
[0044]
The simulation command is transmitted to the VMS 30 using CGI or the like. The command is transmitted to the control unit 34, and the control unit 34 instructs the tool design information database 21 to extract a tool shape and a tool material type corresponding to the tool number. The tool design information database 21 outputs data relating to the tool shape to the mesh creating unit 33, outputs data relating to the tool material type to the tool material characteristic database 32, and sends the physical property values corresponding to the tool material type to the mesh creating unit 33. Output. Further, the control unit 34 outputs data relating to the work material type to the work material characteristic database 31 and causes the mesh creation unit 33 to output the physical property values corresponding to the work material type. Further, the control unit 34 also outputs cutting conditions such as cutting speed, feed, and cutting to the mesh creating unit 33. The mesh creation unit 33 creates a finite element model from the obtained information, and the calculation unit 35 performs the calculation. By this calculation, the nodal coordinates of the finite element model, nodal forces, stresses, and the like are calculated, and the calculation results are sent to the evaluation support system 40. Since these calculations often require several hours of calculation, the user is notified by e-mail or the like together with the calculation result number that the calculation result can be viewed after the calculation is completed. At this time, a calculation result number is assigned to the calculation result, and the calculation result number is output to the notification information creation unit 15.
[0045]
In the evaluation support system 40, the wear rate distribution and the like are calculated by the calculation result processing unit 41 based on the calculation result in the VMS 30, and the various distributions and chip shapes are displayed in the form of images and animations so that the user can browse them with a browser. Is converted to Then, the data such as the image and the animation is stored in the calculation result database 42 together with the quantitative data such as the cutting force.
[0046]
<Evaluation method for each user's tool>
Upon receiving the calculation end notification, the user accesses the server again and extracts the calculation result corresponding to the calculation result number from the calculation result database through “view tool shape / result”. For example, a calculation result screen as shown in FIG. 4 can be browsed. Here, the chip shape is shown by an image together with the tool model number, the work material type, and the cutting conditions, and numerical values such as various curl diameters are also shown. Similarly, the results of other performance items and the evaluation of tool models created and predicted by other users can be viewed.
[0047]
The main performance items shown as simulation results and their evaluation indices are as follows.
Chip shape: A three-dimensional shape of a chip, and an upward curl diameter, a lateral curl diameter, an outflow angle, a chip width, and the like are evaluation indices.
Tool temperature: The temperature of the tool at the time of cutting. The maximum temperature at the time of cutting or the area within a predetermined temperature range from the maximum temperature is used as an evaluation index.
Tool stress: The vertical force per unit area at each point on the tool surface (vertical stress) or the tangential force (shear stress). The stress acts on the tool surface only at the portion in contact with the work material, and is calculated from the stress distribution on the work material side according to the law of action and reaction.
-Wear rate: The wear depth per unit time at each point when the tool surface wears. It can be determined as a function of tool vertical stress, chip scraping speed, and temperature.
-Probability of loss: Probability that the tool will be broken at each point on the tool plane from that point. The probability of occurrence of breakage in each finite element by one impact (bite on the work material) is determined.
・ Cutting force: The force applied to the tool during cutting.
However, as the cutting performance, the tool temperature, the tool stress, and the like are finally reflected in the results of the wear rate and the chipping probability. Therefore, the chip performance, the chipping rate, the chipping rate, and the chipping probability may be particularly indicated. .
[0048]
Among these, the criterion that the smaller the maximum value of the cutting force and the various distributions is, the better. Therefore, quantitative data with clear evaluation criteria is output from the calculation result database 42 to the browsing information creation unit 44 and A ranking is made among the users so that the user can browse them, and the data is used as reference data for user evaluation described later. The browsing information creating unit 44 performs totalization and ranking based on the plurality of evaluation data recorded in the evaluation information database and the quantitative data output from the calculation result database. Further, the browsing information creating unit 44 also performs a calculation relating to a search for an important performance item to be described later and a search for an evaluation index of data which is difficult to quantify.
[0049]
However, it is expected that the evaluation of the parameters and the like representing the chip shape will be different depending on the user. Since there is no general quantification standard for the form of various distributions, it is appropriate to have the user browse the distribution itself and quantify the determination. Therefore, for each performance item, for example, a score of 100 out of 100, "100 to 80: very suitable", "79 to 60: generally suitable", "59 to 40: neither can be said", Scores are given in the form of "39-20 points: not very suitable", "19-0 points: not suitable at all".
[0050]
Then, after the evaluation for each item, the user is asked to evaluate the degree of use desired from the viewpoint of whether he wants to buy (use) the tool. This evaluation is also a perfect score, and is "100-80 points: I want to buy very much", "79-60 points: I want to buy", "59-40 points: Normal", "39-20 points: I do not want to buy much" , "19-0 points: I never want to buy". At the time of such an evaluation, a list of scores scored by the evaluator for each performance item may be made available to the user before the evaluation, and may be used as a reference for the evaluation.
