DK181011B1 - Digital process monitoring - Google Patents
Digital process monitoring Download PDFInfo
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- DK181011B1 DK181011B1 DKPA202100752A DKPA202100752A DK181011B1 DK 181011 B1 DK181011 B1 DK 181011B1 DK PA202100752 A DKPA202100752 A DK PA202100752A DK PA202100752 A DKPA202100752 A DK PA202100752A DK 181011 B1 DK181011 B1 DK 181011B1
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- 238000000034 method Methods 0.000 title claims abstract description 128
- 238000012544 monitoring process Methods 0.000 title description 2
- 238000004458 analytical method Methods 0.000 claims abstract description 27
- 238000004886 process control Methods 0.000 claims abstract description 16
- 238000012545 processing Methods 0.000 claims description 19
- 238000005520 cutting process Methods 0.000 claims description 10
- 239000002994 raw material Substances 0.000 claims description 10
- 238000004891 communication Methods 0.000 claims description 7
- 210000000664 rectum Anatomy 0.000 claims description 5
- 238000003307 slaughter Methods 0.000 claims description 5
- 241001465754 Metazoa Species 0.000 claims description 4
- 210000000481 breast Anatomy 0.000 claims description 4
- 235000013622 meat product Nutrition 0.000 claims description 4
- 238000005553 drilling Methods 0.000 claims description 3
- 238000003860 storage Methods 0.000 claims description 2
- 238000003776 cleavage reaction Methods 0.000 claims 2
- 230000007017 scission Effects 0.000 claims 2
- 210000004720 cerebrum Anatomy 0.000 claims 1
- 238000003384 imaging method Methods 0.000 description 5
- 238000004519 manufacturing process Methods 0.000 description 5
- 238000013473 artificial intelligence Methods 0.000 description 4
- 210000004124 hock Anatomy 0.000 description 4
- 238000003070 Statistical process control Methods 0.000 description 3
- 238000013135 deep learning Methods 0.000 description 3
- 235000013305 food Nutrition 0.000 description 3
- 210000004556 brain Anatomy 0.000 description 2
- 230000007547 defect Effects 0.000 description 2
- 238000003745 diagnosis Methods 0.000 description 2
- 238000010801 machine learning Methods 0.000 description 2
- 241000251468 Actinopterygii Species 0.000 description 1
- 241000283690 Bos taurus Species 0.000 description 1
- 241000287828 Gallus gallus Species 0.000 description 1
- 102100030624 Proton myo-inositol cotransporter Human genes 0.000 description 1
- 101710095091 Proton myo-inositol cotransporter Proteins 0.000 description 1
- 241000282849 Ruminantia Species 0.000 description 1
- 241000282887 Suidae Species 0.000 description 1
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000013459 approach Methods 0.000 description 1
- 235000015278 beef Nutrition 0.000 description 1
- 230000015556 catabolic process Effects 0.000 description 1
- 210000000038 chest Anatomy 0.000 description 1
- 238000004040 coloring Methods 0.000 description 1
- 210000005069 ears Anatomy 0.000 description 1
- 210000003128 head Anatomy 0.000 description 1
- 238000010191 image analysis Methods 0.000 description 1
- 235000013372 meat Nutrition 0.000 description 1
- 239000007858 starting material Substances 0.000 description 1
- 210000003371 toe Anatomy 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/0002—Inspection of images, e.g. flaw detection
- G06T7/0004—Industrial image inspection
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
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- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06T—IMAGE DATA PROCESSING OR GENERATION, IN GENERAL
- G06T7/00—Image analysis
- G06T7/20—Analysis of motion
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- Tourism & Hospitality (AREA)
- Entrepreneurship & Innovation (AREA)
- Quality & Reliability (AREA)
- General Business, Economics & Management (AREA)
- Computer Vision & Pattern Recognition (AREA)
- Operations Research (AREA)
- Multimedia (AREA)
- Primary Health Care (AREA)
- Health & Medical Sciences (AREA)
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Abstract
This invention relates to a method for performing process control in a slaughterhouse, which method comprises a pre- and a post-process control with respect to an overall process, or to an integral, or sub-process, hereof, and which method is based on the use of a vision device, followed by analysis of the obtained results.
Description
DK 181011 B1 1
TECHNICAL FIELD This invention relates to a method for performing process control in a slaughterhouse, which method comprises a pre- and a post-process control with respect to an overall process, or to an integral, or sub-process, hereof, and which method is based on the use of a vision device, followed by an analysis of the obtained results.
