CN116617432A - Optimized sterilization control method and system for medicine production workshop - Google Patents
Optimized sterilization control method and system for medicine production workshop Download PDFInfo
- Publication number
- CN116617432A CN116617432A CN202310619261.0A CN202310619261A CN116617432A CN 116617432 A CN116617432 A CN 116617432A CN 202310619261 A CN202310619261 A CN 202310619261A CN 116617432 A CN116617432 A CN 116617432A
- Authority
- CN
- China
- Prior art keywords
- microorganism
- area
- distribution
- information
- spreading
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000001954 sterilising effect Effects 0.000 title claims abstract description 151
- 238000004659 sterilization and disinfection Methods 0.000 title claims abstract description 144
- 238000004519 manufacturing process Methods 0.000 title claims abstract description 106
- 239000003814 drug Substances 0.000 title claims abstract description 67
- 238000000034 method Methods 0.000 title claims abstract description 41
- 244000005700 microbiome Species 0.000 claims abstract description 295
- 238000009826 distribution Methods 0.000 claims abstract description 114
- 238000003892 spreading Methods 0.000 claims abstract description 90
- 230000007480 spreading Effects 0.000 claims abstract description 90
- 238000005192 partition Methods 0.000 claims abstract description 71
- 238000001514 detection method Methods 0.000 claims abstract description 47
- 238000012544 monitoring process Methods 0.000 claims abstract description 41
- 238000005457 optimization Methods 0.000 claims abstract description 30
- 238000007417 hierarchical cluster analysis Methods 0.000 claims abstract description 12
- OKKJLVBELUTLKV-UHFFFAOYSA-N Methanol Chemical compound OC OKKJLVBELUTLKV-UHFFFAOYSA-N 0.000 claims description 144
- 230000000813 microbial effect Effects 0.000 claims description 39
- 239000007921 spray Substances 0.000 claims description 29
- 238000004220 aggregation Methods 0.000 claims description 24
- 230000002776 aggregation Effects 0.000 claims description 24
- 238000005507 spraying Methods 0.000 claims description 18
- 230000009471 action Effects 0.000 claims description 14
- 238000009423 ventilation Methods 0.000 claims description 13
- 239000003153 chemical reaction reagent Substances 0.000 claims description 11
- 238000003958 fumigation Methods 0.000 claims description 9
- 238000004088 simulation Methods 0.000 claims description 9
- 238000004062 sedimentation Methods 0.000 claims description 8
- 230000001502 supplementing effect Effects 0.000 claims description 4
- 230000008569 process Effects 0.000 description 9
- 229940079593 drug Drugs 0.000 description 8
- 230000000694 effects Effects 0.000 description 7
- 241000894006 Bacteria Species 0.000 description 4
- WSFSSNUMVMOOMR-UHFFFAOYSA-N Formaldehyde Chemical compound O=C WSFSSNUMVMOOMR-UHFFFAOYSA-N 0.000 description 4
- 241000233866 Fungi Species 0.000 description 4
- 238000010586 diagram Methods 0.000 description 4
- 238000013461 design Methods 0.000 description 2
- 230000007613 environmental effect Effects 0.000 description 2
- 244000000010 microbial pathogen Species 0.000 description 2
- ZNZYKNKBJPZETN-WELNAUFTSA-N Dialdehyde 11678 Chemical compound N1C2=CC=CC=C2C2=C1[C@H](C[C@H](/C(=C/O)C(=O)OC)[C@@H](C=C)C=O)NCC2 ZNZYKNKBJPZETN-WELNAUFTSA-N 0.000 description 1
- LFQSCWFLJHTTHZ-UHFFFAOYSA-N Ethanol Chemical compound CCO LFQSCWFLJHTTHZ-UHFFFAOYSA-N 0.000 description 1
- SXRSQZLOMIGNAQ-UHFFFAOYSA-N Glutaraldehyde Chemical compound O=CCCCC=O SXRSQZLOMIGNAQ-UHFFFAOYSA-N 0.000 description 1
- 238000004378 air conditioning Methods 0.000 description 1
- 239000006185 dispersion Substances 0.000 description 1
- 239000000284 extract Substances 0.000 description 1
- 230000010354 integration Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 239000002245 particle Substances 0.000 description 1
- 239000012286 potassium permanganate Substances 0.000 description 1
- 238000012545 processing Methods 0.000 description 1
- BDERNNFJNOPAEC-UHFFFAOYSA-N propan-1-ol Chemical compound CCCO BDERNNFJNOPAEC-UHFFFAOYSA-N 0.000 description 1
Classifications
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61L—METHODS OR APPARATUS FOR STERILISING MATERIALS OR OBJECTS IN GENERAL; DISINFECTION, STERILISATION OR DEODORISATION OF AIR; CHEMICAL ASPECTS OF BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES; MATERIALS FOR BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES
- A61L2/00—Methods or apparatus for disinfecting or sterilising materials or objects other than foodstuffs or contact lenses; Accessories therefor
- A61L2/24—Apparatus using programmed or automatic operation
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61L—METHODS OR APPARATUS FOR STERILISING MATERIALS OR OBJECTS IN GENERAL; DISINFECTION, STERILISATION OR DEODORISATION OF AIR; CHEMICAL ASPECTS OF BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES; MATERIALS FOR BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES
- A61L2/00—Methods or apparatus for disinfecting or sterilising materials or objects other than foodstuffs or contact lenses; Accessories therefor
- A61L2/26—Accessories or devices or components used for biocidal treatment
- A61L2/28—Devices for testing the effectiveness or completeness of sterilisation, e.g. indicators which change colour
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
- C12M37/00—Means for sterilizing, maintaining sterile conditions or avoiding chemical or biological contamination
- C12M37/06—Means for testing the completeness of the sterilization
-
- C—CHEMISTRY; METALLURGY
- C12—BIOCHEMISTRY; BEER; SPIRITS; WINE; VINEGAR; MICROBIOLOGY; ENZYMOLOGY; MUTATION OR GENETIC ENGINEERING
- C12M—APPARATUS FOR ENZYMOLOGY OR MICROBIOLOGY; APPARATUS FOR CULTURING MICROORGANISMS FOR PRODUCING BIOMASS, FOR GROWING CELLS OR FOR OBTAINING FERMENTATION OR METABOLIC PRODUCTS, i.e. BIOREACTORS OR FERMENTERS
- C12M41/00—Means for regulation, monitoring, measurement or control, e.g. flow regulation
- C12M41/30—Means for regulation, monitoring, measurement or control, e.g. flow regulation of concentration
- C12M41/36—Means for regulation, monitoring, measurement or control, e.g. flow regulation of concentration of biomass, e.g. colony counters or by turbidity measurements
-
- A—HUMAN NECESSITIES
- A61—MEDICAL OR VETERINARY SCIENCE; HYGIENE
- A61L—METHODS OR APPARATUS FOR STERILISING MATERIALS OR OBJECTS IN GENERAL; DISINFECTION, STERILISATION OR DEODORISATION OF AIR; CHEMICAL ASPECTS OF BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES; MATERIALS FOR BANDAGES, DRESSINGS, ABSORBENT PADS OR SURGICAL ARTICLES
- A61L2202/00—Aspects relating to methods or apparatus for disinfecting or sterilising materials or objects
- A61L2202/10—Apparatus features
- A61L2202/14—Means for controlling sterilisation processes, data processing, presentation and storage means, e.g. sensors, controllers, programs
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02P—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN THE PRODUCTION OR PROCESSING OF GOODS
- Y02P90/00—Enabling technologies with a potential contribution to greenhouse gas [GHG] emissions mitigation
- Y02P90/02—Total factory control, e.g. smart factories, flexible manufacturing systems [FMS] or integrated manufacturing systems [IMS]
Landscapes
- Health & Medical Sciences (AREA)
- Life Sciences & Earth Sciences (AREA)
- Chemical & Material Sciences (AREA)
- Engineering & Computer Science (AREA)
- Organic Chemistry (AREA)
- Zoology (AREA)
- General Health & Medical Sciences (AREA)
- Wood Science & Technology (AREA)
