CN111445168A - Quality safety third-party supervision system and method - Google Patents
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Abstract
The invention relates to a quality safety third-party supervision system and a quality safety third-party supervision method. By means of a sensing technology, a digital twin technology and a virtual reality technology, a standardized supervision bionic model of a key control point of a supervision object is constructed, supervision element data such as 'human, machine, material, law, ring' and the like are collected through a camera module, a sensor module, manual input and the like of a processing place and are compared with the standardized supervision bionic model, real-time, remote and multi-port operation review of the processing place by a supervision mechanism is realized, a review result without any dispute is obtained, and the purpose of objectively evaluating the quality safety state of the supervision object is achieved. The method can be used for objective and notarization remote supervision and audit of production and processing environment, production and processing process, employee operation, production resource quality and file management, and is applied to law enforcement supervision, third party supervision, quality system authentication, quality system operation review, enterprise quality safety control, large consumer ecology access review and the like.
Description
Technical Field
The invention relates to quality safety supervision, in particular to a quality safety third-party supervision system and a quality safety third-party supervision method, which are widely applied to the field of quality supervision of factory-type products, food, medicines and the like.
Background
The third-party supervision is a public service provided by non-benefit stakeholders, and along with the development of the economic society of China, the quality safety third-party supervision is developed into a tool for improving a national treatment system and strengthening the national treatment capability.
The third party supervision implements on-site review based on supervision element information such as 'people, machines, materials, methods, rings' and the like on the production and processing processes of the supervised object from three levels of 'source control, process management and identification management'. Traditional third party oversight has focused on capturing regulatory information from the field and making review conclusions based on the perception of the field. The disadvantages are as follows: the system is seriously dependent on the knowledge, experience and professional operation of people, and the service cost is high.
The digital twin technology and the virtual reality technology can establish a supervision model through supervision parameters, and a third party supervision model based on the digital twin technology can virtualize the requirement for evaluation and the actual operation of production and processing of customers, so that by means of the digital twin technology, a third party supervision mechanism can realize remote evaluation and achieve the purpose of subverting the traditional service mode.
Disclosure of Invention
The invention aims to provide a quality safety third-party supervision system and method based on a digital twin technology and a remote real-time quality safety supervision method. The method comprises the steps of firstly establishing a standardized supervision bionic model of a key control point of a supervised object, acquiring supervision element data such as 'people, machines, materials, methods and rings' by means of a camera module, a sensor module, manual input and the like of a processing place, comparing the data with the standardized supervision bionic model, realizing real-time, remote and multi-port operation review of the processing place by a supervision mechanism, obtaining a review result which is objective, fair and free of any dispute, and achieving the purpose of objectively evaluating the quality safety state of the supervised object.
In order to achieve the above purpose, the invention constructs a quality safety third-party supervision system based on the supervision element parameters of human, machine, material, law and ring, and the system comprises: a collecting unit, an arithmetic unit and a display unit,
the acquisition unit is used for acquiring a supervision element parameter module comprising human, machine, material, method and ring on the side of a real production scene and feeding back the supervision element parameter module to the operation unit;
the operation unit comprises a standardized bionic supervision model construction module, an automatic refreshing module, a system review module, a difference marking module, a data storage module and a risk warning module;
and the display unit displays the results output by each module in the operation unit.
Preferably, the acquisition unit comprises front-end acquisition equipment and a P L C control module, the front-end acquisition equipment transmits acquired data to the P L C control module, the processed data of the P L C control module are output to the arithmetic unit, and the front-end acquisition equipment comprises a sensing module, a camera module and a manual input end;
preferably, the module for collecting supervision element parameters of "people, machines, materials, methods and rings" includes a "people" parameter module, a "machines" parameter module, a "materials" parameter module, a "methods" parameter module and a "rings" parameter module, wherein:
the "human" parameter module includes but is not limited to data on human health, hygiene requirements, human operation, etc.;
the 'machine' parameter module comprises but is not limited to the data of the operation state, the maintenance state, the cleaning and the disinfection of the facility equipment, etc.;
the material parameter module comprises but is not limited to data such as traceability bar code information, high-risk toxic and harmful factor monitoring and the like;
the 'method' parameter module comprises but is not limited to data such as processes, standard procedures, product operation standards, inspection standards and the like;
the "ring" parameter module includes but is not limited to data such as cleanliness, illuminance, temperature and humidity, cleanliness, foreign matter and living things (mice, flies, insect pests and metals), air quality index and the like.
Preferably, the display unit displays the monitored dynamic record on any one or more of a VR display device, an AR display device, a digital billboard, a PC and a mobile phone APP through a virtual reality technology or a 3D animation technology.
The invention also provides a quality safety third-party supervision method, which is characterized by comprising the following steps:
constructing a standardized bionic supervision model by using a supervision element parameter module of an ideal state 'human, machine, material, method and ring';
based on the 'human, machine, material, law, ring' supervision element parameter module data of the supervision object collected in the production and processing field, the virtual reality of the supervision object is twinned and compared with the standard bionic model;
by updating data in real time and repeatedly comparing for many times, intelligent evaluation, difference marking and warning risk are realized, and output results are displayed on a display terminal.
Preferably, in the intelligent review, the review module of the digital twin server intelligently analyzes and evaluates the digital twin supervision model and the standard supervision model, and performs related marking according to the difference.
Preferably, the warning risk is divided into an acceptable risk, a suspicious risk and an unacceptable risk.
Preferably, the display terminal displays the monitored dynamic record on any one or more of VR, AR display equipment, digital signage, PC and mobile phone APP through a virtual reality technology or a 3D animation technology.
Preferably, the "human, machine, material, law, ring" supervision element parameter module includes a "human" parameter module, a "machine" parameter module, a "material" parameter module, a "law" parameter module, and a "ring" parameter module, wherein:
the human parameter module comprises human health, sanitary requirements and human operation data;
the 'machine' parameter module comprises the running state, the maintenance state and the cleaning and disinfection data of facility equipment;
the material parameter module comprises traceability bar code information and high-risk toxic and harmful factor monitoring data;
the 'method' parameter module comprises a process, a standard procedure, a product operation standard and inspection standard data;
the 'ring' parameter module comprises cleanliness, illuminance, temperature and humidity, cleanliness, foreign matter living objects (mice, flies, insect pests and metals) and air quality index data.
Preferably, the supervision method specifically comprises the following steps:
s1, constructing a standardized supervision bionic model by using the ideal state parameters of human, machine, material, method and ring supervision elements;
s2, installing a collection facility of 'human, machine, material, law and loop' parameters at the supervision client;
s3, refreshing the standard model constructed in S1 by the 'human, machine, material, method and ring' parameter of the supervising client to form the initial state of the supervising client;
s4, repeatedly refreshing the initial state of the supervision client by using the real-time parameters of the supervision client 'human, machine, material, method and ring';
s5, marking the difference between the supervision client 'people, machines, materials, methods and rings' and the standard supervision model;
s6, the system reviews the difference between the supervision client 'people, machines, materials, methods and rings' and the standardized supervision model to form risk warning;
and S7, automatically generating product traceability marks according to the human, machine, material, law and ring evaluation results of the supervision customers, and intelligently managing according to the analysis test results, the public crisis information and the customer complaint information of the finished products.
The invention also provides a remote real-time quality supervision method, which comprises the following steps:
1) checking various parameters of production operation in real time through one or more simulation models presented by VR, AR display equipment, a digital billboard, a PC and an APP;
2) when the parameter information contained in the actual production environment, namely 'man, machine, material, method and ring', changes, the digital twin server can update the corresponding digital twin supervision simulation model in real time and automatically generate an evaluation result;
3) when a certain parameter, which can be manually input, captured by a camera module or acquired by a sensor, exceeds the standard range of the parameter of the monitored object, the system automatically marks the difference, evaluates the difference, immediately generates an alarm signal to assist a manager to quickly locate the problem or prompt the supervisor to pay attention.
From the above, the following beneficial effects can be obtained by applying the technical scheme provided by the invention:
(1) remote evaluation of the processing field;
(2) centralizing quality safety supervision;
(3) the quality safety risk early warning is automated;
(4) product traceability management is intelligent;
(5) and the quality safety crisis management is precise.
