CN114137920A - Intelligent laboratory management system and method for ready-mix plant - Google Patents
Intelligent laboratory management system and method for ready-mix plant Download PDFInfo
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- CN114137920A CN114137920A CN202111420911.6A CN202111420911A CN114137920A CN 114137920 A CN114137920 A CN 114137920A CN 202111420911 A CN202111420911 A CN 202111420911A CN 114137920 A CN114137920 A CN 114137920A
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- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B19/00—Programme-control systems
- G05B19/02—Programme-control systems electric
- G05B19/418—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM]
- G05B19/41865—Total factory control, i.e. centrally controlling a plurality of machines, e.g. direct or distributed numerical control [DNC], flexible manufacturing systems [FMS], integrated manufacturing systems [IMS], computer integrated manufacturing [CIM] characterised by job scheduling, process planning, material flow
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- G—PHYSICS
- G05—CONTROLLING; REGULATING
- G05B—CONTROL OR REGULATING SYSTEMS IN GENERAL; FUNCTIONAL ELEMENTS OF SUCH SYSTEMS; MONITORING OR TESTING ARRANGEMENTS FOR SUCH SYSTEMS OR ELEMENTS
- G05B2219/00—Program-control systems
- G05B2219/30—Nc systems
- G05B2219/32—Operator till task planning
- G05B2219/32252—Scheduling production, machining, job shop
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- 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]
Abstract
The invention discloses a system and a method for managing an intelligent laboratory of a pre-mixing plant, which comprises the following steps: the system comprises a sampling task subsystem, a sample automatic coding subsystem, an experiment detection subsystem and a data statistical analysis subsystem, wherein the sampling task subsystem is used for collecting a concrete raw material sample and a concrete sample; the sample automatic coding subsystem is used for obtaining a coded concrete raw material sample and a coded concrete sample; the experiment detection subsystem is used for acquiring detection data of the concrete raw material sample and detection data of the concrete sample and acquiring detection data of manual detection; and the data statistical analysis subsystem is used for obtaining statistical analysis parameters and obtaining quality performance evaluation based on the statistical analysis parameters. The invention can increase the reality and accuracy of detection data, reduce the detection quality risk, reduce the labor cost, reduce the manual communication and improve the working efficiency.
Description
Technical Field
The invention relates to the technical field of intelligent laboratory management of a premixing plant, in particular to an intelligent laboratory management system and method of the premixing plant.
Background
In the concrete industry, a laboratory of a ready-mix plant is the core of concrete quality control, and the laboratory is responsible for the work of site-entering sampling, experimental detection, concrete sampling and performance detection, experimental instrument and equipment management, field technical service, data statistical analysis and the like of concrete raw materials, and both government supervision and enterprise internal control are based on laboratory detection data, so that the laboratory bears the task of concrete quality risk control of the ready-mix plant and the task of quality risk control of concrete buildings to a certain extent, and the laboratory of the ready-mix plant with strict specifications is vital.
However, the current situation of the laboratory of the premixing plant has the following defects: the first and all links are completed through manual operation, sampling, numbering, detecting, data inputting, analyzing and the like are all performed through manual operation, and the labor cost of laboratory operation is gradually increased along with the increasing rarity of human resources; secondly, as the businesses of raw material entering a factory, acceptance, concrete production, sampling and the like cover different departments, the communication cost is high and the efficiency is low; thirdly, the numbers of the laboratory are generally numbered by the detection personnel during detection, the data are registered on a paper account after the experiment and then are recorded into the spreadsheet, the data are transcribed during statistical analysis, the data may have artificial recording errors and fake records, multiple data transcriptions may cause data confusion, the data cannot be traced back due to no process record, and the three defects cause the gradual increase of the laboratory cost, the low efficiency and the increase of the detection quality risk.
Disclosure of Invention
In order to solve the problems in the prior art, the invention provides an intelligent laboratory management system and method for a ready-mix plant, which can reduce the operation cost of a laboratory, improve the working efficiency and reduce the detection quality risk.