- Bioinformatics & Cheminformatics (AREA)
- Public Health (AREA)
- Epidemiology (AREA)
- Veterinary Medicine (AREA)
- Biomedical Technology (AREA)
- Biotechnology (AREA)
- Microbiology (AREA)
- Sustainable Development (AREA)
- Animal Behavior & Ethology (AREA)
- Biochemistry (AREA)
- General Engineering & Computer Science (AREA)
- Genetics & Genomics (AREA)
- Analytical Chemistry (AREA)
- Molecular Biology (AREA)
- Apparatus Associated With Microorganisms And Enzymes (AREA)
Abstract
The invention provides an optimized sterilization control method and system for a medicine production workshop, which relate to the technical field of intelligent control, and the method comprises the following steps: acquiring use state record information and gas flow state monitoring information of a preset time zone of a clean zone of a pharmaceutical production workshop, determining a microorganism source area, then carrying out microorganism spreading analysis on the microorganism source area and the gas flow state monitoring information, carrying out microorganism detection on a spreading track area, carrying out hierarchical clustering analysis on a microorganism distribution area by a detection result, optimizing sterilization control parameters by the microorganism content information of any partition and the microorganism distribution partition result when the microorganism content information of the partition meets a microorganism content threshold value, and carrying out sterilization treatment on the microorganism distribution partition result of the pharmaceutical production workshop by the sterilization control parameter optimization result, thereby solving the technical problems of low final sterilization efficiency in the prior art due to insufficient refinement degree of sterilization treatment, realizing refined management and control of sterilization treatment and improving sterilization efficiency.
Description
Technical Field
The application relates to the technical field of intelligent control, in particular to an optimized sterilization control system of a medicine production workshop.
Background
Along with the importance of the country to environmental protection and enterprise safety in production, the environment and the safety requirement to the workshop are higher and higher, and the sterilizing device of workshop is the equipment of purifying workshop environment, can disinfect the workshop, and current workshop sterilizing device often is the dispersion, sets up the point to the space of difference in the workshop, dispersedly controls, uses one or more of them to disinfect, and not only sterilization efficiency is lower, and the cost can rise.
In the prior art, the refinement degree of sterilization treatment is insufficient, so that the final sterilization efficiency is low.
Disclosure of Invention
The application provides an optimized sterilization control method and system for a medicine production workshop, which are used for solving the technical problems of low final sterilization efficiency caused by insufficient refinement degree of sterilization treatment in the prior art.
In view of the above problems, the application provides an optimized sterilization control method and system for a pharmaceutical production workshop.
In a first aspect, the present application provides a method for optimizing sterilization control in a pharmaceutical production plant, the method comprising: acquiring use state record information and gas flow state monitoring information of a preset time zone of a clean zone of a medicine production workshop; determining a microorganism source area according to the use state record information; performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area; detecting microorganisms in the spreading track area to obtain a microorganism detection result, wherein the microorganism detection result comprises microorganism content information and a microorganism distribution area; performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results; when the partition microorganism content information of any one of the microorganism distribution partition results meets a microorganism content threshold, optimizing sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition results to obtain a sterilization control parameter optimization result; and carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization results.
In a second aspect, the present application provides an optimized sterilization control system for a pharmaceutical production facility, the system comprising: the information acquisition module is used for acquiring the use state record information and the gas flow state monitoring information of a preset time zone of the clean zone of the medicine production workshop; the area determining module is used for determining a microorganism source area according to the using state record information; the microorganism spreading analysis module is used for performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area; the microorganism detection module is used for detecting microorganisms in the spreading track area to obtain microorganism detection results, wherein the microorganism detection results comprise microorganism content information and microorganism distribution areas; the hierarchical clustering analysis module is used for performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results; the optimizing module is used for optimizing the sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition result when the partition microorganism content information of any one of the microorganism distribution partition results meets a microorganism content threshold value, and obtaining a sterilization control parameter optimizing result; and the sterilization treatment module is used for carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization result.
One or more technical schemes provided by the application have at least the following technical effects or advantages:
the application provides an optimized sterilization control method and system for a medicine production workshop, relates to the technical field of intelligent control, and solves the technical problems that the final sterilization efficiency is low due to insufficient refinement degree of sterilization treatment in the prior art, realizes refined control of sterilization treatment and improves sterilization efficiency.
Drawings
FIG. 1 is a schematic flow chart of an optimized sterilization control method for a pharmaceutical production plant;
FIG. 2 is a schematic diagram of a process for acquiring monitoring information of gas flow state in an optimized sterilization control method of a pharmaceutical production plant;
FIG. 3 is a schematic flow chart of a process for obtaining an extended track area in an optimized sterilization control method of a pharmaceutical production plant;
FIG. 4 is a schematic diagram showing a process for obtaining a microorganism detection result in an optimized sterilization control method for a pharmaceutical production plant;
FIG. 5 is a schematic flow chart of a method for obtaining microorganism distribution partition results in an optimized sterilization control method of a pharmaceutical production plant;
FIG. 6 is a schematic diagram of the process of optimizing the sterilization control parameters in the method for optimizing the sterilization control of the pharmaceutical production plant;
Fig. 7 is a schematic structural diagram of an optimized sterilization control system for a pharmaceutical production plant.
