Quality evaluation method for production processes, quality evaluation apparatus for production processes, and quality evaluation program for production processes.

Abstract

This invention provides a production process quality evaluation method, a production process quality evaluation device, and a production process quality evaluation program that enable the identification of product types or model numbers that should be prioritized for improvement when managing the production of a wide variety of industrial parts. [Solution] The production process quality evaluation device 1, which executes a production process quality evaluation method, comprises a loss amount database 13b stored in storage 13 for storing the amount of loss incurred in the production of machine parts during a predetermined production period, and an evaluation means consisting of a CPU 11 and the like for evaluating the quality of the machine parts production process based on the amount of loss.

Description

Technical Field

[0001] The present invention relates to a method for evaluating the quality of a production process, an apparatus for evaluating the quality of a production process, and a program for evaluating the quality of a production process, which evaluate the quality of the production process of mechanical parts and other industrial products produced by a manufacturing method using, for example, a mold.

Background Art

[0002] Conventionally, in the manufacture of machines composed of various types of mechanical parts, it has been required to efficiently produce the mechanical parts, and various techniques for managing production have been proposed.

[0003] As an example of such a technique, in Patent Document 1, attention is paid to the fact that resources such as molds, various tools, and devices used in the manufacture of products as the mechanical parts change over time and also affect the defects of the manufactured products. A method for suppressing loss costs derived from resources is disclosed by managing workability from the work history of resources such as molds and selecting the resources to be used according to the workability.

Prior Art Documents

Patent Documents

[0004]

Patent Document 1

Summary of the Invention

Problems to be Solved by the Invention

[0005] When focusing on a mold as a method for managing the production of mechanical parts, the performance of the mold is derived, that is, the punching success rate and the defect rate in a predetermined production period are calculated.

[0006] However, as mentioned above, with a wide variety of machine parts, production needs to be managed and improved for each type or model number. Since the production quantities for each type or model number vary greatly, simply calculating the punching success rate or the defect rate makes it difficult to determine which of these types or model numbers should be prioritized for improvement.

[0007] Therefore, the main objective of the present invention is to provide a production process quality evaluation method, a production process quality evaluation apparatus, and a production process quality evaluation program that enable the determination of which product types should be prioritized for improvement when managing the production of multiple product types or multiple model numbers of machine parts. [Means for solving the problem]

[0008] The first aspect of the present invention is an evaluation process that uses a loss amount database for storing the amount of losses incurred in the production of industrial parts during a predetermined production period and a difficulty database for storing the difficulty of producing the industrial parts, and evaluates the quality of the production process of the industrial parts based on the loss amount and the difficulty, the evaluation process being performed by a computer, wherein the loss amount and the difficulty are determined according to the type of industrial part. They are different This is a quality evaluation method used in the production process, expressed as a ratio.

[0010] The 2 The present invention is a first method for evaluating the quality of a production process, wherein the amount of loss includes the amount resulting from the disposal of defective products that occur in the production of the industrial parts.

[0011] The 3 The present invention is a first method for evaluating the quality of a production process, wherein the amount of loss includes the amount incurred due to the purchase, maintenance, or repair of jigs or tools in the production of the industrial parts.

[0012] The 4The present invention includes, in which the amount of loss includes the amount attributable to the labor costs required for the maintenance or repair of the jigs or tools that occur in the production of the industrial parts. 3 This invention relates to a method for evaluating the quality of the production process.

[0014] The 5 The present invention is a first method for evaluating the quality of a production process, which displays information regarding the operating status of the production equipment for the industrial parts and information regarding maintenance or repair of the industrial parts in the production process of the industrial parts as a graph.

[0015] The sixth aspect of the present invention comprises a loss amount database for storing the amount of loss incurred in the production of industrial parts during a predetermined production period, a difficulty database for storing the difficulty of producing the industrial parts, and an evaluation means for evaluating the quality of the production process of the industrial parts based on the loss amount and the difficulty, wherein the loss amount and the difficulty are used in the production of the industrial parts. Department Used in different proportions depending on the type of product. 、 This is a quality evaluation device for the production process.

[0017] The 7 The present invention includes, in which the amount of loss includes the amount resulting from the disposal of defective products that occur in the production of the industrial parts. 6 This invention relates to a quality evaluation apparatus for the production process.

[0018] The 8 The present invention includes, in which the amount of loss includes the amount resulting from the purchase, maintenance, or repair of jigs or tools that occur in the production of the industrial parts. 6 This invention relates to a quality evaluation apparatus for the production process.

[0019] The 9 The present invention is an eighth production process quality evaluation apparatus of the present invention, wherein the amount of loss includes the amount attributable to the labor costs required for the maintenance or repair of the jigs or tools that occur in the production of the industrial parts.

[0021] No. 10 The present invention according to No. is a quality evaluation apparatus for a production process, which displays, as a graph, information regarding the operating state and maintenance or repair of production equipment for industrial parts during the production process of the industrial parts. 6 This is the quality evaluation apparatus for the production process of the present invention according to No.

[0022] No. 11 The present invention according to No. is a quality evaluation program for a production process for causing a computer to execute the evaluation process in the quality evaluation method for a production process of the first present invention.

Effects of the Invention

[0023] According to the present invention, it is possible to provide a quality evaluation apparatus for a production process capable of determining a variety to be preferentially improved in the management of the production of multi-variety or multi-model mechanical parts.

[0024] The above objects, other objects, features, and advantages of the present invention will become more apparent from the following description of the embodiments for carrying out the invention with reference to the drawings.

