Meat processing apparatus and meat processing method

Abstract

To improve the quality of meat separation processing by performing a correction operation according to the state of a workpiece.SOLUTION: The present application relates to a meat processing apparatus for performing meat separation processing on a workpiece that is a piece of bone-in meat on which preprocessing has been performed in advance. The meat processing device acquires imaging data of the workpiece subjected to the meat separation processing, and determines a processing state of the workpiece based on the imaging data. A post-processing operation to be performed on the workpiece is determined based on the determination result of the processing state.SELECTED DRAWING: Figure 5

Description

[Technical Field]

[0001] The present disclosure relates to a meat processing apparatus and a meat processing method. [Background technology]

[0002] The deboning process for the arm or thigh parts of livestock carcasses (hereinafter referred to as "work") used as meat for food, such as pigs, cows, and sheep, involves a scoring process in which cuts are made into the work, and a meat separation process in which the meat is peeled off after the scoring process. Because the work is heavy, deboning by hand is a heavy labor, so development is underway to automate these processes.

[0003] For example, Patent Document 1 discloses an example of this type of meat processing equipment, namely, a deboning system that automatically performs deboning by sequentially performing each process included in the deboning process in units arranged along the conveyor while pre-processed workpieces are suspended and supported by clamps and transported on a conveyor. This system, in particular, includes an X-ray imaging station, one of the units arranged along the conveyor, that irradiates the suspended workpiece with X-rays to take X-ray images for identifying positions requiring incision for other processes to be performed downstream along the conveyor. Patent Document 2 also discloses that by accurately determining the outline of the bone in the workpiece based on the X-ray images taken by irradiating the workpiece with X-rays, it is possible to minimize yield reductions and effectively avoid damage to the cutting blades due to overload caused by interference with the bone. [Prior art documents] [Patent documents]

[0004] [Patent Document 1] Patent No. 5860950 [Patent Document 2] Patent No. 5384740 Summary of the Invention [Problem to be solved by the invention]

[0005] In the deboning process, a scoring process is performed as a pre-processing step to ensure that the meat is properly separated from the workpiece in the meat separation process. In the scoring process, as in the above-mentioned patent documents, scoring is performed at positions identified based on X-ray images of the workpiece taken in advance. However, when the meat separation process is actually performed on workpieces that have been scored in this way, poor separation may occur, such as meat remaining on the workpiece. In this case, in order to improve the quality of the meat separation process, it is desirable to perform a correction operation, such as additional scoring, during the meat separation process depending on the processing status of the workpiece.

[0006] However, because the processing state of the workpieces in the meat separation process has already changed due to some of the meat being separated, it is not possible to accurately determine the processing state based on X-ray images taken in advance. Furthermore, the scoring performed as pre-processing for the meat separation process also varies depending on the individual workpiece. Therefore, when additional reworking is required for the workpieces in the meat separation process, it is not easy to determine what reworking should be performed, which poses a challenge when automating the deboning process.

[0007] At least one embodiment of the present disclosure has been made in consideration of the above circumstances, and aims to provide a meat processing device and a meat processing method that can improve the quality of meat separation processing by performing adjustment operations according to the condition of the work. [Means for solving the problem]

[0008] In order to solve the above problems, at least one embodiment of the meat processing device according to the present disclosure includes: A meat processing apparatus for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, an imaging data acquisition unit for acquiring imaging data of the workpiece on which the meat separation process has been performed; a determination unit for determining a processing state of the workpiece based on the imaging data; a post-processing operation determination unit for determining a post-processing operation to be performed on the workpiece based on a determination result by the determination unit; Equipped with.