Reference numerals illustrate: the system comprises an information acquisition module 1, a region determination module 2, a microorganism spreading analysis module 3, a microorganism detection module 4, a hierarchical cluster analysis module 5, an optimization module 6 and a sterilization processing module 7.
Detailed Description
The application provides an optimized sterilization control method and system for a medicine production workshop, which are used for solving the technical problems of low final sterilization efficiency caused by insufficient refinement degree of sterilization treatment in the prior art.
Example 1
As shown in fig. 1, an embodiment of the present application provides an optimized sterilization control method for a pharmaceutical production plant, including:
step S100: acquiring use state record information and gas flow state monitoring information of a preset time zone of a clean zone of a medicine production workshop;
specifically, the method for optimizing and sterilizing a pharmaceutical production plant is applied to an optimizing and sterilizing control system of a pharmaceutical production plant, so that in order to ensure the efficiency of sterilizing a clean area of the pharmaceutical production plant in the later period, the use state record of the pharmaceutical production plant and the monitoring information of the gas flow state in a preset time zone in the area are required to be correspondingly acquired, the time of the pharmaceutical production working process can be set as the preset time zone in the preset time zone, the use state of the preset time zone refers to the use state of the pharmaceutical production plant in the time range of the pharmaceutical production working, the use state of the pharmaceutical production plant is divided into the use state, the use state and the non-use state, the gas flow state monitoring information refers to the detection of the use state of the pharmaceutical production plant, and if the use state of the pharmaceutical production plant is monitored, the data monitoring integration is carried out on the gas flow direction and the gas flow speed in the current workshop according to the use action in the workshop, and the sterilization treatment is realized as important reference basis for the later period.
Step S200: determining a microorganism source area according to the use state record information;
specifically, on the basis of the workshop use state record information in the preset time zone, the use state of the clean area of the medicine production workshop is set, the use state of the clean area of the medicine production workshop can be unused, in use and completed, the use state of the clean area of the medicine production workshop and the use completion of the workshop are recorded as the occurrence use states, and further, the microorganism detection is needed to detect the number of bacteria and fungi in the use area, detect the unit mass, the volume or the area of the bacteria and the fungi in the current area, thereby determining the microorganism source area and guaranteeing the sterilization treatment of the medicine production workshop.
Step S300: performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area;
specifically, the method uses the determined monitoring information of the gas flow state in the clean area of the medicine production workshop as a basis, further predicts the microorganism spreading area by collecting the use states corresponding to different areas in the set time of the clean room and the ventilation state information in the clean area of the medicine production workshop, firstly extracts the use state occurrence position, the use state occurrence time and the use state occurrence range in the use state record information of different areas in the microorganism source area, estimates the spreading speed of microorganisms according to the gas flow state monitoring information of the areas with the use state after the use state occurrence time, namely, the spreading speed of microorganisms in the set time of the clean room, and collects microorganism sample collection numbers and microorganism spreading routes of different areas with the microorganism spreading direction and the spreading speed of the microorganism source area as the center, thereby acquiring the full-eye track area of microorganisms in the medicine production workshop and realizing the sterilization treatment of the medicine production workshop.
Step S400: detecting microorganisms in the spreading track area to obtain a microorganism detection result, wherein the microorganism detection result comprises microorganism content information and a microorganism distribution area;
specifically, the obtained spreading track area is subjected to microorganism detection on the number of microorganisms, the positions of the microorganisms and the like, the microorganism spreading aggregation degree of the current area is obtained according to the number of the microorganisms in the spreading track area, the spreading route of the microorganisms is obtained according to the positions of the microorganisms in the spreading track area, further, the upper limit of aggregation of the current microorganisms is extracted according to the microorganism spreading aggregation degree of the current area, the range boundary of the current microorganisms is extracted according to the spreading route of the microorganisms in the current area, the area needing to be monitored at present is defined, the microorganism detection is performed in the defined monitoring area, the microorganism detection result comprises microorganism content information and microorganism distribution areas, and the sterilization treatment of a medicine production workshop is realized.
Step S500: performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results;
Specifically, the microorganism content information and the microorganism distribution area in the obtained microorganism detection result are taken as the basis, the microorganism distribution area is hierarchically divided according to the microorganism content, and if the microorganism content in one area is greater than or equal to 50%, the microorganism content is considered to be high and divided into a first-stage microorganism distribution area, if the microorganism content in one area is less than 50%, the microorganism content is considered to be low and divided into a second-stage microorganism distribution area, the microorganism content information respectively contained in the first-stage microorganism distribution area and the second-stage microorganism distribution area is further subjected to difference, if the deviation value is less than 5%, the first-stage microorganism distribution area and the second-stage microorganism distribution area are gathered into one type, the average value of the microorganism content information in the first-stage microorganism distribution area and the second-stage microorganism distribution area is set as the microorganism content information of a new area after clustering, the deviation value is iteratively compared, and when the deviation value is greater than 30%, the microorganism distribution area is finally obtained, and the microorganism distribution area is subjected to sterilization treatment is further carried out for the later production workshop data.
Step S600: when the partition microorganism content information of any one of the microorganism distribution partition results meets a microorganism content threshold, optimizing sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition results to obtain a sterilization control parameter optimization result;
specifically, the microbial distribution partition results obtained by the iteration are randomly extracted, if any one microbial distribution partition result contains partition microbial content information meeting a set microbial content threshold, the microbial content in the current area is regarded as an out-of-standard state, wherein the microbial content threshold is preset by related technicians according to the data amount of the microbial content in the area in big data, further, sterilization control parameters are optimized by the partition microbial content information and the microbial distribution partition result, the sterilization control parameters comprise sterilization control methanol generation amount, sterilization control methanol generation position, sterilization control methanol fumigation time, sterilization control methanol ventilation time, a spray reagent type sterilization device, a sterilization device spray position, a sterilization device spray amount and a sterilization device spray time, and finally, the optimized sterilization control parameters are recorded as sterilization control parameters.
Step S700: and carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization results.
Specifically, since the sterilization process is required to be performed on the used or used pharmaceutical production plant in the later stage to ensure the sterile environment of the pharmaceutical production plant, the sterilization process is required to be performed on the region included in any one of the microorganism distribution partition results in the current tablet production plant in the sterilization control parameter optimization result obtained by optimizing the sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition results, thereby realizing the fine control of the sterilization process and improving the sterilization efficiency.