Brief Description of the Drawings

[0025] [Figure 1] It is a block diagram showing the configuration of a quality evaluation apparatus for a production process according to Embodiment 1 of the present invention. [Figure 2] It is a diagram showing a flowchart of an operation example of a quality evaluation apparatus for a production process according to Embodiment 1 of the present invention. [Figure 3] It is a diagram schematically showing production equipment for mechanical parts, which is an evaluation target of a quality evaluation apparatus for a production process according to Embodiment 1 of the present invention. [Figure 4] (A) It is a diagram schematically showing a mold or the like used for the production of mechanical parts, which is an evaluation target of a quality evaluation apparatus for a production process according to Embodiment 1 of the present invention. (B) It is a diagram schematically showing the produced mechanical parts. [Figure 5](A) A schematic diagram showing molds and the like used in the production of machine parts, which are the targets of evaluation by the production process quality evaluation device according to Embodiment 1 of the present invention. (B) A schematic diagram showing the produced machine parts. [Figure 6] (A) A schematic diagram showing molds and the like used in the production of machine parts, which are the targets of evaluation by the production process quality evaluation device according to Embodiment 1 of the present invention. (B) A schematic diagram showing the produced machine parts. [Figure 7] This figure shows a table indicating the amount of loss calculated by a quality evaluation device for the production process according to Embodiment 1 of the present invention. [Figure 8] This figure shows a table indicating the molding difficulty level calculated by a quality evaluation device for the production process according to Embodiment 1 of the present invention. [Figure 9] This figure shows a table indicating the loss points calculated by a quality evaluation device for the production process according to Embodiment 1 of the present invention. [Figure 10] (A) A table showing an example of quality evaluation of the production process based on the loss points calculated by the quality evaluation device for the production process according to Embodiment 1 of the present invention. (B) A diagram showing a table showing an example of quality evaluation of the production process based on the loss points calculated by the quality evaluation device for the production process according to Embodiment 1 of the present invention. [Figure 11] (A) A table showing another example of quality evaluation of the production process based on the loss points calculated by the quality evaluation device for the production process according to Embodiment 1 of the present invention. (B) A diagram showing a table showing another example of quality evaluation of the production process based on the loss points calculated by the quality evaluation device for the production process according to Embodiment 1 of the present invention. [Figure 12] This figure shows a change point history graph displayed by a quality evaluation device for the production process according to Embodiment 2 of the present invention. [Modes for carrying out the invention]

[0026] The following describes the production process quality evaluation method, production process quality evaluation apparatus, and production process quality evaluation program of the present invention in the form of embodiments.

[0027] (Embodiment 1) Figure 1 is a block diagram showing the configuration of a quality evaluation apparatus for the production process according to Embodiment 1 of the present invention. As shown in Figure 1, the quality evaluation apparatus 1 for the production process includes a network interface (I / F) 10, a CPU 11, memory 12, storage 13, a user I / F 14, and a device I / F 15, all interconnected by a bus 20.

[0028] Network I / F 10 is an interface for connecting to a communication network (not shown), and for example, if the communication network is the Internet, it is implemented as a transceiver operating according to the IP protocol. CPU 11 is the main body of the quality evaluation device 1 in the production process and is a means for processing data in each database in the storage 13, which will be described later. Memory 12 is a means for storing data necessary for the information processing of CPU 11 and for providing a workspace for CPU 11. Storage 13 is a means for storing the OS, data, etc. necessary for the operation of the quality evaluation device 1 in the production process, as well as data to be processed by CPU 11 and data after processing, and is implemented as a hard disk drive (HDD) or solid state drive (SSD).

[0029] Storage 13 contains three databases related to the production equipment for machine parts that are the target of evaluation in the quality evaluation device 1 of the production process (hereinafter referred to as "production equipment"): a main information database 13a, a loss amount database 13b, and a difficulty level database 13c.

[0030] In this embodiment 1, the production equipment refers to equipment that produces machine parts by punching, which processes a workpiece using a punch, die, and stripper.

[0031] The main information database 13a is a database that stores data such as stroke rate, which are basic indicators for evaluating the performance of the mold. The loss amount database 13b is a database that stores loss amount, which is data that quantifies the monetary losses incurred during the production process, and is an indicator for evaluating the performance of the mold, as described later. The difficulty level database 13c is a database that stores molding difficulty level, which is data that quantifies the difficulty of molding machine parts during the production process, and is an indicator for evaluating the performance of the production equipment, as described later.

[0032] The user interface 14 is a means by which an administrator acting as a user inputs initial settings and other data into the main information database 13a, the loss amount database 13b, and the difficulty database 13c of the storage 13, and outputs the information processed by the CPU 11 as video and audio, etc. The user interface 14 is implemented as all or part of a general-purpose or dedicated keyboard, a pointing device such as a mouse, a touch panel, a display, speakers, etc.

[0033] Device I / F15 is an interface for communicating with manufacturing equipment for mechanical parts (not shown). If wired, it is implemented as a dedicated interface or USB (Universal Serial Bus), and if wireless, as a transceiver conforming to a short-range wireless communication protocol such as Bluetooth (registered trademark). Device I / F15 is used to acquire data stored in the main information database 13a, the loss amount database 13b, and the difficulty database 13c from the production equipment.

[0034] The quality evaluation device 1 for the production process may be implemented as dedicated hardware having the above-described components, but it may also be implemented as an existing general-purpose information processing device such as a computer, tablet terminal, or smartphone.

[0035] In the above configuration, the CPU 11, memory 12, and storage 13 constitute the diagnostic means of the present invention. The loss amount database 13b in storage 13 corresponds to the loss amount database of the present invention. The difficulty level database 13c in storage 13 corresponds to the difficulty level database of the present invention.

[0036] In this case, the production process quality evaluation device 1 may be implemented as a system in which the configuration of each of the above parts is distributed among multiple devices, and these devices communicate bidirectionally with each other to integrally execute each step of the production process quality evaluation method of the present invention. For example, the CPU 11 and memory 12 as diagnostic means 13, and part of the storage 13 may be implemented as one or more information communication terminals or personal computers, and the remaining part of the storage 13, including the main information database 13a, loss amount database 13b, and difficulty database 13c, may be implemented as cloud storage by an independent server, and a configuration may be established in which bidirectional communication is performed via a network such as the Internet.