In order to achieve the above object, the present invention is realized by:
in a first aspect, the present invention provides a system for intelligent laboratory management of a ready-mix plant, comprising:
the sampling task subsystem is used for acquiring concrete raw material factory entering data and concrete real-time production data, respectively acquiring a first sampling frequency rule and a second sampling frequency rule based on the concrete raw material factory entering data and the concrete real-time production data, respectively generating a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and sending the first sampling task and the second sampling task to a terminal so as to obtain a concrete raw material sample and a concrete sample which are respectively acquired by the terminal according to the first sampling task and the second sampling task;
the sample automatic coding subsystem is used for respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain the coded concrete raw material sample and the coded concrete sample;
the experiment detection subsystem is used for respectively detecting the coded concrete raw material sample and the coded concrete sample, acquiring detection data of the concrete raw material sample and the detection data of the concrete sample, and acquiring detection data of manual detection;
and the data statistical analysis subsystem is used for generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
Further, the sampling task subsystem is further configured to automatically push the next node sampling task to the terminal through a preset sampling task flow when the previous node sampling task is completed until the sampling task flow is finished.
Further, the assay detection subsystem comprises:
the full-automatic detection module is used for full-automatically detecting the coded concrete raw material sample and the coded concrete sample to obtain detection data of the concrete raw material sample and detection data of the concrete sample;
the system comprises a flow detection module, a flow detection module and a data processing algorithm, wherein the flow detection module is used for acquiring detection data of manual detection, the detection data of the manual detection comprises experiment detection data and an experiment detection result, the manual detection is guided based on the flow steps through presetting flow design models of all experiments and presetting the flow steps of the flow design models, the experiment detection data acquired in each step are recorded, and after all the steps are completed, the experiment detection result is automatically calculated according to the data processing algorithm based on the acquired experiment detection data, and whether the experiment detection result is qualified or not is judged.
Further, the data statistics analysis subsystem comprises:
the report form personalized design module is used for automatically generating an experiment data report form based on the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection and the experiment detection result of the manual detection;
the experimental data statistical analysis module is used for classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection and the experimental detection result of the manual detection to obtain statistical analysis parameters;
and the quality performance evaluation module is used for obtaining quality performance evaluation according to the statistical analysis parameters.
Furthermore, the intelligent laboratory management system also comprises a laboratory equipment management subsystem, the laboratory equipment management subsystem comprises an experimental and maintenance environment early warning module, an experimental equipment state detection module and an experimental equipment verification early warning module, wherein,
the experimental and maintenance environment early warning module is preset with parameter thresholds of experimental environment and maintenance environment and is used for detecting various parameter values of the experimental environment and the maintenance environment in real time, and if the parameter values exceed the parameter thresholds, an alarm signal is sent out and sent to the terminal;
the experimental equipment state detection module is provided with an equipment state detection operation guiding step and is used for detecting the state of the equipment according to the operation guiding step and automatically generating associated information generated when the equipment is used;
the calibration early warning module of the experimental equipment is preset with calibration time and calibration period rules, the calibration time of the experimental instrument is calculated through the calibration time and the calibration period rules, and the calibration time is sent to the terminal through electronic information.
Furthermore, the intelligent laboratory management system also comprises a pouring site service management subsystem, wherein the pouring site service management subsystem comprises a pouring site electronic fence module, a path tracking and recording module, an information recording module and a safety early warning module,
a construction site map is arranged in the pouring site electronic fence module, a pouring site electronic fence is arranged based on the construction site map, and related information of a technician entering the pouring site electronic fence is recorded;
the path tracking recording module is used for drawing the path of the technician in real time;
the information recording module is used for recording the related information of the project implemented by the technical staff and recording the situation of the project implementation site;
the safety early warning module is used for providing a calling function and an alarming function.
Further, wisdom laboratory management system still includes:
the first memory is used for storing the detection data of the concrete raw material sample and the detection data of the concrete sample, which are acquired by the full-automatic detection module, and storing the flow steps, the experimental detection data of each step and the acquired experimental detection results in the flow detection module;
and the second memory is used for storing the related information of the technical staff in the casting site electronic fence module entering the casting site electronic fence and storing the condition of the project implementation site in the information recording module.