Further, as shown in fig. 2, step S100 of the present application further includes:
step S110: setting a to-be-monitored use state, wherein the to-be-monitored use state comprises a sensitive environment state and a sensitive action state;
step S120: setting a use state to-be-monitored index, wherein the use state to-be-monitored index comprises an occurrence position, an occurrence time and an occurrence scale;
step S130: setting a gas flow state to-be-monitored index, wherein the gas flow state to-be-monitored index comprises a gas flow direction and a gas flow speed;
Step S140: when the sensitive environment state and the sensitive action state occur, recording the occurrence position, the occurrence time and the occurrence scale, and acquiring the use state recording information; and
step S150: and monitoring the gas flow direction and the gas flow speed to acquire the gas flow state monitoring information.
Specifically, in order to perform sterilization operation on the medicine production workshop more accurately, the usage state of the medicine production workshop is required to be monitored through the action generated in the medicine production workshop, the usage state can comprise a sensitive environment state and a sensitive action state, namely, when the usage state of the medicine production workshop is monitored, the environment index of bacteria or fungi, namely, temperature, humidity, pH value and the like, are caused to be generated, namely, the action of bacteria or fungi, namely, the artificial activity, the experimental activity and the like, are caused to be monitored as the sensitive environment state, further, the usage state to be monitored of the medicine production workshop is set, the usage state monitoring index comprises the position of the sensitive environment state and the sensitive action state in the medicine production workshop, the time of the sensitive environment state and the sensitive action state in the medicine production workshop, the scale of the sensitive environment state and the sensitive action state in the medicine production workshop, the generation scale is obtained by multiplying the generation time length by the generation times, further, the indexes to be monitored of the gas flow state in the current medicine production workshop are set, the indexes to be monitored of the gas flow state comprise the direction of the gas flow in the current area and the gas flow speed, when the sensitive environment state is monitored in the medicine production workshop to memorize the sensitive action state, the corresponding record is carried out on the generation position, the generation time and the generation scale of the medicine production workshop corresponding to the gas flow state and the gas flow speed, the record information is used as the record information of the current use state, the gas flow direction can be divided into four directions of southeast and northwest in the medicine production workshop, and the gas flow speed is manually moved according to the manual movement, and finally, through real-time monitoring of the two gas flow velocity caused by the movement of the object serving as a reference, correspondingly acquiring the gas flow state monitoring information, and achieving the technical effect of providing important basis for realizing sterilization treatment of a pharmaceutical production workshop in the later period.
Further, as shown in fig. 3, step S300 of the present application further includes:
step S310: acquiring a source region sensitive state type, a source region generation position, a source region generation time and a source region generation scale according to the use state record information of the microorganism source region;
step S320: calibrating the microbial output according to the type of the sensitive state of the source region and the occurrence scale of the source region, and acquiring a microbial output calibration result;
step S330: adding the microbial output calibration result, the source region generation position and the source region generation time into starting point state information;
step S340: determining a propagation velocity vector according to the gas flow state monitoring information after the occurrence time of the source region;
step S350: constructing a simulation environment of the medicine production workshop according to the clean area of the medicine production workshop and the spreading speed vector;
step S360: inputting the starting point state information into the simulation environment of the pharmaceutical production workshop to perform microbial spreading analysis, obtaining a spreading aggregation area and a spreading route area, and adding the information into the spreading track area.
Specifically, in order to determine the spreading area of the flora, a position reference is provided for fine monitoring, so that firstly, the information of the usage state contained in the determined microbial source area needs to be recorded, the sensitive state type, the source area occurrence position, the source area occurrence time and the source area occurrence scale corresponding to the usage process in the source area are acquired, the source area sensitive state type refers to the fact that the microbial source area with the microorganisms is determined to be in the medicine production workshop, the sensitive state type, namely the high sensitive type, the low sensitive type and the like, is determined according to the current temperature, the humidity, the pH value and the artificial activity or the experimental activity, the source area occurrence position refers to the position where the microorganisms exist in the microbial source area, the source area occurrence time refers to the starting time where the microorganisms exist in the microbial source area, the source region occurrence scale is obtained by determining the amount of microorganisms in the source region and the time when the microorganisms exist, further, the yield of the microorganisms is calibrated in the source region sensitive state type and the source region occurrence scale, and the unit amount and the average yield of the states of the microorganisms produced in the source region of the microorganisms are determined, and then the yield, namely the yield calibration result of the microorganisms is determined according to the average yield, so that the obtained yield calibration result of the microorganisms, the obtained source region occurrence position and the source region occurrence time are added to the starting point state information, wherein the starting point state information refers to the information of the moment of the microorganisms in the source region from the beginning to the beginning, and then after the source region occurrence time point, the spreading speed vector of the microorganisms is determined by the gas flow state monitoring information at the moment, the microbial spreading speed vector refers to the spreading direction of the microbes and the quantity of the spread microbes, further, the environment of the current drug production workshop is simulated by the clean area of the drug production workshop and the spreading speed vector, and the temperature, the humidity and the PH value in the clean area of the drug production workshop and the spreading speed of the microbes under the environmental information are based on the temperature, the humidity and the spreading speed of the microbes in the clean area of the drug production workshop, all parameters in the clean area of the drug production workshop are reduced, the simulation of the environment of the drug production workshop is completed, the obtained starting point state information is finally input into the simulation environment of the drug production workshop to analyze the spreading of the microbes, and the spreading aggregation area of the microbes, namely the area with high microbial content and the spreading route area of the microbes, namely the spreading direction of the microbes are added into the spreading track area, so that the drug production workshop is better in sterilization treatment and detection in the later period is ensured.
Further, as shown in fig. 4, step S400 of the present application further includes:
step S410: acquiring the spreading aggregation area and the spreading route area according to the spreading track area;
step S420: determining an aggregation boundary coordinate according to the spreading aggregation area;
step S430: determining path boundary coordinates according to the spreading route area;
step S440: determining a region to be monitored according to the aggregated boundary coordinates and the path boundary coordinates;
step S450: and disposing a sedimentation disc in the area to be monitored for microorganism detection, and obtaining a microorganism detection result.