[0037] The production process quality evaluation device 1 according to Embodiment 1 of the present invention, having the configuration described above, is characterized by comprising a loss amount database 13b that stores the amount of loss incurred in the production of machine parts during a predetermined production period, and a difficulty database 13c that stores the difficulty level of the production of machine parts, and comprising a CPU 11, memory 12, and storage 13 that constitute an evaluation means for evaluating the quality of the production process of machine parts based on the loss amount and difficulty level, mainly focusing on the quality of the molds specifically necessary for the production of the machine parts.

[0038] The following describes an example of the operation of the production process quality evaluation device 1 with reference to the flowchart in Figure 2, and thereby explains one embodiment of the production process quality evaluation method of the present invention.

[0039] (Example of operation) The example operation involves evaluating the quality of the production process when production equipment is operated for a predetermined period. The example operation will be explained below with reference to the flowchart in Figure 2.

[0040] First, based on the administrator's input via the user interface 14, the main information regarding the production of machine parts during a pre-set production period is read from the main information database 13a in the storage 13 (step S101).

[0041] The main information refers to the specific operating conditions of the production equipment, which are the conditions necessary for evaluating the molds included in the production equipment corresponding to a particular type and model of machine part. Specifically, in the production equipment 30 shown in Figure 3, when a production process is executed in which a punch 31 moving along the direction of the arrow in the figure punches out a workpiece 33 in cooperation with a stripper (not shown) according to the corresponding shape of the die 32, the stroke rate and completion rate calculated are read out as the main information.

[0042] In this embodiment, the product type acts as an index to identify the type of mold when different machine parts are produced according to the type of mold, and the model number acts as an index to identify which mold was used when the same machine part is produced using multiple molds.

[0043] The stroke rate is defined as the ratio of the actual number of times the production equipment 30 is operated to the target number of times it is scheduled to be operated within a predetermined production period. For example, if the target number of times is 100,000 and the number of times it is operated is 10,000, the stroke rate is 10%. When the stroke rate is 100%, the production equipment 30 is defined as having completed its operation. When calculating the stroke rate, examples of malfunctions that may cause the production equipment 30 to stop operating include mold wear, cracks, chips, product defects, quality defects, equipment malfunctions, and other defects.

[0044] The completion rate is defined as the number of times the production equipment 30 is operated the planned number of times within a predetermined production period, i.e., the percentage of times the stroke rate reaches 100%. For example, if there are 100 planned operations within a predetermined period, and the stroke rate reaches 100% 10 times, the completion rate would be 10%.

[0045] While it is preferable that the main information, such as stroke rate and completion rate, be automatically acquired from the production equipment 30 via the device I / F 15, they may also be set by manual input by the administrator via the user I / F 14.

[0046] Next, the CPU 11, acting as a diagnostic tool, reads the amount of loss incurred during the production process of the machine parts from the loss amount database 13b in the storage 13 (step S102). The CPU 11 also performs the actions of each subsequent step unless otherwise specified.

[0047] The loss amount represents the monetary loss incurred due to various reasons empirically determined from observations of the current state of the production equipment 30 when producing machine parts of a specific type and model number through its operation. The loss amount includes the amounts listed in (1) to (3) below.

[0048] (1. Product Disposal Loss Amount) This is the amount resulting from the disposal of defective products that occur during the production of machine parts. Specifically, it is the amount of loss incurred when completed machine parts are discarded as defective products because they do not meet quality requirements such as dimensions and appearance during the production process. The product disposal loss amount is calculated, for example, by (unit price per product) × (number of discarded products). Note that the product disposal loss amount may include not only the disposal of defective completed machine parts, but also the amount of waste related to the materials of machine parts before completion. In short, it is acceptable as long as it is an amount directly or indirectly resulting from the disposal of products.

[0049] (2. Loss on Fixtures and Tools) This is the amount incurred due to the purchase, maintenance, or repair of fixtures or tools in the production of machine parts. Specifically, it is the amount of loss incurred when chipping, wear, cracking, etc., of molds in the production process progress faster than usual, requiring polishing or parts replacement beyond the specified limits. The loss on fixtures and tools is calculated, for example, from the maintenance cycle of normal production equipment 30, the number of polishing and replacement operations that occur earlier due to an increase in the amount of polishing per operation, parts costs, outsourcing costs, etc.

[0050] (3. Maintenance Time Loss Amount) This amount is due to labor costs incurred for the maintenance or repair of jigs or tools used in the production of machine parts. Specifically, it is the amount of labor cost loss incurred when defects in molds or products occur during the production process, requiring the production of the product to be stopped earlier than expected, and necessitating extra maintenance work on the production equipment 30. The maintenance time loss amount is calculated, for example, as follows: (Number of maintenance cycles exceeding the normal maintenance cycle of the production equipment 30) × (Manual time per maintenance) × (Hourly wage of the maintenance worker, etc.). Note that the man-hours required for maintenance of machine parts vary depending on the type of part.

[0051] The sum of these amounts (1) to (3) will be treated as the total amount of loss.

[0052] Next, the total amount of losses is normalized as a dimensionless parameter for processing in conjunction with the difficulty information described later (step S103). While well-known and conventional methods can be used for normalization, minimum-maximum normalization or normalization based on a target value is preferred. Here, as an example, minimum-maximum normalization was performed.

[0053] Figure 7 shows a table displaying key information and loss amounts for each type and model number of machine parts. As shown in Figure 7, Table 70 displays the quality of the machine part production process for each type and model number using key information 71, loss amount 72, total loss amount 73, and normalized total loss amount 74, making it possible to compare them with each other. By referring to (Type A)(Model 1) and (Model 2) in Table 70, it can be confirmed that even for the same type, the key information and loss amounts differ due to differences in model numbers, that is, differences in the production equipment used to produce the machine part, specifically the molds and their current usage.

[0054] Furthermore, Table 70, which includes the amount of loss, can be output to the user via the user interface 14 as visualized information (step S104). Table 70 may be shown as a numerical table as shown in Figure 7, or it may be displayed as a graph.