In a second aspect, the present invention provides a method for managing an intelligent laboratory of a ready-mix factory, including:
acquiring raw concrete material factory entering data and real-time concrete production data, respectively acquiring a first sampling frequency rule and a second sampling frequency rule based on the raw concrete material factory entering data and the real-time concrete production data, respectively generating a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and respectively acquiring a raw concrete material sample and a concrete sample based on the first sampling task and the second sampling task;
respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain the coded concrete raw material sample and the coded concrete sample;
respectively detecting the coded concrete raw material sample and the coded concrete sample, acquiring detection data of the concrete raw material sample and the detection data of the concrete sample, and acquiring detection data of manual detection;
and generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
Compared with the prior art, the invention has the following beneficial effects:
the intelligent laboratory management system comprises a sampling task subsystem, a sample automatic coding subsystem, an experiment detection subsystem and a data statistics and analysis subsystem, wherein the sampling task subsystem can automatically generate a sampling task without manual participation, so that inefficient manual communication is avoided, the labor cost is reduced, and the efficiency is improved; the sample automatic coding subsystem automatically codes the samples without manual participation, so that the labor cost is reduced; the experiment detection subsystem is used for detecting the concrete raw material and the concrete, so that the labor cost can be reduced; the data statistical analysis subsystem is used for carrying out statistical analysis on the detection data of the concrete raw material and the concrete, manual participation is not needed, and labor cost is reduced; and the detection data generated by each subsystem in the intelligent laboratory management system does not need paper record, so that the reality and the accuracy of the detection data can be increased, the detection quality risk is reduced, the subsystems in the intelligent laboratory management system cooperate with each other, the manual communication is reduced, and the working efficiency is improved.
Drawings
The above and/or additional aspects and advantages of the present invention will become apparent and readily appreciated from the following description of the embodiments, taken in conjunction with the accompanying drawings of which:
FIG. 1 is a schematic diagram of a system architecture of a pre-mix plant intelligent laboratory management system according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of a system of a Ready-mix plant intelligent laboratory management system according to another embodiment of the present invention;
FIG. 3 is a block diagram of a system for intelligent lab management in a pre-mix plant according to an embodiment of the present invention;
FIG. 4 is a flowchart illustrating a method for intelligent lab management in a pre-mix plant according to one embodiment of the present invention;
description of reference numerals:
100. a sampling task subsystem; 101. a raw material random sampling task module; 102. a concrete random sampling task module; 103. a task automatic transfer module; 200. a sample automatic encoding subsystem; 300. an experiment detection subsystem; 301. a full-automatic detection module; 302. a flow detection module; 400. a data statistical analysis subsystem; 401. a report personalized design module; 402. an experimental data statistical analysis module; 403. a quality performance evaluation module; 500. a laboratory equipment management subsystem; 501. an experiment and maintenance environment early warning module; 502. an experimental equipment state detection module; 503. the test device comprises a test early warning module; 600. a pouring site service management subsystem; 601. pouring the on-site electronic fence module; 602. a path tracking recording module; 603. an information recording module; 604. and a safety early warning module.
Detailed Description
The technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the accompanying drawings, and it is to be understood that the described embodiments are only a part of the embodiments of the present disclosure, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments of the disclosure without making any creative effort, shall fall within the protection scope of the disclosure. It should be noted that the features of the embodiments and examples of the present disclosure may be combined with each other without conflict. In addition, the purpose of the drawings is to graphically supplement the description in the written portion of the specification so that a person can intuitively and visually understand each technical feature and the whole technical solution of the present disclosure, but it should not be construed as limiting the scope of the present disclosure.
In the description of the present invention, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the feature. In the description of the present invention, "a plurality" means two or more unless otherwise specified.
In the description of the present invention, unless otherwise explicitly limited, terms such as arrangement, installation, connection and the like should be understood in a broad sense, and those skilled in the art can reasonably determine the specific meanings of the above terms in the present invention in combination with the specific contents of the technical solutions.
The technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
The current situation of the laboratory of the ready-mix plant has the following disadvantages: the first and all links are completed through manual operation, sampling, numbering, detecting, data inputting, analyzing and the like are all performed through manual operation, and the labor cost of laboratory operation is gradually increased along with the increasing rarity of human resources; secondly, as the businesses of raw material entering a factory, acceptance, concrete production, sampling and the like cover different departments, the communication cost is high and the efficiency is low; thirdly, the numbers of the laboratory are generally numbered by the detection personnel during detection, the data are registered on a paper account after the experiment and then are recorded into the spreadsheet, the data are transcribed during statistical analysis, the data may have artificial recording errors and fake records, multiple data transcriptions may cause data confusion, the data cannot be traced back due to no process record, and the three defects cause the gradual increase of the laboratory cost, the low efficiency and the increase of the detection quality risk.
