Management system and management method

Abstract

To acquire information about a state of a processing machine.SOLUTION: A management system (100) is a system for managing processing equipment, and includes a foreign matter detection machine for detecting whether a foreign matter is mixed in a product (20), and a management device (40) that can process information about the foreign matter. The management device acquires the information about the foreign matter from the foreign matter detection machine, and acquires information about a state of the processing machine on the basis of the information about the foreign matter.SELECTED DRAWING: Figure 1

Description

[Technical field]

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

[0002] Metal detectors and X-ray foreign object detectors are known as technologies (foreign object detectors) for detecting whether foreign objects are mixed into manufactured products in processing facilities that process or manufacture foods, medicines, etc. For example, Patent Document 1 discloses a metal detector for detecting ferromagnetic foreign objects mixed into products. [Prior art documents] [Patent documents]

[0003] [Patent Document 1] Patent No. 5779273 Summary of the Invention [Problem to be solved by the invention]

[0004] When a foreign object is detected by these foreign object detectors, the product containing the foreign object is removed from the production line. Depending on the frequency of contamination by foreign objects and the type of foreign object, the production line may need to be stopped and inspected. In order to obtain information on the status of the processing machines, such as the operating status of the processing equipment, abnormalities in the processing equipment, identification of abnormal parts of the processing equipment, or, in the case where the processing equipment is composed of multiple processing machines, identification of the processing machine where an abnormality has occurred, it is necessary to provide multiple detection means such as sensors and imaging devices.

[0005] However, providing multiple detection means in processing equipment increases costs, makes management more complicated, and increases the burden on workers at the processing equipment. Therefore, the inventors realized that if information about the status of the processing machine could be obtained by using a foreign object detector already installed in the processing equipment, there would be no need to provide multiple detection means, and these problems could be solved. Patent Document 1 does not mention this point at all.

[0006] One aspect of the present disclosure is directed to obtaining information regarding the status of a processing machine. [Means for solving the problem]

[0007] In order to solve the above problems, a management system according to one aspect of the present disclosure is a management system that manages processing equipment. The management system includes a foreign object detector and a processor. The foreign object detector detects whether a foreign object is present in a product produced by a processing machine in the processing equipment. The processor processes information related to the foreign object detected by the foreign object detector. The processor then acquires information related to the foreign object from the foreign object detector, and acquires information related to the status of the processing machine based on the information related to the foreign object.

[0008] In order to solve the above problems, a management method according to one embodiment of the present disclosure is a method for managing processing equipment. This management method includes the following two steps. (1) A step of acquiring information about foreign objects. This step acquires information about foreign objects from a foreign object detector that detects whether or not foreign objects are present in products produced by a processing machine in the processing facility. (2) A step of acquiring information regarding the state of the processing machine, the information being acquired based on the information regarding the foreign object. Effect of the Invention

[0009] According to one aspect of the present disclosure, it is possible to obtain information regarding the status of a processing machine. [Brief description of the drawings]

[0010] [Figure 1] 1 is a schematic configuration diagram of a management system according to a first embodiment of the present disclosure. [Diagram 2] 2 is a block diagram showing a hardware configuration of a management device according to the first embodiment of the present disclosure. FIG. [Diagram 3] FIG. 4 is a diagram illustrating an example of a parts database. [Figure 4] FIG. 2 is a functional block diagram of a processor of a management device according to the first embodiment of the present disclosure. [Diagram 5] 5 is a flowchart illustrating an operation example of the management device according to the first embodiment of the present disclosure. [Figure 6] FIG. 13 is a block diagram showing a hardware configuration according to a modified example of the first embodiment of the present disclosure. [Figure 7] 1 is a graph showing the relationship between X-ray transmission image data and magnetic change amount data. [Figure 8] 11 is a flowchart illustrating an example of an operation of a management device according to a modified example of the first embodiment of the present disclosure. [Figure 9] FIG. 11 is a functional block diagram of a processor of a management device according to a second embodiment of the present disclosure. [Figure 10] 1 is a time series graph showing the relationship between test data and time. [Figure 11] 10 is a flowchart illustrating an operation example of a management device according to a second embodiment of the present disclosure. [Figure 12] FIG. 1 is a diagram showing a product to which a two-dimensional code has been added. DETAILED DESCRIPTION OF THE PREFERRED EMBODIMENTS

[0011] [Embodiment 1] 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 parts are given the same reference numerals and the description will be omitted.

[0012] (Example of configuration of management system 100) 1 is a schematic diagram showing an example of a management system 100. As shown in FIG.

[0013] The location 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 metal detector 10 and the management device 40 will be described taking as an example a case where they are installed in a food processing facility, but the metal detector 10 and the management device 40 may also be installed in a facility that processes or manufactures beverages, medicines, cosmetics, daily necessities, clothing, or the like.