[0055] Next, molding difficulty information regarding the molding difficulty of machine parts associated with the operation of the production equipment 30 is read from the difficulty database 13c in storage 13 (step S105).

[0056] Molding difficulty information refers to the operating conditions associated with the operation of production equipment, and is a parameter that serves as a standard for evaluating a mold consisting of a combination of punch, die, and stripper included in the production equipment. Specifically, in the production equipment 30 shown in Figure 3, when a production process is performed in which a punch 31 moving along the direction of the arrow in the figure punches out a workpiece 33 according to the corresponding shape of the die 32 (the stripper is not shown in Figure 3), the material thickness of the workpiece 33 (hereinafter, "material thickness"), the material hardness of the workpiece 33 (hereinafter, "material hardness"), and the speed of the punch 31 in one punching process (hereinafter, "rotational speed") are set or measured, and these are all set.

[0057] The greater the material thickness, the higher the load on the punch 31 and die 32, increasing the risk of mold malfunction. Similarly, the greater the material hardness and rotational speed, the higher the load on the punch 31 and die 32.

[0058] In this embodiment 1, difficulty information is preferably set by manual input by the administrator via the user interface 14, but it may also be automatically acquired from the production equipment 30 via the device interface 15.

[0059] Furthermore, in addition to the above (1) to (3), the difficulty of the molding process is also set as the difficulty of the process (hereinafter referred to as "process"). The process is a relative index set based on the shape of the die used for punching. For example, when a workpiece 42 is processed with a punch 41 having a circular planar shape as shown in Figure 4(A) to obtain a machine part 43 having a circular planar shape as shown in Figure 4(B), if the shape of the die is uniform in all parts, the outer circumference of the die is smooth and the load required for processing is reduced, so the difficulty of the process can be set as easy.

[0060] Furthermore, when the shape of the mold becomes more complex and uneven due to corners in some parts, such as when a workpiece 52 is processed with a punch 51 having a rhombus-shaped plan view as shown in Figure 5(A) to obtain a machine part 53 having a rhombus-shaped plan view as shown in Figure 5(B), stress concentrates at the corners of the mold, making it more prone to mold abnormalities and wear. Therefore, the difficulty level of the manufacturing method can be set to normal.

[0061] Furthermore, when the shape of the mold becomes more complex, such as when a workpiece 62 is processed with a star-shaped punch 61 as shown in Figure 6(A) to obtain a star-shaped machine part 63 as shown in Figure 6(B), and the mold shape has more corners in some areas, and each of the corners is acute, the effect of stress at the corners of the mold becomes more pronounced, making mold abnormalities and wear more likely to occur. Therefore, the difficulty of the manufacturing method can be defined as difficult.

[0062] As described above, the difficulty of molding each machine part, that is, the differences in mold shape and manufacturing method, directly result in differences in the types of machine parts. In other words, in this embodiment, the type of machine part is defined by the molding difficulty specific to that type.

[0063] Therefore, the machine part 43 shown in Figure 4(A), the machine part 53 shown in Figure 5(A), and the machine part 63 shown in Figure 6(A) are machine parts belonging to different product categories. Furthermore, if there are multiple molds for manufacturing machine parts 43 to 63, each mold is assigned a model number belonging to that product category.

[0064] Next, since the individual molding difficulty information consists of parameters or dimensionless numbers with different units, it is normalized as a dimensionless parameter and then aggregated. The aggregated molding difficulty information is further normalized for processing in conjunction with the total loss amount output earlier (step S106). As for the specific normalization method, well-known and conventional methods can be used, but minimum-maximum normalization or normalization based on a target value is preferred. Here, as an example, minimum-maximum normalization was performed.

[0065] Figure 8 shows a table displaying molding difficulty information for each type of machine part. As shown in Figure 8, Table 80 displays the measured values ​​81 and normalized molding difficulty information 82 for each individual type, as well as the raw values ​​83 and normalized values ​​84 of the combined molding difficulty information, allowing for comparison between them. By referring to (Type A)(Model 1) and (Model 2) in Table 80, it can be confirmed that molding difficulty is a qualitative evaluation specific to the production process of machine parts of the same type, and that the evaluation is always the same for the same type. In other words, molding difficulty does not depend on differences in the model numbers of machine products, i.e., on the production equipment used to produce the machine part in question, specifically the mold and its specific current state of use.

[0066] Table 80 can be output to the user via the user interface 14 as visualized information (step S107). It may be displayed as a numerical table as shown in Figure 8, or as a graph.

[0067] Next, the normalized total loss amount and the normalized aggregated molding difficulty information are weighted (step S108). The weighting process is performed to balance the differences in the contribution of the total loss amount and the molding difficulty information in the quality evaluation of the production process.

[0068] The weighting of total loss amount and molding difficulty information is preferably set to an arbitrary ratio depending on the type and other characteristics of the machine parts. However, generally, since total loss amount has a higher contribution to quality evaluation in the production process than molding difficulty information, the ratio of total loss amount to molding difficulty information is set so that total loss amount is greater. In this embodiment 1, the ratio of total loss amount to molding difficulty information was set to 0.9:0.1. However, in this embodiment, for molding difficulty, processing is performed based on (1 - normalized value) so that a higher value results in a smaller contribution to the loss score.

[0069] Next, the sum of the normalized total loss amount and the combined molding difficulty information after weighting is calculated as the loss score (step S109). The loss score is an index that evaluates the quality of the production process of a machine part based on the actual conditions of the production process of that machine part.

[0070] Finally, the loss score is output to the user via the user interface 14 as visualized information (step S110).

[0071] Figure 9 is a table showing the number of lost points for each type and model number of machine parts. As shown in Figure 9, in Table 90, the normalized molding difficulty information 91 and total loss amount 92, as well as the weighted normalized molding difficulty information 93 and total loss amount 94, are displayed for each type along with the number of lost points 95, allowing for mutual comparison.

