Management system and management method

Abstract

The invention provides a management system and a management method. A management system (100) is a system for managing processing equipment, and is provided with: a foreign matter detector for detecting whether or not a foreign matter is mixed in a product (20); and a management device (40) capable of processing information relating to the foreign matter. The management device acquires information pertaining to the foreign matter from the foreign matter detector, and acquires information pertaining to the state of the processing machine on the basis of the information pertaining to the foreign matter.

Description

Technical Field

[0001] The present disclosure relates to a management system and a management method. Background Art

[0002] In processing equipment for processing or making food, medicine, etc., metal detectors and X-ray foreign matter detectors are known as technologies for detecting whether foreign matter is mixed into the produced products (foreign matter detectors). For example, Patent Document 1 discloses a metal detector for detecting foreign matter of ferromagnetic materials mixed into products.

[0003] Prior art literature

[0004] Patent Literature

[0005] Patent Document 1: Japanese Patent No. 5779273 Summary of the invention

[0006] Problem that the invention aims to solve

[0007] When foreign matter is detected by these foreign matter detectors, the products mixed with foreign matter are removed from the production line. In addition, depending on the frequency of foreign matter mixing and the type of foreign matter, the production line needs to be stopped for inspection. Here, in order to obtain information related to the state of the processing machine, such as the operating status of the processing equipment, the abnormality of the processing equipment, the identification of the abnormal part of the processing equipment, or the identification of the processing machine that has an abnormality when the processing equipment is composed of multiple processing machines, it is necessary to set up multiple detection units such as sensors and camera devices.

[0008] However, when multiple detection units are provided for processing equipment, the cost increases, the management becomes complicated, and the burden on the operators of the processing equipment increases. Therefore, the inventors considered that if the information related to the state of the processing machine can be obtained by using the foreign matter detector already provided for the processing equipment, it is not necessary to provide multiple detection units, thereby solving these problems. Patent Document 1 does not mention this at all.

[0009] An object of one aspect of the present disclosure is to acquire information on the state of a processing machine.

[0010] Solutions for solving problems

[0011] In order to solve the above-mentioned problem, a management system involved in one embodiment of the present disclosure is a management system for managing processing equipment. The management system includes a foreign matter detector and a processor. The foreign matter detector detects whether foreign matter is mixed into a product produced by a processing machine in the processing equipment. The processor processes information related to the foreign matter detected by the foreign matter detector. Moreover, the processor obtains information related to the foreign matter from the foreign matter detector, and obtains information related to the state of the processing machine based on the information related to the foreign matter.

[0012] In order to solve the above-mentioned problems, a management method according to one embodiment of the present disclosure is a management method for managing processing equipment. The management method includes the following two steps.

[0013] (1) Step of acquiring information about foreign matter In this step, information about foreign matter is acquired from a foreign matter detector for detecting whether foreign matter is mixed into a product produced by a processing machine in a processing facility.

[0014] (2) A step of acquiring information on the state of a processing machine. In this step, information on the state of a processing machine is acquired based on information on foreign matter.

[0015] Effects of the Invention

[0016] According to one aspect of the present disclosure, it is possible to acquire information on the state of a processing machine. BRIEF DESCRIPTION OF THE DRAWINGS

[0017] Figure 1 This is a schematic configuration diagram of a management system according to Embodiment 1 of the present disclosure.

[0018] Figure 2 This is a block diagram showing the hardware configuration of the management device according to Embodiment 1 of the present disclosure.

[0019] Figure 3 This is a diagram for explaining an example of a parts database.

[0020] Figure 4 This is a functional block diagram of a processor of the management device according to Embodiment 1 of the present disclosure.

[0021] Figure 5 This is a flowchart for explaining an operation example of the management device according to Embodiment 1 of the present disclosure.

[0022] Figure 6 This is a block diagram showing a hardware configuration according to a modification of the first embodiment of the present disclosure.

[0023] Figure 7 This is a graph showing the relationship between X-ray fluoroscopic image data and magnetic variation data.

[0024] Figure 8 This is a flowchart for explaining an operation example of the management device according to the modification example of the first embodiment of the present disclosure.

[0025] Fig. 9 This is a functional block diagram of a processor of a management device according to Embodiment 2 of the present disclosure.

[0026] Fig.10 It is a time series graph showing the relationship between the inspection data and time.

[0027] Fig.11 This is a flowchart for explaining an operation example of the management device according to Embodiment 2 of the present disclosure.

[0028] Fig.12 The figure shows a product to which a two-dimensional code is given. DETAILED DESCRIPTION

[0029] [Implementation Method 1]

[0030] Hereinafter, the management system 100 according to the first embodiment of the present disclosure will be described in detail with reference to the drawings. In the description of the drawings, the same reference numerals are attached to the same parts, and the description thereof will be omitted.

[0031] (Configuration Example of Management System 100)

[0032] Figure 1 1 is a schematic diagram showing an example of the management system 100. Figure 1 As shown, the management system 100 includes a metal detector 10 and a management device 40 .

[0033] The place where the metal detector 10 and the management device 40 are installed is not particularly limited, but for example, the metal detector 10 and the management device 40 are installed in a food processing facility for processing food. In the following, the case where the metal detector 10 and the management device 40 are installed in a food processing facility is used as an example for explanation, but the metal detector 10 and the management device 40 may also be installed in a facility for processing or manufacturing beverages, medicines, cosmetics, daily necessities, clothing, etc.

