Proposal device, machine system, proposal method, and program

Abstract

A proposal device (10) is provided with a measurement unit (101) and a proposal unit (105). The measurement unit (101) measures the state of a processing machine (2). The proposal unit (105), on the basis of shipping data in which the state of the processing machine (2) at a factory shipping stage and the performance of the processing machine (2) are associated with each other, and the state of the processing machine (2) measured by the measurement unit (101), proposes, to a user, an initial setting that satisfies the performance required by the user for the processing machine (2).

Description

Proposal device, machining system, proposal method and program

[0001] The present disclosure relates to a proposal device, a machining system, a proposal method, and a program.

[0002] In order to operate a machine tool appropriately, the machine tool needs to be set appropriately. In relation to this situation, Patent Document 1 discloses a technology for assisting in setting setting conditions for a machine tool by providing an appropriate range of setting conditions determined in consideration of disturbances.

[0003] Japanese Patent Application Laid-Open No. 2019-098453

[0004] However, even with the technology of Patent Document 1, the user still needs to set the machine tool from various perspectives in order to operate the machine tool at an appropriate speed and accuracy, which places a heavy burden on the user.

[0005] In view of the above circumstances, an object of the present disclosure is to provide a proposal device etc. that can reduce the burden on users in setting up machine tools.

[0006] In order to achieve the above-mentioned object, the proposal device according to the present disclosure includes a measurement means for measuring the state of the machine tool, and a proposal means for proposing to the user initial settings that satisfy the performance required of the machine tool by the user based on shipping data that correlates the state of the machine tool at the time of factory shipment with the performance of the machine tool and the state of the machine tool measured by the measurement means.

[0007] According to the present disclosure, the burden on the user of setting up a machine tool can be reduced.

[0008] A block diagram showing the overall configuration of a machining system according to an embodiment of the present disclosure. A perspective view showing an example of a processing machine according to an embodiment of the present disclosure. A graph showing an example of a maintenance timing prediction by an analysis unit of a proposed device according to an embodiment of the present disclosure. A block diagram showing an example of a hardware configuration of a proposed device according to an embodiment of the present disclosure. A flowchart showing an example of a proposed process by a proposed device according to an embodiment of the present disclosure. A graph showing an example of an analysis execution timing by an analysis unit of a proposed device according to an embodiment of the present disclosure. A flowchart showing an example of a proposed process by a proposed device according to an embodiment of the present disclosure.

[0009] Hereinafter, a machining system according to an embodiment of the present disclosure will be described with reference to the drawings. In each drawing, the same or equivalent parts are denoted by the same reference numerals.

[0010] (Embodiment) A machining system 1 according to an embodiment will be described with reference to FIG. 1 . The machining system 1 includes a processing machine 2, an inspection device 3, and a proposal device 10. The processing machine 2 is a machine tool installed at a production site that processes a workpiece. The inspection device 3 is an inspection device that inspects the workpiece (hereinafter referred to as the "product") processed by the processing machine 2. The proposal device 10 is communicably connected to the processing machine 2 and the inspection device 3. The proposal device 10 measures the state of the processing machine 2, obtains data related to the processing accuracy of the product from the inspection device 3, and proposes initial settings to be set for the processing machine 2 to a user of the processing machine 2. The initial settings here refer to settings that may affect the operating characteristics of the processing machine 2, and are related to installation information such as the number of mounting bolts for the processing machine 2 and the tightening torque values ​​of the mounting bolts; mechanical property information such as mass, rigidity, damping, and friction based on the assembly, configuration, and materials of the processing machine 2 as a whole; and command control information such as the processing shape and shape layout, and refer to settings that may affect the operating characteristics of the processing machine 2 before the processing machine 2 starts operating. When a user inputs requests for the processing machine 2, such as reducing the processing tact time, improving processing accuracy, and reducing power consumption, into the proposal device 10, the proposal device 10 proposes to the user initial settings required to satisfy the requests. This reduces the burden on the user of setting up the processing machine 2. The machining system 1 is an example of a machining system according to the present disclosure.

[0011] As shown in FIG. 2 , the processing machine 2 includes a head 21, a plurality of motors 22, a plurality of fixing parts 23, and a plurality of sliding parts 24. The head 21 includes a tool for processing a workpiece, and is moved by the driving of the plurality of motors 22. For example, when the processing machine 2 is a laser processing machine, the head 21 is a laser head. When each motor 22 is driven, each sliding part 24 operates, and the head 21 moves. The fixing part 23 is a part for fixing the processing machine 2 to a base on which the processing machine 2 is installed. The fixing part 23 is fixed to the base by, for example, a bolt. The processing machine 2 is an example of a machine tool according to the present disclosure.

