CN102930373A - Safety risk monitoring and early warning method for dairy products - Google Patents
Safety risk monitoring and early warning method for dairy products Download PDFInfo
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- CN102930373A CN102930373A CN2012103729387A CN201210372938A CN102930373A CN 102930373 A CN102930373 A CN 102930373A CN 2012103729387 A CN2012103729387 A CN 2012103729387A CN 201210372938 A CN201210372938 A CN 201210372938A CN 102930373 A CN102930373 A CN 102930373A
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Abstract
The invention discloses safety risk monitoring and early warning method for dairy products. The method comprises the following specific steps of: submitting data by a diary product producing enterprise; checking whether the data have obvious errors; preprocessing the accurate data; mining mode data; automatically analyzing the mined mode data, finding abnormal data, and making decisions according to the analysis result; and correcting decisions, and developing an early warning mechanism. The method has the advantages that a reasonable scientific mode for analyzing the production behavior of the enterprise is constructed, an automatic monitoring and early warning mechanism of quality safety key indexes and the like is constructed, and the scientific technical support is provided for deepening the risk management work; and problems in the production and management of the enterprise can be found timely, the disorderly conducts in the production and management can be effectively suppressed, and the enterprise is supervised and urged to strictly carry out the entity responsibility; and the informatization and automation level of food supervision is greatly improved, and the supervision efficiency is promoted to be improved.
Description
Technical field
The present invention relates to a kind of monitoring and pre-alarming method, especially a kind of dairy products security risk monitoring and pre-alarming method is applicable to the problem in the production managements such as dairy enterprises is carried out early warning.
Background technology
In recent years, the quality of dairy products security incident takes place frequently, it is more outstanding that these events expose China's quality of dairy products safety problem, the quality of dairy products safety problem has had a strong impact on the sound development in socialist economy market and the orderly propelling of harmonious society, and the sound development of the healthy of people and dairy products manufacturing enterprise is brought larger negative effect.At present, dairy products manufacturing enterprise lacks certain monitoring and control device to quality of dairy products security risk hidden danger, enterprise's former breast control, daily production management, Product Process are checked on, have deep-seated problem in the factory inspection process, often occur being rejected former breast resell his factory, fight for that the milk source quality descends, management accounts can not be traced to the source, there is fraud in factory inspection etc. and depend merely on the indiscoverable problem of on-the-spot supervision and check.
In addition, in supervision and check in the past, owing to lack the analysis-by-synthesis of data and the lateral comparison between enterprise, even practising fraud, some enterprises also may get by under false pretences.
Summary of the invention
The technical problem to be solved in the present invention provides a kind of dairy products security risk monitoring and pre-alarming method, the technical support of science is provided for the in-depth Risk Management, the effectively abnormal activity in the containment production and operation, supervise enterprise strictly to implement the main body responsibility, greatly promote informationization, the automatization level of foods supervision work, promoted the raising of supervision usefulness.
For solving the problems of the technologies described above, the technical solution used in the present invention is: a kind of dairy products security risk monitoring and pre-alarming method, and its concrete steps are as follows:
(1) submit data to: dairy enterprises to be monitored requires to fill in various data in the dairy products process of manufacture according to the template style of standard, and above-mentioned data are submitted to higher level examining department;
(2) check data: the data that dairy enterprises to be monitored is submitted to are checked by higher level examining department, when above-mentioned data have apparent error, provide explanation of error, and notify dairy enterprises to be monitored to resubmit data; When above-mentioned data do not have apparent error, carry out next step;
(3) preprocessed data: above-mentioned data are carried out data normalization and data characteristics selection processing;
(4) mining mode data: utilize clustering algorithm to excavate pattern rule in the above-mentioned data, utilize PSO and the concrete model parameter of GA Algorithm Learning;
(5) decision-making: the mode data of above-mentioned excavation is carried out automatic analysis, and the data that note abnormalities are made a strategic decision according to above-mentioned analysis result;
(6) revise decision-making: to the determinant attribute setting threshold, and calculate actual average or the variance of above-mentioned determinant attribute, then carry out desk checking, according to the above-mentioned decision-making of check results correction, and finally form early warning.