Specifically, on the basis of the obtained spreading track area, the area with high microorganism content of the microorganisms and the spreading direction of the microorganisms are obtained according to the quantity and spreading speed of the current microorganisms, the spreading aggregation area of the microorganisms and the spreading route area of the microorganisms are further obtained, a rectangular coordinate system is established, namely, the southwest corner of a medicine production workshop is taken as an origin, the north direction is taken as a y axis, the eastern direction is taken as an x axis, the upper aggregation limit of the current microorganisms is extracted according to the spreading aggregation degree of the microorganisms in the current area, the aggregation boundary coordinates in the medicine production workshop coordinate system are determined according to the spreading route of the microorganisms in the current area, the range boundary of the current microorganisms is extracted according to the spreading route of the microorganisms in the current area, the current area to be monitored is determined according to the path boundary coordinates of the current microorganisms, the to-be-monitored boundary coordinates of the medicine production workshop and the microbial path boundary coordinates are further defined, the sedimentation dish is deployed in the determined to-be-monitored area, the sedimentation dish is used for extracting the upper aggregation limit of the microorganisms in the current area according to the spreading aggregation degree of the microorganisms in the current area, the aggregation limit of the microorganisms in the current area is taken as the x axis, the sedimentation dish is used for acquiring the sedimentation results of the biological particle in the medicine production workshop based on the detection results, and the sedimentation dish is used for achieving the accurate sterilization treatment.
Further, step S450 of the present application includes:
step S451: and when the microorganism content information of the microorganism detection result of the area to be monitored meets the microorganism content threshold, performing microorganism detection on the area not to be monitored, and supplementing the microorganism detection result.
Specifically, if the microorganism content information in the microorganism detection result of the area to be monitored meets the microorganism content threshold value, the non-monitoring area is subjected to microorganism monitoring, the microorganism detection result is correspondingly supplemented, namely, when the microorganism content in the area in the medicine production workshop which possibly spreads is smaller, the microorganism content is lower than 50% and is regarded as the microorganism content is smaller, other positions are safe positions, the monitoring is not needed, when the microorganism content is higher than or equal to 50% and is regarded as the microorganism content is higher, the other positions are required to be additionally monitored, and the medicine production workshop is better sterilized on the basis.
Further, as shown in fig. 5, step S500 of the present application further includes:
step S510: acquiring a microorganism content clustering threshold;
Step S520: acquiring a first distribution area and a second distribution area according to the microorganism distribution area, wherein the first distribution area and the second distribution area are adjacent;
step S530: judging whether the deviation value of the microorganism content information of the first distribution area and the second distribution area is smaller than or equal to the microorganism content clustering threshold value;
step S540: if the microbial content information is smaller than or equal to the first distribution area, gathering the first distribution area and the second distribution area into one type, setting the first distribution area and the second distribution area as a first clustering area, and setting the average value of the microbial content information of the first distribution area and the second distribution area as the microbial content information of the first clustering area;
step S550: and repeating clustering until the deviation value of the microorganism content information of any adjacent area is larger than the microorganism content clustering threshold value, and obtaining the microorganism distribution partition result.
Specifically, in order to refine and partition the area according to the microorganism content, a position basis is provided for the subsequent partition sterilization, so that a clustering threshold value of the microorganism content needs to be set, if the microorganism content in a first area is greater than or equal to 50%, the microorganism content is considered to be high, the first area is considered to be a first distribution area, if the microorganism content in a first area is less than 50%, the microorganism content is considered to be low, the first area is considered to be a second area, the first area is adjacent to the second area, further, whether the deviation value of the microorganism content information of the first area and the second area is smaller than or equal to the set microorganism content clustering threshold value is judged, if the deviation value of the microorganism content information of the first area and the second area is smaller than or equal to the set microorganism content clustering threshold value, the deviation value of the microorganism content information of the first area and the second area is considered to be less than or equal to 5%, therefore the first area and the second area are considered to be a second area, the first area and the second area are adjacent to the second area are set, and the second area are set to be a new area, and the microorganism content is not equal to the average value is calculated, when the microorganism content is equal to the set in the first area and the second area is equal to the new area, and the microorganism content is not equal to the set, and the average value is equal to the new microorganism content is calculated, and the average value is more than 30%, and the average value is calculated, and the average value is not equal to the average value, and the average value is obtained when the average value is large when the average value is obtained.
Further, as shown in fig. 6, step S600 of the present application further includes:
step S610: the sterilization control parameters comprise air sterilization control parameters and equipment sterilization control parameters, wherein the air sterilization control parameters comprise methanol generation amount, methanol generation position, methanol fumigation time and methanol ventilation time, and the equipment sterilization control parameters comprise spray reagent type, spray position, spray amount and spray duration;
step S620: optimally designing the methanol generation amount, the methanol generation position, the methanol fumigation time and the methanol ventilation time according to the partition microorganism content information and the microorganism distribution partition result to obtain an air sterilization control parameter optimization result;
step S630: optimizing the type, the spraying position, the spraying quantity and the spraying time of the spraying reagent according to the partition microorganism content information and the microorganism distribution partition result, and obtaining an equipment sterilization control parameter optimizing result;
step S640: and adding the air sterilization control parameter optimization result and the equipment sterilization control parameter optimization result into the sterilization control parameter optimization result.
Specifically, the sterilization control can be better performed on a medicine production workshop in the later period, the sterilization control parameters can comprise an air sterilization control parameter and an equipment sterilization control parameter, the air sterilization control parameter can also comprise a methanol generation amount, a methanol generation position, a methanol fumigation time and a methanol ventilation time, the equipment sterilization control parameter can also comprise a spray reagent type, a spray position, a spray amount and a spray time, the methanol generation amount refers to the methanol content generated in the medicine production workshop, the methanol generation position refers to the area generated by the methanol in the medicine production workshop, the methanol fumigation time refers to the time for killing pathogenic microorganisms by utilizing the reaction of formalin and potassium permanganate, the methanol ventilation time refers to the time for sterilizing pathogenic microorganisms by utilizing formalin and generating the methanol gas, the methanol ventilation time refers to the ventilation time for air in the medicine production workshop for 3-4 times, each ventilation time is about 2 hours, the spray reagent type refers to the min propanol (75%), the alcohol (75%), the dialdehyde, the clean-mole-kill and the like, the spray position in the area for spraying the methanol in the medicine production workshop, the spray reagent in milliliter in the spray area, the spray reagent, the spray time refers to the methanol content in the spray area, the methanol concentration in the spray position, the methanol concentration in the methanol concentration, the methanol concentration and the total consumption in the spray time are, the methanol concentration is further designed, the total time is optimal, the total time is used for the methanol concentration and the microbial sterilization is suitable for the biological sterilization control, and the biological sterilization result is obtained, and the value is obtained by optimizing the value, and the biological sterilization result, and the time is optimal, and the value is obtained The spraying amount and the spraying time length are optimally designed according to the information of the microbial content of the subareas and the microbial distribution subarea result, and the method can be used for placing glutaraldehyde in an automatic sprayer with time control, automatically spraying when a medicine production workshop is in an idle state, adjusting the spraying amount, setting the time, and stopping an air conditioning system during spraying, so that the equipment sterilization control parameter optimization result is continuously obtained, and finally adding the air sterilization control parameter optimization result and the equipment sterilization control parameter optimization result into the sterilization control parameter optimization result to achieve the technical effect of sterilizing the medicine production workshop.