[0012] The processing machine 2 also includes a plurality of sensors (not shown). The processing machine 2 includes sensors that detect the state of the processing machine 2, such as a strain sensor that detects strain in the fixed portion 23 of the processing machine 2, a torque sensor that detects the torque of the motor 22, and an acceleration sensor that detects the acceleration of the head 21. The processing machine 2 also includes sensors that detect the state of the workpiece, such as a camera that captures an image of the workpiece. The processing machine 2 also includes sensors that detect the environment in which the processing machine 2 is installed, such as a temperature sensor, a humidity sensor, and a vibration sensor. These sensors output information indicating the detected state or environment to the proposal device 10.

[0013] Referring again to FIG. 1 , the inspection device 3 inspects the product produced by the processing machine 2. The inspection device 3 particularly inspects the accuracy of the three-dimensional shape and appearance of the product produced by the processing machine 2. The inspection device 3 transmits performance data indicating the accuracy of the shape of the product produced by the processing machine 2 to the proposal device 10. For example, when the shape of the product produced by the processing machine 2 is cylindrical, the inspection device 3 inspects the roundness of the circular portion of the bottom surface of the product. The inspection device 3 transmits data indicating the roundness as performance data to the proposal device 10.

[0014] In response to a user inputting performance requirements for the processing machine 2, such as reduction in processing tact time, improvement in processing accuracy, and reduction in power consumption, the proposal device 10 proposes to the user initial settings required to satisfy the requirements. The proposal device 10 includes a communication unit 100, a performance data acquisition unit 107, a measurement unit 101, a memory unit 102, an input unit 103, an analysis unit 104, a proposal unit 105, and a display unit 106. The proposal device 10 is an example of a proposal device according to the present disclosure.

[0015] The communication unit 100 communicates with the processing machine 2 and the inspection device 3. The communication unit 100 receives information output from a sensor provided in the processing machine 2. The information received from the sensor is used by a measurement unit 101, which will be described later. The communication unit 100 also receives performance data from the inspection device 3. The performance data received from the inspection device 3 is acquired by a performance data acquisition unit 107, which will be described later, and stored in the storage unit 102.

[0016] The performance data acquisition unit 107 acquires performance data received by the communication unit 100 from the inspection device 3 and stores it in the storage unit 102. The performance data acquisition unit 107 cumulatively stores the acquired performance data in the storage unit 102 every time the inspection device 3 inspects a product and transmits performance data.

[0017] The measuring unit 101 uses information received by the communication unit 100 from the sensors of the processing machine 2 to measure the state of the processing machine 2, the installation environment of the processing machine 2, and the state of the workpiece processed by the processing machine 2. The state of the processing machine 2 includes, for example, the amount of strain of the fixing unit 23 of the processing machine 2, the torque of the motor 22 of the processing machine 2, and the acceleration of the head 21 of the processing machine 2. The installation environment of the processing machine 2 includes, for example, the room temperature, humidity, vibration, etc. in the installation environment of the processing machine 2. The state of the workpiece includes, for example, the shape of the workpiece, the presence or absence of scratches on the surface of the workpiece, etc. The measuring unit 101 is an example of a measuring means according to the present disclosure.

[0018] The storage unit 102 stores shipping data that associates the state of the processing machine 2 at the time of shipment from the factory with the performance of the processing machine 2. For example, the manufacturer of the processing machine 2 inspects the processing machine 2 at the time of shipment and stores data that associates the state of the processing machine 2 and the performance of the processing machine 2 as shipping data in the storage unit 102. The performance of the processing machine 2 here includes processing speed, processing accuracy, etc. The performance of the processing machine 2 may include, in addition to processing speed and processing accuracy, for example, power consumption.

[0019] The memory unit 102 also stores performance data that indicates the accuracy of the shape of the product produced by the processing machine 2, which data is transmitted by the inspection device 3 and acquired by the performance data acquisition unit 107. Since the performance data is stored cumulatively, the memory unit 102 accumulates performance data that indicates the accuracy of the shape of the product that has been produced by the processing machine 2 up to now.