[0051]
In addition, since it is difficult to ask the user to evaluate all the results, standard cutting conditions are set for each category (application) such as (1) high-speed cutting, finishing, and difficult-to-cut materials. Ask them to evaluate the calculation results under the conditions. (2) Ask them to browse the results under multiple cutting conditions in each category, and have them evaluate each item from their comprehensive judgment. , And so on. In this case, the quantitative data such as the cutting force, which is used as a reference for evaluation, shall be ranked in each category.
[0052]
The score in the above-described form is registered in the evaluation information database 43 from the “reception of results and impressions” of the WWW server. At the time of evaluation, the contents of the general information database 50 are referred to, and when a specific user attempts to register the second evaluation for a certain result, a warning is issued. By deleting, care is taken not to bias the evaluation of a specific user.
[0053]
In addition, when registering a score, if a score that is more than a certain reference point from the average score described later is given, a confirmation screen is displayed to the user to confirm whether or not there is a mistake. May be ensured. In this case, the average point may be abnormal at a point when the number of parameters is still small, and the score assigned by the designer may be used as a temporary average point for confirmation. Such a temporary average point may be registered in the evaluation information database in advance.
[0054]
<How to combine evaluations>
Basically, scores obtained by a plurality of users are averaged for each calculation result (or a plurality of results in each category). Since the scores are given for each performance item and for the degree of desired use, the scores are averaged as shown in FIG. Then, regarding the degree of desired use of each tool, (1) each category (general purpose, high-speed machining, finishing, difficult-to-cut materials, etc.), (2) industry (judgment from user registration information), (3) For each usage mode (for automatic line or small-volume production: determined from user registration information) and for each of the combinations thereof, the order is represented as a rank, and the user and the designer can browse.
It is also effective that the supplier presents the expected price for the item with the highest rank. For example, when the order is changed in the evaluation information database 43, the fact is transmitted to the notification information creating unit 15 via the browsing information creating unit 44 together with the tool number, and the supplier is notified by e-mail. The supplier who has received the e-mail registers the tool's estimate information from the “price information reception” screen via the WWW server. Then, the price information is transferred to the browse information creating unit 44 and reflected on the browse screen.
[0055]
In addition, for each performance item, the average of the scores given by multiple users is also displayed for each category of category, business type, and usage pattern, so that the user can browse it for reference. May be.
[0056]
<Feedback to the tool design process>
Development priority products are basically those with the highest degree of use desired for each category. However, high-priority products, such as tools that are likely to grow in the future and high-ranking tools for automatic lines with a large purchase volume, are also highly effective as development priority products. The designer registers one or more new tool models obtained by further modifying such a high-order tool and adds them to the evaluation target.
[0057]
Then, for the tool that was finally popular, the supplier carries out detailed design (shape design other than the rake face, cutting edge treatment, detailed material design, process design, etc.). The prototype based on this detailed design is tested and commercialized.
[0058]
<Cutting tool design by multiple designers>
The above-described cutting tool performance evaluation method is effective because it can reflect the needs of a wide range of users even in the same case as the conventional case where a very limited number of suppliers design. Further, by extending this, it becomes possible to design a tool in which the user is mainly as shown in FIG. That is, a tool model designed by the user using the CAD calculation system is registered in the tool design information database 21, and their cutting performance is predicted using the VMS 30. Here, an example is shown in which a user A registers and changes a tool model in addition to a supplier's designer and evaluates the tool model. User B performs only the evaluation, and does not register or change the tool model.
[0059]
The following two forms can be considered as the flow of design, evaluation, and manufacturing when the user designs the tool itself.
[0060]
{Circle around (1)} Each user evaluates only the tool model designed by himself / herself using the VMS, and repeats the process of changing the design. The supplier finally manufactures the tool model determined by each user and provides it to each user.
[0061]
{Circle around (2)} A tool model designed by each of many users is mutually evaluated, and a supplier manufactures and sells a tool that has been highly evaluated by many users by an evaluation method using VMS.
[0062]
As for the former, the cutting tool is made to order for each user, so to speak, it is preferable that the supplier appropriately provides estimation information. Regarding the latter, of course, there may be a user who participates only in the evaluation without performing the design itself. Also, a designer in a normal supplier may be added as one evaluator.
[0063]
Furthermore, by using a common format for the tool design information, a system may be configured so that tool information designed by another user can be extracted, corrected, and performance predicted again. Tools designed in this way are initially designed and modified based on the experience, knowledge, and intuition of each user, so a wider variety of solutions can be used than when only a specific designer designs and modifies. It is thought that candidates are born.