Example two
Based on the same inventive concept as the optimized sterilization control method of a pharmaceutical production plant in the foregoing embodiments, as shown in fig. 7, the present application provides an optimized sterilization control system of a pharmaceutical production plant, the system comprising:
the information acquisition module 1 is used for acquiring use state record information and gas flow state monitoring information of a preset time zone of a clean zone of a pharmaceutical production workshop;
a region determining module 2, wherein the region determining module 2 is used for determining a microorganism source region according to the usage state record information;
the microorganism spreading analysis module 3 is used for performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area;
the microorganism detection module 4 is used for detecting microorganisms in the spreading track area to obtain microorganism detection results, wherein the microorganism detection results comprise microorganism content information and microorganism distribution areas;
the hierarchical clustering analysis module 5 is used for performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results;
The optimizing module 6 is used for optimizing the sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition result when the partition microorganism content information of any one of the microorganism distribution partition results meets the microorganism content threshold value, and obtaining a sterilization control parameter optimizing result;
and the sterilization treatment module 7 is used for carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization result.
Further, the system further comprises:
the state setting module is used for setting a to-be-monitored use state, wherein the to-be-monitored use state comprises a sensitive environment state and a sensitive action state;
the first index setting module is used for setting the indexes to be monitored in the use state, wherein the indexes to be monitored in the use state comprise the occurrence position, the occurrence time and the occurrence scale;
the second index setting module is used for setting an index to be monitored of the gas flow state, wherein the index to be monitored of the gas flow state comprises a gas flow direction and a gas flow speed;
The recording module is used for recording the occurrence position, the occurrence time and the occurrence scale when the sensitive environment state and the sensitive action state occur, and acquiring the use state recording information; and
and the monitoring module is used for monitoring the gas flow direction and the gas flow speed and acquiring the gas flow state monitoring information.
Further, the system further comprises:
the source region module is used for acquiring a source region sensitive state type, a source region generation position, a source region generation time and a source region generation scale according to the use state record information of the microorganism source region;
the calibration module is used for calibrating the microbial output according to the sensitive state type of the source region and the occurrence scale of the source region, and acquiring a microbial output calibration result;
the first adding module is used for adding the microbial output calibration result, the source region occurrence position and the source region occurrence time into starting point state information;
a spreading velocity vector determining module for determining a spreading velocity vector according to the gas flow state monitoring information after the occurrence time of the source region;
The simulation environment module is used for constructing a simulation environment of the medicine production workshop according to the clean area of the medicine production workshop and the spreading speed vector;
the region adding module is used for inputting the starting point state information into the simulation environment of the pharmaceutical production workshop to perform microbial spreading analysis, obtaining a spreading aggregation region and a spreading route region, and adding the information into the spreading track region.
Further, the system further comprises:
the first region acquisition module is used for acquiring the spreading aggregation region and the spreading route region according to the spreading track region;
the first coordinate determining module is used for determining an aggregation boundary coordinate according to the spreading aggregation area;
the second coordinate determining module is used for determining path boundary coordinates according to the spreading route area;
the area determining module is used for determining an area to be monitored according to the aggregation boundary coordinates and the path boundary coordinates;
and the microorganism detection module is used for deploying a sedimentation disc in the area to be monitored to carry out microorganism detection, and acquiring a microorganism detection result.
Further, the system further comprises:
and the supplementing module is used for carrying out microorganism detection on a non-to-be-monitored area and supplementing the microorganism detection result when the microorganism content information of the microorganism detection result of the to-be-monitored area meets the microorganism content threshold.
Further, the system further comprises:
the threshold acquisition module is used for acquiring a microorganism content clustering threshold;
the second region acquisition module is used for acquiring a first distribution region and a second distribution region according to the microorganism distribution region, wherein the first distribution region and the second distribution region are adjacent;
the judging module is used for judging whether the deviation value of the microorganism content information of the first distribution area and the second distribution area is smaller than or equal to the microorganism content clustering threshold value;
the area setting module is used for gathering the first distribution area and the second distribution area into one type if the area setting module is smaller than or equal to the area setting module, setting the first distribution area and the second distribution area as a first clustering area, and setting the average value of the microorganism content information of the first distribution area and the second distribution area as the microorganism content information of the first clustering area;
And the result acquisition module is used for repeatedly clustering until the deviation value of the microorganism content information of any adjacent area is larger than the microorganism content clustering threshold value, and acquiring the microorganism distribution partition result.
Further, the system further comprises:
the parameter acquisition module is used for acquiring sterilization control parameters including air sterilization control parameters and equipment sterilization control parameters, wherein the air sterilization control parameters include methanol generation amount, methanol generation position, methanol fumigation time and methanol ventilation time, and the equipment sterilization control parameters include spray reagent type, spray position, spray amount and spray duration;
the first optimal design module is used for optimally designing the methanol generation amount, the methanol generation position, the methanol fumigation time and the methanol ventilation time according to the partition microorganism content information and the microorganism distribution partition result to obtain an air sterilization control parameter optimization result;
the second optimal design module is used for optimally designing the type, the spraying position, the spraying quantity and the spraying duration of the spraying reagent according to the partition microorganism content information and the microorganism distribution partition result, and obtaining an equipment sterilization control parameter optimization result;
And the second adding module is used for adding the air sterilization control parameter optimization result and the equipment sterilization control parameter optimization result into the sterilization control parameter optimization result.
The foregoing detailed description of an optimized sterilization control method for a pharmaceutical production plant will be clear to those skilled in the art, and the apparatus disclosed in this embodiment is relatively simple to describe, and the relevant points refer to the description of the method section, since it corresponds to the method disclosed in the embodiment.
The previous description of the disclosed embodiments is provided to enable any person skilled in the art to make or use the present application. Various modifications to these embodiments will be readily apparent to those skilled in the art, and the generic principles defined herein may be applied to other embodiments without departing from the spirit or scope of the application. Thus, the present application is not intended to be limited to the embodiments shown herein but is to be accorded the widest scope consistent with the principles and novel features disclosed herein.
Claims (8)
1. An optimized sterilization control method for a pharmaceutical production plant is characterized by comprising the following steps:
acquiring use state record information and gas flow state monitoring information of a preset time zone of a clean zone of a medicine production workshop;
determining a microorganism source area according to the use state record information;
performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area;
detecting microorganisms in the spreading track area to obtain a microorganism detection result, wherein the microorganism detection result comprises microorganism content information and a microorganism distribution area;
performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results;
when the partition microorganism content information of any one of the microorganism distribution partition results meets a microorganism content threshold, optimizing sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition results to obtain a sterilization control parameter optimization result;
and carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization results.
