JP7537191B2 - Information processing device and information processing program - Google Patents

Description

The present invention relates to an information processing device and an information processing program.

Patent document 1 describes an automatic quotation method that allows users to easily determine item specifications while taking into account price and delivery time.

Patent No. 5753621

The present invention aims to improve the accuracy of estimates and reduce the labor required for estimating the costs required for manufacturing parts compared to configurations in which estimates are made manually.

The information processing device of the first aspect includes a processor, which recognizes the dimensions of the part to be estimated and recognizes specific shapes that will affect the increase in the cost required to manufacture the part from the acquired three-dimensional shape data of the part, and estimates the cost based on the recognized dimensions and specific shapes.

The information processing device of the second aspect is the information processing device of the first aspect, in which the processor estimates the cost by taking into account estimation conditions that cannot be determined from the acquired three-dimensional shape data of the part.

The information processing device of the third aspect is the information processing device of the first or second aspect, and the processor determines the manufacturing conditions of the part based on the recognized dimensions and specific shape, and estimates the cost taking into account the determined manufacturing conditions.

The information processing device of the fourth aspect is any of the information processing devices of the first to third aspects, and the processor displays a three-dimensional image of the part in a manner that allows the specific shape contained in the part to be identified, together with the cost estimate.

The information processing device of the fifth aspect is the information processing device of the fourth aspect, in which the processor uniformly displays the appearance of other parts of the part other than the specific shape as the three-dimensional image.

The sixth aspect of the information processing device is the fifth aspect of the information processing device, in which the processor represents the three-dimensional image in multiple colors and represents the specific shape in a color of the three-dimensional image that has a high contrast with the colors of the other parts.

The seventh aspect of the information processing device is any of the fourth to sixth aspects, and when the specific shape included in the part is of multiple types, the processor displays the three-dimensional image in a manner that allows the specific shape to be identified for each type.

The information processing device of the eighth aspect is any of the information processing devices of the first to seventh aspects, and the processor displays the degree of increase in the cost due to the specific shape included in the part together with the cost estimate.

The ninth aspect of the information processing program causes a computer to execute a process that recognizes the dimensions of a part to be estimated and recognizes specific shapes that will affect the increase in cost required to manufacture the part from the acquired three-dimensional shape data of the part, and estimates the cost based on the recognized dimensions and specific shapes.

According to the first aspect, it is possible to improve the accuracy of the estimate and reduce the labor required for the estimate, compared to a configuration in which the cost of manufacturing parts is estimated manually.

According to the second aspect, it is possible to improve the accuracy and quality of the estimate compared to a configuration in which an estimate is made by considering only conditions that can be determined from the three-dimensional shape data of the part.

According to the third aspect, the estimation man-hours can be reduced compared to a configuration in which an estimate is made without determining the manufacturing conditions of the parts.

The fourth aspect makes it easier to identify specific shapes compared to a configuration in which the overall appearance of the 3D image of the part is displayed in a unified manner.

According to the fifth aspect, it is easier to identify the specific shape compared to a configuration in which parts other than the specific shape contained in the part are displayed in various ways.

According to the sixth aspect, it becomes easier to identify the specific shape compared to a configuration in which the specific shape is represented in a three-dimensional image in a color that has low contrast with the color of other parts of the part other than the specific shape.

According to the seventh aspect, it is easier to identify specific shapes for each type compared to a configuration in which the aspects of multiple types of specific shapes are displayed in a unified manner.

According to the eighth aspect, it becomes easier to understand the cause of the increase in costs compared to a configuration in which only a cost estimate is displayed.

According to the ninth aspect, it is possible to improve the accuracy of the estimate and reduce the labor required for the estimate, compared to a configuration in which the cost of manufacturing parts is estimated manually.

FIG. 1 is a diagram illustrating a schematic configuration of an estimation system. FIG. 2 is a block diagram showing a hardware configuration of the information processing device. FIG. 2 is a block diagram showing the hardware configuration of a user terminal. 13 is a flowchart showing the flow of an estimate process. 13 is a display example of an operation screen for specifying image data of a target part and inputting estimate conditions. 13 is a diagram showing an example of a display screen showing an estimate result for a target part. 13 is a flowchart showing a process for determining a shape pattern of a specific shape.

(First embodiment)
The estimation system according to the present embodiment will be described below.

FIG. 1 is a diagram showing a schematic configuration of an estimation system according to the present embodiment.
1, the estimation system includes an information processing device 10 and a user terminal 40. The information processing device 10 and the user terminal 40 are connected via a network N. For example, the Internet, a LAN (Local Area Network), a WAN (Wide Area Network), etc. are applied to this network N.