[0009] In order to solve the above problems, at least one embodiment of the meat processing method of the present disclosure includes: A meat processing method for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, A step of acquiring imaging data of the workpiece on which the meat separation process has been performed; A step of determining a processing state of the workpiece based on the imaging data; determining a post-processing operation to be performed on the workpiece based on the determination result of the processing state; Equipped with. [Effects of the Invention]

[0010] According to at least one embodiment of the present disclosure, a meat processing device and a meat processing method can be provided that can improve the quality of the meat separation process by performing adjustment operations depending on the condition of the workpiece. [Brief explanation of the drawings]

[0011] [Figure 1] 1 is a schematic diagram showing the overall configuration of a meat processing apparatus according to one embodiment. [Figure 2A] FIG. 1 is a schematic diagram showing the relationship between a livestock carcass and a workpiece. [Figure 2B] FIG. 2 is a schematic cross-sectional view of a workpiece. [Figure 3A] FIG. 2 is a perspective view showing the meat separation processing station of FIG. 1. [Figure 3B] 3B is a diagram showing the operation of meat separation processing in the meat separation processing station of FIG. 3A. FIG. [Figure 4] 1 is a flowchart illustrating a meat processing method according to one embodiment. [Figure 5] FIG. 2 is a diagram showing a block configuration of the control device of FIG. [Figure 6]6 is an example of post-processing operation data that can be referred to by the post-processing operation determination unit of FIG. 5. [Figure 7A] 5 is a flowchart showing a specific example of meat separation processing performed in step S103 of FIG. 4. [Figure 7B] 5 is a flowchart showing a specific example of meat separation processing performed in step S103 of FIG. 4. [Figure 8A] 7B is a schematic diagram showing a processing state of the workpiece when the first meat separation processing is performed in step S201 of FIG. 7A. FIG. [Figure 8B] FIG. 7B is a schematic diagram showing a processing state of the workpiece when the second meat separation processing is performed in step S206 of FIG. 7A. [Figure 8C] FIG. 7C is a schematic diagram showing a processing state of the workpiece when the third meat separation processing is performed in step S211 of FIG. 7B. DETAILED DESCRIPTION OF THE INVENTION

[0012] Hereinafter, several embodiments of the present invention will be described with reference to the accompanying drawings. However, the dimensions, materials, shapes, relative arrangements, etc. of the components described as embodiments or shown in the drawings are merely illustrative examples and are not intended to limit the scope of the present invention.

[0013] 1 is a schematic diagram showing the overall configuration of a meat processing apparatus 1 according to one embodiment. The meat processing apparatus 1 is an apparatus for processing workpieces W, which are pieces of meat with bones, and includes a loading station ST1, a measuring station ST2, a pre-processing station ST3, a meat separation processing station ST4, and a discharging station ST5. These stations are arranged in order along a track 2 along which the workpieces W are transported.

[0014] 1 illustrates an example in which each station provided in the meat processing apparatus 1 has a functional configuration corresponding to each process performed on the workpiece W. These stations may be integrated or may be further divided into smaller functional units. Furthermore, if there are other functions that the meat processing apparatus 1 can realize, other stations may be provided in addition to these stations.

[0015] The input station ST1 is configured to input the workpiece W to be processed onto the track 2. The meat processing apparatus 1 has a transport conveyor (not shown) arranged along the track 2 along which the workpiece W is transported, and at the input station ST1, the workpiece W is input onto the transport conveyor from outside. The input of the workpiece W at the input station ST1 may be performed manually by an operator or by using an automated machine.

[0016] The workpiece W handled by the meat processing apparatus 1 is bone-in meat such as the arm or thigh part of a livestock carcass, such as a pig, cow, or lamb, that is used as meat. The workpiece W handled in this embodiment is bone-in meat obtained by cutting off the trotter part of the pig's thigh part, as shown in Fig. 2A. As shown in Fig. 2B, this workpiece W includes a tibia 6a, a patella 6b, and a femur 6c as bone parts 6, and has meat parts 8 around the bone parts 6.

[0017] Returning to FIG. 1 , the workpiece W loaded at the loading station ST1 is transported along the track 2 to the measurement station ST2. The measurement station ST2 is a station for measuring the workpiece W loaded on the track 2, and measures information necessary for pre-processing at the subsequent pre-processing station ST3. Specifically, using measuring equipment such as an X-ray camera or a 3D camera, information about the structure of the workpiece W is measured to identify the position where creasing processing will be performed as pre-processing. The information measured at the measurement station ST2 is stored in a storage device such as a memory (not shown) and can be used for each process at other stations.