[0014] The metal detector 10 is a device for inspecting whether or not a metallic foreign object 30 is present in a product 20 produced in a food processing facility. The metal detector 10 detects a metallic foreign object 30 present inside the product 20, which is difficult to visually recognize from the outside. In this embodiment, a so-called magnetic bias type magnetic field line method is adopted as an example of a method for detecting the metallic foreign object 30. To explain the "magnetic bias type magnetic field line method", the metal detector 10 is provided with magnets (not shown) so as to sandwich the production line in the vertical direction. When the metallic foreign object 30 passes between the magnets, a change occurs in the magnetic field lines emitted from the magnets. In the magnetic bias type magnetic field line method, the metallic foreign object 30 is detected based on the change in the magnetic field lines. The metallic foreign object 30 may be a foreign object composed of only a metallic element, or may be a foreign object composed of a metallic element and a non-metallic element. The metallic element may be a single element, or may be a multiple element (so-called alloy).

[0015] Compared to the conventional so-called search coil method, the magnetic bias type magnetic field line method enables highly accurate detection of metallic foreign bodies not only in paper, vinyl, and plastic packaging, but also in products with aluminum vapor-deposited packaging such as retort foods, and liquid foods with high salt concentrations such as curry roux and soy sauce.

[0016] Metal foreign matter 30 that may be mixed into product 20 includes parts of processing machinery. Examples of parts of processing machinery include metal bolts, nuts, and screws, and plastic cable ties containing magnetic powder. Food processing generally consists of many steps, and dedicated processing machinery is used for each step.

[0017] Types of processing machines include cutting machines that slice or cut ingredients, mixing machines that mix ingredients, filling machines that fill beverages into pouches, and packaging machines that package processed products.

[0018] An example of the product 20 to be inspected is food or beverage packed in a package or container.

[0019] During operation of food processing equipment, bolts, nuts, screws, etc. may fall off from processing machinery due to rust, loosening of assembly, metal fatigue, etc. If metal that has fallen off in this way gets mixed into product 20, it will be detected as metallic foreign matter 30 by metal detector 10.

[0020] When the metal detector 10 detects the metallic foreign object 30, the following process may be performed in general.

[0021] First, a worker working at the food processing facility is notified that a metallic foreign object 30 has been detected. The worker who receives the notification, for example, removes the product 20 containing the metallic foreign object 30 from the production line and stops all processing machines. After that, the worker starts to inspect all processing machines.

[0022] If it were possible to know from which processing machine the metal foreign matter 30 mixed in the product 20 came before starting the inspection of the processing machines, it would be possible to significantly reduce the time and cost required for inspecting the processing machines, and the burden on the workers would be reduced. If the workers inspect and repair only the target processing machine, they can operate the processing machine again, and production activities can be resumed safely.

[0023] Therefore, in this embodiment, a configuration is adopted in which the processing machine from which the metal foreign matter 30 mixed in the product 20 fell off is inferred and identified, and the result is notified to the worker. As a result, as described above, it is possible to significantly reduce the time and cost required for inspecting the processing machines, and the burden on the worker is reduced. An example of the identification method and notification method will be explained step by step below. Note that, hereinafter, "inferring and identifying" may be simply referred to as "identifying".

[0024] When inspecting the product 20 coming down the production line, the metal detector 10 converts data relating to the inspection into an electric signal regardless of whether or not a metallic foreign object 30 is detected, and transmits the data to the management device 40 using a predetermined communication method. When a metallic foreign object 30 is detected, the metal detector 10 converts data relating to foreign object detection, such as changes in magnetic field lines, into an electric signal and transmits the data to the management device 40. An example of "data relating to foreign object detection, such as changes in magnetic field lines" is a voltage waveform with a voltage width or time width based on an electric signal that changes relative to the magnetic field changed by the metallic foreign object 30. The communication may be performed either wired or wirelessly, and any communication method may be used as long as the communication between them can be performed. In this embodiment, the communication between the metal detector 10 and the management device 40 is described as being performed using Wi-Fi (registered trademark).

[0025] (Hardware configuration of management device 40) Next, the hardware configuration of the management device 40 will be described with reference to Fig. 2. Fig. 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.

[0026] 2, 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 to each other via a bus 45 so as to be able to communicate with each other.

[0027] The processor 41 is an arithmetic unit that executes various programs, such as a CPU (Central Processing Unit). The processor 41 reads programs from the ROM 42 or the storage device 44, and executes the various programs using the RAM 43 as a working area.

[0028] The ROM 42 stores various programs and various data. The RAM 43 temporarily stores programs or data as a working area. Note that computer-readable recording media are not limited to the ROM 42 and RAM 43, and may include EPROM (Erasable Programmable ROM), EEPROM (registered trademark) (Electrically Erasable Programmable ROM), etc.

[0029] Storage device 44 is configured with a hard disk drive (HDD), a solid state drive (SSD), a flash memory, or the like, and stores various programs and various data. Storage device 44 stores a parts database 441. Parts database 441 is a database that stores information on parts that configure processing machines installed in food processing facilities. Examples of "parts that configure processing machines" include metal parts (bolts, nuts, screws, etc.) and non-metallic parts that contain metal (such as resin cable ties mixed with magnetic powder).