The information processing device 10 estimates the cost (hereinafter referred to as "part manufacturing cost") required to manufacture the part to be estimated (hereinafter referred to as "target part"), and transmits the estimate result to the user terminal 40. Details of the information processing device 10 will be described later. In addition, the part manufacturing cost in the first embodiment includes the sales cost per target part (hereinafter referred to as "part cost") and the cost of the mold used to manufacture the target part (hereinafter referred to as "mold cost").

The user terminal 40 transmits image data of the target part to the information processing device 10. The user terminal 40 also displays the estimate results transmitted from the information processing device 10. Details of the user terminal 40 will be described later.

FIG. 2 is a block diagram showing the hardware configuration of the information processing device 10. As an example, the information processing device 10 is a general-purpose computer device such as a server computer or a personal computer (PC).

As shown in FIG. 2, the information processing device 10 includes a CPU 20 (Central Processing Unit), a ROM 22 (Read Only Memory), a RAM 24 (Random Access Memory), a storage unit 26, an input unit 28, a display unit 30, and a communication unit 32. Each component is connected to each other via a bus 34 so as to be able to communicate with each other.

The CPU 20 is a central processing unit, and executes various programs and controls each part. That is, the CPU 20 reads the program from the ROM 22 or the storage unit 26, and executes the program using the RAM 24 as a working area. The CPU 20 controls each of the above components and performs various calculation processes according to the program recorded in the ROM 22 or the storage unit 26. In the first embodiment, the ROM 22 or the storage unit 26 stores an information processing program for estimating the part manufacturing cost of the target part. The information processing program may be pre-installed in the information processing device 10, or may be stored in a non-volatile storage medium or distributed via the network N and appropriately installed in the information processing device 10. Examples of non-volatile storage media include CD-ROM, optical magnetic disk, HDD (= Hard Disk Drive), DVD-ROM, flash memory, memory card, etc.

The ROM 22 stores various programs and various data. The RAM 24 temporarily stores programs or data as a working area. The storage unit 26 is composed of a storage device such as an HDD, SSD (Solid State Drive) or flash memory, and stores various programs including the operating system, and various data.

The input unit 28 includes a pointing device such as a mouse and a keyboard, and is used to perform various inputs.

The display unit 30 is, for example, a liquid crystal display, and displays various information. The display unit 30 may be a touch panel type and function as the input unit 28.

The communication unit 32 is an interface for communicating with other devices such as the user terminal 40. For this communication, for example, a wired communication standard such as Ethernet (registered trademark) or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi (registered trademark) is used.

When executing the above information processing program, the information processing device 10 uses the above hardware resources to execute processing based on the information processing program.

Figure 3 is a block diagram showing the hardware configuration of the user terminal 40. As an example, the user terminal 40 may be a general-purpose computer device such as a server computer or a personal computer.

As shown in FIG. 3, the user terminal 40 includes a CPU 50, a ROM 52, a RAM 54, a storage unit 56, an input unit 58, a display unit 60, and a communication unit 62. Each component is connected to each other via a bus 64 so as to be able to communicate with each other.

The CPU 50 is a central processing unit that executes various programs and controls each part. That is, the CPU 50 reads a program from the ROM 52 or the storage unit 56, and executes the program using the RAM 54 as a working area. The CPU 50 controls each of the above components and performs various calculation processes according to the program recorded in the ROM 52 or the storage unit 56.

The ROM 52 stores various programs and various data. The RAM 54 temporarily stores programs or data as a working area. The storage unit 56 is composed of a storage device such as an HDD, SSD, or flash memory, and stores various programs including an operating system, and various data.

The input unit 58 includes a pointing device such as a mouse and a keyboard, and is used to perform various inputs.

The display unit 60 is, for example, a liquid crystal display, and displays various information. The display unit 60 may be a touch panel type and function as the input unit 58.

The communication unit 62 is an interface for communicating with other devices such as the information processing device 10. For this communication, for example, a wired communication standard such as Ethernet (registered trademark) or FDDI, or a wireless communication standard such as 4G, 5G, or Wi-Fi (registered trademark) is used.

Figure 4 is a flowchart showing the flow of the estimation process by the information processing device 10. The CPU 20 reads out the information processing program from the ROM 22 or the storage unit 26, deploys it in the RAM 24, and executes it to perform the estimation process. In the first embodiment, the target part for which the part manufacturing cost is estimated by the estimation process is a plastic part manufactured using a mold.

In step S10 shown in FIG. 4, the CPU 20 acquires image data and estimation conditions for the target part. Then, the process proceeds to step S11.