In order to solve the problems, the intelligent laboratory management system comprises a sampling task subsystem 100, a sample automatic coding subsystem 200, an experiment detection subsystem 300 and a data statistics analysis subsystem 400, and the sampling task can be automatically generated through the sampling task subsystem 100 without manual participation, so that the inefficient manual communication is avoided, the labor cost is reduced, and the efficiency is improved; the sample automatic coding subsystem 200 automatically codes the samples without manual participation, so that the labor cost is reduced; the experiment detection subsystem 300 is used for detecting the concrete raw materials and the concrete, so that the labor cost can be reduced; the data statistical analysis subsystem 400 is used for carrying out statistical analysis on the detection data of the concrete raw materials and the concrete, manual participation is not needed, and labor cost is reduced; and the detection data generated by each subsystem in the intelligent laboratory management system does not need paper record, so that the reality and the accuracy of the detection data can be increased, the detection quality risk is reduced, the subsystems in the intelligent laboratory management system cooperate with each other, the manual communication is reduced, and the working efficiency is improved.
Referring to fig. 1 to 3, an embodiment of the present invention provides an intelligent lab management system for a pre-mix plant, including a sampling task subsystem 100, a sample automatic encoding subsystem 200, an experiment detection subsystem 300, a data statistics analysis subsystem 400, a lab equipment management subsystem 500, and a casting field service management subsystem 600, wherein,
the sampling task subsystem 100 is configured to obtain raw concrete material factory entering data and real-time concrete production data, respectively obtain a first sampling frequency rule and a second sampling frequency rule based on the raw concrete material factory entering data and the real-time concrete production data, respectively generate a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and send the first sampling task and the second sampling task to a terminal, so as to obtain a raw concrete material sample and a concrete sample which are respectively collected by the terminal according to the first sampling task and the second sampling task.
Further, the sampling task subsystem 100 is further configured to automatically push the sampling task of the next node to the terminal through a preset sampling task flow when the sampling task of the previous node is completed until the sampling task flow is finished.
Specifically, the sampling task subsystem 100 includes a raw material random sampling task module 101, a concrete random sampling task module 102, and an automatic task flow module 103, wherein,
the raw material random sampling task module 101 is used for acquiring data of various concrete raw materials entering a factory, wherein the data of the concrete raw materials entering the factory comprises data of manufacturers, batches, transportation license plates, drivers, quantity, date and the like, a first sampling frequency rule is acquired based on the data of the concrete raw materials entering the factory, a first sampling task is generated according to the first sampling frequency rule, the first sampling task is sent to a terminal in an electronic information mode, the terminal is provided with corresponding service personnel to read information, and after the service personnel read the information, the concrete raw material samples are acquired according to the first sampling task to acquire the concrete raw material samples.
The concrete random sampling task module 102 is configured to obtain concrete real-time production data, where the concrete real-time production data includes data such as items, structure parts, concrete labels, accumulated production quantity, and dates, obtain a second sampling frequency rule based on the concrete real-time production data, generate a second sampling task according to the second sampling frequency rule, and send the second sampling task to a terminal in the form of electronic information, where the terminal has information read by a corresponding service person, and the service person reads the information and then collects a concrete sample according to the second sampling task to obtain the concrete sample.
And the task automatic circulation module 103 automatically pushes the next node sampling task to the terminal when the previous node sampling task is completed through a preset sampling task flow until the sampling task flow is finished.
According to the embodiment, the sampling task can be automatically generated through the sampling task subsystem 100, manual participation is not needed, and the labor cost is reduced.
And the sample automatic coding subsystem 200 is used for respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain a coded concrete raw material sample and a coded concrete sample.
Specifically, the sample automatic coding subsystem 200 performs sample coding on the concrete raw material sample and the concrete sample according to a preset coding rule to obtain a coded concrete raw material sample and a coded concrete sample, wherein the sample coding refers to writing of information such as sampling original information and detection index information on the concrete raw material sample and the concrete sample.
According to the embodiment, the sample automatic coding subsystem 200 can automatically code without manual participation, so that the labor cost is reduced.
And the experiment detection subsystem 300 is used for respectively detecting the coded concrete raw material sample and the coded concrete sample, acquiring detection data of the concrete raw material sample and the concrete sample, and acquiring detection data of manual detection.
Specifically, the experimental detection subsystem 300 includes a fully automatic detection module 301 and a flow-through detection module 302, wherein,
and the full-automatic detection module 301 is configured to fully automatically detect the encoded concrete raw material sample and the encoded concrete sample, and obtain detection data of the concrete raw material sample and detection data of the concrete sample.