2. The method of claim 1, wherein the acquiring the usage status record information and the gas flow status monitoring information for the predetermined time zone of the clean zone of the pharmaceutical production plant comprises:
setting a to-be-monitored use state, wherein the to-be-monitored use state comprises a sensitive environment state and a sensitive action state;
setting a use state to-be-monitored index, wherein the use state to-be-monitored index comprises an occurrence position, an occurrence time and an occurrence scale;
setting a gas flow state to-be-monitored index, wherein the gas flow state to-be-monitored index comprises a gas flow direction and a gas flow speed;
when the sensitive environment state and the sensitive action state occur, recording the occurrence position, the occurrence time and the occurrence scale, and acquiring the use state recording information; and
and monitoring the gas flow direction and the gas flow speed to acquire the gas flow state monitoring information.
3. The method of claim 1, wherein said performing a microbial creep analysis based on said microbial source area and said gas flow state monitoring information to obtain a creep trace area comprises:
Acquiring a source region sensitive state type, a source region generation position, a source region generation time and a source region generation scale according to the use state record information of the microorganism source region;
calibrating the microbial output according to the type of the sensitive state of the source region and the occurrence scale of the source region, and acquiring a microbial output calibration result;
adding the microbial output calibration result, the source region generation position and the source region generation time into starting point state information;
determining a propagation velocity vector according to the gas flow state monitoring information after the occurrence time of the source region;
constructing a simulation environment of the medicine production workshop according to the clean area of the medicine production workshop and the spreading speed vector;
inputting the starting point state information into the simulation environment of the pharmaceutical production workshop to perform microbial spreading analysis, obtaining a spreading aggregation area and a spreading route area, and adding the information into the spreading track area.
4. The method of claim 3, wherein the performing the microorganism detection on the locus of spread to obtain the microorganism detection result comprises:
acquiring the spreading aggregation area and the spreading route area according to the spreading track area;
Determining an aggregation boundary coordinate according to the spreading aggregation area;
determining path boundary coordinates according to the spreading route area;
determining a region to be monitored according to the aggregated boundary coordinates and the path boundary coordinates;
and disposing a sedimentation disc in the area to be monitored for microorganism detection, and obtaining a microorganism detection result.
5. The method as recited in claim 4, further comprising: and when the microorganism content information of the microorganism detection result of the area to be monitored meets the microorganism content threshold, performing microorganism detection on the area not to be monitored, and supplementing the microorganism detection result.
6. The method of claim 1, wherein performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results comprises:
acquiring a microorganism content clustering threshold;
acquiring a first distribution area and a second distribution area according to the microorganism distribution area, wherein the first distribution area and the second distribution area are adjacent;
judging whether the deviation value of the microorganism content information of the first distribution area and the second distribution area is smaller than or equal to the microorganism content clustering threshold value;
If the microbial content information is smaller than or equal to the first distribution area, gathering the first distribution area and the second distribution area into one type, setting the first distribution area and the second distribution area as a first clustering area, and setting the average value of the microbial content information of the first distribution area and the second distribution area as the microbial content information of the first clustering area;
and repeating clustering until the deviation value of the microorganism content information of any adjacent area is larger than the microorganism content clustering threshold value, and obtaining the microorganism distribution partition result.
7. The method of claim 1, wherein when the partition microorganism content information of any one of the microorganism distribution partition results satisfies the microorganism content threshold, optimizing the sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition results, and obtaining the sterilization control parameter optimization result includes:
the sterilization control parameters comprise air sterilization control parameters and equipment sterilization control parameters, wherein the air sterilization control parameters comprise methanol generation amount, methanol generation position, methanol fumigation time and methanol ventilation time, and the equipment sterilization control parameters comprise spray reagent type, spray position, spray amount and spray duration;
Optimally designing the methanol generation amount, the methanol generation position, the methanol fumigation time and the methanol ventilation time according to the partition microorganism content information and the microorganism distribution partition result to obtain an air sterilization control parameter optimization result;
optimizing the type, the spraying position, the spraying quantity and the spraying time of the spraying reagent according to the partition microorganism content information and the microorganism distribution partition result, and obtaining an equipment sterilization control parameter optimizing result;
and adding the air sterilization control parameter optimization result and the equipment sterilization control parameter optimization result into the sterilization control parameter optimization result.
8. An optimized sterilization control system for a pharmaceutical production facility, comprising:
the information acquisition module is used for acquiring the use state record information and the gas flow state monitoring information of a preset time zone of the clean zone of the medicine production workshop;
the area determining module is used for determining a microorganism source area according to the using state record information;
the microorganism spreading analysis module is used for performing microorganism spreading analysis according to the microorganism source area and the gas flow state monitoring information to obtain a spreading track area;
The microorganism detection module is used for detecting microorganisms in the spreading track area to obtain microorganism detection results, wherein the microorganism detection results comprise microorganism content information and microorganism distribution areas;
the hierarchical clustering analysis module is used for performing hierarchical clustering analysis on the microorganism distribution area according to the microorganism content information to obtain microorganism distribution partition results;
the optimizing module is used for optimizing the sterilization control parameters according to the partition microorganism content information and the microorganism distribution partition result when the partition microorganism content information of any one of the microorganism distribution partition results meets a microorganism content threshold value, and obtaining a sterilization control parameter optimizing result;