[0020] The input unit 103 accepts input operations by a user. The input unit 103 includes input devices such as a keyboard, a mouse, a touch screen, etc. The input unit 103 particularly accepts input by the user of performance requirements for the processing machine 2, such as operating speed and operating accuracy.

[0021] The analysis unit 104 performs a processing simulation to virtually perform processing using the processing machine 2 based on the mechanical property information measured by the measurement unit 101, such as information on the assembly, component configuration, and installation of the processing machine 2; information on the surrounding environment, such as the temperature and vibration of the installation environment of the processing machine 2; and information on the accuracy of the three-dimensional shape dimensions and appearance of the workpiece, as well as the performance data stored in the memory unit 102 and performance requirements for the processing machine 2 input by the user via the input unit 103. The analysis unit 104 performs the processing simulation with the goal of improving the accuracy of the shape of the products previously produced by the processing machine 2, as indicated by the performance data. For example, when the roundness indicated by the performance data is 0.05 mm, the analysis unit 104 performs the processing simulation with the goal of improving the roundness to 0.04 mm. The analysis unit 104 analyzes characteristics that affect the processing accuracy of the processing machine 2 based on the results of the processing simulation. Examples of characteristics that can affect the processing accuracy include the installation environment of the processing machine 2, the product structure of the processing machine 2, options applicable to the processing machine 2, and the control program for the processing machine 2. The analysis unit 104 is an example of an analysis means according to the present disclosure.

[0022] Furthermore, based on the analysis results of the above analysis, the analysis unit 104 may learn the relationship between parameters related to the machining machine 2, such as the amount of distortion of the fixed part 23, the torque of the motor 22, the acceleration of the head 21, the room temperature, humidity, and vibration in the installation environment of the machining machine 2, and the sensitivity of the machining machine 2 to the machining accuracy.

[0023] In addition, based on the analysis results of the above analysis, the analysis unit 104 may analyze the characteristics that affect the processing speed of the processing machine 2, which are in a trade-off relationship with the processing accuracy, and learn the relationship between the sensitivity of the processing machine 2 and the processing accuracy.

[0024] In addition, based on the analysis results of the above analysis, the analysis unit 104 may analyze characteristics that affect the power consumption or structural strength of the processing machine 2, which are in a trade-off relationship with the processing speed, and learn the relationship between the sensitivity of the processing machine 2 and the processing speed.

[0025] Furthermore, when the above analysis is performed multiple times, the analysis unit 104 may predict the timing and maintenance parts of the processing machine 2 based on time-series changes in the analysis results. For example, as shown in FIG. 3 , when it is analyzed that the torque of the motor 22 is decreasing linearly, it is possible to predict the time when the torque will fall below an empirically determined threshold. The time when it is predicted that the torque will fall below the threshold can be set as the maintenance timing. Note that a constant may be set as the threshold, or, for example, the threshold may be set so that its value increases according to the number of days elapsed since the most recent maintenance was performed. In this case, for example, driving parts such as a ball screw and a rack and pinion may also be predicted as maintenance parts at the same time.

[0026] Furthermore, when the state of the processing machine 2 measured by the measurement unit 101 satisfies a predetermined condition, the analysis unit 104 may perform an analysis to diagnose the processing machine 2. For example, as shown in Fig. 6, when a measurement value of the acceleration or the like of the processing machine 2 falls below a value twice the threshold value, a processing simulation may be executed to perform an analysis, and thereafter, the analysis may be executed periodically, for example once a month, to identify a parameter that is causing an abnormality among the parameters related to the processing machine 2 and diagnose the processing machine 2.

[0027] Referring back to FIG. 1 , the suggestion unit 105 proposes to the user initial settings that satisfy the performance requirements input by the user based on the analysis by the analysis unit 104 by displaying them on the display unit 106 (described later). More specifically, the suggestion unit 105 proposes initial settings for the installation environment of the processing machine 2, the product structure of the processing machine 2, options applicable to the processing machine 2, and the control program of the processing machine 2 based on the state and performance of the processing machine 2 at the time of factory shipment indicated by the shipping data stored in the memory unit 102 and the characteristics that affect the processing accuracy of the processing machine 2 analyzed by the analysis unit 104. For example, when the characteristics of the processing machine 2 obtained by the analysis are inferior to those at the time of factory shipment, the suggestion unit 105 proposes initial settings that improve the characteristics. To give the user room for choice, the suggestion unit 105 preferably proposes initial settings for at least two of the installation environment, product structure, options, and control program. For example, assume that the suggestion unit 105 proposes two initial settings: one for the product structure and one for the options. In this case, if it is difficult to change the initial settings of the product structure due to circumstances at the production site, the user can change the initial settings of the processing machine 2 based on the initial settings for the options proposed by the other party. Note that if the current initial settings satisfy the performance required by the user, the suggestion unit 105 does not need to suggest initial settings. The suggestion unit 105 is an example of a suggestion means according to the present disclosure.