BACKGROUND ART Slaughterhouse processes are constantly challenged, making it essential to work agile. Faults and breakdowns at the slaughterhouse are the cause of reduced production capacity, quality defects and reduced yields. Fewer quality defects and better utilisation of the carcass result in more sustainable production and reduced climate footprint.
There are great demands for uptime and efficient utilisation of the production apparatus, at the same time as a need to be able to act agile based on production data. During the slaughter process, processes can fail because the equipment is out of control.
However, it can also be due to previous process errors, or because the carcass is out of specification.
There is a need for ongoing system monitoring, so that the status and capability of the process or its elements can be proactively monitored.
EP1939811 discloses a method for associating source information for a source unit with a product converted therefrom, which method comprises the use of a computer system and imaging sensors that capture image data of a carcass, as it moves through a processing facility and is converted into individual food products.
EP2923305 discloses a method for scoring and controlling the quality of a plurality of moving food products, which method comprises image capturing of the incoming food products, and image analysis of the recorded data.
However, the method of the present invention for performing process control in a slaughterhouse has never been disclosed or suggested.
SUMMARY OF THE INVENTION The present invention discloses a method for performing process control in a slaughterhouse, which method comprises a pre- and a post-process control with respect
DK 181011 B1 2 to an overall process, or to an integral, or sub-, process hereof, using a vision device in communication/operation with a processing means.
The method of the invention offers solutions to various process challenges, and allows statistical treatment of the process in question, e.g., number of errors, error frequency, etc. The present method also provides for a verification if the equipment is in order, and also allows for diagnosis of the process equipment and indicate on which part of the equipment it has gone wrong.
The method further offers the opportunity to check for errors associated with the raw material and allows for adjustment of the process based on input control, and an analysis of whether the raw material, e.g., the incoming pig, is suitable for being processed as planned, and the method offers feed-back to the process operator.
The method also allows for identification of human or manual errors.
The method of the invention also may prevent incorrect production, e.g., reduced yield, reduced quality, etc., and allows to correct errors associated with the choice of starting material and the intended processing of the raw material.
Moreover, the method of the invention allows for equipment diagnosis and statistical process control, as well as check for manual processing errors, and enables feedback - to the database and/or to the process operator.
The method of the invention is based on image capturing and computation of the acquired image data using algorithms for control of manual or automatic processes or equipment.
Other objects of the invention will be apparent to the person skilled in the art from reading the following detailed description and accompanying drawings.
Any combination of two or more of the embodiments described herein is considered within the scope of the present invention.
BRIEF DESCRIPTION OF THE DRAWINGS The present invention is further illustrated by reference to the accompanying drawing, in which, Fig. 1 shows an example of a system used in the method of the invention: Starting product/incoming carcass (1A); Processed product/decapitated carcass (1B); Pre-process vision device/camera (2A); Post-process vision device/camera (2B); Pre-process processor (3A); Post-process processor (3B); Processing equipment/head cutting tool (5).
DK 181011 B1 3
DETAILED DISCLOSURE OF THE INVENTION The present invention provides a method for performing process control in a slaughterhouse, processing animals for slaughter and meat items (1), which method comprises a pre- and a post-process control with respect to an overall process, or to an integral, or sub-, process hereof, using a vision device (2) in communication/operation with one or more processing means (3).
The method of the invention may be characterised by comprising the subsequent steps of: i. subjecting a starting product/raw material (1A) to analysis by use of the vision device (2), and transmitting/communicating the obtained results to a means for storing information (4); ii. subjecting the processed product (1B) to analysis by use of the vision device (2), and transmitting/communicating the obtained results to a means for storing information (4); iii. using the results of the pre-process analyses obtained according to step i to determine whether the process should have been successful, and, using the results of the post-process analyses obtained according to step ii, to determine whether the process has actually been successful; and iv. comparing the occurrence of instances where the post process control performed according to step ii, has failed in instances where the product/raw material is analysed, according to step i, as being suitable for the process, with a statistical discriminator that determines when to consider the process as out of control.
When determining, according to the pre-process control step i, whether the process is predicted and expected to be able to run and be completed successfully, and, according to the post-process control step ii, whether the process has been successfully completed, the analysis may, in particular, be based on reference data obtained from a product specification, and this product specification should be accessible to the processing means (3).
In one embodiment, in step ii according to the method of the invention, the processed product is analysed for compliance with a product specification.
In another embodiment, the method of the invention may be applied to the process of placing the incoming pig on the gambrel/hanger and to performing an analysis of correct placement of the carcass.
In a third embodiment, the method of the invention is applied to the process of bung handling/loosening of the rectum, and to performing an analysis of the drilling of the rectum.
DK 181011 B1 4 In a fourth embodiment, the method of the invention is applied to the process of splitting the breast, and to performing an analysis of the splitting.