Data normalization in the above-mentioned steps (3) utilizes BPNN or RBFNN algorithm to process.
Clustering algorithm in the above-mentioned steps (4) is specially decision Tree algorithms, genetic algorithm, SVM algorithm, k-means algorithm or DBScan algorithm.
Beneficial effect of the present invention is as follows: made up the rational scientific mode of analysis enterprise production behavior, set up the automatic monitoring early warning mechanism of quality safety key index etc., formed the high efficiency technical means of finding quality of dairy products security risk hidden danger; Played the effect of disposing early discovery, early early warning, morning, the technical support of science is provided for the in-depth Risk Management.
Can in time find the problem in the enterprise production management, effectively contain the abnormal activity in the production and operation, supervise enterprise strictly to implement the main body responsibility.
Greatly promote informationization, the automatization level of foods supervision work, promoted the raising of supervision usefulness; Strengthened specific aim, make supervision from before enterprise interrogate topic, change into now and look into enterprise with problem; Promoted validity, realized from the point problem discover systematicness problem, from the problem discover professional problem of an enterprise, thereby in time find what is called " underlying rule " problem that exists in the industry; Saved the cost of supervise and control, remedied well that food enterprise is many, the supervisor is few, peopleware is weak and a large amount of input but can't find the realistic problems such as risk hidden danger, reached the supervision effect that all kinds of problems to enterprise, industry " stay indoors, have a panoramic view ".
Embodiment
The method of the invention is mainly used in monitoring 7 class important indicators of dairy products, comprises Key Quality Indicator (enterprise inspection by oneself such as protein content, fat content, freezing point, dry matter content and supervision sampling observation data), price based on supply and demand, former breast buying and finished product quantity, raw material and finished product reduction coefficient, rejects that former breast is reviewed, defective finished product is reviewed, the Production Regional distribution.Use for reference advanced food safety risk Early-warning Model both at home and abroad, adopt trend analysis, comparative analysis, supply and demand analysis, historical analysis, terrain analysis, industrial analysis, 7 kinds of modes of retrospective analysis, the various information of the dairy products manufacturing enterprise that collects are carried out the deep layer statistics, are analyzed, sum up the general rules of 9 Risk-warnings of dairy products manufacturing enterprise:
1, enterprise reports with batch products self check data and sampling observation Monitoring Data and departs from when larger, and early warning enterprise may exist to dispatch from the factory and do not examine, dispatches from the factory first rear check, self check mistake equivalent risk.
2, during crucial quality safety index substantial deviation the whole province general rule of the former breast of enterprise or finished product, may there be illegal interpolation in early warning, be watered dilution, inferior raw material, transfer milk temporarily, rob the milk equivalent risk.
When 3, the former newborn procurement price in enterprise or certain zone seriously was lower than market average price, early warning may exist purchased in violation of rules and regulations inferior raw material, illegally adds and mass-sends the epidemic disease equivalent risk.
When 4, the former newborn procurement price fluctuation in enterprise or certain zone was larger, the milk equivalent risk not fixed, be robbed to early warning may in the interior milk source of domain of the existence.
When 5, enterprise or certain former newborn amount of purchase in zone and finished product turnout were not inconsistent, may there be illegal interpolation in early warning or be watered the dilution equivalent risk.
When 6, single former newborn supplier was supplied to the former milk protein content, price etc. of different enterprises relatively large deviation to occur, may there be the problems such as illegal interpolation, milk inferior in early warning.
When 7, the actual reduction coefficient of enterprise's single product material quantity and output was unstable, early warning may exist not by explained hereafter, the former breast of shipping and reselling on another market, fail to report part milk source equivalent risk.