[0072] The loss scores 95 presented in Table 90 are based on a quantitative evaluation of loss amounts, which stems from differences in the machine part model number, i.e., differences in the production equipment used in production, specifically the molds and their current usage. In addition, the evaluation also takes into account the type of machine part, i.e., the molding difficulty, which is a qualitative evaluation specific to the production process of machine parts of the same type. The quantities in Table 90 may also be displayed as graphs.

[0073] Next, the quality evaluation of the production process obtained from the above example of operation will be explained for each normalization method, with reference to the tables in Figures 10 and 11.

[0074] (Maximum-Minimum Normalization) Figure 10(A) is a table 100 in which, starting from a certain point in time (Month X, 2025), production equipment 30 was operated for a predetermined period of one month to produce a total of four machine parts: (Type A, Type B, Type C), (Type A, Type A, Type 2), (Type B, Type 1), and (Type C, Type 1), with three types of parts, Type A having two type numbers, Type A and Type 2. The table 100 calculates and displays the number of lost parts for each machine part according to the operation example.

[0075] In Table 100, the normalization of the normalized molding difficulty information 101 and the normalized total loss amount 102 is based on the maximum-minimum normalization method. As a result, the loss score is expressed as a relative evaluation based on the first-ranked and last-ranked machine parts out of a total of four points. Specifically, in the loss score 103 of Table 100, the first-ranked part is always 100 points, the last-ranked part is always 0 points, and the ranks between them are expressed as scores greater than 0 and less than 100. If no total loss amount is incurred, the loss score is set to 0 regardless of the value of the molding difficulty information.

[0076] In this example, the top-ranked product (Product A, Model 1) was evaluated as having the highest total loss amount and the lowest molding difficulty. The second-ranked product (Product A, Model 2), although having the same molding difficulty as the first-ranked product, had a lower total loss amount due to the difference in the molds used in production, resulting in a lower overall loss score than the first-ranked product.

[0077] Furthermore, when displaying Tables 100 and 110, it is preferable to also display the ranking for each variety and model number being evaluated.

[0078] Table 100, based on such relative evaluations, has the advantage of making it easy to determine the quality of the production process between different varieties and model numbers.

[0079] Furthermore, when the total amount of losses is the same in actual monetary terms across multiple varieties, it has the advantage of making it easier to determine the priority of improvements.

[0080] On the other hand, relative evaluation is not suitable for evaluations over different periods. Figure 10(B) is Table 110, which shows the loss points for each of the four machine parts (Type A, Model 1), (Type A, Model 2), (Type B, Model 1), and (Type C, Model 1) produced by operating production equipment 30 for one month following the evaluation of Table 100 (Month 2025(X+1)), according to the operation example. In Table 110, (Type A, Model 2) is ranked first with a higher loss point than the previous month, but this is based on a decrease in the total loss amount for (Type A, Model 1) from the previous month and does not reflect the actual situation of the production process.

[0081] In this case, it is preferable to take measures such as making the evaluation period and aggregation period arbitrary, rather than regular, for example, evaluating before and after implementing measures against losses in the production equipment 30, in order to obtain evaluations for different periods.

[0082] (Normalization based on target values) Figure 11(A) is a table 120 in which the number of lost parts for each machine component was calculated and displayed, following the example of operation, after the production equipment 30 was operated for a predetermined period of one month from a certain point in time (month X, 2025) to produce four machine components: (product type A, model number 1), (product type A, model number 2), (product type B, model number 1), and (product type C, model number 1).

[0083] However, in Table 120, the normalization of the normalized molding difficulty information 121 and the normalized total loss amount 112 is based on a target value-based normalization method, that is, the degree of achievement against a predetermined target value. Here, the target value is preferably a predetermined target amount (100,000 yen) as separately stated.

[0084] As a result, the loss score of 123 is expressed by an absolute evaluation among the four machine parts. In this example, if no total loss amount is incurred, the loss score is set to 0, regardless of the value of the molding difficulty information.

[0085] Figure 11(B) is Table 130, which shows the loss points for each machine part calculated and displayed according to the operation example, produced by operating production equipment 30 for one month in the month following the evaluation of Table 120 (Month 2025(X+1)) to produce four machine parts: (Type A, Model 1), (Type A, Model 2), (Type B, Model 1), and (Type C, Model 1). In Table 130, the target values ​​are set to the same values ​​(amounts) as the previous month. This makes it easy to determine the changes in quality during the production process for each machine part over each evaluation period.

[0086] Table 120, which uses such absolute evaluation, has the advantage of making it easy to determine the quality of each machine part in the production process for each evaluation period in light of the target value.

[0087] Furthermore, when displaying Tables 100-130, it is preferable to display both the current and previous rankings for each machine part being evaluated. Also, although the above explanation assumes the specified period is one month, the specified period may be any unit, such as a quarter, half-year, or one year, as long as it allows for the aggregation and comparison of loss points.

[0088] According to the production process quality evaluation device 1 of this embodiment 1, by executing the production process quality evaluation method performed in the above example of operation, the evaluation means consisting of a CPU 11, etc., evaluates the quality of the production process of machine parts based on the amount of loss incurred in the production of machine parts during a predetermined production period, which is read from the loss amount database 13b in the storage 13, and calculates it as a loss score.

[0089] In the above configuration, the quality of the machine parts production process is evaluated quantitatively not solely on conventional primary information (stroke rate, completion rate), but based on actual monetary losses incurred. This makes it possible to accurately determine which product types should be prioritized for improvement, depending on the differences in production quantities for each product type.

[0090] For example, in industries that require a wide variety of machine parts, such as automotive parts manufacturers, the production volume of machine parts differs significantly for each type, and the ranking of production volume rarely changes drastically in the short term (e.g., within about a year). Therefore, misidentifying the most impactful product types is not just a one-time problem, but can lead to the risk of continuously misjudging the priority of improvement targets.