[0028] Furthermore, the proposing unit 105 may propose to the user a combination of structural parameters and control parameters that are highly sensitive to machining accuracy, based on the learning result by the analyzing unit 104 of the relationship between the parameters and their sensitivity to the machining accuracy of the processing machine 2. This allows the user to change the initial settings by focusing on the proposed parameter combination when they want to prioritize improving the machining accuracy.

[0029] In addition, the proposal unit 105 may propose a set of structure and control parameters that simultaneously optimizes the machining accuracy and machining speed of the machining machine 2 based on the learning results of the relationship between the sensitivity of the machining machine 2 to the machining accuracy obtained from the analysis results of the analysis unit 104 and the sensitivity of the machining machine 2 to the machining speed, which is a trade-off with the machining accuracy.

[0030] In addition, the proposal unit 105 may propose a set of structural and control parameters that simultaneously optimizes the machining speed of the machining machine 2 and the power consumption or structural strength, based on the learning results of the relationship between the sensitivity of the machining machine 2 to the machining speed obtained from the analysis results of the analysis unit 104 and the sensitivity of the machining machine 2 to the power consumption or structural strength, which is a trade-off with the machining speed.

[0031] Furthermore, when the analysis unit 104 predicts the timing of maintenance, the suggestion unit 105 may suggest the timing of maintenance to the user.

[0032] Furthermore, when the analysis unit 104 diagnoses the processing machine 2, the suggestion unit 105 may present the diagnosis results to the user and suggest that the user contact customer service.

[0033] The display unit 106 displays the content of the proposal made by the proposal unit 105 under the control of the proposal unit 105. This allows the user to know the content of the proposal made by the proposal unit 105. The display unit 106 is, for example, a display.

[0034] Based on these explanations, an example of an analysis by the analysis unit 104 and a proposal by the proposal unit 105 will be described. The analysis unit 104 performs a machining simulation and analysis based on the amount of strain of the fixed part 23 of the processing machine 2 measured by the measurement unit 101 and the acceleration of the head 21 of the processing machine 2 measured by the measurement unit 101. If the analysis results in a failure to meet the processing accuracy required by the user, the proposal unit 105 proposes, for example, adding bolts or tightening the bolts as a proposal related to the installation environment to eliminate the strain of the fixed part 23 and reduce vibration, and proposes replacing the head 21 with a lighter one to reduce wobble of the head 21 as a proposal related to the product structure and options. Adding bolts or tightening the bolts reduces the impact of vibration on the processing machine 2 and is therefore a proposal to improve the installation environment, i.e., a proposal related to the installation environment. Replacing the head 21 involves replacing the head 21 with an optional part and improving the product structure, and is therefore a proposal related to the product structure and options. The user may change the initial settings based on both proposals, or based on only one proposal. The user may also issue instructions to the processing machine 2 for processing parts required to change the product structure or add optional items.

[0035] An example of the hardware configuration of the proposal device 10 will be described with reference to Fig. 4. The proposal device 10 shown in Fig. 4 is realized by a computer such as a personal computer or a microcontroller.

[0036] The proposed device 10 includes a processor 1001 , a memory 1002 , an interface 1003 , and a secondary storage device 1004 , which are connected to each other via a bus 1000 .

[0037] The processor 1001 is, for example, a CPU (Central Processing Unit). The processor 1001 loads an operating program stored in the secondary storage device 1004 into the memory 1002 and executes the program, thereby realizing each function of the proposed device 10.

[0038] The memory 1002 is a main storage device configured, for example, by a RAM (Random Access Memory). The memory 1002 stores the operating program that the processor 1001 reads from the secondary storage device 1004. The memory 1002 also functions as a working memory when the processor 1001 executes the operating program.

[0039] The interface 1003 is an I / O (Input / Output) interface such as a serial port, a USB (Universal Serial Bus) port, or a network interface.