[0018] After the measurement at the measuring station ST2 is completed, the workpiece W is transported along the track 2 to the subsequent pre-processing station ST3. The pre-processing station ST3 is configured to perform pre-processing on the workpiece W, and in this embodiment, in particular, performs incision processing on the workpiece W based on the measurement results at the measuring station ST2. Specifically, the incision processing is performed on the workpiece W placed on the transport conveyor by operating a robot arm equipped with a tool such as a cutter at its tip. At this time, the operation of the robot arm is automatically controlled based on the measurement results at the measuring station ST2 so that incision is performed along the cut line required to separate the meat portion 8 from the workpiece W in the meat separation processing.

[0019] The work W that has been pre-processed in the pre-processing station ST3 is transported along the track 2 to the meat separation processing station ST4. The meat separation processing station ST4 is configured to perform a meat separation process for separating the meat portion 8 from the work W.

[0020] Here, a specific configuration of the meat separation processing station ST4 in Fig. 1 will be described with reference to Fig. 3A and Fig. 3B. Fig. 3A is a perspective view showing the meat separation processing station ST4 in Fig. 1, and Fig. 3B is a diagram showing the operation of the meat separation processing in the meat separation processing station ST4 in Fig. 3A.

[0021] The meat separation processing station ST4 includes a transfer conveyor 10 continuing from each upstream station, a first robot arm 12, a second robot arm 14, and a meat separator 22.

[0022] The first robot arm 12 is a multi-axis robot, and is movable based on a control signal from the control device 100. The first robot arm 12 is a multi-axis robot or a robot structure having multiple axes, and is configured to be able to grip the workpiece W being sent onto the transport conveyor 10 from an upstream station using a clamp unit 18 mounted on the tip. Specifically, by operating the first robot arm 12, the clamp unit 18 approaches the workpiece W on the transport conveyor 10, and the clamp unit 18 grabs one end of the workpiece W and pulls it upward. As a result, the workpiece W gripped by the clamp unit 18 is in a hanging position with one end facing upward and the other end facing downward.

[0023] The second robot arm 14 is a multi-axis robot, similar to the first robot arm 12 described above, and is movable based on control signals from the control device 100. The second robot arm 14 also has a robot structure with six or more axes, and is configured so that a tool 20 mounted on the tip can approach the workpiece W gripped by the clamp unit 18 of the first robot arm 12 at any angle or posture. The tool 20 mounted on the tip of the second robot arm 14 is a multi-tool including a cutter and a scraper for making incisions in the workpiece W. As a result, by operating the second robot arm 14 on which the tool 20 is mounted, it is possible to perform an incision making operation in which a notch is formed in the workpiece W using the cutter, and to simultaneously widen the notch using the scraper.

[0024] The meat pressing member 16 is configured to be rotated from a retracted position to a pressing position as shown by arrow Y1 in Fig. 3B, and inserted into a slit formed in the workpiece W gripped by the clamp unit 18, thereby separating (peeling off) the meat portion 8 from the workpiece W. When inserting the meat separator 22 into the slit formed in the workpiece W, the slit formed in the workpiece W gripped in a hanging position by the clamp unit 18 of the first robot arm 12 is widened by a scraper included in the tool 20 mounted on the tip of the second robot arm 14, allowing the meat separator 22 to be inserted properly.

[0025] A meat separator 22 is provided opposite the meat pressing member 16. The meat separator 22 is provided with a recess 23 for positioning the workpiece W held in a hanging position by the clamp unit 18 of the first robot arm 12. When the meat pressing member 16 is rotated from the retracted position to the pressing position while the workpiece W held in a hanging position by the clamp unit 18 of the first robot arm 12 is aligned with the recess 23 of the meat separator 22, the meat separator 22 is inserted into the slit formed in the workpiece W. When the workpiece W is sandwiched between the meat separator 22 and the meat pressing member 16 in this way, the clamp unit 18 is pulled up by the first robot arm 12, as shown by arrow Y2 in FIG. 3B , the meat portion 8 is separated from the workpiece W.

[0026] The meat separation processing station ST4 also includes an imaging device 24 for acquiring, as image data, the processing state of the workpiece W undergoing the meat separation processing. The image data acquired by the imaging device 24 is sent to the control device 100 and can be used for various processes described below. As will be described in detail below, if the processing state of the workpiece W is determined to be abnormal based on the image data acquired by the imaging device 24, a correction operation can be performed by making additional incisions using a cutter included in a tool 20 mounted on the tip of the second robot arm 14.