[0030] Here, an example of the parts database 441 will be described with reference to FIG. 3. As shown in FIG. 3, the parts database 441 stores the name of each part, the shape of each part, and the processing machine to which each part is attached. For example, a bolt B1, a nut N1, and a screw S1 are attached to a mixing machine. A bolt B2, a nut N2, and a screw S2 are attached to a filling machine. A bolt B3, a nut N3, and a screw S3 are attached to a packaging machine. The shape of each part indicates a size according to, for example, the JIS standard, and is indicated by φ (diameter), length, pitch, etc. The outer shapes of the bolts B1 to B3, the nuts N1 to N3, and the screws S1 to S3 may also be stored in the parts database 441. In this embodiment, the "shape of a part" means both the "size of a part" and the "outer shape of a part".

[0031] Returning to FIG. 2, the display 47 is configured with a liquid crystal display, an organic EL display, or the like, and displays various information.

[0032] The communication I / F 46 is implemented as hardware such as a network adapter, communication software, or a combination of these, and communicates with the metal detector 10.

[0033] (Functions of processor 41 of management device 40) Next, functions of the processor 41 of the management device 40 will be described with reference to Fig. 4. Fig. 4 is a functional block diagram of the processor 41 of the management device 40. As shown in Fig. 4, in the management device 40 of this embodiment, the processor 41 executes a specific program to function as an inspection data acquisition unit 411, a processing machine data acquisition unit 412, and an output unit 413.

[0034] 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. An example of the information related to the state of the processing machine includes information specifying which processing machine the metallic foreign object 30 has fallen from. In other words, the processing machine data acquisition unit 412 has a function of specifying which processing machine the metallic foreign object 30 has fallen from based on the data acquired by the inspection data acquisition unit 411. 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 an operator of the food processing facility.

[0035] Next, an example of the operation of the management device 40 will be described with reference to the flowchart of Fig. 5. The process shown in Fig. 5 is repeatedly executed at a predetermined cycle.

[0036] In step S101, the processor 41 of the management device 40 acquires data related to the inspection from the metal detector 10 via the communication I / F 46. The data related to the inspection includes, for example, data indicating that a metallic foreign object 30 has been detected and data related to foreign object detection.

[0037] If the data acquired in the process of step S101 includes data indicating that a metallic foreign matter 30 has been detected (YES in step S102), 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 a metallic foreign matter 30 has been detected (NO in step S102), the process ends.

[0038] In step S103, the processor 41 of the management device 40 infers the shape of the metallic foreign object 30 based on the data on foreign object detection acquired in the process of step S101. For example, as described above, when the data on foreign object detection is a voltage waveform with a voltage width and a time width based on an electric signal that changes relatively to a magnetic field changed by the metallic foreign object 30, the processor 41 of the management device 40 can infer the shape of the metallic foreign object 30 based on this data. The processor 41 of the management device 40 compares the data on the inferred shape of the metallic foreign object 30 with the data stored in the part database 441, and infers a part that matches or nearly matches the detected metallic foreign object 30. Here, for example, it is assumed that the shape of the metallic foreign object 30 acquired in the process of step S101 matches or nearly matches the shape of the bolt B3 shown in FIG. 3. In this case, the processor 41 of the management device 40 can identify that the metallic foreign object 30 mixed in the product 20 is the bolt B3 (step S104). Furthermore, processor 41 of management device 40 can determine that the processing machine to which bolt B3 is attached is a packaging machine by referring to part database 441. Therefore, in the processing of step S104, processor 41 of management device 40 can identify that metal foreign matter 30 mixed into product 20 is bolt B3, and can also identify that bolt B3 has fallen off from the packaging machine.

[0039] The process proceeds to step S105, where the processor 41 of the management device 40 displays the result identified in step S104 on the display 47 to notify the worker. For example, the display 47 displays, "The detected metal foreign object is highly likely to be bolt B3 that fell off from a packaging machine." The worker who checks the display 47 can know from which processing machine the metal foreign object 30 that has entered the product 20 fell off.

[0040] Note that the process flow described in FIG. 5 is just an example, and steps may be deleted, new steps may be added, or the order of steps may be changed without departing from the spirit of the invention.

[0041] (Modification) Next, a modified example of the first embodiment will be described with reference to FIG. 6. In the modified example, as shown in FIG. 6, the management device 40 acquires data related to inspection from two metal detectors 10, 11. The metal detector 10 is the same as that in the first embodiment. The metal detector 11 is a machine that detects metallic foreign bodies 30 using an X-ray method. The X-ray method is a method in which X-rays, a type of electromagnetic wave, are irradiated onto the product 20 to detect metallic foreign bodies 30 based on the difference in the amount of transmission. The amount of transmission depends on the thickness and density, and the thicker and denser the product is, the more X-rays are blocked. Metal has a high density and appears darker in color than the product being inspected, so it can be detected as a foreign body.

[0042] In the modified example, two methods, a magnetic bias type magnetic field line method and an X-ray method, are used in combination as a method for detecting the metallic foreign matter 30. By using the two methods in combination, it becomes possible to estimate the shape of the metallic foreign matter 30 with higher accuracy than when only the magnetic bias type magnetic field line method is used.