[0040] The secondary storage device 1004 is, for example, a flash memory, a hard disk drive (HDD), or a solid state drive (SSD). The secondary storage device 1004 stores the operating programs executed by the processor 1001.

[0041] An example of the proposal process by the proposal device 10 will be described with reference to Fig. 5. The process shown in Fig. 5 is executed, for example, every business day before the operation of the processing machine 2. It is also assumed that performance data has already been accumulated in the storage unit 102 when the process shown in Fig. 5 is executed.

[0042] The measurement unit 101 of the proposed device 10 measures the state of the processing machine 2, the installation environment of the processing machine 2, and the state of the workpiece (step S1).

[0043] The analysis unit 104 of the proposal device 10 waits for the user to input performance requirements for the processing machine 2 via the input unit 103 (step S2). When the user inputs the performance requirements, the process proceeds from step S3.

[0044] The analysis unit 104 executes a processing simulation to virtually perform processing using the processing machine 2 based on the state of the processing machine 2 measured in step S1, the installation environment of the processing machine 2, and the state of the workpiece to be processed, the actual data stored in the memory unit 102, and the performance requirements for the processing machine 2 input in step S2 (step S3).

[0045] The analysis unit 104 analyzes the characteristics that affect the machining accuracy of the processing machine 2 based on the results of the processing simulation in step S3 (step S4).

[0046] The proposing unit 105 of the proposing device 10 displays initial settings that satisfy the performance requirements input by the user on the display unit 106 (described later) based on the analysis in step S4, and proposes them to the user (step S5).The proposing device 10 then ends the proposal process.

[0047] Another example of the proposal process by the proposal device 10 will be described with reference to Fig. 7. The process shown in Fig. 7 is executed, for example, once a month before the operation of the processing machine 2. It is also assumed that performance data has already been accumulated in the storage unit 102 when the process shown in Fig. 7 is executed.

[0048] The measurement unit 101 of the proposed device 10 measures the state of the processing machine 2, the installation environment of the processing machine 2, and the state of the workpiece (step T1).

[0049] The analysis unit 104 of the proposal device 10 waits for the user to input performance requirements for the processing machine 2 via the input unit 103 (step T2). When the user inputs the performance requirements, the process proceeds from step T3.

[0050] The analysis unit 104 executes a processing simulation to virtually perform processing using the processing machine 2 based on the state of the processing machine 2 measured in step T1, the installation environment of the processing machine 2, and the state of the workpiece to be processed, the actual data stored in the memory unit 102, and the performance requirements for the processing machine 2 input in step T2 (step T3).

[0051] Based on the results of the machining simulation in step T3, the analysis unit 104 repeatedly executes the machining simulation in step T3 while varying the structural and control parameters of the machining machine within a predetermined range, and simultaneously learns the sensitivity of characteristics that affect the machining accuracy, machining speed, power consumption, and structural strength. The parameter variation range can be set arbitrarily by the user, and may be a range that reflects the product variation range or functional constraints (step T4).

[0052] The proposal unit 105 of the proposal device 10 derives an optimal structure and control parameter set that maintains a balance between machining accuracy, machining speed, power consumption, and structural strength based on the learning results of step T4 and the user's performance requirements (step T5).

[0053] The proposing unit 105 of the proposing device 10 instructs the machining of parts to be mounted on the processing machine 2 in order to reflect the structural parameters derived in step T5 in an actual product (step T6). For example, the proposing unit 105 instructs the machining of removable parts around the processing head in order to achieve parameters that reduce the weight of the processing head by 10%.

[0054] The proposing unit 105 of the proposing device 10 proposes a method for mounting the part machined in step T6 on the product and its assembly configuration (step T7). For example, the proposing unit 105 proposes an assembly configuration in which mounting holes are machined in additional sheet metal to improve the product rigidity and the additional sheet metal is fastened together to a screw fixing portion of the processing machine 2.

[0055] The proposing unit 105 of the proposing device 10 displays an initial setting that satisfies the performance requirements input by the user on the display unit 106 (described later) based on the parameter set derived in step T5 and the assembly configuration proposed in step T7, and proposes it to the user (step T8).The proposing device 10 then ends the proposal process.