[0027] Returning to FIG. 1, the workpieces W that have undergone meat separation processing at the meat separation processing station ST4 are transported along the track 2 to the discharge station ST5. The discharge station ST5 is configured to discharge the workpieces W that have undergone meat separation processing to the outside. As will be described in detail later, the workpieces W that have undergone meat separation processing at the meat separation processing station ST4 are discharged via different transport paths depending on their processing status. This allows the workpieces W to be separated according to their processing status.

[0028] The meat processing apparatus 1 also includes a control device 100 for controlling each of these stations. The control device 100 is configured, for example, by a computer including a central processing unit, memory, an external storage device, an input device, and an output device. A control program for implementing a control method described below is also pre-installed in the control device 100, and various functions are realized by executing the control program. The various functions realized by the control device 100 will be described later with reference to Figure 5.

[0029] Next, a description will be given of a meat processing method that can be carried out using the meat processing apparatus 1 having the above configuration. Figure 4 is a flowchart showing a meat processing method according to one embodiment.

[0030] First, at the loading station ST1, the workpiece W is loaded onto the track 2 (step S100). The loaded workpiece W is transported along the track 2 to reach the measurement station ST2, where various pieces of information required for pre-processing are measured (step S101). In step S101, as described above, the shape and the like of the workpiece W are measured using, for example, an X-ray camera or a three-dimensional camera.

[0031] Next, in the pre-processing station ST3, pre-processing is performed on the workpiece W (step S102). In step S102, pre-processing including scoring and the like is performed using the measurement results from step S101, taking into consideration individual differences between the workpieces W. After the pre-processing is completed, the workpiece W is subjected to a meat separation process in the meat separation process station ST4, whereby the meat portion 8 is separated from the workpiece W (step S103). After the meat separation process, the workpiece W is discharged to the outside via a predetermined transport path depending on its processing state (step S104).

[0032] Next, the meat separation process performed in step S103 will be described in detail. Fig. 5 is a block diagram showing the configuration of the control device 100 shown in Fig. 1.

[0033] In Figure 5, the components of the control device 100 related to the meat separation process are shown as functional blocks, and the control device 100 includes an imaging data acquisition unit 102, a judgment unit 104, a post-processing operation determination unit 106, a first robot arm control unit 108, and a second robot arm control unit 110.

[0034] The imaging data acquisition unit 102 is configured to acquire imaging data of the workpiece W captured by the imaging device 24 (see FIG. 3) provided in the meat separation processing station ST4. The imaging device 24 captures an image of the workpiece W at any timing during the meat separation processing, and the captured image is digitized to create imaging data.

[0035] The determination unit 104 is configured to determine the processing state of the workpiece W based on the imaging data acquired by the imaging data acquisition unit 102. The determination unit 104 predicts the processing state of the workpiece W based on the imaging data acquired by the imaging data acquisition unit 102 through rule-based image analysis, and determines whether or not the processing state of the workpiece W is normal based on the prediction result. A learning model can also be used in determining the processing state in the determination unit 104. In this case, the imaging data acquired by the imaging data acquisition unit 102 is input into the learning model to predict the processing state of the workpiece W, and determines whether or not the processing state of the workpiece W is normal based on the prediction result.

[0036] The learning model is constructed by machine learning using training data that associates imaging data with processing states corresponding to the imaging data. Specifically, a large number of imaging data whose processing states have been specified in advance are prepared as training data, and a learning model that represents the correlation between the imaging data and the processing states is constructed using the training data.

[0037] In this embodiment, a processing state corresponding to imaging data is constructed based on at least one of rule-based image analysis and a learning model so that it can be predicted into one of multiple predefined classes A, B, .... Class A is a classification class corresponding to normal processing states. On the other hand, classes B and above are classification classes corresponding to abnormal processing states, and are subdivided to correspond to different processing states. The determination unit 104 predicts into which class the processing state of the workpiece W will be classified based on the imaging data acquired by the imaging data acquisition unit 102.