[0034] The metal detector 10 is a device for checking whether a metal foreign body 30 is mixed into a product 20 produced by a food processing device. The metal detector 10 detects a metal foreign body 30 mixed into the inside of the product 20 which is difficult to visually confirm from the outside. In the present embodiment, as an example of a detection method for the metal foreign body 30, a so-called magnetic bias type magnetic line of force method is adopted. If the "magnetic bias type magnetic line of force method" is explained, in the metal detector 10, a magnet (not shown) is arranged in a manner of clamping the production line in the upper and lower directions. When the metal foreign body 30 passes between the magnets, the magnetic lines of force emitted from the magnets change. In the magnetic bias type magnetic line of force method, the metal foreign body 30 is detected based on the change of the magnetic lines of force. In addition, the metal foreign body 30 can be a foreign body composed only of metal elements, or a foreign body composed of metal elements and non-metal elements. In addition, the metal element can be either a single element or a plurality of elements (so-called alloys).

[0035] The magnetic bias magnetic field line method achieves high-precision detection of metal foreign matter not only in products packaged in paper, polyvinyl chloride, and plastic, but also in products such as canned foods with aluminum vapor-deposited on the packaging, and liquid foods with high salt concentrations such as curry paste and soy sauce, compared to the previous so-called detection coil method.

[0036] As the metal foreign matter 30 that may be mixed into the product 20, there can be cited parts of processing machinery. As an example of parts of processing machinery, there can be cited metal bolts, nuts, screws, resin cable ties mixed with magnetic powder, etc. Generally speaking, food processing consists of a large number of processes, and a dedicated processing machine is used in each process.

[0037] Examples of the types of processing machines include cutting machines for slicing or cutting materials, stirring machines for stirring materials, filling machines for filling beverages into filling bags, and packaging machines for packaging processed products.

[0038] Examples of the product 20 as the inspection object include food and beverage filled in a package, a container, and the like.

[0039] During the operation of food processing equipment, bolts, nuts, screws, etc. may fall off from the processing machinery due to rust, loose assembly, metal fatigue, etc. If the metal thus fallen off is mixed into the product 20, it will be detected by the metal detector 10 as a metallic foreign body 30.

[0040] When the metal foreign matter 30 is detected by the metal detector 10 , the following processing can be considered as a general processing thereafter, for example.

[0041] First, an operator working on a food processing facility is notified of the detection of a metal foreign body 30. The operator who receives the notification removes the product 20 mixed with the metal foreign body 30 from the production line and stops all processing machines. Thereafter, the operator starts inspection of all processing machines.

[0042] Here, if it is possible to know from which processing machine the metal foreign matter 30 mixed in the product 20 has fallen off before starting the inspection of the processing machine, the time and cost required for the inspection of the processing machine can be greatly reduced, and the burden on the operator can be reduced. The operator only needs to inspect and repair the processing machine that is the target, and then the processing machine can be operated again, so that production activities can be safely resumed.

[0043] Therefore, in this embodiment, the following structure is set: infer and determine from which processing machine the metal foreign matter 30 mixed in the product 20 fell off, and notify the operator of the result. As a result, as described above, the time and cost required for the inspection of the processing machine can be greatly reduced, and the burden on the operator is reduced. Below, an example of the determination method and the notification method are described in turn. In addition, in the following, "infer and determine" is sometimes referred to as "determine".

[0044] When the metal detector 10 inspects the product 20 flowing on the production line, regardless of whether the metal foreign body 30 is detected, the data related to the inspection is converted into an electrical signal and sent to the management device 40 using a prescribed communication method. In the case of detecting a metal foreign body 30, the metal detector 10 converts the data related to the foreign body detection, such as the change of the magnetic line of force, into an electrical signal and sends it to the management device 40. An example of "data related to foreign body detection, such as the change of the magnetic line of force" is the following voltage waveform: the voltage waveform is formed by the voltage amplitude and time width of the electrical signal that changes relative to the magnetic field that changes due to the metal foreign body 30. Communication can be performed in any wired or wireless manner, and the communication method can be any as long as mutual communication can be performed. In this embodiment, it is assumed that Wi-Fi (registered trademark) is used to communicate between the metal detector 10 and the management device 40 for explanation.

[0045] (Hardware Configuration of Management Device 40)

[0046] Next, refer to Figure 2 The hardware structure of the management device 40 will be described. Figure 2 2 is a block diagram showing the hardware configuration of the management device 40. The management device 40 is, for example, a general-purpose computer.

[0047] like Figure 2As shown, the management device 40 includes a processor 41, a ROM (Read Only Memory) 42, a RAM (Random Access Memory) 43, a storage device 44, a communication I / F (interface) 46, and a display 47. Each component is connected via a bus 45 so as to be able to communicate with each other.

[0048] The processor 41 is a computing unit that executes various programs, and is, for example, a CPU (Central Processing Unit). The processor 41 reads programs from the ROM 42 or the storage device 44 and executes various programs using the RAM 43 as a work area.

[0049] ROM 42 stores various programs and various data. RAM 43 temporarily stores programs or data as a work area. In addition, the computer-readable recording medium is not limited to ROM 42 and RAM 43, and may also include EPROM (Erasable Programmable ROM: Erasable Programmable Read-Only Memory), EEPROM (registered trademark) (Electrically Erasable Programmable ROM: Electrically Erasable Programmable Read-Only Memory), etc.