and the sterilization treatment module is used for carrying out sterilization treatment on any one of the microorganism distribution partition results of the medicine production workshop according to the sterilization control parameter optimization result.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310619261.0A CN116617432B (en) | 2023-05-29 | 2023-05-29 | Optimized sterilization control method and system for medicine production workshop |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202310619261.0A CN116617432B (en) | 2023-05-29 | 2023-05-29 | Optimized sterilization control method and system for medicine production workshop |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN116617432A true CN116617432A (en) | 2023-08-22 |
| CN116617432B CN116617432B (en) | 2023-11-21 |
Family
ID=87641355
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202310619261.0A Active CN116617432B (en) | 2023-05-29 | 2023-05-29 | Optimized sterilization control method and system for medicine production workshop |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN116617432B (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117235475A (en) * | 2023-11-07 | 2023-12-15 | 江苏旭龙环境科技有限公司 | Distributed operation control method and system for cadmium treatment equipment |
| CN117590788A (en) * | 2023-12-18 | 2024-02-23 | 广州市广味源食品有限公司 | Soybean sauce production workshop environment monitoring system based on sterilization control |
Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006067974A (en) * | 2004-09-06 | 2006-03-16 | Sysmex Corp | Method for measuring sterilization effect on microorganism |
| JP2013190381A (en) * | 2012-03-15 | 2013-09-26 | Shimizu Corp | Sterilization performance predicting system and sterilization performance predicting program |
| US20160348146A1 (en) * | 2014-03-20 | 2016-12-01 | Hitachi Plant Services Co., Ltd. | Microorganism measuring system and microorganism measuring method |
| WO2018106036A2 (en) * | 2016-12-07 | 2018-06-14 | 유버 주식회사 | Air sterilizing purifier and control method thereof |
| KR20190132090A (en) * | 2018-05-18 | 2019-11-27 | 주식회사 더웨이브톡 | Microorganism population counting method and system for the same |
| US20220016286A1 (en) * | 2019-03-29 | 2022-01-20 | Ushio Denki Kabushiki Kaisha | Sterilization status detection method, sterilization method, sterilization status detection device, sterilization device |
| CN114272418A (en) * | 2021-12-30 | 2022-04-05 | 楚天科技股份有限公司 | Vaporized hydrogen peroxide sterilization strengthening method based on hydroxyl free radical monitoring |
| CN114281051A (en) * | 2021-12-31 | 2022-04-05 | 智迈思(广东)科技有限公司 | Intelligent GMP clean area rotation disinfection control system |
| CN114617984A (en) * | 2020-12-11 | 2022-06-14 | 北京大学 | Sterilization and disinfection method and device |
| CN114649086A (en) * | 2022-05-13 | 2022-06-21 | 山东润一智能科技有限公司 | Intelligent microorganism monitoring system based on medical health safety |
-
2023
- 2023-05-29 CN CN202310619261.0A patent/CN116617432B/en active Active
Patent Citations (10)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| JP2006067974A (en) * | 2004-09-06 | 2006-03-16 | Sysmex Corp | Method for measuring sterilization effect on microorganism |
| JP2013190381A (en) * | 2012-03-15 | 2013-09-26 | Shimizu Corp | Sterilization performance predicting system and sterilization performance predicting program |
| US20160348146A1 (en) * | 2014-03-20 | 2016-12-01 | Hitachi Plant Services Co., Ltd. | Microorganism measuring system and microorganism measuring method |
| WO2018106036A2 (en) * | 2016-12-07 | 2018-06-14 | 유버 주식회사 | Air sterilizing purifier and control method thereof |
| KR20190132090A (en) * | 2018-05-18 | 2019-11-27 | 주식회사 더웨이브톡 | Microorganism population counting method and system for the same |
| US20220016286A1 (en) * | 2019-03-29 | 2022-01-20 | Ushio Denki Kabushiki Kaisha | Sterilization status detection method, sterilization method, sterilization status detection device, sterilization device |
| CN114617984A (en) * | 2020-12-11 | 2022-06-14 | 北京大学 | Sterilization and disinfection method and device |
| CN114272418A (en) * | 2021-12-30 | 2022-04-05 | 楚天科技股份有限公司 | Vaporized hydrogen peroxide sterilization strengthening method based on hydroxyl free radical monitoring |
| CN114281051A (en) * | 2021-12-31 | 2022-04-05 | 智迈思(广东)科技有限公司 | Intelligent GMP clean area rotation disinfection control system |
| CN114649086A (en) * | 2022-05-13 | 2022-06-21 | 山东润一智能科技有限公司 | Intelligent microorganism monitoring system based on medical health safety |
Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN117235475A (en) * | 2023-11-07 | 2023-12-15 | 江苏旭龙环境科技有限公司 | Distributed operation control method and system for cadmium treatment equipment |
| CN117235475B (en) * | 2023-11-07 | 2024-02-13 | 江苏旭龙环境科技有限公司 | Distributed operation control method and system for cadmium treatment equipment |
| CN117590788A (en) * | 2023-12-18 | 2024-02-23 | 广州市广味源食品有限公司 | Soybean sauce production workshop environment monitoring system based on sterilization control |
| CN117590788B (en) * | 2023-12-18 | 2024-05-31 | 广州市广味源食品有限公司 | Soybean sauce production workshop environment monitoring system based on sterilization control |
Also Published As
| Publication number | Publication date |
|---|---|
| CN116617432B (en) | 2023-11-21 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| CN116617432B (en) | Optimized sterilization control method and system for medicine production workshop | |
| CN114297954A (en) | Big data intelligent analysis digital management and control platform based on sewage treatment plant | |
| CN116975378B (en) | Equipment environment monitoring method and system based on big data | |
| EP2270198A1 (en) | Method for analyzing image for cell observation, image processing program, and image processing device | |
| CN116307383B (en) | Ecological balance-based land fine conservation improvement method and system | |
| CN109634233A (en) | Industrial big data intellectual analysis decision-making technique, readable storage medium storing program for executing and terminal | |
| CN116216819B (en) | Intelligent water affair data analysis management system and method | |
| CN114662344B (en) | Atmospheric pollution source tracing prediction method and system based on continuous online observation data | |
| CN117114749B (en) | Intelligent pig frozen semen management method and system | |
| CN116258238A (en) | Crop management system based on Internet of things | |
| AU2021105327A4 (en) | A computer implemented and IoT based method for increasing crop production using machine learning model | |
| CN116663904A (en) | Intelligent target supervision system and method based on data analysis | |
| CN110277139B (en) | Microorganism limit checking system and method based on Internet | |
| Ruiz-Arenas et al. | Implementation of system operation modes for health management and failure prognosis in cyber-physical systems | |
| CN115757836A (en) | Product carbon footprint analysis system based on knowledge graph | |
| Náhlík et al. | On-line parameter and state estimation of continuous cultivation by extended Kalman filter | |
| CN116543838B (en) | Data analysis method for biological gene selection expression probability | |
| CN113983600B (en) | Indoor air quality intelligent management system based on big data | |
| CN117989676B (en) | Air conditioner energy consumption data supervision method and system based on big data | |
| CN116777086B (en) | Predictive maintenance method and system for intelligent steel structure production line based on multimode data | |
| CN118070664B (en) | Building energy consumption intelligent simulation method based on Internet of things and BIM | |
| US20230377354A1 (en) | Continuous detection and species classification of biological particles in a sample | |
| Nasution et al. | Application of Open Garden Sensor on Hydroponic Maintenance Management | |
| CN118897529A (en) | Control method of microbial agent expanding culture and automatic feeding equipment | |
| CN118051859B (en) | Automatic analysis system for microorganism culture result |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant |