KR102617618B1 - Device, method and system for providing artificial intelligence-based decision-making service for replacement of high-efficiency equipment replacement in industrial factories - Google Patents

Abstract

The present invention involves inputting measurement data and equipment data, which are digital data, analyzing the measurement data, searching and selecting equipment to replace the existing equipment, displaying a report of the selected equipment, and data analysis of the measurement data. Equipment selection, which uses equipment data to select equipment to replace existing equipment; Performs a result report that displays the analysis results of the measurement data and a report of the selected equipment.

Description

Device, method and system for providing artificial intelligence-based decision-making services for high-efficiency equipment replacement in industrial plants

The present invention relates to an artificial intelligence-based decision-making service providing device, method, and system for replacing high-efficiency equipment in industrial plants. More specifically, it relates to making rapid decisions in equipment selection, introducing high-efficiency equipment, and reducing operating costs. , An artificial intelligence-based decision-making service providing device and method for replacing old equipment with high-efficiency equipment to reduce energy waste, reduce operating costs, register greenhouse gas reductions, and receive carbon emissions refunds for replacement of high-efficiency equipment in industrial plants. and systems.

Prior art related to the present invention includes energy saving and energy efficiency diagnosis. Patent Document 1 Energy-saving system installation service method and service server can be installed in a building without paying a separate installation fee for the energy-saving system from the building owner or manager's perspective. In addition, Patent Document 2, a server, method, and system that provides a service for diagnosing the energy efficiency of a target building provides a service by diagnosing the energy efficiency of the building in advance in order for non-experts to discover business opportunities related to the energy efficiency of the building. can do.

Registered Patent Publication No. 10-1854913 (2018.05.04) Public Patent Publication No. 10-2019-0119467 (2019.10.22)

The present invention is an artificial intelligence-based doctor for high-efficiency equipment replacement in industrial plants that inputs digital data such as measurement data and equipment data, analyzes the measurement data, searches and selects equipment to replace existing equipment, and displays a report of the selected equipment. The purpose is to provide decision service provision devices, methods, and systems.

Additionally, the present invention relates to data analysis of measurement data; Equipment selection, which uses equipment data to select equipment to replace existing equipment; The purpose is to provide an artificial intelligence-based decision-making service providing device, method, and system for high-efficiency equipment replacement in industrial plants that performs a result report that displays the results of analysis of measurement data and a report of selected equipment.

According to a preferred embodiment of the present invention, an artificial intelligence-based decision-making service providing device for high-efficiency equipment replacement in industrial plants is an artificial intelligence-based decision-making service providing device that measures physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics at industrial sites. Measuring equipment 32 that measures and inputs the measured data into a control unit; a data input unit 33 that inputs measurement data and equipment data, which are digital data, from the measurement equipment 32 and the keyboard 53 to the control unit; and data analysis of measurement data (41); Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; It is characterized in that it includes a control unit that performs a result report 43 that displays a report of the selected equipment as a result of analysis of the measurement data.

In addition, the data analysis 41 includes data collection and preprocessing to collect measurement data, extract necessary data and convert it into an appropriate format, and remove or correct error data; Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpreting and visualizing the data analysis results and displaying them in graphs, charts, and maps; the equipment selection 42 selects equipment to replace the existing equipment using the analysis results of the measurement data; , equipment review of price, performance, maintenance cost, and reliability of equipment; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; Equipment is selected taking into account the purchase and installation of equipment, and the result report 43 includes purpose setting, result summary, visualization, result interpretation, conclusion and suggestion, and displays the operation status of the control unit, analysis progress, and equipment report. It is characterized by processing.

In addition, an artificial intelligence-based decision-making service providing system for replacing high-efficiency equipment in industrial plants includes data analysis of measurement data (41); Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; A terminal (6) including a control unit that performs a result report (43) that displays a report of the selected equipment as a result of analysis of the measurement data; Integrated control of multiple terminals (6), storing sensor values received from the terminal (6) and monitoring them over time, processing operation errors of the terminal (6), and sending error messages to other terminals (6) ) and a cloud 12 that controls switching of the terminal 6 that is the control target; and receiving a kit value from the terminal 6, receiving the kit value and user information from the terminal 6 through a duplicated data channel, comparing the kit value of the terminal 6 with the user information, and matching the user information. and an authentication server 7 that processes authentication for use of the system by the terminal 6 and transmits the authentication result to the terminal 6 to permit the user to use the system.