[0091] According to this embodiment 1, since the target for improvement can be accurately identified, it is suitable for application to production sites in industries that require a wide variety of machine parts.

[0092] Furthermore, according to this embodiment 1, the loss score calculated by the evaluation means is a quantitative evaluation, that is, an objective indicator based on numerical values. Therefore, when producing a wide variety of machine parts, it becomes easier to unify understanding among departments in the production site, such as quality, production, and maintenance, regarding which product types should be prioritized for improvement.

[0093] Furthermore, according to this embodiment 1, since the loss score calculated by the evaluation means is an index based on specific monetary amounts, the advantages and disadvantages of improvement can be clearly explained based on economic value. This has the effect of making it easier to obtain investment decisions regarding improvements from the management of manufacturers.

[0094] Furthermore, according to this embodiment 1, since the loss score calculated by the evaluation means is an indicator based on specific monetary amounts, it becomes possible to evaluate the Return on Investment (ROI) of improvement measures. In other words, by comparing the man-hours and costs involved in the improvement with the monetary effect obtained, it becomes possible to select measures that are worth pursuing for improvement.

[0095] Furthermore, according to this embodiment 1, since the loss score calculated by the evaluation means is an objective indicator based on numerical values, it has the effect of enabling data-driven decision-making regarding improvements, moving away from subjective and experiential judgments.

[0096] Furthermore, according to the production process quality evaluation apparatus of this embodiment 1, the evaluation means, consisting of a CPU 11 and the like, further uses molding difficulty information indicating the molding difficulty of machine parts stored in the difficulty database 13c in the storage 13 to calculate a loss score in the quality evaluation of the production process of machine parts, taking into account the molding difficulty as a qualitative evaluation specific to the production process of machine parts of the same type.

[0097] In other words, in punching processes using molds such as the punch 31 and die 32 shown in Figure 3, the manufacturing method and processing difficulty differ depending on the type of machine part being produced, resulting in different loads on the mold and different molding difficulty for each type. In particular, when the material thickness is thick, the load on the mold increases, which tends to increase the risk of cracking and wear. Improving the production process of machine parts using such molds requires a great deal of manpower, time, and economic costs, and even if the monetary loss caused by the machine part is large, the actual cost-effectiveness may be low.

[0098] According to this embodiment 1, the qualitative difficulties involved in the production of such machine parts are quantified as molding difficulty, and by considering this molding difficulty, it becomes possible to accurately determine which of the various machine part production processes should be prioritized for improvement. Specifically, it becomes possible to lower the hurdle for starting improvements. In other words, the effect is that a workplace that was exhausted from tackling only difficult improvement themes will be able to achieve results starting with themes that are relatively less difficult.

[0099] More specifically, it becomes possible to accelerate the cycle of continuous improvement activities. In other words, it becomes possible to select improvement targets that are easy to improve and yield results at the workplace, and to improve motivation for improvement activities by gaining early success experiences.

[0100] Furthermore, according to this embodiment 1, since the molding difficulty used by the evaluation means is quantified as a parameter, it is possible to eliminate the reliance on individual expertise in evaluating and improving the production process. This means that the qualitative judgments that previously depended on the experience and skills of skilled specialists are being replaced with quantitative judgments.

[0101] Furthermore, according to this embodiment 1, since the molding difficulty used by the evaluation means is quantified as a parameter, it is possible to improve the accuracy of cost estimation and budgeting for improvement proposals. This is because the molding difficulty can approximate the man-hours required for improvement, and these man-hours can be visualized numerically.

[0102] Furthermore, when producing the same type of machine part using multiple molds and distinguishing the finished machine part by part number, it is preferable to consider the following: That is, while the basic shape and dimensions of the molds using punch 31 and die 32, etc., are given to each part number as having the same molding difficulty, the measured values ​​of the molds (flatness, parallelism, perpendicularity, roundness, etc.) and the degree of wear that occurs due to use will differ for each mold.

[0103] Since such differences are thought to directly affect production performance, they can be observed from changes in conventional stroke rates, completion rates, and even loss amounts. Furthermore, if there are differences in the number of lost parts for the same type of machine part, it becomes possible to estimate the degree of mold wear, etc., based on these changes.

[0104] Furthermore, according to the production process quality evaluation device 1 of this embodiment, the loss amount stored in the loss amount database 13b in the storage 13 includes the product scrap loss amount, which is the amount resulting from the disposal of defective products that occur in the production of machine parts.

[0105] This allows for the evaluation of direct monetary losses incurred during the production process as part of the loss amount, and enables a more precise determination of which product types should be prioritized for improvement, depending on the differences in production quantities for each type and model number of machine parts.

[0106] Furthermore, according to the production process quality evaluation device 1 of this embodiment 1, the loss amount stored in the loss amount database 13b in the storage 13 includes the jig and tool cost loss amount, which is the amount resulting from the purchase, maintenance, or repair of jigs or tools.

[0107] This allows for the evaluation of indirect monetary losses incurred during the production process as part of the loss amount, and enables a more precise determination of which product types should be prioritized for improvement, depending on the differences in production quantities for each type and model number of machine parts.

[0108] Furthermore, according to the production process quality evaluation device 1 of this embodiment 1, the loss amount stored in the loss amount database 13b in the storage 13 includes the maintenance time loss amount, which is the amount resulting from the labor costs required for the maintenance or repair of the jigs or tools.

[0109] This allows for the evaluation of fluid monetary losses incurred during the production process as part of the loss amount, and enables a more precise determination of which product types should be prioritized for improvement, depending on the differences in production quantities for each type and model number of machine parts.

[0110] Furthermore, according to the production process quality evaluation device 1 of this embodiment, the evaluation means quantitatively weights the amount of loss and the difficulty of molding, that is, uses different ratios depending on the type of machine part, to evaluate the quality of the production process of the machine part and calculate it as a loss score.

[0111] This makes it possible to conduct a precise evaluation by taking into account the actual situation of quality evaluation in the production process, specifically the differences in the contribution of total loss amounts and molding difficulty information in quality evaluation in the production process.