In a fifth embodiment, the method of the invention is applied to the process of cutting along the spine, and to performing an analysis of the cutting.
In a sixth embodiment, the method of the invention is applied to the process of cleaving the carcass, and to an analysis of the spinal canal, of the brain halves, and of the tail.
Statistical discriminators The method of the invention involves the identification of processes that are assumed to run smoothly, but still did not proceed as expected.
When analysing the obtained results, and comparing, according to step iv, the occurrence of instances where the post process control performed according to step ii, has failed in instances where the product/raw material analysed, according to step i, as suitable for the process, this analysis shall be based/associated with a statistical discriminator that determines when to consider the process as out of control.
Examples of statistical discriminators include any occurrence, even just one instance, where the process has failed, even though it should be able to proceed successfully.
Alternatively, statistical discriminators contemplated according to the invention include instances, e.g., X cases in a row (X being e.g., 2-8, 3-7, 4-6, etc.), or frequencies, e.g., Y out of 100 cases (Y being e.g., more than 5, more than 10, more than 20, more than 30, etc.), that should be able to run successfully, but did not go well.
Moreover, statistical discriminators contemplated according to the invention include, e.g., changes in the error rate over time, or deviation or drift from a normal rate, e.g., from 10% to 12%, or the observation of greater variance.
Process control may be monitored using various Statistical Process Control (SPC) tools, that also can determine whether a process is in or out of control. When points on a control chart move outside the upper or lower control Hmit, the process is said to be ”out of control” As long as the points are within control limits, the process is considered Sin control.” Qut of control incidents may include instances where the process equipment is out of alignment or is broken, or, in case of a manual process, include instances where a process regulation has not been followed, The starting product/raw material The starting product/raw material contemplated according to the invention may be any animal intended for slaughter, e.g., fattening pigs, broilers, beef cattle or other
DK 181011 B1 ruminants for human consumption, or it may be fish, and/or any products or sub- products hereof.
In one embodiment, the method of the invention may be applied to control of the method of removing tenderloin.
5 In another embodiment, the method of the invention may be applied to control of the method of cutting of heads, toes, ears, and/or jaw removal.
Other embodiments of the method of the invention include three-splitting of the carcass, point-back sawing, middle splitting of chest and comb, and/or derinding.
When considering the process of three-splitting of the carcass, the post-process analyses obtained according to step ii, may include an analysis of the various cut surfaces.
Examples of process steps to become subject to analysis according to the invention include, e.g.: Placement of the incoming pig on the gambrel/hanger: Is the carcass placed correctly on the gambrel; Are the hinge joints and hooks intact; Is the stab in the hock made correctly.
Bung handling/loosening of the rectum: Checking whether the right place has been drilled; Checking if drilling is correct.
Splitting of the breast: Checking that the start of the splitting is done in the right place; Check that the splitting has been carried out correctly.
Cutting along the spine: Checking whether the breast is straight, and that the subsequent manual procedures up to the cutting are OK; Check that the cutting has been carried out correctly.
Cleaving the carcass: Checking that the spinal canal is exposed along the entire length of the carcass; Checking that both brain halves remain in the head; Checking that the tail is not damaged. The vision device The vision device (2) for use according to the invention typically comprises a camera with a lens, an image sensor, a vision processing means, and communication means. Optionally the vision system for use according to the invention also include lighting means.
The vision device (2) for use according to the invention shall be in communication with the processing means (3).
The cameras for use according to the invention may be any suitable camera/area- scan camera, e.g., a monochrome camera, a colour camera (RGB), multispectral camera (e.g., including both visible and infrared wavelengths), or a 3C/depth camera (e.g., a time-of-flight camera or a stereo camera system).
DK 181011 B1 6 The means for storing information The method of the invention comprises steps wherein data obtained by use of the vision device (2) is transmitted or communicated to a means for storing information (4).
The means for storing information (4) for use according to the invention may be any media intended or suited for storage of digital information and may include the hard desk of the processing means (3) used according to the invention, or its memory (RAM), and/or, from an external hard desk, server, or central database.
The processing means For computing data obtained from the vision device (2), and, optionally, for communication with a means for storing information (4), the method of the invention comprises the use of one or more processing means (3).
The processing means (3) for use according to the invention may be any available computation device (e.g., GPU, CPU, PLC, and/or PC), in operation with, and capable of receiving and processing data obtained from the vision device (2). Artificial Intelligence (AI) applications/algorithms For performing the various analysis included in the method of the invention, different algorithms can be used, incl. self-learning algorithms and deep learning algorithms.