Drawings
FIG. 1 is a block diagram of a monitoring system according to an embodiment of the present invention;
FIG. 2 is a diagram of a front-end acquisition device according to an embodiment of the present invention;
FIG. 3 is a flow chart of steps of creating a digital twin supervisory model according to an embodiment of the present invention;
FIG. 4 is a risk assessment system diagram according to an embodiment of the present invention.
Detailed Description
In order that those skilled in the art can understand and implement the present invention, the following embodiments of the present invention will be further described with reference to the accompanying drawings.
In order to solve the problems of the existing quality safety supervision, the food safety third party safety supervision is taken as an example below. An intelligent supervision model is constructed based on a digital twin technology, and the quality safety of the example product is monitored in real time through intelligent supervision and evaluation of the elements of human, machine, material, law and ring of a supervision object.
Referring to fig. 1 and 2, the present invention provides a quality-safe third-party supervision system, including an acquisition unit 1: collecting supervision element parameters including human, machine, material, law, ring and the like on the side of a real production scene;
arithmetic unit 2 (digital twin server): by means of a digital twin technology and a virtual reality technology, a standardized bionic supervision model is constructed by using supervision element parameters of 'human, machine, material, method and ring' in an ideal state. Based on the supervision element data of 'people, machines, materials, methods, rings' and the like of the supervision object collected in the production and processing field, the virtual reality of the supervision object is twin, and is compared with the standard bionic model. Through real-time data, repeated comparison is carried out for many times, and intelligent evaluation, difference marking and warning risks are achieved.
The display unit 3: through virtual reality technology and 3D technique, present real-time digital twin supervision state at VR, AR display device, digital billboard, PC and APP.
The acquisition unit 1 comprises a front-end acquisition device 11 and a P L C control module 12, the front-end acquisition device 11 transmits acquired data to the P L C control module 12, the P L C control module 12 outputs the processed data to the arithmetic unit 2, and the front-end acquisition device 11 comprises a sensing module 111, a camera module 112 and an artificial input end 113.
Wherein, the supervision element parameter module for collecting the 'people, machines, materials, methods and rings' comprises a 'people' parameter module 101, a 'machines' parameter module 102, a 'materials' parameter module 103, a 'methods' parameter module 104 and a 'rings' parameter module 105, wherein:
the "people" (R) parameter module 101: including r1 personnel health, r2 sanitary requirements, r3 personnel operations, etc.
"machine" (J) parameter module 102: the j1 facility equipment running state, j2 maintenance state, j3 cleaning and disinfecting and other data, the main equipment comprises:
water supply and drainage facilities, cleaning and disinfection facilities, waste storage facilities, personal hygiene facilities, ventilation facilities, lighting facilities and temperature control facilities.
The material (L) parameter module 103 comprises data such as l1 traceability bar code information, l2 high-risk toxic and harmful factor monitoring data and the like.
The "method" (F) parameter module 104: the method comprises the following steps: f1 process, f2 standard procedure, f3 product operation standard, f4 inspection standard and the like.
The "Ring" (H) parameter module 105: h1 cleanliness, h2 illuminance, h3 temperature and humidity, h4 cleanliness, h5 foreign matter living things (mice, flies, insect pests and metals), h6 air quality index and the like, wherein the parameters are only an example.
The operation unit 2, namely the digital twin server part, completes the core operation, maintains the corresponding digital twin supervision model, and finally shows the operation, including:
(1) the method comprises the following steps of constructing a digital twin supervision model 201, wherein the part relates to a core algorithm of a system, and constructing a standardized supervision model according to supervision element parameters of supervision products (services) such as people, machines, materials, methods and rings.
(2) And the automatic refreshing module 203 automatically refreshes the supervision model by means of the supervision element information of 'people, machines, materials, methods and rings' transmitted back by the acquisition facility in real time, and generates a real-time continuous supervision state (virtual reality).
(3) The system review module 202 analyzes the data of the real-time monitoring parameters according to the algorithm of the system review system, generates a review result, and outputs a risk warning to the risk warning module 205.
(4) And a difference marking module 204, when the acquired parameters exceed the standard range of the parameters, the system automatically marks the difference and stores the mark.