[0038] The post-processing operation determination unit 106 is configured to determine the post-processing operation to be performed on the workpiece W based on the determination result of the determination unit 104 when the meat separation process is performed in the meat separation process station ST4. As described above with reference to FIG. 3B , the meat portion 8 is separated from the workpiece W in the meat separation process. However, during this process, defects such as the meat portion 8 not being properly separated from the workpiece W may occur. Therefore, in the meat separation process station ST4, the quality of the workpiece W can be improved by performing post-processing operations according to the processing state of the workpiece W. In particular, when the determination unit 104 determines that the processing state of the workpiece W is abnormal, the quality of the meat separation process can be improved by performing post-processing operations including correction operations such as additional scoring or re-execution of the separation operation.

[0039] The relationship between the processing state of the workpiece W determined as a result of the determination by the determination unit 104 and the implementation details of the post-processing operation may be prepared in advance as post-processing operation data D. FIG. 6 shows an example of the post-processing operation data D that can be referenced by the post-processing operation determination unit 106 shown in FIG. 5. The post-processing operation data D is prepared as data that associates the classification class determined as a result of the determination by the determination unit 104 with the post-processing operation. In this example, a first operation is associated with class A as the post-processing operation. As described above, the processing state of class A is normal, so this first operation does not include a readjustment operation. A second operation is associated with each of classes B and higher as the post-processing operation. As described above, the processing state of class B and higher is abnormal, so this second operation includes a readjustment operation. This readjustment operation is defined as an operation required to improve the processing quality in the processing state corresponding to each class from class B onwards. As a result, even if the processing state of the workpiece W is classified as class B or higher, which is abnormal, the quality of the meat separation process can be effectively improved by performing a post-processing operation including a readjustment operation.

[0040] When the post-processing operation determination unit 106 determines the post-processing operation, the first robot arm control unit 108 and the second robot arm control unit 110 transmit control signals to the first robot arm 12 and the second robot arm 14 to realize the post-processing operation. As a result, the first robot arm 12 and the second robot arm 14 cooperate to perform the post-processing operation according to the processing state of the workpiece W.

[0041] Next, the meat separation process performed in step S103 will be described in more detail. Figures 7A and 7B are flowcharts showing a specific example of the meat separation process performed in step S103 of Figure 4, Figure 8A is a schematic diagram showing the processed state of the workpiece W when the first meat separation process is performed in step S201 of Figure 7A, Figure 8B is a schematic diagram showing the processed state of the workpiece W when the second meat separation process is performed in step S206 of Figure 7A, and Figure 8C is a schematic diagram showing the processed state of the workpiece W when the third meat separation process is performed in step S211 of Figure 7B.

[0042] In this embodiment, first, a slit serving as a starting point for meat separation is formed in the ankle of the workpiece W held in a hanging position by the clamp unit 18 (step S200). Then, as described above with reference to FIG. 3B, the clamp unit 18 is moved upward with the meat separator 22 inserted into the slit formed in step S200, thereby performing a first separation process (step S201). In the first separation process, as shown in FIG. 8A, meat portion 8 around the lower leg bone 6a of the workpiece W in a pre-processed state is partially separated (pulled off).

[0043] 8A as a result of the first meat separation process being performed (step S202), and the determination unit 104 determines whether the processing state of the workpiece W is normal or not based on the image data acquired in step S202 (step S203). If the processing state of the workpiece W in the first meat separation process is normal (step S203: YES), the post-processing operation determination unit 106 determines the first operation as the post-processing operation, and the first robot arm control unit 108 and the second robot arm control unit 110 send control signals for executing the first operation to the first robot arm 12 and the second robot arm 14, thereby performing the first operation that does not include a rework operation (step S204). The first action performed in step S204 may be no action.

[0044] On the other hand, if the processing state of the workpiece W in the first meat separation process is not normal (step S203: NO), the post-processing operation determination unit 106 determines a second operation as the post-processing operation, and the first robot arm control unit 108 and the second robot arm control unit 110 send control signals for executing the second operation to the first robot arm 12 and the second robot arm 14, thereby carrying out the second operation (step S205). This second operation may include, for example, an additional incision process performed as a repair operation for workpiece W that was not in a normal processing state when the first meat separation process was carried out, thereby improving the processing quality in the subsequent second meat separation process (step S206) and third meat separation process (step S211).