The process detection module 302 is configured to obtain detection data of manual detection, where the detection data of manual detection includes experiment detection data and an experiment detection result. By presetting the process design models of all the experiments in the process detection module 302, the process design models are internally provided with process steps, manual detection is guided based on the process steps, the experiment detection data obtained in each step are input, after all the steps are completed, the experiment detection result is automatically calculated according to a data processing algorithm based on the obtained experiment detection data, and whether the experiment detection result is qualified or not is judged.
In the embodiment, a pure manual detection experiment is replaced by the full-automatic detection module 301 and the flow detection module 302, paperless office work is realized, one-time generation permanent storage of data is realized, the accuracy of the data is improved, and the traceability of the data is realized.
And the data statistical analysis subsystem 400 is used for generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
Specifically, the data statistics analysis subsystem 400 includes a report personalization design module 401, an experimental data statistics analysis module 402, and a quality performance evaluation module 403, wherein,
the report personalized design module 401 is configured to automatically generate an experimental data report based on the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection, and the experimental detection result of the manual detection, and the experimental data report generates different personalized reports according to different requirements of the user through the report personalized design module 401.
The experimental data statistical analysis module 402 is configured to classify, count, and analyze the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection, and the experimental detection result of the manual detection to obtain statistical analysis parameters, where the statistical analysis parameters include parameters such as a mean, a variance, an extreme value, strength, and a yield.
And the quality performance evaluation module 403 is configured to perform quality performance evaluation on the operators of the pre-mix plant, each department of the pre-mix plant, or the plant station of the pre-mix plant according to the statistical analysis parameters such as the mean, the variance, the extreme value, the strength, and the qualification rate, so as to obtain the quality performance evaluation.
In the embodiment, the data statistics and analysis subsystem 400 is used for realizing automatic statistics and analysis, automatically outputting the personalized report, avoiding the waste of human resources and ensuring the authenticity and instructive data statistics.
The laboratory equipment management subsystem 500 includes an experimental and maintenance environment early warning module 501, an experimental equipment status detection module 502, and an experimental equipment verification early warning module 503, wherein,
experiment and maintenance environment early warning module 501 has preset the parameter threshold of experiment environment and maintenance environment, experiment and maintenance environment early warning module 501 is used for each parameter value of real-time detection experiment environment and maintenance environment, this parameter value includes the temperature parameter and the humidity parameter of experiment environment and maintenance environment, if temperature parameter value and humidity parameter value exceed the parameter threshold, experiment and maintenance environment early warning module 501 sends alarm signal to terminal, this terminal has corresponding business personnel to receive this alarm signal, business personnel maintain the detection to experiment environment and maintenance environment according to alarm signal, adjust experiment environment and maintenance environment temperature and humidity, with this stability of the temperature and humidity of guaranteeing experiment environment and maintenance environment.
The experimental equipment state detection module 502 is provided with an operation guiding step for equipment state detection, before an experiment, the experimental equipment state detection module 502 guides a business person to detect the state of the equipment according to the operation guiding step, the state comprises normal, damaged and to be detected, the equipment is allowed to perform the experiment under the condition that the state of the equipment is normal, the experimental equipment state detection module 502 automatically generates associated information generated when the equipment is used, and if the equipment is in a damaged state or in a state to be detected, the business person does not use the equipment.
The calibration time and the calibration cycle rule are preset in the experimental equipment calibration early warning module 503, the calibration time of the experimental instrument is calculated according to the calibration time and the calibration cycle rule, and corresponding calibration personnel are reminded to perform calibration through electronic information in advance for a certain time.
The intelligent management of equipment has been realized through laboratory facilities management subsystem 500 to this embodiment, and equipment status real time monitoring need not the manual work and detects repeatedly, avoids manpower resources's waste.
The pour site service management subsystem 600 includes a pour site electronic fence module, a path tracking recording module 602, an information recording module 603, and a security pre-warning module 604, wherein,
the method comprises the steps that a construction site map is arranged in a pouring site electronic fence module, the pouring site electronic fence is arranged on the basis of the construction site map, when a technician enters a pouring site electronic fence implementation project, relevant information of the technician entering the pouring site electronic fence is recorded, and the relevant information comprises information such as the name of the implementation project, the name of the technician, the time of entering the pouring site electronic fence and the like.
The path tracking recording module 602 is used for drawing the path of the technician in real time, recording the path of the technician in real time, and facilitating the scheduling of the technician.