When 8, enterprise's rejection breast was purchased in other enterprises, may there be the situation of purchasing former breast inferior in early warning.
When 9, enterprise or certain regional actual output were far below the design production capacity, early warning may exist robbed milk, illegal interpolation, purchase milk inferior equivalent risk.
The below enumerates and severally utilizes dairy products security risk monitoring and pre-alarming method of the present invention that dairy products manufacturing enterprise is monitored and the example of early warning.
Embodiment 1
Certain dairy products manufacturing enterprise purchases fresh milk protein average content in October, 2011 to Dec and is respectively 3.135g/100g, 3.093g/100g, 3.078g/100g, set up regression model according to fuzzy mearue and fuzzy integral, excavate pattern rule in the above-mentioned data by genetic algorithm, drawing data is walked power curve, find that these presentation of datas walk low tendency gradually, with the whole province same period, high trend was inconsistent gradually.
According to above-mentioned Risk-warning second rule " during the crucial quality safety index substantial deviation the whole province general rule of the former breast of enterprise or finished product; may there be illegal interpolation in early warning, be watered dilution, inferior raw material, transfer milk, rob the milk equivalent risk " temporarily, may there be above-mentioned risk in this enterprise of early warning, and report relevant administrative responsibile institution, the production and management of this enterprise is examined, disposed.
Embodiment 2
The fresh milk price that certain dairy products manufacturing enterprise purchases certain milk family in November, 2011 and Dec is 0.29 ten thousand yuan/ton, the same period, the whole province's average price was 0.34 ten thousand yuan/ton, utilize clustering algorithm k-means to carry out outlier detection and obtain model threshold, actual specific reaches 14.7% to rear discovery deviation, surpasses threshold value 10%.
According to the 3rd of above-mentioned Risk-warning " when enterprise or certain former newborn procurement price in zone seriously are lower than market average price; early warning may exist purchases in violation of rules and regulations inferior raw material, illegally adds and mass-send the epidemic disease equivalent risk ", may there be above-mentioned risk in this enterprise of early warning, and report relevant administrative responsibile institution, the production and operation situation of this enterprise is examined one by one, disposed.
Embodiment 3
" the producing modulation milk product technical papers " of certain dairy products manufacturing enterprise requires raw milk and finished product breast reduction coefficient is 0.8:1, the former breast of actual purchase and finished product reduction coefficient are 1.05:1, utilize the clustering algorithms such as k-means, DBScan to carry out outlier detection and obtain model threshold, actual specific reaches 31.3% to rear discovery deviation, surpasses threshold value 20%.
According to the 7th of above-mentioned Risk-warning " when enterprise's single product material quantity and the actual reduction coefficient of output are unstable; early warning may exist not by explained hereafter, the former breast of shipping and reselling on another market, fail to report part milk source equivalent risk ", may there be above-mentioned risk in this enterprise of early warning, and report relevant administrative responsibile institution, the production and operation situation of this enterprise is examined and disposed.
After adopting said method, some monitored enterprises of ging wrong and being investigated and prosecuted have been subject to very big vibrations, not only in time perfect relative recording, processed relevant person liable, and strict management system, strengthened staff training, strengthened to detect and dropped into, Consciousness Self-discipline obviously strengthens.
Claims (3)
1. dairy products security risk monitoring and pre-alarming method is characterized in that its method step is as follows:
(1) submit data to: dairy enterprises to be monitored requires to fill in various data in the dairy products process of manufacture according to the template style of standard, and above-mentioned data are submitted to higher level examining department;
(2) check data: the data that dairy enterprises to be monitored is submitted to are checked by higher level examining department, when above-mentioned data have apparent error, provide explanation of error, and notify dairy enterprises to be monitored to resubmit data; When above-mentioned data do not have apparent error, carry out next step;
(3) preprocessed data: above-mentioned data are carried out data normalization and data characteristics selection processing;
(4) mining mode data: utilize clustering algorithm to excavate pattern rule in the above-mentioned data, utilize PSO and the concrete model parameter of GA Algorithm Learning;
(5) decision-making: the mode data of above-mentioned excavation is carried out automatic analysis, and the data that note abnormalities are made a strategic decision according to above-mentioned analysis result;
(6) revise decision-making: to the determinant attribute setting threshold, and calculate actual average or the variance of above-mentioned determinant attribute, then carry out desk checking, according to the above-mentioned decision-making of check results correction, and finally form early warning.