[0056] The machining system 1 according to the embodiment has been described above. According to the machining system 1, a user simply inputs performance requirements for the processing machine 2 into the proposal device 10, and the measurement unit 101 of the proposal device 10 measures the state of the processing machine 2, the installation environment of the processing machine 2, and the state of the workpiece, the analysis unit 104 of the proposal device 10 executes a processing simulation to perform an analysis, and the proposal unit 105 of the proposal device 10 proposes appropriate initial settings based on the analysis. This allows the user to easily set initial settings for the processing machine 2 that satisfy the performance requirements. In other words, the proposal device 10 reduces the burden on the user of setting up the machine tool.

[0057] (Modification) In the embodiment, the processing machine 2 is exemplified as an example of a machine tool, but the proposing device 10 may also propose initial settings for a machine tool other than the processing machine 2.

[0058] 4, the proposed device 10 includes a secondary storage device 1004. However, the present invention is not limited to this, and the secondary storage device 1004 may be provided outside the proposed device 10, and the proposed device 10 and the secondary storage device 1004 may be connected via an interface 1003. In this configuration, removable media such as a USB flash drive or a memory card can also be used as the secondary storage device 1004.

[0059] 4, the proposed device 10 may be configured by a dedicated circuit using an ASIC (Application Specific Integrated Circuit), an FPGA (Field Programmable Gate Array), etc. In the hardware configuration shown in FIG. 4, some of the functions of the proposed device 10 may be realized by a dedicated circuit connected to the interface 1003, for example.

[0060] The program used in the proposed device 10 can be stored and distributed on a computer-readable recording medium such as a CD-ROM (Compact Disc Read Only Memory), a DVD (Digital Versatile Disc), a USB flash drive, a memory card, or a HDD. By installing such a program on a specific or general-purpose computer, the computer can function as the proposed device 10.

[0061] Furthermore, the above-mentioned program may be stored in a storage device owned by another server on the Internet, and the program may be downloaded from that server.

[0062] The present disclosure allows various embodiments and modifications without departing from the broad spirit and scope of the present disclosure. Furthermore, the above-described embodiments are intended to explain the present disclosure and do not limit the scope of the present disclosure. In other words, the scope of the present disclosure is defined by the claims, not the embodiments. Various modifications made within the scope of the claims and the meaning of equivalent disclosures are considered to be within the scope of the present disclosure.

[0063] This application is based on Japanese Patent Application No. 2024-117114, filed on July 22, 2024. The entire specification, claims, and drawings of Japanese Patent Application No. 2024-117114 are incorporated herein by reference.

[0064] Various aspects of the present disclosure are summarized below as appendices.

[0065] (Supplementary Note 1) A proposal device comprising: a measurement means for measuring the state of a machine tool; and a proposal means for proposing to the user an initial setting that satisfies the performance required by the machine tool by the user, based on shipping data correlating the state of the machine tool at the time of factory shipment with the performance of the machine tool, and the state of the machine tool measured by the measurement means. (Supplementary Note 2) The measurement means further measures an installation environment of the machine tool and the state of a workpiece machined by the machine tool, and further comprises analysis means for analyzing characteristics that affect the performance of the machine tool, based on the state of the machine tool measured by the measurement means, the installation environment of the machine tool, and the state of the workpiece, the accuracy of shapes of products generated by the machine tool so far, and performance requirements for the machine tool input by the user, and the proposal means further proposes to the user the initial setting that satisfies the performance required by the machine tool by the user, based on the analysis by the analysis means. (Supplementary Note 3) The proposal device according to Supplementary Note 2, wherein the analysis means further learns the relationship between the parameters related to the machine tool and their sensitivity to multiple performance characteristics of the machine tool based on the analysis results by the analysis means, and the proposal means further proposes a combination of parameters highly sensitive to each of the multiple performance characteristics of the machine tool based on the learning results by the analysis means. (Supplementary Note 4) The proposal device according to Supplementary Note 2, wherein the analysis means further learns the sensitivity to multiple performance characteristics of the machine tool simultaneously based on the analysis results by the analysis means, and the proposal means further derives a parameter set that optimizes the multiple performance characteristics of the machine tool based on the learning results by the analysis means and the performance requirements corresponding to the machine tool. (Supplementary Note 5) The proposal device according to Supplementary Note 4, wherein the proposal means further instructs the machine tool to machine parts to be mounted on the machine tool based on the derived parameter set, proposes a mounting method for the parts to be mounted on the machine tool, and proposes an assembly configuration of the machine tool.(Supplementary Note 6) The proposal device described in any one of Supplements 2 to 5, wherein the analysis means further predicts maintenance timing for the machine tool based on time-series changes in the analysis results, and the proposal means further proposes the maintenance timing predicted by the analysis means. (Supplementary Note 7) The analysis means further diagnoses the machine tool by executing analysis by the analysis means when the state of the machine tool measured by the measurement means satisfies a predetermined condition, The proposal device described in any one of Supplements 2 to 6. (Supplementary Note 8) A machining system comprising the proposal device described in any one of Supplements 1 to 7 and the machine tool. (Supplementary Note 9) A proposal method, wherein a computer measures the state of the machine tool, and proposes to the user initial settings that satisfy the performance required of the machine tool by the user based on shipping data that associates the state of the machine tool at the factory shipping stage with the performance of the machine tool and the measured state of the machine tool. (Supplementary Note 10) A program that causes a computer to measure the state of a machine tool, and to suggest to a user initial settings that satisfy the performance required by the user for the machine tool based on shipping data that correlates the state of the machine tool at the time of factory shipment with the performance of the machine tool and the measured state of the machine tool.