The information recording module 603 is configured to record related information of project implementation performed by a technician when the technician enters the electronic fence in a casting site to perform technical service, where the related information includes information such as a project name, a construction unit, a casting location on the same day, a concrete label, and the like, and record a situation of the project implementation site of the technical service in a form of text, sound recording, pictures, video, and the like.
The safety early warning module 604 is provided with a calling function and an alarming function, and is used for taking corresponding rescue measures in time when a technician encounters danger, so that the danger of a pouring site is reduced.
In the embodiment, the pouring site service management subsystem 600 realizes the digital recording of the concrete pouring site technical service, and achieves the effects of technical service examination and data permanent storage traceability.
It should be noted that the implementation platform of the intelligent laboratory management system of the present embodiment may be a desktop computer, a notebook computer, or other devices.
Referring to fig. 4, an embodiment of the present invention provides a method for managing an intelligent laboratory of a pre-mix plant, further including:
step S100, acquiring raw concrete material factory entering data and real-time concrete production data, respectively acquiring a first sampling frequency rule and a second sampling frequency rule based on the raw concrete material factory entering data and the real-time concrete production data, respectively generating a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and respectively acquiring a raw concrete material sample and a concrete sample based on the first sampling task and the second sampling task;
s200, respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain a coded concrete raw material sample and a coded concrete sample;
step S300, detecting the coded concrete raw material sample and the coded concrete sample respectively, acquiring detection data of the concrete raw material sample and the concrete sample, and acquiring detection data of manual detection;
and S400, generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
It should be noted that, since the intelligent lab management method in the embodiment of the invention is based on the same inventive concept as the intelligent lab management system in the ready-mix factory, the corresponding contents in the system embodiment are also applicable to the embodiment of the invention, and are not described in detail herein.
Each subsystem/module in the embodiments of the present invention may be integrated into one processing subsystem/module, or each subsystem/module may exist alone physically, or two or more subsystems/modules may be integrated into one unit/module. The integrated subsystems/modules may be implemented in the form of hardware or software subsystems/modules.
From the above description of embodiments, it is clear for a person skilled in the art that the embodiments described herein can be implemented in hardware, software, firmware, middleware, code or any appropriate combination thereof. For a hardware implementation, a processor may be implemented in one or more of the following units: an Application Specific Integrated Circuit (ASIC), a Digital Signal Processor (DSP), a Digital Signal Processing Device (DSPD), a Programmable Logic Device (PLD), a Field Programmable Gate Array (FPGA), a processor, a controller, a microcontroller, a microprocessor, other electronic units designed to perform the functions described herein, or a combination thereof. For a software implementation, some or all of the procedures of an embodiment may be performed by a computer program instructing associated hardware. In practice, the program may be stored on or transmitted over as one or more instructions or code on a computer-readable medium. Computer-readable media includes both computer storage media and communication media including any medium that facilitates transfer of a computer program from one place to another. A storage media may be any available media that can be accessed by a computer. Computer-readable media can include, but is not limited to, RAM, ROM, EEPROM, CD-ROM or other optical disk storage, magnetic disk storage or other magnetic storage devices, or any other medium that can be used to carry or store desired program code in the form of instructions or data structures and that can be accessed by a computer.
In the description herein, references to the description of the term "one embodiment," "some embodiments," "an illustrative embodiment," "an example," "a specific example," or "some examples" or the like mean that a particular feature, structure, material, or characteristic described in connection with the embodiment or example is included in at least one embodiment or example of the invention. In this specification, the schematic representations of the terms used above do not necessarily refer to the same embodiment or example. Furthermore, the particular features, structures, materials, or characteristics described may be combined in any suitable manner in any one or more embodiments or examples.
While the preferred embodiments of the present invention have been described in detail, it will be understood by those skilled in the art that the foregoing and various other changes, omissions and deviations in the form and detail thereof may be made without departing from the scope of this invention.
Claims (7)
1. The utility model provides a pre-mix factory wisdom laboratory management system which characterized in that includes:
the sampling task subsystem is used for acquiring concrete raw material factory entering data and concrete real-time production data, respectively acquiring a first sampling frequency rule and a second sampling frequency rule based on the concrete raw material factory entering data and the concrete real-time production data, respectively generating a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and sending the first sampling task and the second sampling task to a terminal so as to obtain a concrete raw material sample and a concrete sample which are respectively acquired by the terminal according to the first sampling task and the second sampling task;
the sample automatic coding subsystem is used for respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain the coded concrete raw material sample and the coded concrete sample;
the experiment detection subsystem is used for respectively detecting the coded concrete raw material sample and the coded concrete sample, acquiring detection data of the concrete raw material sample and the detection data of the concrete sample, and acquiring detection data of manual detection;
and the data statistical analysis subsystem is used for generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
2. The intelligent lab management system of claim 1, wherein the sampling task subsystem is further configured to automatically push a next node sampling task to the terminal through a preset sampling task flow when a previous node sampling task is completed until the sampling task flow is completed.