[0045] Next, the workpiece W that has been subjected to the first meat separation process is subjected to a second meat separation process (step S206). In the second meat separation process, as shown in Fig. 8B, meat separation is continued on the workpiece W from which meat portion 8 has been partially separated from around the lower leg bone 6a in the first meat separation process, so that meat portion 8 around the trochanter bone 6b is further separated (pulled off).

[0046] 8B as a result of the second meat separation process (step S207), and the determination unit 104 determines whether the processing state of the workpiece W is normal or not based on the imaging data obtained in step S207 (step S208). If the processing state of the workpiece W in the second meat separation process is normal (step S208: YES), the post-processing operation determination unit 106 determines the first operation as the post-processing operation, and executes the first operation, which does not include a reworking operation, by sending control signals for executing the first operation from the first robot arm control unit 108 and the second robot arm control unit 110 to the first robot arm 12 and the second robot arm 14 (step S209). The first action performed in step S209 may be no action.

[0047] On the other hand, if the processing state of the workpiece W in the second meat separation process is not normal (step S208: NO), the post-processing operation determination unit 106 determines the second operation as the post-processing operation, and the first robot arm control unit 108 and the second robot arm control unit 110 send control signals for executing the second operation to the first robot arm 12 and the second robot arm 14, thereby carrying out the second operation (step S210). In this second operation, for example, for workpiece W whose processing state when the second meat separation process was carried out was not normal, by including re-executing the peeling operation as a repair operation, the processing quality in the third meat separation process (step S11) carried out thereafter can be improved.

[0048] Next, a third meat separation process is performed on the workpiece W after the second meat separation process has been performed (step S211). In the third meat separation process, as shown in Fig. 8C, meat separation is performed on the workpiece W from which meat portion 8 has been partially separated from around the pelvic bone 6b in the second meat separation process, so that meat portion 8 around the femur bone 6c is further separated (pulled off).

[0049] 8C as a result of the third meat separation process being performed (step S212), and the determination unit 104 determines whether the processing state of the workpiece W is normal or not based on the imaging data acquired in step S212 (step S213). If the processing state of the workpiece W in the third meat separation process is normal (step S138: YES), the post-processing operation determination unit 106 determines the first operation as the post-processing operation, and executes the first operation, which does not include a reworking operation, by sending control signals for executing the first operation from the first robot arm control unit 108 and the second robot arm control unit 110 to the first robot arm 12 and the second robot arm 14 (step S214).

[0050] The first operation performed in step S214 includes discharging the workpiece W (i.e., the bone portion 6 and meat portion 8 after separation) that has undergone meat separation processing under normal processing conditions into appropriate discharge lanes (e.g., a discharge lane for the bone portion 6 that has been properly separated and a discharge lane for the meat portion 8 that has been properly separated) provided in the downstream discharge station ST5.

[0051] On the other hand, if the processing state of the workpiece W in the third meat separation process is not normal (step S213: NO), the post-processing operation determination unit 106 determines the second operation as the post-processing operation, and performs the second operation by sending control signals for executing the second operation from the first robot arm control unit 108 and the second robot arm control unit 110 to the first robot arm 12 and the second robot arm 14 (step S215). The second operation performed in step S215 includes an operation of discharging the workpiece W, for which meat separation processing has been performed in an abnormal processing state, to an appropriate discharge lane (for example, a discharge lane for improperly processed workpiece W) provided in the discharge station ST5 located downstream.

[0052] As described above, according to each of the above embodiments, the post-processing operation to be performed on the workpiece W is determined based on the processing state of the workpiece W determined based on the image data acquired in the meat separation process. By performing the post-processing operation determined in this manner on the workpiece in the meat separation process, it is possible to automatically perform a high-quality meat separation process.

[0053] (1) A meat processing device according to one aspect of the present invention includes: A meat processing apparatus for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, an imaging data acquisition unit for acquiring imaging data of the workpiece on which the meat separation process has been performed; a determination unit for determining a processing state of the workpiece based on the imaging data; a post-processing operation determination unit for determining a post-processing operation to be performed on the workpiece based on a determination result by the determination unit; Equipped with.