(5) And the data storage module 206, the system can store the running records of people, machines, materials, methods, rings and the like related to the supervision process in real time.
The display unit 3 includes a display module 301 that displays the result output by the operation unit 2 through a display terminal 302, specifically, it presents the real-time digital twin supervision state on one or more of VR, AR display equipment, digital signage, PC and APP through a virtual reality technology and a 3D technology.
In a subdivision, the presentation unit 3, i.e. the digital twin supervision model, comprises two parts:
(1) by port of the display, we can display the dynamic record of the supervision on the digital billboard, the PC end and the APP.
(2) According to the displayed technology, a virtual reality technology, namely VR/AR display, can be selected; and meanwhile, the method can be displayed in a mode of constructing 3D animation or 2D pictures.
With reference to fig. 3 to 4, the present invention further provides a quality safety supervision method for a product (service) by applying the supervision system, and the specific scheme is as follows:
s1, according to the supervision product of the embodiment, a standardized supervision bionic model is constructed by using the ideal state parameters of human, machine, material, law and ring supervision elements;
s2, installing a facility for collecting human, machine, material, law and ring supervision parameters in a supervision client site;
referring to fig. 1, in this embodiment, the data of the acquisition unit is classified into "human, machine, material, method, and ring" by type, and the corresponding data parameter definitions (R, J, L, F, H) are as follows:
the "human" (R) parameter module: including r1 personnel health, r2 sanitary requirements, r3 personnel operations, etc.
Establishing staff health files based on finger model recognition, iris recognition and face recognition, acquiring data R1, installing an image sensor, an image sensor and a motion detection sensor to acquire R2 and R3 data in real time in production and processing sites of monitored objects, carrying out information interaction with the sensors through a P L C wireless communication control module, and acquiring a "person" data subset ∑ R (R1, R2 and R3) of the sites.
"machine" (J) parameter module: j1 facility equipment running state, j2 maintenance state and j3 cleaning and disinfecting data. Comprises the following devices: water supply and drainage facilities, cleaning and disinfection facilities, waste storage facilities, personal hygiene facilities, ventilation facilities, lighting facilities and temperature control facilities.
A water quality sensor, a temperature and humidity sensor, a light intensity sensor, a turbidity sensor, a gas sensor and an air pollution sensor are installed on a production and processing site of a supervision client to acquire site data in real time, information interaction is carried out between the sensors and the P L C wireless communication control module, and a machine data subset ∑ J (J1, J2, J3) on the site is acquired.
The material (L) parameter module comprises data such as l1 traceability bar code data, l2 high-risk toxic and harmful factor monitoring data and the like.
A bar code reader, an image sensor and an image sensor are installed on a production and processing field of a supervision client to acquire field data in real time, information interaction is carried out between the bar code reader, the image sensor and the sensor through a P L C wireless communication control module, and a field 'material' data subset ∑L (l1, l2) is acquired.
The "method" (F) parameter module: the method comprises the following steps: f1 process, f2 standard procedure, f3 product operation standard, f4 inspection standard and the like.
The image sensor, the image sensor and the motion detection sensor are installed on the production and processing site of the supervision client, and the behavior action of the supervision object is uploaded through the equipment, so that the 'law' data subset ∑ F (F1, F2, F3 and F4) of the site is collected.
"Ring" (H) parameter Module: h1 cleanliness, h2 illuminance, h3 temperature and humidity, h4 cleanliness, h5 foreign matter living things (mice, flies, insect pests and metals), h6 air quality index and the like, wherein the parameters are only an example.
A water quality sensor, a temperature and humidity sensor, a light intensity sensor, a turbidity sensor, a gas sensor and an air pollution sensor are installed on a production and processing site of a supervision client to acquire site data in real time, information interaction is carried out between the sensors and a P L C wireless communication control module, and a field 'ring' data subset ∑ H (H1, H2, H3, H4, H5 and H6) is acquired.
The system collects the five types of data according to the supervision requirement, and sends the data and real-time change to the digital twin server through the Internet or the 5G network.