[0043] (An example of how to estimate foreign matter) An example of a method for estimating the type of foreign object detected by the magnetic bias type magnetic field line method and the X-ray method will be described below. In a modified example, a threshold value is set for estimating the type of foreign object based on X-ray transmission image data and magnetic change amount data obtained through experiments and simulations using foreign object samples.

[0044] The threshold value will be described with reference to FIG. 7. FIG. 7 is a graph showing the relationship between X-ray transmission image data and magnetic change amount data. The vertical axis of FIG. 7 shows X-ray transmission image data by the X-ray method, and the horizontal axis shows magnetic change amount data by the magnetic bias type magnetic field line method. Note that in FIG. 7, foreign matter includes resin foreign matter in addition to metal foreign matter. That is, in this embodiment, foreign matter to be detected is not limited to metal foreign matter, and may include resin foreign matter.

[0045] The X-ray transmission image data includes, for example, the amount of X-ray transmission and the area of ​​the sample that has been transmitted. The magnetic change amount data includes, for example, the amplitude of the voltage waveform, the time integral of the voltage, and the amount of voltage change per unit time. The Mahalanobis distance is set using the so-called MT method (Maharanobis Taguchi) from the X-ray transmission image data and magnetic change amount data that have been obtained in advance through experiments and simulations using foreign matter samples. In the modified example, for example, the Mahalanobis distance is used as a threshold for estimating the type of foreign matter, i.e., what type of foreign matter a foreign matter is. The MT method sets thresholds A to D, which are indicated by circles, as shown in FIG. 7. Hereinafter, unless otherwise specified, the thresholds A to D will be referred to as "threshold circles A to D".

[0046] The type of foreign matter is estimated depending on whether the data detected by the magnetic bias type magnetic field line method and the X-ray method is present in any one of the threshold circles A to D. Specifically, if the data related to the inspection is present in the threshold circle A, the foreign matter is estimated to be an organic foreign matter such as resin. If the data related to the inspection is present in the threshold circle B, the foreign matter is estimated to be a metal foreign matter such as a bolt, nut, or screw. If the data related to the inspection is present in the threshold circle C, the foreign matter is estimated to be a metal foreign matter such as a wire or a cutting chip on a line. If the data related to the inspection is present in the threshold circle D, the foreign matter is estimated to have not been detected. If the data related to the inspection is present in a position far away from these threshold circles A to D, the processor 41 of the management device 40 may determine that a sudden abnormality has occurred in the food processing equipment and display the same on the display 47.

[0047] Next, an example of the operation of the management device 40 in the modified example will be described with reference to the flowchart of Fig. 8. The process shown in Fig. 8 is repeatedly executed at a predetermined cycle. It is also assumed that the threshold circles A to D described in Fig. 7 are set in advance.

[0048] In step S201, the processor 41 of the management device 40 acquires data relating to the inspection from the metal detectors 10 and 11 via the communication I / F 46.

[0049] In step S202, the processor 41 of the management device 40 calculates where on the graph of FIG. 7 the data acquired in the process of step S201 exists.

[0050] If the data acquired in the processing of step S201 is located far away from the threshold circles A to D (YES in step S203), the processor 41 of the management device 40 determines that a sudden abnormality has occurred in the food processing equipment, and notifies the operator of this by displaying the abnormality on the display 47 (step S215).

[0051] If the result of step S203 is NO, the process proceeds to step S204. If the data acquired in the process of step S201 exists within the threshold circle A (YES in step S204), the process proceeds to step S205, and the processor 41 of the management device 40 estimates that the foreign matter mixed into the product 20 is an organic foreign matter such as a resin.

[0052] The process proceeds to step S206, where the processor 41 of the management device 40 checks the data relating to the shape of the foreign object against the data stored in the part database 441.

[0053] The process proceeds to step S207, where the processor 41 of the management device 40 infers and identifies from which processing machine the foreign matter that has entered the product 20 has fallen off, based on the comparison result of step S206.

[0054] The process proceeds to step S215, where the processor 41 of the management device 40 displays the result determined in step S207 on the display 47 to notify the operator.

[0055] If the data acquired in the processing of step S201 does not exist within threshold circle A (NO in step S204), the processing proceeds to step S208. If the data acquired in the processing of step S201 exists within threshold circle B (YES in step S208), the processing proceeds to step S209, and the processor 41 of the management device 40 estimates that the foreign object mixed into the product 20 is a metallic foreign object 30 such as a bolt, nut, or screw.

[0056] The process proceeds to step S210, where the processor 41 of the management device 40 compares the data relating to the shape of the metallic foreign matter 30 with the data stored in the part database 441.

[0057] The process proceeds to step S211, where the processor 41 of the management device 40 infers and identifies from which processing machine the metallic foreign matter 30 that has become mixed into the product 20 has fallen off, based on the comparison result of step S210.

[0058] The process proceeds to step S215, where the processor 41 of the management device 40 displays the result of step S211 on the display 47 to notify the operator.