[0054] According to the above aspect (1), the processing state of the workpiece is determined based on the image data acquired during the meat separation process, and the post-processing operation to be performed on the workpiece is determined based on the determination result. By performing the post-processing operation determined in this way on the workpiece during the meat separation process, it is possible to automatically perform a high-quality meat separation process.

[0055] (2) In another embodiment, in the above embodiment (1), If the determining unit determines that the processing state is not normal, the post-processing operation includes a correction operation for the pre-processing.

[0056] According to the above aspect (2), if the processing state of the workpiece is determined to be abnormal based on the image data, post-processing operations including adjustment operations are performed. As a result, based on the determination result of the processing state of the workpiece to be subjected to the meat separation process, adjustment operations are performed as the post-processing operations to be performed next to normalize the processing state (or to approach normal), thereby suitably improving the quality of the meat separation process.

[0057] (3) In another embodiment, in the above embodiment (2), If the determining unit determines that the processing state is normal, the post-processing operation does not include the repair operation.

[0058] According to the above aspect (3), when the processing state of the workpiece is determined to be normal based on the image data, post-processing operations that do not include adjustment operations are performed. This simplifies the post-processing operations compared to when the processing state of the workpiece is determined to be abnormal, thereby shortening the time required for meat separation processing and suitably improving productivity.

[0059] (4) In another embodiment, in any one of the above (1) to (3), The determination unit determines the processing state corresponding to the imaging data using at least one of rule-based image analysis or a learning model constructed using training data that associates the imaging data with the processing state corresponding to the imaging data.

[0060] According to the above aspect (4), the processing state corresponding to the image data is obtained using at least one of rule-based image analysis and learning model. These methods allow the real-time processing state of the workpiece to be appropriately determined, and the post-processing operation can be appropriately determined based on the determination result. When a learning model is used, the learning model may be constructed by performing machine learning using training data that associates imaging data with processing states, for example.

[0061] (5) In another embodiment, in the above embodiment (4), the determination unit classifies the processing state corresponding to the imaging data into one of a plurality of classes defined in advance for each processing state using the learning model; The post-processing operation determination unit determines, as the post-processing operation, an operation that is associated in advance with the class classified by the determination unit.

[0062] According to the above aspect (5), the learning model is constructed to classify the processing state corresponding to the image data into one of a plurality of predefined classes. As a result, the determination unit determines which class the image data acquired using the learning model belongs to, and determines an operation previously associated with the determined class as the post-processing operation, thereby enabling the selection of an appropriate post-processing operation according to the processing state of the workpiece.

[0063] (6) In another embodiment, in any one of the above (1) to (5), The meat separation process includes: a first separation process for partially separating a meat portion from the workpiece; a second separation process for further separating the meat portion from the workpiece on which the first separation process has been performed; Including, The determination unit determines the processing state based on the imaging data of the workpiece on which the first separation processing has been performed, and the post-processing operation determination unit determines the post-processing operation to be performed on the workpiece between the first separation processing and the second separation processing based on the determination result, The judgment unit judges the processing state based on the imaging data of the work on which the second separation processing has been performed, and the post-processing operation determination unit determines the post-processing operation to be performed after the second separation processing based on the judgment result.

[0064] According to the above aspect (6), the meat separation process performed on the workpiece is performed in stages, including a first separation process and a second separation process. In this case, the processing state when the first separation process is performed is determined based on the imaging data, and the post-processing operation to be performed between the first separation process and the subsequent second separation process is determined based on the determination result. Thereafter, the processing state when the second separation process is performed is similarly determined based on the imaging data, and the post-processing operation to be performed after the second separation process is determined based on the determination result. When the meat separation process is performed in stages in this way, the processing state is determined based on the imaging data acquired as the processing stage progresses, and the post-processing operation to be performed before proceeding to the next processing stage is appropriately determined, thereby enabling high-quality meat separation processing to be performed.

[0065] (7) In another embodiment, in any one of the above (1) to (6), The pre-processing is a process for making incisions in the workpiece, The meat separation process is a process for separating the meat portion on the other end side of the workpiece from the workpiece while supporting one end side of the workpiece.

[0066] According to the above aspect (7), the workpiece to be subjected to the meat separation process is scored as a pre-processing. The scored workpiece is subjected to the meat separation process by separating the meat portion at the other end while supporting one end.