2. dairy products security risk monitoring and pre-alarming method according to claim 1 is characterized in that, the data normalization in the described step (3) utilizes BPNN or RBFNN algorithm to process.
3. dairy products security risk monitoring and pre-alarming method according to claim 1 is characterized in that, the clustering algorithm in the described step (4) is specially decision Tree algorithms, genetic algorithm, SVM algorithm, k-means algorithm or DBScan algorithm.
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| CN2012103729387A CN102930373A (en) | 2012-09-29 | 2012-09-29 | Safety risk monitoring and early warning method for dairy products |
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Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103631900A (en) * | 2013-11-20 | 2014-03-12 | 广东电网公司电力科学研究院 | Data comparing method based on main gateway and standby gateway comparison |
| CN108510159A (en) * | 2018-03-08 | 2018-09-07 | 北京化工大学 | Quality of dairy products Risk Identification Method based on reference model and crucial hazard analysis |
| CN110363435A (en) * | 2019-07-16 | 2019-10-22 | 华中农业大学 | A kind of food safety appraisal procedure of multi-source information |
| CN111325471A (en) * | 2020-02-27 | 2020-06-23 | 贵州省分析测试研究院 | White spirit is traceed back and quality safety protection system based on society is controlled altogether |
| CN115242349A (en) * | 2022-06-21 | 2022-10-25 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method and device, computer equipment and storage medium |
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| CN1658607A (en) * | 2004-12-23 | 2005-08-24 | 郑州市疾病预防控制中心 | Digital information managing system for medical inspection laboratory |
| CN101770609A (en) * | 2008-12-30 | 2010-07-07 | 北京大学 | Food safety monitoring system |
| CN202443496U (en) * | 2011-12-29 | 2012-09-19 | 钟安清 | Food safety third-party supervisory system based on SPS and HACCP |
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2012
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| CN1658607A (en) * | 2004-12-23 | 2005-08-24 | 郑州市疾病预防控制中心 | Digital information managing system for medical inspection laboratory |
| CN101770609A (en) * | 2008-12-30 | 2010-07-07 | 北京大学 | Food safety monitoring system |
| CN202443496U (en) * | 2011-12-29 | 2012-09-19 | 钟安清 | Food safety third-party supervisory system based on SPS and HACCP |
Cited By (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN103631900A (en) * | 2013-11-20 | 2014-03-12 | 广东电网公司电力科学研究院 | Data comparing method based on main gateway and standby gateway comparison |
| CN108510159A (en) * | 2018-03-08 | 2018-09-07 | 北京化工大学 | Quality of dairy products Risk Identification Method based on reference model and crucial hazard analysis |
| CN110363435A (en) * | 2019-07-16 | 2019-10-22 | 华中农业大学 | A kind of food safety appraisal procedure of multi-source information |
| CN111325471A (en) * | 2020-02-27 | 2020-06-23 | 贵州省分析测试研究院 | White spirit is traceed back and quality safety protection system based on society is controlled altogether |
| CN115242349A (en) * | 2022-06-21 | 2022-10-25 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method and device, computer equipment and storage medium |
| CN115242349B (en) * | 2022-06-21 | 2023-11-14 | 苏州盈数智能科技有限公司 | Enterprise-level data verification method, enterprise-level data verification device, computer equipment and storage medium |
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Application publication date: 20130213 |