[0059] If the data acquired in the processing of step S201 does not exist within threshold circle B (NO in step S208), the processing proceeds to step S212. If the data acquired in the processing of step S201 exists within threshold circle C (YES in step S212), the processing proceeds to step S213, and the processor 41 of the management device 40 estimates that the foreign matter mixed into the product 20 is a metallic foreign matter such as a wire, a linear chip, or fine metal powder.

[0060] The process proceeds to step S214, where the processor 41 of the management device 40 performs a prediction process based on the estimation result of step S213. Details of this prediction process will be described later in the second embodiment.

[0061] If the data acquired in the processing of step S201 is not within threshold circle C (NO in step S212), that is, if the data acquired in the processing of step S201 is within threshold circle D, processor 41 of management device 40 assumes that no foreign object has been detected, and the series of processes ends.

[0062] It should be noted that the process flow described in FIG. 8 is just an example, and steps may be deleted, new steps may be added, or the process order may be changed without departing from the spirit of the invention.

[0063] (Action and effect) As described above, according to the first embodiment, the following advantageous effects can be obtained.

[0064] The management system 100 is a system for managing processing equipment, and includes a foreign object detector that detects whether or not foreign objects have been mixed into products 20 produced by processing machines in the processing equipment, and a processor 41 of a management device 40 that is capable of processing information regarding foreign objects detected by the foreign object detector.

[0065] The processor 41 of the management device 40 acquires information about foreign objects from the foreign object detector, and acquires information about the state of the processing machine based on the information about the foreign objects. The "foreign objects" here include at least metallic foreign objects 30 and resin foreign objects. An example of a foreign object detector is the metal detectors 10 and 11.

[0066] As described above, when a processing facility is composed of multiple processing machines, in order to acquire information on the status of the processing machines, such as identifying a processing machine where an abnormality has occurred, multiple detection means such as sensors and imaging devices must be provided, but this creates problems such as increased costs and increased burden on workers. The inventors focused on acquiring information on the status of the processing machines by utilizing a foreign object detector already installed in the processing facility. According to the above configuration, it is possible to acquire information on the status of the processing machines without providing multiple detection means, which contributes to cost reduction and further reduces the burden on workers.

[0067] The information on the state of the processing machine may be information for identifying a target processing machine among a plurality of processing machines. The "target processing machine" here refers to the processing machine from which the foreign object fell off. The foreign object may be a metallic foreign object 30.

[0068] When it is detected that the product 20 contains a foreign metal object 30, the worker stops all the processing machines and starts inspecting all the processing machines. Inspection here refers to the task of finding which processing machine the foreign metal object 30 fell from. It is considered that the inspection is carried out by a veteran worker who is familiar with food processing equipment, but in the current situation where there is a labor shortage on-site and workers are busy with daily production, even if the product 20 containing the foreign metal object 30 can be prevented from being released onto the market, there is a risk that there will be a delay in dealing with the cause of the contamination itself.

[0069] According to the above configuration, the processor 41 of the management device 40 can identify from which processing machine the metallic foreign matter 30 mixed in the product 20 fell off. The processor 41 of the management device 40 may display the identified result on the display 47 to notify the worker. The worker who checks the display 47 can know from which processing machine the metallic foreign matter 30 mixed in the product 20 fell off. This allows even a worker who has no knowledge of processing machines to immediately identify the processing machine that caused the contamination. This makes it possible to significantly reduce the time and cost required for inspecting the processing machines, and reduces the burden on the workers. The worker can operate the processing machines again by inspecting and repairing only the target processing machines, and production activities can be resumed quickly and safely.

[0070] The foreign object detector may also be a device that detects foreign objects using magnetic lines of force. The processor 41 of the management device 40 may infer the shape of the foreign object based on the information about the foreign object, and identify a target processing machine from among a plurality of processing machines by comparing the shape of the foreign object with data on parts stored in advance.

[0071] According to the above configuration, it is possible to identify the processing machine from which the foreign object has fallen out from among a large number of processing machines.

[0072] Furthermore, by using a magnetic bias type magnetic field line method as a method for detecting metallic foreign matter 30, it becomes possible to detect metallic foreign matter 30 not only in paper, vinyl, and plastic packaging, but also in aluminum packaging. The magnetic bias type magnetic field line method also makes it possible to detect packaging abnormalities such as the state of welding of packaging by the strength of eddy currents generated on the surface of conductive packaging material such as aluminum packaging. This makes it possible to not only identify the target processing machine, but also to detect abnormalities in the packaging machine based on the results of abnormality detection of conductive packaging material.

[0073] Furthermore, the metal detector 10 may be a first metal detector that uses magnetic lines to detect foreign objects, and the management system 100 may further include a second metal detector that uses X-rays to detect foreign objects. The processor 41 of the management device 40 may acquire information about the foreign object from the first metal detector and the second metal detector, infer the shape of the foreign object based on the information about the foreign object, and identify a target processing machine from among a plurality of processing machines by comparing the shape of the foreign object with pre-stored part data. The second metal detector may correspond to the metal detector 11.