[0050] The storage device 44 is composed of a HDD (Hard Disk Drive), an SSD (Solid State Drive), or a flash memory, and is used to store various programs and various data. A component database 441 is stored in the storage device 44. The component database 441 refers to a database that stores information on components constituting a processing machine installed in a food processing facility. Examples of "components constituting a processing machine" include metal components (bolts, nuts, screws, etc.), non-metallic components containing metal (resin cable ties mixed with magnetic powder, etc.), and the like.

[0051] Here, refer to Figure 3 An example of the parts database 441 is described below. Figure 3As shown, the name of each component, the shape of each component, and the processing machine on which each component is installed are stored in the component database 441. For example, a bolt B1, a nut N1, and a screw S1 are installed in a mixing machine. A bolt B2, a nut N2, and a screw S2 are installed in a filling machine. A bolt B3, a nut N3, and a screw S3 are installed in a packaging machine. The shape of each component is, for example, data showing the size in accordance with the JIS standard, represented by φ (diameter), length, pitch, etc. In addition, the outer shapes of the bolts B1 to B3, nuts N1 to N3, and screws S1 to S3 may also be stored in the component database 441. In the present embodiment, the "shape of the component" refers to both the "size of the component" and the "outer shape of the component".

[0052] return Figure 2 The display 47 is composed of a liquid crystal display or an organic EL display, etc., and is used to display various information.

[0053] The communication I / F 46 is implemented as hardware such as a network adapter, communication software, or a combination thereof, and is used to communicate with the metal detector 10 .

[0054] (Function of the Processor 41 of the Management Device 40)

[0055] Next, refer to Figure 4 The function of the processor 41 of the management device 40 will be described. Figure 4 FIG. 4 is a functional block diagram of the processor 41 of the management device 40. Figure 4 As shown, in the management device 40 of the present embodiment, the processor 41 functions as an inspection data acquisition unit 411, a processing machine data acquisition unit 412, and an output unit 413 by executing a specific program.

[0056] The inspection data acquisition unit 411 acquires data related to the inspection from the metal detector 10 via the communication I / F 46, and stores the acquired data in the storage device 44. The processing machine data acquisition unit 412 acquires information related to the state of the processing machine based on the data acquired by the inspection data acquisition unit 411. As an example of the information related to the state of the processing machine, there is information that determines from which processing machine the metal foreign body 30 has fallen off. In other words, the processing machine data acquisition unit 412 has the following function: based on the data acquired by the inspection data acquisition unit 411, it determines from which processing machine the metal foreign body 30 has fallen off. The output unit 413 displays the information related to the processing machine acquired by the processing machine data acquisition unit 412 on the display 47 to notify the operator of the food processing equipment.

[0057] Next, refer to Figure 5 An operation example of the management device 40 is described with reference to the flowchart of FIG. Figure 5 The processing shown is repeatedly executed in a predetermined cycle.

[0058] In step S101, the processor 41 of the management device 40 acquires data related to inspection from the metal detector 10 via the communication I / F 46. The data related to inspection includes, for example, data indicating that the metallic foreign matter 30 has been detected and data related to foreign matter detection.

[0059] If the data acquired in the process of step S101 includes data indicating that the metal foreign matter 30 is detected (step S102: "Yes"), the process proceeds to step S103. On the other hand, if the data acquired in the process of step S101 does not include data indicating that the metal foreign matter 30 is detected (step S102: "No"), the series of processes ends.

[0060] In step S103, the processor 41 of the management device 40 infers the shape of the metal foreign body 30 based on the data related to the foreign body detection obtained in the process of step S101. For example, as described above, in the case where the data related to the foreign body detection is a voltage waveform formed by the voltage amplitude and time width of the electric signal that changes relative to the magnetic field that changes due to the metal foreign body 30, the processor 41 of the management device 40 can infer the shape of the metal foreign body 30 based on the data. The processor 41 of the management device 40 compares the inferred data related to the shape of the metal foreign body 30 with the data stored in the component database 441 to infer a component that is consistent or substantially consistent with the detected metal foreign body 30. Here, for example, it is assumed that the shape of the metal foreign body 30 obtained in the process of step S101 is consistent with Figure 3 The shapes of the bolts B3 shown in FIG. 4 are consistent or substantially consistent. In this case, the processor 41 of the management device 40 can determine that the metal foreign matter 30 mixed in the product 20 is the bolt B3 (step S104). In addition, the processor 41 of the management device 40 can grasp that the processing machine on which the bolt B3 is installed is a packaging machine by referring to the parts database 441. Therefore, in the processing of step S104, the processor 41 of the management device 40 can determine that the metal foreign matter 30 mixed in the product 20 is the bolt B3, and that the bolt B3 has fallen off from the packaging machine.

[0061] The process proceeds to step S105, and the processor 41 of the management device 40 displays the result determined in step S104 on the display 47 to notify the operator. For example, the display 47 displays "It is highly likely that the detected metal foreign matter is the bolt B3 that fell off from the packaging machine." The operator who checks the display 47 can know from which processing machine the metal foreign matter 30 mixed in the product 20 fell off.

[0062] In addition, Figure 5 The processing flow described in the description is an example, and steps may be deleted, new steps may be added, or the order of steps may be exchanged without departing from the scope of the subject matter.