The imaging devices (4) for use according to the invention shall be an adaptive imaging system, based on the use of artificial intelligence (AI). The imaging system must be robust and capable of detecting e.g., meat products with a large biological variation. Robustness is gradually improved through self-learning.
In the context of this invention, and in accordance with established terminology, an Artificial Intelligence (AI) application/algorithm covers machine learning and deep learning algorithms.
Machine learning is an application of artificial intelligence (AI) which use statistical techniques to perform automated decision-making, and optionally improve performance on specific tasks based on experience without being explicitly programmed.
Several approaches to machine leaning exists, e.g., supervised learning, reinforced learning, imitation learning and un-supervised learning.
In supervised learning, the computer may be presented with example inputs and their desired outputs, as given by the supervisor, and the goal is to learn a general rule that maps inputs to outputs. Using large sets of reference data, covering different product types, along with the desired output for each element in the data sets, a supervised learning algorithm is trained to learn a general rule that maps inputs to outputs.
DK 181011 B1 7 As data is building up, the precision and robustness of the system increases, but occasionally, e.g., caused by quality errors or recognition errors, manual assistance may be needed, for additional training of the system. Carcasses and meat products are characterized by large variation in physical appearance. This variation comes from biological variation as well as machine and/or operator induced variations from previous stages in the processing. The variation is characterized not only by differences between different types of products, but in particular by differences between products of the same type, e.g., in deformation, flexibility, colouring, shape, size, surface texture (e.g., wet, greasy, icy).
The vision system for use according to this invention may comprise both state- of-the-art and custom designed deep learning algorithms for detecting objects and positions in the images, combined in a way which meets the capacity requirements.
List of reference signs This is a listing of various elements relating to the present invention and shown in the appended figures. Alternative/synonymous designations are separated by slashes.
1. Work piece/animal for slaughter/meat product 1A. Starting product 1B. Processed product
2. Vision device/imaging device/camera 2A. Pre-process vision device/camera 2B. Post-process vision device/camera
3. Processing means 3A. Pre-process processor 3B. Post-process processor 4, Means for storing information/hard desk/server/central database
5. Processing equipment (head cutting tool)
Claims (7)
Priority Applications (3)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DKPA202100752A DK181011B1 (en) | 2021-07-09 | 2021-07-09 | Digital process monitoring |
| EP22741172.5A EP4367612A1 (en) | 2021-07-09 | 2022-06-27 | A method for digital process monitoring in a slaughterhouse |
| PCT/EP2022/067469 WO2023280606A1 (en) | 2021-07-09 | 2022-06-27 | A method for digital process monitoring in a slaughterhouse |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| DKPA202100752A DK181011B1 (en) | 2021-07-09 | 2021-07-09 | Digital process monitoring |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| DK181011B1 true DK181011B1 (en) | 2022-09-21 |
| DK202100752A1 DK202100752A1 (en) | 2022-09-21 |
Family
ID=82494084
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| DKPA202100752A DK181011B1 (en) | 2021-07-09 | 2021-07-09 | Digital process monitoring |
Country Status (3)
| Country | Link |
|---|---|
| EP (1) | EP4367612A1 (en) |
| DK (1) | DK181011B1 (en) |
| WO (1) | WO2023280606A1 (en) |
Family Cites Families (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| ES2167841T3 (en) * | 1997-05-06 | 2002-05-16 | Slagteriernes Forskningsinst | METHOD AND APPARATUS FOR CHANNEL EVISCERATION. |
| US7949154B2 (en) | 2006-12-18 | 2011-05-24 | Cryovac, Inc. | Method and system for associating source information for a source unit with a product converted therefrom |
| US9014434B2 (en) | 2012-11-26 | 2015-04-21 | Frito-Lay North America, Inc. | Method for scoring and controlling quality of food products in a dynamic production line |
| US10117438B2 (en) * | 2016-10-28 | 2018-11-06 | Jarvis Products Corporation | Beef splitting method and system |
| DK180199B1 (en) * | 2018-12-17 | 2020-08-13 | Teknologisk Inst | Cellular meat production |
-
2021
- 2021-07-09 DK DKPA202100752A patent/DK181011B1/en active IP Right Grant
-
2022
- 2022-06-27 WO PCT/EP2022/067469 patent/WO2023280606A1/en active Application Filing
- 2022-06-27 EP EP22741172.5A patent/EP4367612A1/en active Pending
Also Published As
| Publication number | Publication date |
|---|---|
| WO2023280606A1 (en) | 2023-01-12 |
| EP4367612A1 (en) | 2024-05-15 |
| DK202100752A1 (en) | 2022-09-21 |
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