[0074] According to the above configuration, the processor 41 of the management device 40 estimates the shape of the foreign object using information detected by the magnetic bias type magnetic field line method and the X-ray method. By using the two methods in combination, the accuracy of estimating the shape of the foreign object is improved compared to using only one of the methods. The processor 41 of the management device 40 identifies from which processing machine the foreign object that has mixed into the product 20 has fallen off by comparing the estimated shape of the foreign object with the part information of the processing machine stored in advance in the parts database 441. Since the accuracy of estimating the shape of the foreign object is improved, the accuracy of identifying the processing machine is also improved.

[0075] [Embodiment 2] Next, a second embodiment of the present disclosure will be described with reference to Figures 9 to 11. For ease of explanation, the same reference numerals will be used to designate members having the same functions as those described in the first embodiment, and the explanations thereof will not be repeated.

[0076] 9 is a functional block diagram of the processor 41 of the management device 40 according to the embodiment 2. The difference from the embodiment 1 is that in the management device 40 of the embodiment 2, the processor 41 further functions as a prediction unit 414 by executing a specific program.

[0077] The prediction unit 414 predicts the replacement time of a metal blade provided in a processing machine based on, for example, inspection data obtained by an X-ray method or a magnetic bias type magnetic field line method. A blade used for kneading or stirring food is worn due to friction with a metal container into which materials are put and aging deterioration of the blade itself. Fine metal powder generated by this wear may be mixed into the product 20. The longer the blade is used, the more powder generated by wear increases, and the time comes when replacement is necessary. The prediction unit 414 predicts such replacement time. An example of a method for predicting the replacement time of a blade will be described with reference to FIG. 10. As an example, the powder is fine metal powder having a predetermined size or less. The predetermined size is calculated through, for example, an experiment or a simulation. The powder may be fine resin powder having a predetermined size or less.

[0078] (An example of how to predict when to replace) Fig. 10 is a time series graph showing the relationship between time and inspection data obtained by the X-ray method or the magnetic bias type magnetic field line method. The vertical axis of Fig. 10 shows inspection data obtained by the X-ray method or the magnetic bias type magnetic field line method, and the horizontal axis shows time. When the vertical axis shows inspection data obtained by the X-ray method, an example of the inspection data is X-ray transmission image data. When the vertical axis shows inspection data obtained by the magnetic bias type magnetic field line method, an example of the inspection data is magnetic change amount data.

[0079] As shown in FIG. 10, the inspection data changes as the blade is used for a longer period of time. As is clear from FIG. 10, the inspection data tends to increase. This change is caused by an increase in fine metal powder caused by wear of the blade due to friction between the blade and the container and deterioration of the blade over time. The processor 41 of the management device 40 can predict the timing T at which the inspection data reaches a threshold value 70 indicating an abnormal value as the time to replace the blade by approximating the plotted inspection data with a straight line 71 using, for example, a simple regression analysis. The least squares method may be used to calculate the straight line 71. The method of analyzing the inspection data is not limited to simple regression analysis, and may be multiple regression analysis or machine learning.

[0080] An operation example of the management device 40 according to the second embodiment will be described with reference to the flowchart of Fig. 11. As described in the modified example of the first embodiment, the flowchart of Fig. 11 corresponds to the process of step S214 in Fig. 8.

[0081] 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 on an increasing trend. If the inspection data is on an increasing trend (YES in step S301), the process proceeds to step S302, where the processor 41 of the management device 40 predicts the time to replace the blade using, for example, the simple regression analysis described above, and notifies the operator of the prediction result by displaying it on the display 47.

[0082] Although the above description has been given taking blades as an example of a metal part for which replacement time prediction is to be performed, the present invention is not limited to this, and any metal part that is subject to wear can be used as a target for replacement time prediction.

[0083] In addition, the target of prediction is the replacement time of the blade, but is not limited to this. For example, the target of prediction may be the inspection time of the blade. In other words, the target of prediction may be the maintenance time of the blade, including replacement and inspection.

[0084] (Action and effect) As described above, according to the second embodiment, the following advantageous effects can be obtained.

[0085] The processor 41 of the management device 40 may obtain information about foreign objects from the foreign object detector, and predict the maintenance time for the processing machine based on the information about the foreign object. In other words, the information about the state of the processing machine may be prediction information about the maintenance time for the processing machine. Note that the "maintenance time for the processing machine" may be rephrased as "the maintenance time for the parts that constitute the processing machine."

[0086] An example of a part is the above-mentioned metal blade used for kneading and stirring food. Such blades wear due to friction with the metal container into which the food is put and due to deterioration of the blade itself over time. In many cases, the degree of wear is checked visually by an operator, which poses the problem of securing workers to carry out maintenance work and a certain amount of inventory. According to the above-mentioned configuration, by predicting the maintenance time for the blade and notifying the operator of the prediction result, it is possible to reduce the burden of the worker's checking work and to limit and manage the number of blades in inventory.

[0087] The information on the foreign matter may be information indicating that the size of the foreign matter is powder having a predetermined size or less. The processor 41 of the management device 40 may predict the maintenance timing of the processing machine based on the detected amount of powder that increases over time.