In addition, in the method of providing an artificial intelligence-based decision-making service for replacing high-efficiency equipment in industrial plants, the control unit inputs digital data such as measurement data and equipment data from the measuring equipment 32 and the keyboard 53 in the data input step (S101). And a data analysis step of the measured data (S102); Equipment selection step (S103) of selecting equipment to replace existing equipment using the equipment data; As a result of the analysis of the measurement data, a result report step (S104) is performed to display a report of the selected equipment.

In addition, the data analysis step (S102) includes data collection and preprocessing to collect measurement data, extract necessary data, convert it into an appropriate format, and remove or correct error data. Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpreting and visualizing the data analysis results and displaying them in graphs, charts, and maps; performing the equipment selection step (S103) to select equipment to replace the existing equipment using the analysis results of the measurement data. and review of equipment price, performance, maintenance cost, and reliability; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; Equipment is selected in consideration of equipment purchase and installation, and the result report step (S104) includes goal setting, result summary, visualization, result interpretation, conclusion and suggestion, operation status of the control unit, analysis progress level, equipment It is characterized by processing report display.

The present invention inputs measurement data and equipment data, which are digital data, analyzes the measurement data, searches for and selects equipment to replace existing equipment, and displays a report of the selected equipment, thereby making quick decisions on equipment selection and installing high-efficiency equipment. It has the effect of reducing operating costs.

Additionally, the present invention relates to data analysis of measurement data; Equipment selection, which uses equipment data to select equipment to replace existing equipment; By performing a result report that displays the results of the analysis of measurement data and the report of the selected equipment, you can reduce energy waste by replacing old equipment with high-efficiency equipment, reduce operating costs, register greenhouse gas reductions, and receive a refund of carbon emissions credits. It works.

Figure 1 is an exemplary diagram showing the configuration of an artificial intelligence-based decision-making service providing device for replacing high-efficiency equipment in an industrial factory of the present invention.
Figure 2 is a block diagram showing the detailed configuration of an artificial intelligence-based decision-making service providing device for replacing high-efficiency equipment in an industrial factory of the present invention.
Figure 3 is a block diagram showing the configuration of an artificial intelligence-based decision-making service provision system for replacing high-efficiency equipment in an industrial factory of the present invention.
Figure 4 is a flowchart showing the operation of the method of providing an artificial intelligence-based decision-making service for replacing high-efficiency equipment in an industrial factory of the present invention.

Hereinafter, with reference to the drawings, an apparatus, method, and system for providing an artificial intelligence-based decision-making service for replacing high-efficiency equipment in an industrial factory according to an embodiment of the present invention will be described in detail. Below, descriptions of previously known matters are omitted or simplified to clarify the gist of the present invention. The components included in the description of the present invention operate individually or in combination.

Figure 1 is an exemplary diagram showing the configuration of an artificial intelligence-based decision-making service providing device for replacing high-efficiency equipment in an industrial factory of the present invention.

Referring to Figure 1, an industrial site is a place where actual production and work takes place in various industrial fields such as manufacturing, construction, transportation, and energy, where the compressor 31 can be used, and to produce products or services desired by customers or consumers. to provide. For example, in the manufacturing industry, production work takes place in factories or manufacturing facilities; in the construction industry, work takes place at building sites; in the transportation industry, work takes place in transportation and logistics facilities that operate vehicles, ships, and airplanes; , the energy industry produces energy in power plants, crude oil refineries, and solar power plants. The compressor 31 produces compressed air, stores it at high pneumatic pressure, and then supplies the compressed air to various pneumatic machines. For example, the present invention provides a decision-making service for replacing the compressor 31 with high-efficiency equipment in an industrial factory.

The measuring equipment 32 measures physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics at industrial sites and inputs the measured data to the control unit. For example, for length, use a ruler, meter, stick, height gauge, or micrometer, for mass, use a scale or weight, for temperature, use a thermometer or infrared thermal imaging camera, and for pressure, use a pressure gauge or vacuum gauge. For electricity, use a multimeter, oscilloscope, and power meter, for environment, use a fine dust meter and material analyzer, and for optics, use a spectro meter.

The user inputs digital data such as measurement data and equipment data into the control unit using the keyboard 53, the control unit analyzes the measurement data, searches for and selects equipment to replace the existing equipment, and reports the selected equipment to the display unit 51. It is displayed in For example, the display unit 51 processes the operation status of the control unit, analysis progress, and displays equipment reports.