[0067] (8) In another embodiment, in any one of the above (1) to (7), Based on the determination result of the determination unit, the discharge path of the workpiece for which the post-processing operation has been performed can be switched.

[0068] According to the above aspect (8), by switching the discharge path of the workpieces depending on the processing state of the workpieces determined based on the imaging data, it is possible to separate the workpieces according to their processing state.

[0069] (9) A meat processing method according to one embodiment includes: A meat processing method for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, A step of acquiring imaging data of the workpiece on which the meat separation process has been performed; A step of determining a processing state of the workpiece based on the imaging data; determining a post-processing operation to be performed on the workpiece based on the determination result of the processing state; Equipped with.

[0070] According to the above aspect (9), the processing state of the workpiece is determined based on the image data acquired during the meat separation process, and the post-processing operation to be performed on the workpiece is determined based on the determination result. By performing the post-processing operation determined in this way on the workpiece during the meat separation process, it is possible to automatically perform a high-quality meat separation process. [Explanation of symbols]

[0071] 1 Meat processing equipment 2 orbits 6 Bones 6a Lower leg bone 6b Disc bone 6c femur 8 Meat part 10 Transport conveyor 12 First robot arm 14 Second Robot Arm 16 Meat holding member 18 Clamp section 20 Tools 22 Meat Separator 23 Recess 24 Imaging device 100 control device 102 Imaging data acquisition unit 104 Judgment section 106 Post-processing operation decision unit 108 First robot arm control unit 110 Second robot arm control unit D Post-processing operation data ST1 Input Station ST2 Measuring Station ST3 Pre-treatment Station ST4 Meat Separation Processing Station ST5 Discharge Station double work

Claims

1. A meat processing apparatus for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, an imaging data acquisition unit for acquiring imaging data of the workpiece on which the meat separation process has been performed; a determination unit for determining a processing state of the workpiece based on the imaging data; a post-processing operation determination unit for determining a post-processing operation to be performed on the workpiece based on a determination result by the determination unit; A meat processing device comprising:

2. The meat processing apparatus according to claim 1 , wherein, when the determining unit determines that the processing state is not normal, the post-processing operation includes a correction operation for the pre-processing.

3. The meat processing apparatus according to claim 2 , wherein the post-processing operation does not include the adjustment operation when the determining unit determines that the processing state is normal.

4. 3. The meat processing apparatus according to claim 1, wherein the determination unit determines the processing state corresponding to the imaging data using at least one of rule-based image analysis and a learning model constructed using teacher data that associates the imaging data with the processing state corresponding to the imaging data.

5. the determination unit classifies the processing state corresponding to the imaging data into one of a plurality of classes defined in advance for each processing state using the learning model; The meat processing apparatus according to claim 4 , wherein the post-processing operation determination unit determines, as the post-processing operation, an operation that is previously associated with the class classified by the determination unit.

6. The meat separation process includes: a first separation process for partially separating a meat portion from the workpiece; a second separation process for further separating the meat portion from the workpiece on which the first separation process has been performed; Including, The determination unit determines the processing state based on the imaging data of the workpiece on which the first separation processing has been performed, and the post-processing operation determination unit determines the post-processing operation to be performed on the workpiece between the first separation processing and the second separation processing based on the determination result, 3. The meat processing apparatus according to claim 1, wherein the judgment unit judges the processing state based on the imaging data of the work on which the second separation process has been performed, and the post-processing operation determination unit determines the post-processing operation to be performed after the second separation process based on the judgment result.

7. The pre-processing is a process for making incisions in the workpiece, 3. The meat processing apparatus according to claim 1, wherein the meat separating process is a process for separating the meat portion on the other end side of the work from the work while supporting one end side of the work.

8. The meat processing apparatus according to claim 1 or 2, wherein a discharge path for the workpieces for which the post-processing operation has been performed is switchable based on the determination result of the determination unit.

9. A meat processing method for performing a meat separation process on a workpiece that is bone-in meat that has been pre-processed in advance, A step of acquiring imaging data of the workpiece on which the meat separation process has been performed; A step of determining a processing state of the workpiece based on the imaging data; determining a post-processing operation to be performed on the workpiece based on the determination result of the processing state; A meat processing method comprising:

Images