[0088] According to the above configuration, when continuous occurrence of powder contamination is found, the processor 41 of the management device 40 can predict the maintenance timing of the parts constituting the processing machine causing the problem and notify the operator of the prediction result. This enables the operator to replace the parts at the appropriate time or to limit and manage the number of parts in stock.

[0089] [Embodiment 3] Next, a third embodiment of the present disclosure will be described below with reference to Fig. 12. For ease of explanation, the same reference numerals will be given to members having the same functions as those described in the first embodiment, and the description thereof will not be repeated.

[0090] 12, a two-dimensional code 80 may be attached to the packaging of the product 20. Predetermined information is stored in the two-dimensional code 80. Examples of the predetermined information include information indicating the date, time, and location 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 entity that inspected the product 20.

[0091] By providing the two-dimensional code 80 to the product 20, the consumer can know when, where and by which business the product 20 was inspected, and what the inspection results were.

[0092] Foreign matter contamination occurs not only due to broken or fallen parts of processing machines, but also in some cases where consumers intentionally add foreign matter to products 20 when the products are sold in the market, such as retail stores. For this reason, the collection and management of foreign matter inspection data by producers alone may not be sufficient. By assigning the foreign matter inspection data to each product using a two-dimensional code 80, it becomes possible to immediately check the foreign matter inspection results when foreign matter contamination occurs in the market, and it becomes possible to confirm the safety of food products during production.

[0093] The type of the two-dimensional code 80 is not particularly limited, but for example, a QR code (registered trademark) may be used, which allows consumers to easily obtain information using a smartphone or the like.

[0094] In the above-mentioned first and second embodiments, it has been explained that the processor 41 of the management device 40 identifies a target processing machine based on the information on the metallic foreign matter 30, or predicts the maintenance timing of a part based on the information on the metallic foreign matter 30. These configurations may be rephrased as follows. That is, it may be rephrased that the processor 41 of the management device 40 estimates the state of the processing machine based on the information on the metallic foreign matter 30.

[0095] "Predicting the state of a processing machine" includes "identifying a target processing machine" and "predicting the maintenance timing of parts provided in the processing machine." This point will be described below.

[0096] With regard to "identifying the target processing machine", an example of identification from information on the metallic foreign matter 30 has been described in the above-mentioned embodiment 1. While this identification process is being performed, the background process of the processor 41 of the management device 40 can determine the state of the processing machine, for example, from information on the metallic foreign matter 30. A specific example of the state of the processing machine is whether it is normal or abnormal. That is, the background process of the processor 41 of the management device 40 can perform determination processes such as "mixing machine: normal", "filling machine: normal", and "packaging machine: abnormal". Here, the packaging machine is determined to be abnormal because, as described above, it has been identified that the bolt B3 has fallen off the packaging machine.

[0097] In this way, "identifying the processing machine from which the metal foreign object 30 fell, i.e., identifying that the metal foreign object 30 fell from a packaging machine" can be said to be "inferring the state of the processing machine, i.e., inferring that the packaging machine is in an abnormal state."

[0098] Next, with regard to "predicting the maintenance timing of parts installed in a processing machine", an example of prediction based on information on the metallic foreign matter 30 has been described in the above-mentioned second embodiment. Predicting the maintenance timing of a part means, in other words, estimating the extent to which the deterioration of the part has progressed, or the extent to which the deterioration will progress in the future if the part is continued to be used as is. In addition, since a part is "a part of the processing machine", "predicting the maintenance timing of a part" can be said to be "estimating the condition of the processing machine".

[0099] [Software implementation example] The functions of the management device 40 can be realized by a program for causing a computer to function as the management device 40 and a program for causing a computer to function as each control block of the management device 40 .

[0100] In this case, the management device 40 includes a computer having at least one device (e.g., a processor) and at least one storage device (e.g., a memory) as hardware for executing a program. The computer executes the program to realize each function described in each embodiment.

[0101] The program may be recorded in one or more computer-readable recording media, not temporarily. The recording media may or may not be included in 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.

[0102] In addition, some or all of the functions of each control block can be realized by a logic circuit. For example, an integrated circuit in which a logic circuit that functions as each control block is formed is also included in the scope of the present disclosure. In addition, the functions of each control block can be realized by, for example, a quantum computer.

[0103] Furthermore, each process described in each embodiment may be executed by AI (Artificial Intelligence). In this case, the AI ​​may be operated on the management device 40 or may be operated on another device (for example, an edge computer or a cloud server).

[0104] The present disclosure is not limited to the above-described embodiments, and various modifications are possible within the scope of the claims. Embodiments obtained by appropriately combining the technical means disclosed in different embodiments are also included in the technical scope of the present disclosure.

[0105] [Additional Notes] The present disclosure can also be expressed as follows.

[0106] The management system according to aspect 1 of the present disclosure is a management system for managing processing equipment, and includes a foreign object detector that detects whether foreign objects are present in products produced by processing machines in the processing equipment, and a processor capable of processing information about the foreign objects detected by the foreign object detector, wherein the processor obtains information about the foreign objects from the foreign object detector, and obtains information about the status of the processing machine based on the information about the foreign objects.