Figure 2 is a block diagram showing the detailed configuration of an artificial intelligence-based decision-making service providing device for replacing high-efficiency equipment in an industrial factory of the present invention.

Referring to FIG. 2, the terminal 6 includes a measurement equipment 32, a data input unit 33, a data analysis 41, a facility selection 42, a result report 43, and a control unit.

The measuring equipment 32 measures physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics at industrial sites and inputs the measured data to the control unit.

The data input unit 33 inputs measurement data and equipment data, which are digital data, from the measurement equipment 32 and the keyboard 53 to the control unit. Measurement data includes physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics; equipment data includes technical information such as manufacturer, model, serial number, capacity, and specifications of the equipment; Operational records of operating records, anomalies, maintenance history, and inspection schedules; sensor data measured in the facility; Includes maintenance and repair records;

The control unit performs data analysis 41 of the measurement data; Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; As a result of the analysis of the measurement data, a result report 43 that displays a report of the selected equipment is performed. Data analysis (41) includes data collection and preprocessing, which involves collecting measurement data, extracting the necessary data and converting it into an appropriate format, and removing or correcting erroneous data; Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpret and visualize data analysis results and display them in graphs, charts, and maps. Equipment selection (42) uses the analysis results of measurement data to select equipment to replace existing equipment, and reviews the price, performance, maintenance cost, and reliability of the equipment; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; Select equipment by considering equipment purchase and installation. The result report 43 includes goal setting, result summary, visualization, result interpretation, conclusion and suggestion, and processes the operation status of the control unit, analysis progress, and equipment report display.

Figure 3 is a block diagram showing the configuration of an artificial intelligence-based decision-making service provision system for replacing high-efficiency equipment in an industrial factory of the present invention.

Referring to FIG. 3, the decision-making service providing system includes a terminal 6, which is a decision-making service providing device, a cloud 12 that monitors and manages the operation of the terminal 6, and an authentication system that authenticates the operation authority of the terminal 6. Includes server (7).

The terminal 6 performs data analysis 41 of the measurement data; Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; It includes a control unit that performs a result report 43 that displays a report of the selected equipment as a result of analysis of the measurement data.

The cloud 12 integrates control of multiple terminals 6, stores sensor values received from the terminal 6, monitors them over time, processes operation errors of the terminal 6, and sends error messages to other terminals. Notifies the terminal 6, and performs switching control on the terminal 6 that is the control target.

The authentication server 7 receives the kit value from the terminal 6, receives the kit value and user information from the terminal 6 through a duplicated data channel, compares the kit value and the user information of the terminal 6, and By matching, authentication for use of the system of the terminal 6 is processed. The authentication server 7 transmits the authentication result to the terminal 6 to authorize the user's use of the system.

The terminal 6 includes a processor, memory, input/output device, operating system, and control unit.

Processors are CPUs (Central Processing Units), GPUs (Graphic Processing Units), FPGAs (Field Programmable Gate Array), and NPUs (Neural Processing Units), which execute the operating system and control unit's execution code mounted on the memory.

Memory may include non-permanent mass storage devices such as random access memory (RAM), read only memory (ROM), disk drives, solid state drives (SSD), flash memory, etc. .

Input/output devices include devices such as cameras, keyboards, microphones, and mice, including audio sensors and/or image sensors, as input devices, and devices such as displays, speakers, and haptic feedback devices, as output devices. can do.

The operating system may include Windows, Linux, IOS, virtual machines, web browsers, and interpreters, and supports tasks, threads, timer execution, scheduling, resource management, graphics, font processing, and communication.

The control unit, with the support of the operating system, determines the state of the input/output device through sensor, key, touch, and mouse input and performs operations according to the determined state. The control unit performs job scheduling using timers and threads as a parallel execution routine.

The control unit determines the state using sensor values of the input/output device and performs an algorithm according to the determined state.

Referring to Figure 3, the system authentication configuration includes a terminal 6 including a control unit and an authentication server 7.

The terminal 6 duplicates the data channel, receives the key value and biometric information of the terminal 6, and requests user authentication through the first data channel to the authentication server 7, and the terminal 6 receives the generated kit value. It is displayed on the display and transmitted to the authentication server (7).