[0063] (Variation Example)

[0064] Next, refer to Figure 6 To illustrate a variation of implementation mode 1. In the variation, Figure 6 As shown, the management device 40 obtains data related to the inspection from two metal detectors 10 and 11. The metal detector 10 is the same as that in the first embodiment. The metal detector 11 is a machine for detecting metal foreign matter 30 by X-ray method. The X-ray method is a method of irradiating X-rays, which are a type of electromagnetic waves, to the product 20 and detecting the metal foreign matter 30 based on the difference in the amount of transmission. The amount of transmission depends on the thickness and density. The thicker the thickness and the greater the density, the more the X-rays are blocked. The density of metal is high, and the color is photographed darker than the inspected product, so it can be detected as a foreign matter.

[0065] In the modified example, both the magnetic bias magnetic flux method and the X-ray method are used as detection methods for the metal foreign matter 30. By using these two methods simultaneously, the shape of the metal foreign matter 30 can be estimated with higher accuracy compared to the case where only the magnetic bias magnetic flux method is used.

[0066] (An example of a method for estimating foreign matter)

[0067] An example of a method for estimating what kind of foreign matter detected by a magnetic bias type magnetic field line method and an X-ray method is. In a modified example, a threshold value for estimating what kind of foreign matter is and the type of foreign matter is set based on X-ray fluoroscopic image data and magnetic variation data obtained by experiments, simulations, etc. using foreign matter samples.

[0068] Reference Figure 7 To illustrate the threshold. Figure 7 This is a graph showing the relationship between X-ray fluoroscopic image data and magnetic variation data. Figure 7 The vertical axis represents the X-ray fluoroscopic image data obtained by the X-ray method, and the horizontal axis represents the magnetic variation data obtained by the magnetic bias type magnetic field line method. Figure 7 In the embodiment, foreign matter includes not only metal foreign matter but also resin foreign matter. That is, in the present embodiment, foreign matter to be detected is not limited to metal foreign matter but may also include resin foreign matter.

[0069] As an example, X-ray fluoroscopic image data includes X-ray transmission amount, transmission sample area, etc. As an example, magnetic variation data includes the amplitude of voltage waveform, time integral of voltage, voltage variation per unit time, etc. Based on X-ray fluoroscopic image data and magnetic variation data obtained in advance through experiments, simulations, etc. using foreign body samples, the Mahalanobis distance is set using the so-called MT method (Maharanobis Taguchi). In a modified example, as an example, the Mahalanobis distance is used as a threshold value for estimating what kind of foreign body the foreign body is and the type of foreign body. By the MT method, as Figure 7 As shown in FIG. 1 , threshold values ​​A to D indicated by circles are set. Hereinafter, the threshold values ​​A to D are referred to as "threshold value circles A to D" unless otherwise specified.

[0070] The type of foreign matter is estimated based on whether the data detected by the magnetic bias type magnetic line of force method and the X-ray method exists within the threshold circles A to D and within which circle. Specifically, when the data related to the inspection exists within the threshold circle A, it is estimated that the foreign matter is an organic foreign matter such as resin. In addition, when the data related to the inspection exists within the threshold circle B, it is estimated that the foreign matter is a metal foreign matter such as bolts, nuts, and screws. In addition, when the data related to the inspection exists within the threshold circle C, it is estimated that the foreign matter is a metal foreign matter such as metal wire and metal wire cuttings. In addition, when the data related to the inspection exists within the threshold circle D, it is estimated that no foreign matter is detected. In addition, it is also possible that when the data related to the inspection exists in a position away from these threshold circles A to D, the processor 41 of the management device 40 determines that a sudden abnormality has occurred in the food processing equipment and displays this on the display 47.

[0071] Next, refer to Figure 8 An operation example of the management device 40 in the modified example is described with reference to the flowchart of FIG. Figure 8 The processing shown is repeated in a predetermined cycle. Figure 7 Threshold circles A to D described in .

[0072] In step S201 , the processor 41 of the management device 40 acquires data related to inspection from the metal detectors 10 and 11 via the communication I / F 46 .

[0073] In step S202, the processor 41 of the management device 40 calculates whether the data acquired in the process of step S201 exists in Figure 7 Where on the chart of .

[0074] When the data acquired in the processing of step S201 exists at a position far from the threshold circles A to D (step S203: Yes), the processor 41 of the management device 40 determines that a sudden abnormality has occurred in the food processing equipment and displays this fact on the display 47 to notify the operator (step S215).

[0075] If the result of step S203 is "No", the process proceeds to step S204. If the data acquired in the process of step S201 is within the threshold circle A (step S204: "Yes"), the process proceeds to step S205, and the processor 41 of the management device 40 estimates that the foreign matter mixed in the product 20 is an organic foreign matter such as resin.

[0076] The process proceeds to step S206 , and the processor 41 of the management device 40 compares the data related to the shape of the foreign matter with the data stored in the parts database 441 .

[0077] The process proceeds to step S207 , and the processor 41 of the management device 40 infers and specifies from which processing machine the foreign matter mixed in the product 20 has fallen off based on the comparison result of step S206 .

[0078] The process proceeds to step S215, and the processor 41 of the management device 40 displays the result determined in step S207 on the display 47 to notify the operator.

[0079] If the data acquired in the process of step S201 does not exist within the threshold circle A (step S204: No), the process proceeds to step S208. If the data acquired in the process of step S201 exists within the threshold circle B (step S208: Yes), the process proceeds to step S209, and the processor 41 of the management device 40 estimates that the foreign matter mixed in the product 20 is a metal foreign matter 30 such as a bolt, nut, or screw.

[0080] The process proceeds to step S210 , and the processor 41 of the management device 40 compares the data related to the shape of the metallic foreign matter 30 with the data stored in the parts database 441 .

[0081] The process proceeds to step S211 , and the processor 41 of the management device 40 infers and specifies from which processing machine the metallic foreign matter 30 mixed in the product 20 has fallen off based on the comparison result of step S210 .

[0082] The process proceeds to step S215, and the processor 41 of the management device 40 displays the result determined in step S211 on the display 47 to notify the operator.

[0083] If the data acquired in the process of step S201 does not exist within the threshold circle B (step S208: No), the process proceeds to step S212. If the data acquired in the process of step S201 exists within the threshold circle C (step S212: Yes), the process proceeds to step S213, and the processor 41 of the management device 40 estimates that the foreign matter mixed in the product 20 is a metal foreign matter such as a metal wire, metal wire shavings, or fine metal powder.

[0084] The process proceeds to step S214, and processor 41 of management device 40 performs prediction processing based on the estimation result of step S213. The details of this prediction processing will be described in Embodiment 2 described later.

[0085] When the data acquired in the processing of step S201 does not exist within the threshold circle C (step S212: "No"), that is, when the data acquired in the processing of step S201 exists within the threshold circle D, the processor 41 of the management device 40 estimates that no foreign matter is detected and ends a series of processing.

[0086] In addition, Figure 8 The processing flow described in the description is an example, and steps may be deleted, new steps may be added, or the processing order may be exchanged without departing from the scope of the subject matter.

[0087] (Effect)

[0088] As described above, according to the first embodiment, the following effects can be obtained.

[0089] The management system 100 is a system for managing processing equipment, and comprises: a foreign matter detector for detecting whether foreign matter is mixed into the product 20 produced by the processing machinery in the processing equipment; and a processor 41 of the management device 40, which can process information related to foreign matter detected by the foreign matter detector.

[0090] The processor 41 of the management device 40 obtains information about foreign matter from the foreign matter detector, and obtains information about the state of the processing machine based on the information about the foreign matter. The "foreign matter" mentioned here includes at least metal foreign matter 30 and resin foreign matter. An example of a foreign matter detector is a metal detector 10, 11.

[0091] As described above, in order to obtain information related to the status of the processing machine, such as the identification of the processing machine that has an abnormality, when the processing equipment is composed of multiple processing machines, it is necessary to set up multiple detection units such as sensors and cameras, but there are problems such as increased costs and increased burdens on operators. The inventors considered obtaining information related to the status of the processing machine by using a foreign body detector that has been set up for the processing equipment. According to the above structure, it is possible to obtain information related to the status of the processing machine without setting up multiple detection units, which can help reduce costs and reduce the burden on operators.

[0092] The information on the state of the processing machine may also be identification information for identifying the processing machine to be the target from among a plurality of processing machines. The "target processing machine" referred to here refers to the processing machine from which the foreign matter has fallen off. In addition, the foreign matter may also be a metal foreign matter 30.

[0093] When it is detected that the metal foreign matter 30 is mixed in the product 20, the operator stops all the processing machines and starts the inspection of all the processing machines. The inspection here refers to the operation of finding which processing machine the metal foreign matter 30 has fallen off from. It is conceivable that the inspection is performed by experienced operators who are familiar with food processing equipment. However, under the current situation of insufficient manpower on site and high daily production pressure, even if the product 20 mixed with the metal foreign matter 30 can be prevented from flowing into the market, the response to the cause of the mixing itself may be delayed.

[0094] According to the above structure, the processor 41 of the management device 40 can determine from which processing machine the metal foreign matter 30 mixed in the product 20 fell off. The processor 41 of the management device 40 can also display the determined result on the display 47 to notify the operator. The operator who has confirmed the display 47 can know from which processing machine the metal foreign matter 30 mixed in the product 20 fell off. Thus, even an operator who has no knowledge of processing machinery can immediately determine the processing machinery that is the cause of the mixing. Thus, the time and cost required for the inspection of the processing machinery can be greatly reduced, and the burden on the operator is reduced. The operator can make the processing machinery run again as long as he only inspects and repairs the processing machinery that is the target, so that production activities can be resumed in advance and safely.

[0095] In addition, the foreign body detector may also be a device that uses magnetic lines of force to detect foreign bodies. The processor 41 of the management device 40 may also infer the shape of the foreign body based on the information related to the foreign body, and compare the shape of the foreign body with the pre-stored component data to determine the processing machine that is the target from multiple processing machines.

[0096] According to the above configuration, a processing machine from which foreign matter has fallen off can be identified from among a large number of processing machines.

[0097] In addition, as a method for detecting metal foreign matter 30, by using a magnetic bias type magnetic force line method, it is possible to detect not only metal foreign matter 30 in paper, polyvinyl chloride, and plastic packaging, but also metal foreign matter 30 in aluminum packaging. According to the magnetic bias type magnetic force line method, it is also possible to check packaging abnormalities such as the welding status of the packaging based on the strength of the eddy current generated on the surface of conductive packaging materials such as aluminum packaging. In this way, in addition to determining the processing machinery to be targeted, it is also possible to detect abnormalities in the packaging machinery based on the abnormality detection results of the conductive packaging material.

[0098] In addition, the metal detector 10 may be a first metal detector that detects foreign matter using magnetic lines of force, and the management system 100 may also include a second metal detector that detects foreign matter using X-rays. The processor 41 of the management device 40 may also obtain information related to foreign matter from the first metal detector and the second metal detector, infer the shape of the foreign matter based on the information related to the foreign matter, and compare the shape of the foreign matter with the pre-stored component data to determine the processing machine that is the target from a plurality of processing machines. In addition, the second metal detector may correspond to the metal detector 11.

[0099] According to the above structure, the processor 41 of the management device 40 uses the information detected by the magnetic bias type magnetic field line method and the X-ray method to estimate the shape of the foreign matter. By using these two methods at the same time, the estimation accuracy of the foreign matter shape is improved compared with the case of using only one method. The processor 41 of the management device 40 compares the estimated shape of the foreign matter with the part information of the processing machine stored in the part database 441 in advance to determine which processing machine the foreign matter mixed in the product 20 fell off from. Since the estimation accuracy of the foreign matter shape is improved, the determination accuracy of the processing machine is also improved.

[0100] [Implementation Method 2]

[0101] Next, refer to Figures 9 to 11 Embodiment 2 of the present disclosure will be described. In addition, for the sake of convenience of description, the same reference numerals are given to components having the same functions as those described in Embodiment 1, and description thereof will not be repeated.

[0102] Fig. 9 This is a functional block diagram of the processor 41 of the management device 40 according to Embodiment 2. Different from Embodiment 1, in the management device 40 according to Embodiment 2, the processor 41 also functions as a prediction unit 414 by executing a specific program.

[0103] The prediction unit 414 predicts the replacement period of metal blades installed in the processing machinery based on the inspection data obtained by the X-ray method or the magnetic bias type magnetic line method. The blades used for kneading and stirring food are worn due to friction between the blades and the metal container into which the materials are put, the blades themselves deteriorate over time, etc. Sometimes fine metal powder or powder generated by this wear is mixed into the product 20. The longer the blade is used, the more powder is generated by wear, and the time comes when replacement is required. The prediction unit 414 predicts such a replacement period. Refer to Fig.10 An example of a method for predicting the replacement period of blades is described below. As an example, the powder is set to be a fine metal powder of a predetermined size or less. The predetermined size is calculated, for example, by experiments, simulations, etc. In addition, the powder may also be a fine resin powder of a predetermined size or less.

[0104] (An example of a method for predicting replacement time)

[0105] Fig.10 This is a time series graph showing the relationship between inspection data obtained by the X-ray method or the magnetic bias type magnetic field line method and time. Fig.10 The vertical axis represents the inspection data obtained by the X-ray method or the magnetic bias type magnetic line of force method, and the horizontal axis represents time. When the vertical axis is set to the inspection data obtained by the X-ray method, an example of the inspection data is X-ray fluoroscopic image data. When the vertical axis is set to the inspection data obtained by the magnetic bias type magnetic line of force method, an example of the inspection data is magnetic variation data.

[0106] like Fig.10 As shown in Figure 2, as the blades are used for a certain period of time, the inspection data will change. Fig.10 It can be seen that the inspection data is on an increasing trend. The cause of this change is that the amount of fine metal powder generated by the wear of the blades due to the friction between the blades and the container and the degradation of the blades over the years has increased. The processor 41 of the management device 40 can predict the time T when the inspection data reaches the threshold 70 representing an abnormal value as the time to replace the blades by approximating the marked inspection data with a straight line 71 using, for example, a univariate regression analysis. In addition, for the calculation of the straight line 71, for example, the least squares method can also be used. In addition, the analysis method of the inspection data is not limited to a univariate regression analysis, but can also be a multivariate regression analysis or machine learning.

[0107] Reference Fig.11 Here, as described in the variation of the first embodiment, Fig.11 The flowchart corresponds to Figure 8 Processing of step S214.

[0108] In step S301, the processor 41 of the management device 40 determines whether the inspection data obtained by the X-ray method or the magnetic bias type magnetic field line method is in an increasing trend. If the inspection data is in an increasing trend (step S301: "Yes"), the process proceeds to step S302, and the processor 41 of the management device 40 predicts the replacement period of the blade using, for example, the above-mentioned univariate regression analysis, and displays the prediction result on the display 47 to notify the operator.

[0109] Furthermore, although the blade is described as an example of a metal component that is a target of replacement timing prediction, the present invention is not limited to this, and any metal component that is subject to wear can be a target of replacement timing prediction.

[0110] In addition, as the object of prediction, the replacement period of the blade is predicted, but it is not limited to this. For example, the object of prediction may also be the inspection period of the blade. In other words, the object of prediction may also be the maintenance period of the blade including replacement and inspection.

[0111] (Effect)

[0112] As described above, according to the second embodiment, the following effects can be obtained.

[0113] The processor 41 of the management device 40 may also obtain information related to foreign matter from the foreign matter detector, and predict the maintenance period of the processing machine based on the information related to the foreign matter. In other words, the information related to the state of the processing machine may also be the prediction information for predicting the maintenance period of the processing machine. In addition, the "maintenance period of the processing machine" may also be expressed in another way as "the maintenance period of the components constituting the processing machine".

[0114] An example of a component is the metal blade used in kneading and stirring the food mentioned above. Such blades wear due to friction with the metal container into which the food is put and due to the degradation of the blades themselves over the years. Regarding the confirmation of the degree of wear, there are many cases where it is done by the operator's visual inspection. Therefore, problems such as ensuring that operators engaged in maintenance work and ensuring a certain inventory can be cited. According to the above structure, by predicting the maintenance period of the blades and notifying the operator of the prediction result, the burden of the operator's confirmation work can be reduced, or management can be performed in a manner that limits the number of blade inventory.

[0115] The information on the foreign matter may be information indicating that the foreign matter is powder having a size smaller than or equal to a predetermined size. The processor 41 of the management device 40 may predict a maintenance period for the processing machine based on the detected amount of powder that increases with time.

[0116] According to the above configuration, when it is determined that powder mixing occurs continuously, the processor 41 of the management device 40 can predict the maintenance period of the component of the processing machine that is the cause, and notify the operator of the prediction result. Thus, the operator can replace the component at an appropriate time or manage the inventory of the component in a manner that limits the number of components.

[0117] [Implementation method 3]

[0118] Next, refer to Fig.12 , Embodiment 3 of the present disclosure will be described below. In addition, for the sake of convenience of description, the same reference numerals are given to components having the same functions as those described in Embodiment 1, and their description will not be repeated.

[0119] like Fig.12 As shown, a two-dimensional code 80 may be given to the package of the product 20. The two-dimensional code 80 stores predetermined information. An example of the predetermined information is information indicating the date, time and location of the foreign matter inspection process performed by the foreign matter detector, information indicating the foreign matter inspection result, and information indicating the business operator who inspected the product 20.

[0120] By assigning the two-dimensional code 80 to the product 20 , the consumer can understand when and where the product 20 was inspected by which service provider and what the inspection result was.

[0121] The mixing of foreign matter is not only caused by the breakage or detachment of parts of processing machinery, but also by intentional mixing by consumers when the product 20 is put on the market such as retail. Therefore, it is sometimes not enough to collect and manage foreign matter inspection data only on the producer side. By assigning foreign matter inspection data to each product with a two-dimensional code 80, the foreign matter inspection result can be confirmed immediately when foreign matter is mixed in the market, so that the safety of food during production can be confirmed.

[0122] In addition, the type of the two-dimensional code 80 is not particularly limited, and for example, a QR code (registered trademark) may be used. Thus, consumers can easily obtain information using a smartphone or the like.

[0123] In the above-mentioned Embodiments 1 and 2, it is described that the processor 41 of the management device 40 determines the processing machine to be the target based on the information related to the metal foreign matter 30, or predicts the maintenance period of the component based on the information related to the metal foreign matter 30. These structures can also be expressed in another way as follows. That is, in other words, the processor 41 of the management device 40 estimates the state of the processing machine based on the information related to the metal foreign matter 30.

[0124] “Estimating the state of a processing machine” includes “determining a processing machine to be targeted” and “predicting a maintenance period for a component installed in the processing machine.” This will be described below.

[0125] Regarding "determining the processing machine to be the target", an example of determination based on the information of the metal foreign matter 30 is described in the above-mentioned embodiment 1. While performing this determination processing, it is possible to determine the state of the processing machine based on, for example, the information of the metal foreign matter 30 in the background processing of the processor 41 of the management device 40. A specific example of the state of the processing machine is whether it is normal or abnormal. That is, in the background processing of the processor 41 of the management device 40, for example, determination processing such as "mixing machine: normal", "filling machine: normal", "packaging machine: abnormal" can be performed. Here, as described above, the packaging machine is determined to be abnormal because it is determined that the bolt B3 has fallen off from the packaging machine.

[0126] In this way, "determining the processing machine from which the metal foreign matter 30 has fallen, that is, determining that the metal foreign matter 30 has fallen from the packaging machine" can be said to be "estimating the state of the processing machine, that is, estimating that the packaging machine is in an abnormal state."

[0127] Next, regarding "predicting the maintenance period of a component installed in a processing machine", an example of prediction based on the information of the metal foreign matter 30 is described in the above-mentioned embodiment 2. When it comes to predicting the maintenance period of a component, in other words, it is to predict to what extent the deterioration of the component has progressed, or to what extent the deterioration will progress in the future if it continues to be used as usual. In addition, a component is "a part of the processing machine", so "predicting the maintenance period of the component" can also be said to be "predicting the state of the processing machine".

[0128] [Software-based implementation example]

[0129] The function as the management device 40 can be realized by a program for causing a computer to function as the management device 40 , that is, a program for causing a computer to function as each control module of the management device 40 .

[0130] In this case, the management device 40 includes a computer as hardware for executing the program, and the computer has at least one device (eg, a processor) and at least one storage device (eg, a memory). The functions described in each embodiment are realized by executing the program by the computer.

[0131] The program may be recorded in one or more non-transitory computer-readable recording media. The recording media may or may not be provided by the management device 40. In the latter case, the program may be supplied to the management device 40 via any wired or wireless transmission medium.

[0132] In addition, part or all of the functions of each control module can also be implemented by a logic circuit. For example, an integrated circuit having a logic circuit that functions as each control module is also included in the scope of the present disclosure. In addition, for example, the functions of each control module can also be implemented by a quantum computer.

[0133] In addition, each process described in each embodiment may be executed by AI (Artificial Intelligence). In this case, AI may be operated by the management device 40 or by another device (for example, an edge computer or a cloud server).

[0134] The present disclosure is not limited to the above-described embodiments, and various modifications can be made within the scope of the claims. Embodiments obtained by appropriately combining technical means disclosed in different embodiments are also included in the technical scope of the present disclosure.

[0135] [Additional Notes]

[0136] In addition, the present disclosure can also be expressed as follows.

[0137] The management system involved in method 1 of the present disclosure is used to manage processing equipment, and its structure is as follows: a foreign matter detector, which detects whether foreign matter is mixed in the product produced by the processing machinery in the processing equipment; and a processor, which can process information related to the foreign matter detected by the foreign matter detector, wherein the processor obtains the information related to the foreign matter from the foreign matter detector, and obtains information related to the status of the processing machinery based on the information related to the foreign matter.

[0138] Regarding the management system according to the second aspect of the present disclosure, in the first aspect, the information on the state of the processing machine may be identification information for identifying a target processing machine from among a plurality of processing machines.

[0139] Regarding the management system according to the third aspect of the present disclosure, in the first aspect, the information on the state of the processing machine may be prediction information for predicting a maintenance period of the processing machine.

[0140] Regarding the management system involved in Mode 4 of the present disclosure, in the above-mentioned Mode 2, it can also be set to the following structure, wherein the foreign object detector is a device that uses magnetic lines to detect the foreign object, and the processor infers the shape of the foreign object based on information related to the foreign object, and compares the shape of the foreign object with pre-stored data of the components constituting the processing machine to determine the processing machine that is the target from the multiple processing machines.

[0141] Regarding the management system involved in mode 5 of the present disclosure, in the above-mentioned mode 2 or 4, it can also be set to the following structure, wherein the foreign object detector is a first foreign object detector that uses magnetic lines to detect the foreign object, and also has a second foreign object detector, and the second foreign object detector uses X-rays to detect the foreign object, and the processor obtains information related to the foreign object from the first foreign object detector and the second foreign object detector, infers the shape of the foreign object based on the information related to the foreign object, and compares the shape of the foreign object with pre-stored data of the components constituting the processing machine to determine the processing machine to be the object from the multiple processing machines.

[0142] Regarding the management system involved in mode 6 of the present disclosure, in the above-mentioned mode 3, it can also be set to the following structure, wherein the information related to the foreign matter is information indicating that the foreign matter is a powder with a size smaller than a specified size, and the processor predicts the maintenance period of the processing machine based on the detection amount of the powder that increases with the passage of time.

[0143] Regarding the management system according to the seventh aspect of the present disclosure, in any of the first to sixth aspects described above, the processor may perform processing for displaying the acquired information on the state of the processing machine on a display.

[0144] Regarding the management system involved in mode 8 of the present disclosure, in any of the above-mentioned modes 1 to 7, it can also be set to the following structure, wherein a QR code is assigned to the packaging body of the product that is the detection object of the foreign object detector, and the QR code stores information indicating the date, time and place where the foreign object inspection process was performed by the foreign object detector, information indicating the foreign object inspection result, and information indicating the business provider who performed the inspection of the product.

[0145] Regarding the management system according to the ninth aspect of the present disclosure, in any one of the first to eighth aspects described above, the foreign matter may be a metal foreign matter.

[0146] The management method involved in method 10 of the present disclosure is used to manage processing equipment, and includes the following steps: obtaining information related to foreign matter from a foreign matter detector, wherein the foreign matter detector is used to detect whether the foreign matter is mixed into the product produced by the processing machinery in the processing equipment; and obtaining information related to the status of the processing machinery based on the information related to the foreign matter.

Claims

1. A management system for managing processing equipment, having: a foreign matter detector for detecting whether foreign matter is mixed into a product produced by a processing machine in the processing equipment; and a processor capable of processing information related to the foreign matter detected by the foreign matter detector, in, The processor obtains information related to the foreign matter from the foreign matter detector, The processor acquires information about a state of the processing machine based on the information about the foreign matter.

2. The management system according to claim 1, wherein: The information on the state of the processing machine is identification information for identifying a target processing machine from among a plurality of processing machines.

3. The management system according to claim 1, wherein: The information on the state of the processing machine is prediction information for predicting a maintenance period of the processing machine.

4. The management system according to claim 2, wherein: The foreign body detector is a device that uses magnetic lines to detect the foreign body. the processor infers a shape of the foreign object based on information related to the foreign object, The processor compares the shape of the foreign matter with pre-stored data of components constituting the processing machine to identify a target processing machine from among the plurality of processing machines.

5. The management system according to claim 2 or 4, wherein: The foreign body detector is a first foreign body detector that detects the foreign body using magnetic lines of force. further comprising a second foreign matter detector, the second foreign matter detector detecting the foreign matter using X-rays, The processor obtains information related to the foreign matter from the first foreign matter detector and the second foreign matter detector, the processor infers a shape of the foreign object based on information related to the foreign object, The processor compares the shape of the foreign matter with pre-stored data of components constituting the processing machine to identify a target processing machine from among the plurality of processing machines.

6. The management system according to claim 3, wherein: The information related to the foreign matter is information indicating that the foreign matter is a powder having a size smaller than a predetermined size. The processor predicts a maintenance period of the processing machine based on the detected amount of the powder that increases with time.

7. The management system according to any one of claims 1 to 6, wherein: The processor performs processing for displaying the acquired information on the state of the processing machine on a display.

8. The management system according to any one of claims 1 to 7, wherein: A QR code is assigned to the packaging of the product that is the object of inspection by the foreign object detector. The QR code stores information indicating the date, time and location of the foreign object inspection process performed by the foreign object detector, information indicating the foreign object inspection result, and information indicating the business provider that performed the inspection of the product.

9. The management system according to any one of claims 1 to 8, wherein: The foreign matter is a metallic foreign matter.

10. A management method for managing processing equipment, comprising the following steps: Obtain information related to foreign matter from the foreign matter detector, including: The foreign matter detector is used to detect whether the foreign matter is mixed into the product produced by the processing machinery in the processing equipment; and Information on the state of the processing machine is acquired based on the information on the foreign matter.

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