[0107] In the management system according to aspect 2 of the present disclosure, in aspect 1 above, the information on the state of the processing machine may be specific information of a target processing machine from among a plurality of processing machines.

[0108] In the management system according to aspect 3 of the present disclosure, in aspect 1 above, the information on the state of the processing machine may be prediction information on the timing of maintenance of the processing machine.

[0109] A management system according to aspect 4 of the present disclosure may be configured in such a way that, in aspect 2 above, the foreign object detector is a device that detects the foreign object using magnetic lines of force, and the processor infers the shape of the foreign object based on information about the foreign object, and compares the shape of the foreign object with pre-stored data on parts that make up the processing machine to identify a target processing machine from among the plurality of processing machines.

[0110] The management system of aspect 5 of the present disclosure, in aspect 2 or 4 above, may be configured so that the foreign object detector is a first foreign object detector that detects the foreign object using magnetic lines and further includes a second foreign object detector that detects the foreign object using X-rays, and the processor acquires information about the foreign object from the first foreign object detector and the second foreign object detector, infers a shape of the foreign object based on the information about the foreign object, and compares the shape of the foreign object with pre-stored data on parts that constitute the processing machine to identify a target processing machine from among the plurality of processing machines.

[0111] A management system according to aspect 6 of the present disclosure, in aspect 3 above, may be configured such that the information regarding the foreign matter is information indicating that the size of the foreign matter is powder having a predetermined size or less, and the processor predicts the time for maintenance of the processing machine based on the detected amount of the powder which increases over time.

[0112] The management system according to a seventh aspect of the present disclosure, in any one of the first to sixth aspects, may be configured so that the processor performs processing to display the acquired information regarding the state of the processing machine on a display.

[0113] The management system according to aspect 8 of the present disclosure, in any of aspects 1 to 7 above, may be configured such that the packaging of the product that is the target of detection by the foreign object detector is provided with a two-dimensional code storing information indicating the date, time and location at which the foreign object inspection process was performed by the foreign object detector, information indicating the foreign object inspection result, and information indicating the business that inspected the product.

[0114] The management system according to a ninth aspect of the present disclosure may be configured in any one of the first to eighth aspects, wherein the foreign object is a metallic foreign object.

[0115] A management method according to aspect 10 of the present disclosure is a management method for managing processing equipment, and includes a step of acquiring information regarding a foreign object from a foreign object detector that detects whether a foreign object is present in a product produced by a processing machine in the processing equipment, and a step of acquiring information regarding the status of the processing machine based on the information regarding the foreign object. [Explanation of symbols]

[0116] 100 Management system, 10, 11 Metal detector, 20 Product, 30 Metal foreign object, 40 Management device, 41 Processor, 47 Display

Claims

1. A management system for managing processing equipment, a foreign object detector that detects whether or not a foreign object is present in a product produced by a processing machine in the processing facility; a processor capable of processing information about the foreign object detected by the foreign object detector; Equipped with The processor, acquiring information about the foreign object from the foreign object detector; acquiring information about a state of the processing machine based on the information about the foreign object; Management system.

2. The information regarding the state of the processing machine is specific information regarding a target processing machine among a plurality of processing machines. The management system according to claim 1 .

3. The information regarding the state of the processing machine is prediction information regarding a maintenance time for the processing machine. The management system according to claim 1 .

4. the foreign object detector is a device for detecting the foreign object by using magnetic lines of force, The processor, Inferring a shape of the foreign object based on information about the foreign object; identifying a target processing machine from among the plurality of processing machines by comparing the shape of the foreign object with pre-stored data on parts constituting the processing machines; The management system according to claim 2.

5. the foreign object detector is a first foreign object detector that detects the foreign object by using a magnetic field; A second foreign object detector that detects the foreign object using X-rays is further provided. The processor, acquiring information about the foreign object from the first foreign object detector and the second foreign object detector; Inferring a shape of the foreign object based on information about the foreign object; identifying a target processing machine from among the plurality of processing machines by comparing the shape of the foreign object with pre-stored data on parts constituting the processing machines; The management system according to claim 2.

6. the information about the foreign matter is information indicating that the foreign matter is powder having a size equal to or smaller than a predetermined size, The processor, predicting a maintenance timing for the processing machine based on the detected amount of the powder that increases over time; The management system according to claim 3.

7. The processor, performing a process of displaying the acquired information regarding the state of the processing machine on a display; The management system according to claim 1 .

8. A two-dimensional code is attached to the package of the product that is the target of detection by the foreign object detector, the two-dimensional code storing information indicating the date 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 that inspected the product. The management system according to claim 1 .

9. The foreign matter is a metal foreign matter. The management system according to any one of claims 1 to 8.

10. A method for managing processing equipment, comprising: acquiring information about the foreign object from a foreign object detector that detects whether or not a foreign object is present in a product produced by a processing machine in the processing facility; acquiring information about a state of the processing machine based on the information about the foreign object; Management methods including.

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