[0066] 1 Machining system, 2 Processing machine, 3 Inspection device, 10 Proposal device, 21 Head, 22 Motor, 23 Fixed part, 24 Sliding part, 100 Communication part, 101 Measurement part, 102 Memory part, 103 Input part, 104 Analysis part, 105 Proposal part, 106 Display part, 107 Performance data acquisition part, 1000 Bus, 1001 Processor, 1002 Memory, 1003 Interface, 1004 Secondary storage device.

Claims

1. A proposal device comprising: a measuring means for measuring the state of a machine tool; and a proposal means for proposing to a user initial settings that satisfy the performance required of the machine tool by the user, based on shipping data that correlates the state of the machine tool at the time of factory shipment with the performance of the machine tool, and the state of the machine tool measured by the measuring means.

2. The proposal device described in claim 1, wherein the measurement means further measures the installation environment of the machine tool and the state of the workpiece machined by the machine tool, and further comprises analysis means for analyzing characteristics that affect the performance of the machine tool based on the state of the machine tool, the installation environment of the machine tool, and the state of the workpiece measured by the measurement means, the accuracy of the shapes of products produced by the machine tool so far, and performance requirements for the machine tool input by the user, and the proposal means further proposes to the user the initial settings that satisfy the performance required by the user for the machine tool based on the analysis by the analysis means.

3. The proposal device according to claim 2, wherein the analysis means further learns the relationship between the parameters related to the machine tool and their sensitivity to multiple performance characteristics of the machine tool based on the analysis results by the analysis means, and the proposal means further proposes combinations of parameters that are highly sensitive to each of the multiple performance characteristics of the machine tool based on the learning results by the analysis means.

4. The proposal device according to claim 2, wherein the analysis means further learns the sensitivity of the machine tool to multiple performance characteristics simultaneously based on the analysis results by the analysis means, and the proposal means further derives a parameter set that optimizes multiple performance characteristics of the machine tool based on the learning results by the analysis means and the corresponding performance requirements of the machine tool.

5. The proposal device according to claim 4, wherein the proposal means further instructs the machine tool to process parts to be mounted on the machine tool based on the derived parameter set, proposes a mounting method for the parts to be mounted on the machine tool, and proposes an assembly configuration for the machine tool.

6. A proposal device according to any one of claims 2 to 5, wherein the analysis means further predicts the timing of maintenance of the machine tool based on time-series changes in the analysis results, and the proposal means further proposes the maintenance timing predicted by the analysis means.

7. The proposed device according to any one of claims 2 to 6, wherein the analysis means further diagnoses the machine tool by performing analysis by the analysis means when the state of the machine tool measured by the measurement means satisfies a predetermined condition.

8. A machining system comprising the proposed device according to any one of claims 1 to 7 and the machine tool.

9. A proposal method in which a computer measures the state of a machine tool, and proposes to a user initial settings that satisfy the performance required by the user for the machine tool based on shipping data that correlates the state of the machine tool at the time of factory shipment with the performance of the machine tool and the measured state of the machine tool.

10. A program that causes a computer to measure the condition of a machine tool, and based on shipping data that correlates the condition of the machine tool at the time of factory shipment with the performance of the machine tool and the measured condition of the machine tool, suggests to the user initial settings that satisfy the performance required by the user for the machine tool.

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