[0064]
As described above, the users of the VMS can be expanded to sales representatives of the supplier who can easily understand customer needs, a limited number of contract users who have concluded a confidentiality agreement, or general users. Further, since the sales person in the supplier uses the information, many customer needs can be reflected even when the tool is closed in the supplier in order to enhance the confidentiality of the tool design information. As described above, the range of the user is appropriately selected by the supplier from the viewpoint of keeping the confidentiality of the tool design information.
[0065]
<Utilization of information>
The above-mentioned method enables the design of cutting tools to reflect the needs of more users, but various kinds of information appearing in the process can be used for ordinary tool development or for users with a few opinions. There are many important things to do. Hereinafter, a method for extracting such information will be described.
[0066]
(1) Search for important performance items (user needs)
In the above evaluation, since the score for each performance item and the score for the desired use degree are given, it is possible to know which item is emphasized and the purchase decision is made. For example, as shown in FIG. 7, the absolute value of the difference between the "score for each item" and the "score of desired use degree" is made into a histogram for each item, and the absolute value is obtained by the designer browsing or calculating the statistical value. It can be understood that the smaller the average of the values is, the higher the importance is, and the larger the variance is, the more the user's judgment criteria are different.
[0067]
If the score of the desired use degree is low (high) while the score of a certain performance item is high (low), it can be said that the performance item is not important and the other performance items are important. Conversely, if the score of a certain performance item and the score of the desired use are both high (low), it can be said that the performance item is important. For example, it is assumed that the score of the cutting force is 10 points and the desired use degree is 80 points, and the score of the chip is 80 points and the desired use degree is also 80 points. Then, the absolute value related to the cutting force is large, and the absolute value related to the chip is small. Therefore, if there are many evaluators whose absolute values are small, the performance evaluation is regarded as important, and in the example of FIG. 7, it can be understood that the chips are more important performance items.
[0068]
Furthermore, since the performance items to be emphasized can be found for each category (high-speed cutting, finishing, etc.) and for each type of business, this is important information for future tool development and sales strategies.
[0069]
(2) Search for evaluation indexes for data that is difficult to quantify
The chip shape can be quantified into several parameters, but it is not always possible to judge the quality based on the magnitude of a specific parameter. Furthermore, the shape of various distributions is not sufficiently established as a parameter itself as an evaluation criterion.However, any parameter such as a value at a certain point, an area having a value equal to or larger than a reference value, or some statistical value can be expressed as a parameter. it can. Taking the degree of correlation between the numerical data and the average value of the evaluation for each performance item given by the user from the data of some tools, the important parameters among those parameters can be seen.
[0070]
For example, as shown in FIG. 8, regarding the temperature distribution on the tool rake face, the relationship between the maximum temperature and the evaluation and the relationship between the area within 50 ° C. from the maximum temperature and the evaluation are graphed. For more suitable parameters, there should be a correlation between the parameter change and the evaluation score. In the example of FIG. 8, the area within 50 ° C. from the maximum temperature has a higher correlation, and it can be determined that the area is more suitable as an evaluation index of the tool rake face temperature than the maximum temperature.
[0071]
The degree of correlation may be displayed on a graph as shown in FIG. 8 so that the viewer can determine the degree of correlation, or may be automatically determined by a computer by calculating a correlation coefficient by correlation analysis. .
[0072]
Since these tend to be different for each category, it is also possible to take a correlation for each. In this way, it is possible to optimize the browsing information in the evaluation system by adding new parameters to the user browsing information and ranking quantitative data, and deleting parameters having a low degree of correlation.
[0073]
In addition, if a parameter having a high degree of correlation with the user evaluation is determined for the above important performance items, a designer in the supplier designs a cutting tool using the parameter as an evaluation criterion. Can be provided.
[0074]
(3) User knowledge acquisition
In the design method of the present invention, minority opinions are likely to be discarded, but important user knowledge may be reflected in them. For example, as described in the evaluation method, when a user gives a score that is more than a certain reference point from the average point, a confirmation screen is displayed to the user, and if there is no error, the reason for the reason is further commented. You can also get it. If the designer browses the contents and picks up information that is considered important, it can be used for future tool development.
[0075]
(4) Effective change of tool shape
If one user makes various changes to a specific tool, and tracking the change with a certain evaluation item, the knowledge and ideas that the user has about the relationship between the evaluation item and the tool shape Can be clarified.
[0076]
▲ 5 ▼ Provision of solutions
In the design method according to the present invention, it is considered that it is difficult for a user who has a few opinions to obtain a desired tool because a large number of opinions are prioritized, but the needs of each user can be individually analyzed. By analyzing them, it is highly probable that alternative tools and off-the-shelf products will be included, so it is possible to provide individual solutions to a small number of users It is.
[0077]
【The invention's effect】
As described above, according to the present invention, in designing a cutting tool, many users can evaluate tool performance and develop a cutting tool with high user satisfaction that captures the needs of many users. Can be.
[0078]
Further, according to the present invention, not only the designer of the supplier but also many users can design the cutting tool, so that a variety of design solution candidates are created, and therefore, the design solution falls into a local solution. It is easier to avoid, and an effect close to optimization appears.
[0079]
Furthermore, according to the present invention, by repeatedly changing and evaluating the tool model, the evaluation and design reflect the knowledge and experience of the user. To provide materials for providing solutions to
[Brief description of the drawings]
FIG. 1 is a schematic diagram showing the overall configuration of the system of the present invention.
FIG. 2 is a functional block diagram showing a configuration of an evaluation server in the system of the present invention.
FIG. 3 is a flowchart showing an evaluation procedure using the system of the present invention.
FIG. 4 is an explanatory diagram of an example of a performance prediction result browsing screen.
FIG. 5 is an explanatory diagram of how to give evaluation scores and a tallying method.
FIG. 6 is a schematic diagram showing the overall configuration of the system of the present invention when a user also proposes a tool model.
FIG. 7 is an explanatory diagram of a procedure for searching for an important performance item.
FIG. 8 is an explanatory diagram of a procedure for searching for an optimal parameter serving as an evaluation index of a performance item.
[Explanation of symbols]
1 evaluation server
10 User interface
11 FTP server
12 WWW server
13 SMTP server
14 Authentication Department
15 Notification information creation unit
20 Tool information providing system
21 Tool design information database
22 Information Format Inspection Unit
30 Virtual Cutting System (VMS)
31 Work Material Property Database
32 Tool Material Property Database
33 mesh creation unit
34 control unit
35 Calculation section
40 Evaluation Support System
41 Calculation result processing unit
42 Calculation result database
43 Evaluation Information Database
44 Browsing information creation unit
50 general information database

Claims (9)

A tool design information database for registering tool model information,
Based on the tool model information extracted from the tool design information database by the user via the communication network and the cutting conditions set by the user, the chip generation process when using the tool model is simulated and the result of the performance item is simulated. Cutting performance prediction means for predicting
A calculation result database storing the prediction results obtained by the prediction means,
An evaluation information database in which a user registers evaluation results for prediction results extracted from a calculation result database via a communication network;
Means for counting the evaluation results ,
In the evaluation information database, each performance item evaluation and the desired use degree evaluation of the tool model are quantified and accumulated,
Means the absolute value of the difference between the user-selected evaluation with each performance item rating, and wherein Rukoto comprises means for determining the performance items conscious user to the basis of the accumulation result for the absolute value of the aggregate Cutting tool performance evaluation system. The prediction means is configured to obtain a prediction result for a plurality of tool models,
The cutting tool performance evaluation system according to claim 1, wherein the totaling means includes means for ranking the tool models for each performance item. The cutting tool performance evaluation according to claim 1, wherein the summing up means sums up the evaluation results of the user for at least one of the use of the tool model, the use form of the tool, and the type of tool user. system. The cutting performance prediction means, a plurality of evaluation index parameters to index performance item prediction results,
The aggregation means includes means for obtaining a correlation between an evaluation index parameter and an evaluation of a prediction result for each performance item, and determining a suitable evaluation index parameter based on the correlation. Item 2. The cutting tool performance evaluation system according to Item 1. Furthermore, a cutting condition database that records the range of cutting conditions corresponding to each use of the tool model,
2. The cutting device according to claim 1, further comprising: means for comparing a cutting condition set by a user with a range of the cutting condition for each application read from the cutting condition database to determine a use of the tool model. Tool performance evaluation system. A cutting tool design method using an evaluation server accessible to a user,
Registering the tool model information presented by the model provider in the tool design information database of the evaluation server ;
Evaluation server, the user is to predict the outcome of the simulated to performance item the chip production process at the time of tool model used in the cutting conditions set information to the user of the tool model selected from the tool design information database Steps and
An evaluation server storing the prediction result in a calculation result database;
A step in which the evaluation server quantifies the evaluation result for the prediction result extracted from the calculation result database by the user into each performance item evaluation and the tool model use degree evaluation and registers the evaluation result in the evaluation information database;
An evaluation server for determining an absolute value of a difference between each performance item evaluation and a desired use degree evaluation, and determining a performance item to be emphasized by the user based on the absolute value ;
Adding information of the tool model changed by the model provider based on the total result to a tool design information database of the evaluation server . 7. The cutting tool according to claim 6 , wherein a user other than the model provider also changes the tool model information based on the result of the aggregation and registers new tool model information in the tool design information database. Design method. The model provider is the user,
The method for designing a cutting tool according to claim 6 , wherein the user who evaluates the tool model is also the same user as the model provider. The model provider is the user,
The method of designing a cutting tool according to claim 6 , wherein the users who evaluate the tool model are a plurality of users different from the model provider.

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