[0112] (Embodiment 2) The production process quality evaluation device according to Embodiment 2 of the present invention visualizes the changes in production process quality over time, as another example of operation of the production process quality evaluation device 1 of Embodiment 1.

[0113] The operation of the production process quality evaluation apparatus 1 according to this second embodiment will be described below with reference to Figure 12. Figure 12 is a diagram showing the change point history graph included in the screen displayed via the user I / F 14 by the processing of the CPU 11.

[0114] As described in Embodiment 1, the production process quality evaluation device 1 stores stroke rate and completion rate as main information regarding the production of a specific machine part during a predetermined production period in the main information database 13a within the storage 13. The change point history graph 140 displays the changes in stroke rate and completion rate, respectively, within a predetermined production period unit. In the change point history graph 140, the horizontal axis represents a predetermined production period, with the production serial number, i.e., one production lot of machine parts produced by operating the production equipment 30, as the unit. The vertical axis represents the production performance, with the completion rate performance shown as a series of rectangles representing either completion or failure, and the stroke rate performance shown as a line graph showing changes within the range of 0 to 100%.

[0115] Furthermore, in the change point history graph 140, the history of events such as maintenance and repair of the production equipment 30 is displayed as 4M (Man, Material, Machine, Method) change points using points and lines. In Figure 12, as an example, the replacement history of the punch 31 and die 32 of the mold in the production equipment 30 is shown with a signed dashed line, while the replacement history of special parts, the timing of mold reassembly / treatment, and mold polishing are each shown with different shapes.

[0116] The 4M change points are preferably recorded in the main information database 13a within the storage 13 or in a separate storage area. The 4M change points are preferably automatically acquired from the production equipment 30 via the device I / F 15 each time an event occurs, but they may also be set by manual input by the administrator via the user I / F 14.

[0117] Furthermore, it is more preferable that the user interface 14 be linked to the display of tables 90, 100, 110, 120, and 130 in Example 1, and that it be able to call up change point history graphs 140 corresponding to the varieties included in those tables.

[0118] This second embodiment, by incorporating a configuration for displaying the change point history graph 140 as described above, achieves the following effects. Specifically, by using the production serial number on the horizontal axis of the change point history graph 140, it becomes possible to uniquely track when the target machine part was produced in chronological order, and continuous visualization is achieved that is independent of the type, model number, and date of the machine part.

[0119] Furthermore, in the change point history graph 140, the performance is plotted on the vertical axis, displaying the performance for each production serial number.

[0120] In other words, the change point history graph 140 visualizes the operating status of the production equipment 30 and information regarding maintenance or repairs during the production process, as a time-series representation of the changes in quality during the production process.

[0121] By referring to the change point history graph 140, the deterioration in production process performance, as well as the timing and causes of that deterioration, can be grasped visually and intuitively. The point at which performance began to deteriorate can be clearly identified in conjunction with the 4M change points. This makes it possible to improve the initial speed of factor investigation and countermeasure planning.

[0122] For example, traditionally, investigating the causes of problems involved a great deal of time spent interviewing workers and reviewing past data, but by referring to the change point history graph 140, the situation can be grasped at a glance.

[0123] Furthermore, the slope of the graph and the distribution of change points in the change point history graph 140 allow for a visual determination of whether the deterioration in performance is a "sudden problem" or a "continuous problem," making it easier to formulate countermeasures. Specifically, it makes it easy to identify the following patterns of performance deterioration.

[0124] (Sudden problem) If the stroke rate suddenly decreases and a sudden deterioration in performance occurs, the 4M change point immediately preceding this can be inferred to be the cause of the deterioration. Specifically, the mold polishing history 141 in Figure 12 can be inferred to be the cause of the deterioration in performance.

[0125] (Ongoing Problems) If chronic deterioration in stroke rate or completion rate occurs, it can be inferred that a fundamental review of the mold design and manufacturing method is necessary.

[0126] Furthermore, the 4M change points do not necessarily display all history; only those considered to have a high correlation with performance deterioration may be extracted and displayed. In this case, performance deterioration can be detected, as described above, from a decrease in the stroke rate or the consistent occurrence of non-completion rates in the completion rate. This prevents the change point history graph 140 from becoming information overload and improves the accuracy of the analysis.

[0127] Furthermore, according to this second embodiment, the configuration for displaying the change point history graph 140 reduces the risk of human error and omissions in recording when diagnosing deterioration in performance. In other words, it becomes possible to make judgments based on objective historical data without relying on the operator's memory.

[0128] Furthermore, according to this second embodiment, the configuration for displaying the change point history graph 140 facilitates information sharing between the production site and other departments. In other words, by visualizing the production performance, problem occurrences, and changes in abnormalities of machine parts in a time-series format that anyone can understand, it becomes possible to facilitate information sharing between quality, production, and maintenance.

[0129] As described above, the present invention makes it possible to provide a production process quality evaluation device that can determine which types of machine parts should be prioritized for improvement when managing the production of a wide variety of machine parts.

[0130] (Variations, etc.) In the above explanation, the weighting process performed to balance the data used in quality evaluation during the production process (Example 1, Step S108) was applied to the total loss amount and molding difficulty information. However, the weighting process may also be performed among the material thickness, material hardness, rotation speed, and manufacturing method, which constitute the molding difficulty information. This is because the contributions of material thickness, material hardness, rotation speed, and manufacturing method to molding difficulty are all different.

[0131] Therefore, in step S106 described above, performing a weighting process after normalizing the individual molding difficulty information is preferable because it can improve the accuracy of the combined molding difficulty information. For example, since the degree of difference in material thickness contributes more to molding difficulty than the degree of difference in manufacturing method, it is preferable to increase the ratio of material thickness in molding difficulty. A similar weighting process may also be performed among the product waste loss amount, tooling cost loss amount, and maintenance time loss amount, which constitute the total loss amount.