S3, refreshing the standard model constructed in S1 by the 'human, machine, material, method and ring' parameter of the supervision client to form the supervision state of the supervision client;
the digital twin server builds the supervising model of the supervising customer, namely ∑ C (R ', J ', L ', F ', H '), from the aggregated five major classes of subset data.
S4, repeatedly refreshing the initial state of the supervision client by using the real-time parameters of the supervision client 'human, machine, material, method and ring';
deconstructing the supervisory client model data accepted by the digital twin server, namely ∑ C (R ', J ', L ', F ', H '). based on the specific digital twin algorithm, various data are synchronized into the supervisory client model, and the data of ' people, machines, materials, methods, rings ' and the like of the supervisory model are ensured to be dynamically consistent with the real environment.
S5, marking the difference between the supervision client 'people, machines, materials, methods and rings' and the standard supervision model;
referring to fig. 3, in this embodiment, the evaluation module of the digital twin server intelligently analyzes and evaluates the digital twin inter-custody model ∑ C (R ', J ', L ', F ', H ') and the standard custody model ∑ C (R, J, L, F, H), and performs related labeling according to differences.
Such as Δ ∑ (0-10) acceptable risk (low risk), Δ ∑ (10-30) suspected risk (general risk), Δ ∑ (30-100) unacceptable risk (high risk).
S6, the system reviews the difference between the supervision client 'people, machines, materials, methods and rings' and the standardized supervision model to form risk warning;
and S7, automatically generating product traceability marks according to the human, machine, material, law and ring evaluation results of the supervision customers, and intelligently managing according to the analysis test results, the public crisis information and the customer complaint information of the finished products.
Based on the above scheme, the present invention can also provide a remote real-time quality safety supervision method, which comprises:
1) checking various parameters of production operation in real time through simulation models presented by VR, AR display equipment, a digital billboard, a PC and an APP;
2) when the parameter information contained in the actual production environment, namely 'man, machine, material, method and ring', changes, the digital twin server can update the corresponding digital twin supervision simulation model in real time and automatically generate an evaluation result;
3) when a certain parameter, which can be manually input, captured by a camera module or acquired by a sensor, exceeds the standard range of the parameter of the monitored object, the system automatically marks the difference and evaluates the difference. And then an alarm signal is generated to assist a manager to quickly locate the problem or prompt a supervisor to pay attention.
The above-described system embodiments are merely illustrative, and the units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment, and those skilled in the art can understand and implement the solution without creative efforts.
Through the above description of the embodiments, those skilled in the art will clearly understand that each embodiment can be implemented by software plus a necessary general hardware platform, and certainly can also be implemented by hardware. With this understanding in mind, the above-described technical solutions may not be part of or make a contribution to the prior art, and may be embodied in a software product, which may be stored in a computer-readable storage medium, such as ROM/RSM, magnetic disk, optical disk, etc., and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device, etc.) to execute the methods described in the various embodiments or some parts of the embodiments.
The above-mentioned embodiments only express several embodiments of the present invention, and the description thereof is more specific and detailed, but not construed as limiting the scope of the present invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the inventive concept, which falls within the scope of the present invention. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. The utility model provides a quality safety third party supervisory systems, includes acquisition unit, arithmetic unit, display element, characterized in that:
the acquisition unit is used for acquiring a supervision element parameter module comprising human, machine, material, method and ring on the side of a real production scene and feeding back the supervision element parameter module to the operation unit;
the operation unit comprises a standardized bionic supervision model construction module, an automatic refreshing module, a system review module, a difference marking module, a data storage module and a risk warning module;
and the display unit displays the results output by each module in the operation unit.
2. The quality safety third-party supervision method according to claim 1, wherein the acquisition unit comprises a front-end acquisition device and a P L C control module, the front-end acquisition device transmits acquired data to the P L C control module, the P L C control module outputs processed data to the arithmetic unit, and the front-end acquisition device comprises a sensing module, a camera module and a manual input end;
the collection 'people, machine, material, method, ring' supervision element parameter module comprises a 'people' parameter module, a 'machine' parameter module, a 'material' parameter module, a 'method' parameter module and a 'ring' parameter module, wherein:
the human parameter module comprises human health, sanitary requirements and human operation data;
the 'machine' parameter module comprises the running state, the maintenance state and the cleaning and disinfection data of facility equipment;
the material parameter module comprises traceability bar code information and high-risk toxic and harmful factor monitoring data;
the 'method' parameter module comprises a process, a standard procedure, a product operation standard and inspection standard data;
the 'ring' parameter module comprises cleanliness, illuminance, temperature and humidity, cleanliness, foreign matter living objects (mice, flies, insect pests and metals) and air quality index data.