3. The intelligent lab management system of claim 1, wherein the experiment detection subsystem comprises:
the full-automatic detection module is used for full-automatically detecting the coded concrete raw material sample and the coded concrete sample to obtain detection data of the concrete raw material sample and detection data of the concrete sample;
the system comprises a flow detection module, a flow detection module and a data processing algorithm, wherein the flow detection module is used for acquiring detection data of manual detection, the detection data of the manual detection comprises experiment detection data and an experiment detection result, the manual detection is guided based on the flow steps through presetting flow design models of all experiments and presetting the flow steps of the flow design models, the experiment detection data acquired in each step are recorded, and after all the steps are completed, the experiment detection result is automatically calculated according to the data processing algorithm based on the acquired experiment detection data, and whether the experiment detection result is qualified or not is judged.
4. The intelligent lab management system of claim 1, wherein the data statistics analysis subsystem comprises:
the report form personalized design module is used for automatically generating an experiment data report form based on the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection and the experiment detection result of the manual detection;
the experimental data statistical analysis module is used for classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample, the detection data of the manual detection and the experimental detection result of the manual detection to obtain statistical analysis parameters;
and the quality performance evaluation module is used for obtaining quality performance evaluation according to the statistical analysis parameters.
5. The intelligent lab management system of claim 1, further comprising a lab equipment management subsystem, wherein the lab equipment management subsystem comprises an experimental and maintenance environment early warning module, a lab equipment status detection module, and a lab equipment verification early warning module, wherein,
the experimental and maintenance environment early warning module is preset with parameter thresholds of experimental environment and maintenance environment and is used for detecting various parameter values of the experimental environment and the maintenance environment in real time, and if the parameter values exceed the parameter thresholds, an alarm signal is sent out and sent to the terminal;
the experimental equipment state detection module is provided with an equipment state detection operation guiding step and is used for detecting the state of the equipment according to the operation guiding step and automatically generating associated information generated when the equipment is used;
the calibration early warning module of the experimental equipment is preset with calibration time and calibration period rules, the calibration time of the experimental instrument is calculated through the calibration time and the calibration period rules, and the calibration time is sent to the terminal through electronic information.
6. The intelligent lab management system of claim 1, further comprising a casting site service management subsystem, wherein the casting site service management subsystem comprises a casting site electronic fence module, a path tracking recording module, an information recording module, and a safety precaution module, wherein,
a construction site map is arranged in the pouring site electronic fence module, a pouring site electronic fence is arranged based on the construction site map, and related information of a technician entering the pouring site electronic fence is recorded;
the path tracking recording module is used for drawing the path of the technician in real time;
the information recording module is used for recording the related information of the project implemented by the technical staff and recording the situation of the project implementation site;
the safety early warning module is used for providing a calling function and an alarming function.
7. A management method for an intelligent laboratory of a ready-mix plant is characterized by comprising the following steps:
acquiring raw concrete material factory entering data and real-time concrete production data, respectively acquiring a first sampling frequency rule and a second sampling frequency rule based on the raw concrete material factory entering data and the real-time concrete production data, respectively generating a first sampling task and a second sampling task according to the first sampling frequency rule and the second sampling frequency rule, and respectively acquiring a raw concrete material sample and a concrete sample based on the first sampling task and the second sampling task;
respectively carrying out sample coding on the concrete raw material sample and the concrete sample to obtain the coded concrete raw material sample and the coded concrete sample;
respectively detecting the coded concrete raw material sample and the coded concrete sample, acquiring detection data of the concrete raw material sample and the detection data of the concrete sample, and acquiring detection data of manual detection;
and generating an experimental data report according to the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection, classifying, counting and analyzing the detection data of the concrete raw material sample, the detection data of the concrete sample and the detection data of the manual detection to obtain statistical analysis parameters, and obtaining quality performance evaluation based on the statistical analysis parameters.
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