Image data is data that allows the three-dimensional shape of the target part to be recognized, and an example is three-dimensional CAD (Computer Aided Design) data that includes dimensional data of the target part. Image data is an example of "three-dimensional shape data."

Estimation conditions are conditions that cannot be determined from the image data of the target part, and examples include the "material," "flame retardant grade," and "production region" of the target part.

For example, the CPU 20 acquires image data and quotation conditions for the target part by performing operations on the user terminal 40 according to the operation screen shown in FIG. 5.

Figure 5 shows an example of the operation screen where image data of the target part is specified and quotation conditions are entered.

As shown in FIG. 5, the operation screen displayed on the display unit 60 of the user terminal 40 includes an image data designation section 70, an estimate condition input section 72, and a completion button 74.

The image data designation unit 70 is a part that accepts designation of image data to be transmitted to the information processing device 10. For example, the image data to be transmitted to the information processing device 10 is designated by the user dragging and dropping a file that stores image data of the target part onto the image data designation unit 70.

The quotation conditions input section 72 is a section that accepts input of quotation conditions. For example, when the user left-clicks on the input field of each item (e.g., materials) in the quotation conditions input section 72 with the mouse serving as the input section 58, a pull-down menu is displayed, and by left-clicking to select any condition displayed in the pull-down menu, the quotation conditions corresponding to each item are input.

The Complete button 74 becomes clickable after the designation of the image data to be sent to the information processing device 10 and the input of the quotation conditions are completed. Then, when the Complete button 74 is left-clicked with the mouse serving as the input unit 58, the image data of the target part and the quotation conditions designated or input on the operation screen are sent to the information processing device 10.

Returning to FIG. 4, in step S11, the CPU 20 recognizes the dimensions and shape of the target part from the acquired image data. Then, the process proceeds to step S12.

In step S11, the CPU 20 recognizes the dimensions of the target part in each direction, such as the width direction, depth direction, and height direction, from the dimensional data included in the image data. The CPU 20 also recognizes the shape of the target part by performing a known image recognition process on the acquired image data. Furthermore, when recognizing the shape of the target part, the CPU 20 recognizes whether or not the shape includes a specific shape that will affect the increase in the part manufacturing cost of the target part.

For example, the CPU 20 recognizes whether a specific shape is included in the shape of the target part as follows:

The specific shapes in the first embodiment include "slides," "louvers," "press-off shapes," "ribs," "holes," "curved surfaces," and "slope." The ROM 22 or the storage unit 26 stores general shape patterns corresponding to each of the specific shapes. The general shape pattern is a general shape pattern of the specific shape, and in the case of a rib, for example, a definition is predefined to determine which shapes are or are not determined to be ribs, such as the formation position and width on the target part.

First, when the CPU 20 receives image data from the user terminal 40, it retrieves the general pattern corresponding to each specific shape from the ROM 22 or the memory unit 26.

Next, the CPU 20 executes a known image recognition process to search whether the target part, whose shape has been recognized, contains a general pattern corresponding to each specific shape. Then, the CPU 20 recognizes whether the specific shape is contained within the shape of the target part based on the search results.

In step S12, the CPU 20 determines the manufacturing conditions for the target part based on the dimensions and shape of the target part recognized in step S11. Then, the process proceeds to step S13.

For example, the CPU 20 determines the manufacturing conditions for the target part in the following manner.
The manufacturing conditions in the first embodiment include "mold dimensions,""moldtype,""productionequipment," and "cavity." The ROM 22 or the storage unit 26 stores manufacturing conditions that can be selected according to the dimensions and shape of the parts. Note that "cavity" refers to the number of target parts that can be manufactured in one molding. For example, six cavities means that six target parts are manufactured in one molding.

Based on the dimensions and shape of the target part recognized in step S11, the CPU 20 searches the ROM 22 or the memory unit 26 for manufacturing conditions that can be selected based on the dimensions and shape. As a result, the CPU 20 determines the manufacturing conditions according to the dimensions and shape of the target part, for example, "mold dimensions: A", "mold type: B", "production equipment: facility C", and "cavity: 1". In the first embodiment, as an example, among the manufacturing conditions, "mold dimensions", "mold type", and "cavity" are determined based on the dimensions and shape of the target part recognized in step S11, and "production equipment" is determined based on the previously determined items. In other words, in the first embodiment, among the manufacturing conditions, after "mold dimensions" are determined, "production equipment" that can use a mold with that "mold dimensions" is determined.

In step S13, the CPU 20 calculates the part manufacturing cost of the target part. Then, the process proceeds to step S14.

For example, the CPU 20 calculates the part manufacturing cost of the target part as follows.
Here, the ROM 22 or the storage unit 26 stores predetermined calculation formulas for calculating the part manufacturing costs of the target parts, specifically, the part costs and die costs.

The CPU 20 derives an evaluation value for calculating the part manufacturing cost from each of the acquired dimensions, shape, estimation conditions, and manufacturing conditions of the target part. A plurality of evaluation values are provided according to each of the above, and the CPU 20 replaces the acquired dimensions of the target part with the corresponding evaluation value, for example, "1" if the acquired dimensions of the target part are within a first range, and "2" if they are within a second range. After deriving all evaluation values, the CPU 20 reads out a predetermined calculation formula from the ROM 22 or the storage unit 26. The CPU 20 then calculates the part manufacturing cost including the part cost and the mold cost by substituting the derived evaluation values into the calculation formula corresponding to the read part cost and the calculation formula corresponding to the mold cost.

In step S14, the CPU 20 transmits the estimate results, including the part manufacturing costs of the target part, to the user terminal 40. Then, the process ends.

FIG. 6 shows an example of a display screen of the estimate result for the target part.
As shown in FIG. 6, the display screen displayed on the display unit 60 of the user terminal 40 is provided with a cost display unit 80, a condition display unit 82, a specific shape display unit 84, and an image display unit 86.

The cost display section 80 is a section that displays the part manufacturing costs, including the part cost and die cost of the target part. As shown in FIG. 6, the cost display section 80 displays the amounts corresponding to each of the part cost and die cost of the target part.

The condition display section 82 is a section that displays the estimation conditions for the target part. For example, the condition display section 82 shown in FIG. 6 displays estimation conditions corresponding to "material," "flame retardant grade," and "production area." Although not shown in FIG. 6, the condition display section 82 can also display estimation conditions other than "material," "flame retardant grade," and "production area."

The specific shape display section 84 is the section that displays the "type of specific shape," "presence or absence of a specific shape in the target part," and "evaluation value."

In the specific shape display section 84, the column labeled "Type" displays various shapes defined as specific shapes. In FIG. 6, "Slide," "Louver," "Push-off shape," "Rib," "Hole," "Curved surface," and "Slope" are displayed as types of specific shapes, but other types of specific shapes can also be displayed.

In the specific shape display section 84, the column marked "Present/Absent" displays whether or not the target part has a specific shape. In FIG. 6, "holes" and "curved surfaces" are displayed as "present," and everything else is displayed as "absent."

In the specific shape display section 84, the column labeled "evaluation value" displays the evaluation value of the specific shape of the target part. In the first embodiment, the evaluation value is displayed to indicate the degree of increase in part manufacturing costs due to the specific shape. In the first embodiment, the larger the evaluation value, the higher the degree of increase in part manufacturing costs, i.e., the higher the monetary amount of part manufacturing costs. In FIG. 6, "hole" is displayed as "2" and "curved surface" as "1", and the rest are displayed as "-". Note that "-" is displayed when the corresponding part in the column labeled "presence/absence" is displayed as "absent", and indicates that the evaluation value is "0".

The image display unit 86 is a section that displays a three-dimensional image of the target part. For example, the image display unit 86 shown in FIG. 6 displays a target part in which a through hole is formed penetrating in the axial direction of a cylinder. In addition, in the first embodiment, the target part being displayed can be rotated by left-clicking the target part displayed in the image display unit 86 with the mouse as the input unit 58, and then moving the position of the mouse while maintaining that state.

Here, the image display unit 86 displays a three-dimensional image of the target part in a manner that allows the specific shape contained in the target part to be identified. Furthermore, if the target part contains multiple types of specific shapes, the image display unit 86 displays the three-dimensional image in a manner that allows the specific shape of each type to be identified. In the first embodiment, the specific shape contained in the target part can be identified by setting a color in the image data of the target part.

As described above, the target part shown in FIG. 6 includes "holes" and "curved surfaces" as specific shapes, and therefore the "holes" and "curved surfaces" are represented in an identifiable manner. In the first embodiment, the "holes" and "curved surfaces" are represented in similar colors, and as an example, the "holes" are represented in "orange" and the "curved surfaces" in "yellow." Note that in FIG. 6, the "holes" and "curved surfaces" are lined with diagonal lines to represent that colors have been assigned to the specific shapes. Also, in FIG. 6, the "holes" and "curved surfaces" are lined with different types of diagonal lines to represent the specific shapes of each type in an identifiable manner.

The image display unit 86 also displays a three-dimensional image of the target part with the appearance of the other parts other than the specific shape included in the target part being uniform. In the first embodiment, the colors set for the other parts are uniform. Note that in FIG. 6, unlike the specific shapes of "hole" and "curved surface", the other parts are not shaded to represent the uniform colors set for the other parts.

Furthermore, the image display unit 86 displays a three-dimensional image of the target part in which the specific shape is expressed in a color that has a high contrast with the color of other parts other than the specific shape. In the first embodiment, the high contrast colors are expressed in a color scheme in which the color of the other parts and the color of the specific shape are complementary colors or have a similar relationship to complementary colors. A "relationship similar to complementary colors" means that the colors are not complementary to each other, but are in a similar color relationship to the complementary color. In the first embodiment, as an example, the color of the other parts is expressed in "purple," which is a complementary color to the "yellow" of the "curved surface" which is the specific shape.

Conventionally, the cost required to manufacture a part was estimated manually by the part's designer himself, using his experience. However, manual estimations tend to vary depending on the individual's estimation method, which in turn leads to variation in the resulting estimates, making it difficult to ensure sufficient accuracy. Furthermore, manual estimations can sometimes result in deviations between the expected cost and the actual estimate due to the variation in the individual's estimation method, which can lead to reworking the design process to reduce costs. If reworking the design process results in a new cost estimate for the part, this can increase the overall labor hours required to estimate compared to when no reworking of the design process occurs, and can delay the market introduction of the part.

In contrast, in the first embodiment, the information processing device 10 estimates the part manufacturing cost of the target part as described above. Specifically, in the first embodiment, the CPU 20 recognizes the dimensions and specific shape of the target part from the acquired image data of the target part, and estimates the part manufacturing cost based on the recognized dimensions and specific shape.

Therefore, in the first embodiment, unlike manual estimation that makes use of the experience of each individual, there is no variation in the estimation method. As a result, in the first embodiment, the occurrence of variation in the estimation results is suppressed, and stable estimation accuracy is ensured. In addition, in the first embodiment, by suppressing the occurrence of variation in the estimation results, the deviation between the expected costs and the estimated results is also suppressed, and the probability of reworking the design process is reduced.

As described above, according to the first embodiment, it is possible to improve the accuracy of the estimate and reduce the labor required for the estimate, compared to a configuration in which the cost of manufacturing parts is estimated manually.

In addition, if the part manufacturing cost is estimated by considering only the dimensions of the target part and its shape, including the specific shape, as conditions that can be determined from the image data of the target part, there is a risk that the expected cost may deviate from the estimated result, or that there may be variation in the quality of the target part. This is because, for example, it is expected that the estimated result may vary depending on the type of material used, and that the quality of the target part may vary depending on the production region.

In contrast, in the first embodiment, the CPU 20 estimates the part manufacturing costs by taking into account estimation conditions that cannot be determined from the acquired image data of the target part. Therefore, according to the first embodiment, it is possible to improve the estimation accuracy and quality compared to a configuration in which an estimate is made by considering only conditions that can be determined from the image data of the target part.

In addition, estimating the part manufacturing costs without determining the manufacturing conditions of the target part may result in reworking the design process, which may result in an increase in the overall estimated man-hours. This is because, for example, when the production equipment that can be selected is determined based on the dimensions of the mold to be used, if the part manufacturing costs are estimated without determining the manufacturing conditions, there may be no production equipment that can use a mold with the determined dimensions, which is likely to result in reworking the design process.

In contrast, in the first embodiment, the CPU 20 determines the manufacturing conditions of the target part based on the recognized dimensions and specific shape of the target part, and estimates the part manufacturing costs taking into account the determined manufacturing conditions. Therefore, according to the first embodiment, the estimation man-hours can be reduced compared to a configuration in which an estimate is made without determining the manufacturing conditions of the target part.

In addition, in the first embodiment, the CPU 20 displays a three-dimensional image of the target part in such a manner that the specific shape included in the target part can be identified, together with an estimate of the part manufacturing cost. In the first embodiment, the CPU 20 sets a color to the image data of the target part, thereby making it possible to identify the specific shape included in the target part. The CPU 20 then includes the color-set image data in the estimate result together with the estimate of the part manufacturing cost and transmits it to the user terminal 40. As a result, in the estimate result displayed on the display unit 60 of the user terminal 40, the specific shape included in the target part can be identified by the color set by the CPU 20 (see FIG. 6).

Therefore, according to the first embodiment, it is easier to identify a specific shape compared to a configuration in which the overall appearance of the 3D image of the target part is displayed in a unified manner.

In addition, in the first embodiment, the CPU 20 displays a three-dimensional image of the target part by unifying the appearance of the other parts other than the specific shape included in the target part. In the first embodiment, the CPU 20 unifies the appearance of the other parts by setting a uniform color to the image data of the other parts. The CPU 20 then includes the image data in which the uniform color is set for the other parts in the estimate result and transmits it to the user terminal 40. As a result, the estimate result displayed on the display unit 60 of the user terminal 40 displays a three-dimensional image of the target part in which the appearance of the other parts is unified (see FIG. 6). As a result, it is possible to identify in the three-dimensional image displayed as the estimate result that the part with an appearance different from the appearance of the other parts is a specific shape.

Therefore, according to the first embodiment, it is easier to identify the specific shape compared to a configuration in which parts other than the specific shape contained in the target part are displayed in various forms.

In addition, in the first embodiment, the CPU 20 expresses a three-dimensional image of the target part using multiple colors, and expresses the specific shape in a color that has a high contrast with the color of other parts of the three-dimensional image other than the specific shape included in the target part. In the first embodiment, the CPU 20 expresses a high-contrast color by setting the color of the other parts and the color of the specific shape to a color scheme that is complementary or similar to complementary colors.

Therefore, according to the first embodiment, it is easier to identify the specific shape compared to a configuration in which the specific shape is represented in a color that has low contrast with the color of other parts of the 3D image of the target part other than the specific shape.

In addition, in the first embodiment, when the target part contains multiple types of specific shapes, the CPU 20 displays a three-dimensional image of the target part in a manner that allows the specific shapes to be identified for each type. In the first embodiment, when the target part contains multiple types of specific shapes, the CPU 20 sets similar colors to the multiple types of specific shapes in the image data of the target part, making it possible to identify the multiple types of specific shapes. The CPU 20 then transmits the image data in which similar colors have been set to the multiple types of specific shapes to the user terminal 40, including them in the estimate result. As a result, in the estimate result displayed on the display unit 60 of the user terminal 40, the multiple types of specific shapes contained in the target part can be identified by the colors set by the CPU 20 (see FIG. 6).

Therefore, according to the first embodiment, it is easier to identify specific shapes for each type compared to a configuration in which the aspects of multiple types of specific shapes are displayed in a unified manner.

In the first embodiment, the CPU 20 displays the degree of increase in the part manufacturing cost due to the specific shape included in the target part along with the estimated part manufacturing cost. In the first embodiment, the degree of increase in the part manufacturing cost due to the specific shape is shown by displaying an evaluation value. The larger the evaluation value, the higher the degree of increase in the part manufacturing cost, i.e., the higher the amount of the part manufacturing cost. The CPU 20 then includes the evaluation value corresponding to each specific shape in the estimate result and transmits it to the user terminal 40. As a result, the estimate result displayed on the display unit 60 of the user terminal 40 displays the evaluation value corresponding to each specific shape along with the estimated part manufacturing cost (see FIG. 6).

Therefore, according to the first embodiment, it is easier to understand the cause of an increase in part manufacturing costs compared to a configuration in which only an estimate of part manufacturing costs is displayed.

Second Embodiment
The second embodiment is common to the first embodiment in that the target part is manufactured using a die, but is different from the first embodiment in that the target part is a pressed part.

The second embodiment will be described below while omitting or simplifying parts that overlap with other embodiments.

The specific shapes in the second embodiment include shapes that are common to the first embodiment and shapes that are different, specifically, "unfolded outline," "holes," "louvers," "drawing shapes," "bent shapes," "embossing," and "burring."

The manufacturing conditions in the second embodiment include conditions common to the first embodiment and conditions that are different, specifically including the "process," "mold dimensions," "construction method," and "production equipment."

In the second embodiment, in step S11 shown in FIG. 4, when the CPU 20 executes a known image recognition process on the image data to recognize the shape of the target part, it determines whether or not a predetermined condition is met for each specific shape, and determines a shape pattern for that specific shape based on whether or not the determined condition is met. At least two or more types of shape patterns are provided. Note that, depending on the specific shape, multiple predetermined conditions are provided, and in this case, the shape pattern for that specific shape may be determined based on a combination of whether or not the multiple conditions are met.

As an example, the above process flow will be explained using the flowchart shown in FIG. 7 for a "hole" among the specific shapes. In the second embodiment, three types of predefined conditions corresponding to a "hole" are provided: a first condition, a second condition, and a third condition.

In step S20, the CPU 20 determines whether or not a general pattern corresponding to a "hole" is included in the image data of the target part as a first condition, and if it is determined that a general pattern corresponding to a "hole" is included (step S20: YES), the process proceeds to step S21. On the other hand, if the CPU 20 determines that a general pattern corresponding to a "hole" is not included (step S20: NO), the process proceeds to step S23.

In step S21, the CPU 20 determines whether the "number of holes" contained in the image data of the target part is equal to or greater than a predetermined threshold as the second condition, and if it determines that the "number of holes" is equal to or greater than the predetermined threshold (step S21: YES), the process proceeds to step S22. On the other hand, if the CPU 20 determines that the "number of holes" is less than the predetermined threshold (step S21: NO), the process proceeds to step S24.

In step S22, the CPU 20 determines whether the "hole dimension" included in the image data of the target part is equal to or greater than a predetermined threshold value as the third condition, and if it determines that the "hole dimension" is equal to or greater than the predetermined threshold value (step S22: YES), the process proceeds to step S25. On the other hand, if the CPU 20 determines that the "hole dimension" is less than the predetermined threshold value (step S22: NO), the process proceeds to step S24.

In step S23, the CPU 20 determines the shape pattern of the "hole" in the target part to be "Pattern A." Then, the process ends.

In step S24, the CPU 20 determines the shape pattern of the "hole" in the target part to be "Pattern B." Then, the process ends.

In step S25, the CPU 20 determines the shape pattern of the "hole" in the target part to be "Pattern C." Then, the process ends.

In the second embodiment, the ROM 22 or the memory unit 26 stores "steps" corresponding to the combinations of the shape patterns of each specific shape that can be determined in step S11. The "steps" include the number of steps and the work to be performed in each step.

Then, in step S12 shown in FIG. 4, the CPU 20 searches the ROM 22 or the storage unit 26 for a "process" corresponding to the combination of shape patterns of each specific shape determined in step S11. For example, if the shape patterns of "unfolded outline," "hole," "louver," "drawing shape," "bent shape," "embossing," and "burring" determined in step S11 are all "pattern A," the CPU 20 determines that the "process" among the manufacturing conditions of the target part is "process A" with the number of processes being "1." Next, the CPU 20 determines the "mold dimensions" and "construction method" among the manufacturing conditions of the target part based on the "process" determined above and the dimensions and shape of the target part. After that, the CPU 20 determines the "production equipment" that can use a mold with the "mold dimensions" among the manufacturing conditions of the target part.

Third Embodiment
The third embodiment differs from the other embodiments in that the target parts are manufactured by machining, specifically, cutting, without using a die. Therefore, the part manufacturing cost in the third embodiment does not include the die cost, and is composed of only the part cost.

The third embodiment will be described below while omitting or simplifying parts that overlap with other embodiments.

The specific shapes in the third embodiment include shapes that are common to the other embodiments and shapes that are different, specifically including "holes," "tapers," so-called "D-cut shapes," and "step-downs."

The manufacturing conditions in the third embodiment are different from those in the other embodiments, and specifically include the "machining method," "machining diameter," "machining length," and "machining process sequence."

In the third embodiment, in step S11 shown in FIG. 4, when the CPU 20 executes a known image recognition process on the image data to recognize the shape of the target part, it determines the processing direction and determines whether or not a specific shape is included in the shape of the target part from a viewpoint looking from the upstream side to the downstream side of the processing direction.

(others)
In the above embodiment, the estimation system is configured with two computer devices, the information processing device 10 and the user terminal 40, but the estimation system is not limited to this and may be configured with one computer device or three or more computer devices.

In the above embodiment, "material," "flame retardant grade," and "production region" are given as examples of quotation conditions, but they are not limited to the above, as long as the conditions cannot be determined from the image data of the target part.

In the above embodiments, specific shapes for each embodiment are exemplified, but the specific shapes of each embodiment may be included in the specific shapes of other embodiments as appropriate. In addition, examples of specific shapes are not limited to those exemplified in the above embodiments, so long as they correspond to shapes that affect the increase in the part manufacturing costs of the target parts.

In the above embodiments, the manufacturing conditions for each embodiment are exemplified, but the manufacturing conditions of each embodiment may be included in the manufacturing conditions of other embodiments as appropriate. Furthermore, examples of manufacturing conditions are not limited to those exemplified in the above embodiments.

In the above embodiment, the specific shape contained in the target part can be identified by setting a color in the image data of the target part, but this is not a limiting example of an identifiable manner. For example, the specific shape may be represented in an identifiable manner in the three-dimensional image of the target part by setting a pattern in the image data of the target part or displaying an arrow pointing to the specific shape.

In the above embodiment, the portion showing the specific shape is always displayed in color in the image display section 86 of the display screen shown in FIG. 6. However, this is not limited to the above, and when a specific shape is specified, the portion showing the specific shape in the image display section 86 may be colored. For example, when a specific shape (e.g., "hole") displayed in the specific shape display section 84 is left-clicked with the mouse as the input section 58, the portion showing the specific shape (e.g., "hole") in the image display section 86 may be colored.

In the above embodiment, when the target part contains multiple types of specific shapes, each specific shape is represented in a similar color, but this is not limited to this. For example, each specific shape may be represented in a complementary color, and the combination of hues is not particularly limited.

In the above embodiment, a high contrast color is expressed by setting the color of the specific shape and the color of the other parts other than the specific shape to a color scheme that is complementary or similar to complementary colors. However, this is not limited to this, and high contrast may also be expressed by adjusting the brightness or saturation of the color of the specific shape and the color of the other parts other than the specific shape.

In the above embodiment, the combination of "orange," "yellow," and "purple" was given as an example of the colors to be set in the image data of the target part, but these hue combinations are not particularly limited.

Here, in the display screen shown in FIG. 6, if the target part contains multiple types of specific shapes, the multiple specific shapes contained in the 3D image of the target part may be displayed in different ways depending on the degree of increase in part manufacturing costs due to the specific shapes, i.e., the evaluation value. That is, in FIG. 6, the evaluation values for "holes" and "curved surfaces" are different, so they are displayed in different colors, but if there are multiple specific shapes with the same evaluation value, the multiple specific shapes may be displayed in the same color.

The display screen shown in FIG. 6 may additionally display manufacturing conditions for the target part. Furthermore, a color indicating a specific shape in the image display section 86 may be set to a portion of the specific shape display section 84 that corresponds to that specific shape. For example, in the example shown in FIG. 6, the same color indicating the specific shape in the image display section 86 may be set to the rows indicating "hole" and "curved surface" in the specific shape display section 84.

In each of the above embodiments, the CPU 20 provided in the information processing device 10 is an example of a processor. This processor refers to a processor in a broad sense, and includes a general-purpose processor (e.g., CPU: Central Processing Unit, etc.) and a dedicated processor (e.g., GPU: Graphics Processing Unit, ASIC: Application Specific Integrated Circuit, FPGA: Field Programmable Gate Array, programmable logic device, etc.).

The operations of the above processors may not only be performed by a single processor, but may also be performed by multiple processors located at physically separate locations working together. Furthermore, the order of the operations of the above processors is not limited to the order described in the above embodiment, and may be changed as appropriate.

10 Information processing device 20 CPU (an example of a processor)

Claims (9)

A processor is provided.
The processor,
From the obtained three-dimensional shape data of the part to be estimated, the dimensions of the part and specific shapes that will affect the increase in the cost required for manufacturing the part are recognized;
generating said cost estimate based on said identified dimensions and said specific shape;
When the specific shape included in the part is of a plurality of types, the specific shapes included in the three-dimensional image of the part displayed on a display unit are displayed in different modes according to the degree of increase in the cost due to each of the plurality of specific shapes.
Information processing device. The processor,
The information processing apparatus according to claim 1 , wherein the cost estimate is performed taking into consideration estimation conditions that cannot be determined from the obtained three-dimensional shape data of the part. The processor,
determining manufacturing conditions for the part based on the recognized dimensions and specific shape;
The information processing apparatus according to claim 1 or 2, wherein the cost estimate is performed taking into account the determined manufacturing conditions. The processor,
The information processing apparatus according to claim 1 , further comprising: a display unit configured to display, together with the cost estimate, a three-dimensional image of the part in such a manner that the specific shape included in the part can be identified. The processor,
The information processing apparatus according to claim 4 , wherein the three-dimensional image is displayed in a unified manner in accordance with aspects of portions other than the specific shape included in the part. The processor,
The three-dimensional image is expressed in multiple colors;
The information processing apparatus according to claim 5 , wherein the specific shape is represented in a color having a high contrast with a color of the other portion of the three-dimensional image. The processor,
The information processing apparatus according to claim 1 , further comprising: displaying, together with the cost estimate, a degree of increase in the cost due to the specific shape included in the part. The processor,
When the degree of increase in the cost due to each of the plurality of specific shapes is different, the plurality of specific shapes included in the three-dimensional image are displayed in different manners;
When the degree of increase in cost due to each of the plurality of specific shapes is the same, the plurality of specific shapes included in the three-dimensional image are displayed in the same manner.
The information processing device according to claim 1 . On the computer,
From the obtained three-dimensional shape data of the part to be estimated, the dimensions of the part and specific shapes that will affect the increase in the cost required for manufacturing the part are recognized;
generating said cost estimate based on said identified dimensions and said specific shape;
When the specific shape included in the part is of a plurality of types, the specific shapes included in the three-dimensional image of the part displayed on a display unit are displayed in different modes according to the degree of increase in the cost due to each of the plurality of specific shapes.
An information processing program for executing processing.