[0132] Furthermore, although the weighting process in the above explanation uses fixed values ​​as an example, it may be made variable according to the type and model number of the machine parts, molding difficulty information, and the operating time of the production equipment 30. This makes it possible to evaluate the quality of the production process of machine parts with greater precision.

[0133] Furthermore, in the above description, the quality evaluation device 1 for the production process according to each embodiment of the present invention has a punch 31 and a die 32 as well as a stripper (not shown) as molds as shown in Figure 3, and evaluates the quality of the production process of machine parts by punching the operation of a machine parts production facility 30 that produces machine parts by punching. However, the configuration of the present invention is not limited thereto.

[0134] In other words, the production process quality evaluation apparatus of the present invention only needs to evaluate the quality of the production process of industrial parts, and is not limited by the specific content of the industrial parts, or in other words, by the type of industry and production.

[0135] Therefore, industrially produced parts may include not only mechanical parts, but also electrical components, electronic components, parts used in construction and equipment, chemicals, pharmaceuticals, and any other parts. Furthermore, the manufacturing method for producing such industrial parts may be cutting, casting, forging, sintering, resin molding, 3D printing, chemical processes, or any other method, and the difficulty level will be determined according to the manufacturing method and the tools, jigs, etc. required for that method.

[0136] Furthermore, in the above description, the production process quality evaluation device 1 is described as evaluating the quality of the production process using both the total amount of losses and the difficulty of molding. However, in the present invention, it is sufficient to evaluate the quality of the production process using at least the amount of losses, and the difficulty of molding may not be used.

[0137] Furthermore, in the above description, the quality evaluation device 1 in the production process is assumed to include product waste loss, tooling cost loss, and maintenance time loss as the total loss amount. However, in the present invention, one or two of these loss amounts may be selectively used as the loss amount. In fact, only a portion of the product waste loss, tooling cost loss, and maintenance time loss may be used.

[0138] Furthermore, in the above description, the quality evaluation device 1 for the production process is shown as sequentially processing the total amount of losses and the difficulty of molding, but the time sequence of these processes can be arbitrary and may be performed in parallel.

[0139] Furthermore, in the above description, the present invention was described as a production process quality evaluation device, with production process quality evaluation device 1 as an example, and a production process quality evaluation method as its operation. However, the present invention may also be a production process quality evaluation program, which is a computer program that causes a computer to execute each step of the production process quality evaluation method, which is executed by a CPU 11 or the like.

[0140] This makes it possible to easily implement the present invention as a quality evaluation device for the production process using general-purpose servers, computers, and other information processing terminals.

[0141] As described above, embodiments of the present invention are disclosed in the above description, but the present invention is not limited thereto.

[0142] In other words, without departing from the scope of the technical idea and objectives of the present invention, various changes can be made to the embodiments and each of the modifications described above in terms of mechanism, shape, material, quantity, position or arrangement, etc., and these are included in the present invention. [Explanation of symbols]

[0143] 1. Quality evaluation equipment for the production process 10 Network Interface 11 CPU 12 memory 13 Storage 13a Main Information Database 13b Loss Amount Database 13c Difficulty Database 14 User Interface 15 devices 20 Bus Interface 30 Production Equipment 31, 41, 51, 61 punches 32 Dies Work 33, 42, 52, 62 43, 53, 63 Machine parts Tables 70, 80, 90, 100, 110, 120, 130 71 Main Information 82, 91, 93, 101, 121 Molding difficulty information 140 Change Point History Graph 141 History

Claims

1. An evaluation process for evaluating the quality of the production process of industrial parts, using a loss amount database that stores the amount of losses incurred in the production of industrial parts during a predetermined production period and a difficulty database that stores the difficulty of producing the industrial parts, wherein the evaluation process is performed by a computer, and the evaluation process is performed by a computer. The aforementioned loss amount and the aforementioned difficulty are used in different ratios depending on the type of industrial part. Quality evaluation methods for the production process.

2. The aforementioned loss amount includes the amount resulting from the disposal of defective products that occur in the production of the aforementioned industrial parts. A method for evaluating the quality of a production process as described in claim 1.

3. The aforementioned loss amount includes the amount resulting from the purchase, maintenance, or repair of jigs or tools in the production of the aforementioned industrial parts. A method for evaluating the quality of a production process as described in claim 1.

4. The aforementioned loss amount includes the amount resulting from labor costs required for the maintenance or repair of the jigs or tools that occur in the production of the industrial parts. A method for evaluating the quality of a production process as described in claim 3.

5. The operating status of the production equipment for the industrial parts and information regarding maintenance or repair during the production process of the industrial parts are displayed as a graph. A method for evaluating the quality of a production process as described in claim 1.

6. A loss amount database that stores the amount of losses incurred in the production of industrial parts during a predetermined production period, A difficulty database that stores the difficulty of producing the aforementioned industrial parts, The system includes an evaluation means for evaluating the quality of the production process of the industrial parts based on the amount of loss and the difficulty level, The aforementioned loss amount and the aforementioned difficulty are used in different ratios depending on the type of industrial part. Quality evaluation equipment for the production process.

7. The aforementioned loss amount includes the amount resulting from the disposal of defective products that occur in the production of the aforementioned industrial parts. A quality evaluation apparatus for the production process according to claim 6.

8. The aforementioned loss amount includes the amount resulting from the purchase, maintenance, or repair of jigs or tools in the production of the aforementioned industrial parts. A quality evaluation apparatus for the production process according to claim 6.

9. The aforementioned loss amount includes the amount resulting from labor costs required for the maintenance or repair of the jigs or tools that occur in the production of the industrial parts. The production process quality evaluation apparatus according to claim 8.

10. In the production process of the aforementioned industrial parts, the operating status of the production equipment for the industrial parts and information regarding maintenance or repair are displayed as graphs. A quality evaluation apparatus for the production process according to claim 6.

11. A production process quality evaluation program for causing a computer to perform the evaluation step of the production process quality evaluation method described in claim 1.

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