3. The quality safety third-party supervision method according to claim 1, characterized in that the display unit displays the supervised dynamic record on any one or more of VR, AR display equipment, digital signage, PC, mobile phone APP through virtual reality technology or 3D animation technology.
4. A quality security third party supervision method is characterized by comprising the following steps:
constructing a standardized bionic supervision model by using a supervision element parameter module of an ideal state 'human, machine, material, method and ring';
based on the 'human, machine, material, law, ring' supervision element parameter module data of the supervision object collected in the production and processing field, the virtual reality of the supervision object is twinned and compared with the standard bionic model;
by updating data in real time and repeatedly comparing for many times, intelligent evaluation, difference marking and warning risk are realized, and output results are displayed on a display terminal.
5. The method of claim 4, wherein the intelligent review module of the digital twin server intelligently analyzes and evaluates the digital twin supervision model and the standard supervision model, and marks the difference.
6. A quality safety third-party supervision method according to claim 4, characterized in that the alarm risks are classified as acceptable, suspicious and unacceptable.
7. The method of claim 4, wherein the display terminal displays the dynamic record of supervision on any one or more of VR, AR display equipment, digital signage, PC, and mobile phone APP by virtual reality technology or 3D animation technology.
8. A quality safety third-party supervision method according to claim 4, characterized in that the "people, machines, materials, law, ring" supervision element parameter modules comprise a "people" parameter module, a "machines" parameter module, a "materials" parameter module, a "law" parameter module, a "ring" parameter module, wherein:
the human parameter module comprises human health, sanitary requirements and human operation data;
the 'machine' parameter module comprises the running state, the maintenance state and the cleaning and disinfection data of facility equipment;
the material parameter module comprises traceability bar code information and high-risk toxic and harmful factor monitoring data;
the 'method' parameter module comprises a process, a standard procedure, a product operation standard and inspection standard data;
the 'ring' parameter module comprises cleanliness, illuminance, temperature and humidity, cleanliness, foreign matter living objects (mice, flies, insect pests and metals) and air quality index data.
9. A quality-safe third-party oversight method according to claim 4, characterized in that it comprises the following steps:
s1, constructing a standardized supervision bionic model by using the ideal state parameters of human, machine, material, method and ring supervision elements;
s2, installing a collection facility of 'human, machine, material, law and loop' parameters at the supervision client;
s3, refreshing the standard model constructed in S1 by the 'human, machine, material, method and ring' parameter of the supervising client to form the initial state of the supervising client;
s4, repeatedly refreshing the initial state of the supervision client by using the real-time parameters of the supervision client 'human, machine, material, method and ring';
s5, marking the difference between the supervision client 'people, machines, materials, methods and rings' and the standard supervision model;
s6, the system reviews the difference between the supervision client 'people, machines, materials, methods and rings' and the standardized supervision model to form risk warning;
and S7, automatically generating product traceability marks according to the human, machine, material, law and ring evaluation results of the supervision customers, and intelligently managing according to the analysis test results, the public crisis information and the customer complaint information of the finished products.
10. A method for remote real-time quality supervision, the method comprising:
1) checking various parameters of production operation in real time through one or more simulation models presented by VR, AR display equipment, a digital billboard, a PC and an APP;
2) when the parameter information contained in the actual production environment, namely 'man, machine, material, method and ring', changes, the digital twin server can update the corresponding digital twin supervision simulation model in real time and automatically generate an evaluation result;
3) when a certain parameter, which can be manually input, captured by a camera module or acquired by a sensor, exceeds the standard range of the parameter of the monitored object, the system automatically marks the difference, evaluates the difference, immediately generates an alarm signal to assist a manager to quickly locate the problem or prompt the supervisor to pay attention.
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