The terminal 6 inputs the kit value displayed on the display of the terminal 6 and transmits it along with the user information to the authentication server 7 through the second data channel. The terminal 6 requests the authentication server 7 to authenticate the system mounted on the terminal 6 using the kit value and user information. The kit value of the terminal 6 can be generated from computer-specific information, such as the CPU manufacturing number and the Ethernet chip number. The terminal 6 can obtain user information through face recognition using a camera, voice recognition using a microphone, and handwriting recognition using a display, and use it for authentication.

The authentication server 7 receives the kit value from the terminal 6, receives the kit value and user information from the terminal 6 through a duplicated data channel, compares the kit value and the user information of the terminal 6, and By matching, authentication for use of the system of the terminal 6 is processed. The authentication server 7 transmits the authentication result to the terminal 6 to authorize the user's use of the system. Due to the dual data channels of the terminal 6, kit value loss can be minimized.

The authentication server 7 performs history analysis of user information and compares and determines consistency and changes in user information over time. In history analysis, if user information shows consistency, the user's use is permitted; if it shows changes, the user's use is not permitted. By allowing users to use the system when user information shows consistency, security is strengthened to prevent users with altered user information from accessing the system.

The authentication server 7 assigns weights to consistency, change, frequency, frequency trend, and high frequency, and blocks access by untrusted users using a combination of weights. For example, if the frequency threshold is exceeded, access by untrusted users can be blocked in proportion to the accumulated number of excesses, and users who attempt access over a long period of time can be authenticated. At this time, additional authentication is requested for untrusted users.

When the concentration of authentication frequency over time is concentrated in a specific section, the authentication server 7 blocks access of the untrusted user terminal 6 and requests additional authentication for the untrusted user terminal 6. The authentication server 7 counts the number of authentication attempts over time, accumulates the number at regular time intervals, and blocks access by the untrusted user terminal 6 when the number of authentication attempts in a specific section exceeds a threshold.

The terminal 6, which is a means of authenticating the use of the system, does not connect directly to the system, but forms a bypass route through the authentication server 7, so that the network that makes up the Internet network is composed of an internal network and an external network, and the IP address setting process There is an advantage that the authentication process using the terminal 6 is performed smoothly in this cumbersome time. At this time, the system is mounted on the terminal 6, the terminal 6 becomes an authentication terminal means, and the authentication server 7 becomes an authentication server means.

The cloud (12) is a modularization of the container (14) with the support of an operating system that manages the processor, memory, input/output devices, and communication unit (6), including the web (8), DB (9), protocol (10), and library (11). It provides services, and the control unit executes a cloud application using the services of the container 14. A standard software package, called a container (14), bundles an application's code with associated configuration files, libraries (11), and dependencies needed to run the app.

The cloud 12 integrates control of multiple terminals 6, stores sensor values received from the terminal 6, monitors them over time, processes operation errors of the terminal 6, and sends error messages to other terminals. Notifies the terminal 6, and performs switching control on the terminal 6 that is the control target.

The cloud 12 calculates the frequency concentration for the probability frequency of the sensor value of the terminal 6, increases the system resources devoted to the monitoring operation when the frequency concentration exceeds a certain threshold, and stops the monitoring operation when the system resources are depleted. do. The cloud 12 separates the components of the sensor value with high frequency concentration to distribute the frequency concentration, and repeats the separation and distribution operation until the frequency concentration decreases below a certain threshold.

Neural network learning selects features from time series data collected from input devices such as temperature, altitude, fingerprints, various sensors, images, infrared cameras, and lidar, selects a model through algorithm selection, and repeats through the learning and performance verification process. Model selection is repeated through trial and error. After performance verification is completed, an artificial intelligence model is selected.

The control unit performs a deep learning algorithm using a neural network to determine sensor values, uses training data to learn the neural network, and verifies the neural network performance with test data.

The control unit inputs data from data analysis (41), facility selection (42), and result report (43) as time series data, and uses an artificial intelligence model to analyze data (41), facility selection (42), and result report (43). ) performs optimization. The artificial intelligence model is selected through repeated trial and error of learning and performance verification, and the output of data analysis (41), facility selection (42), and result report (43) is optimized.

In addition, the control unit uses an artificial intelligence model to optimize data analysis (41), equipment selection (42), and result report (43) for the data analysis (41), equipment selection (42), and result report (43) commands. Optimization is related to data analysis (41), equipment selection (42), and result report (43), and how much power consumption and equipment selection are performed in data analysis (41), equipment selection (42), and result report (43). Data analysis (41), facility selection (42), and result report (43) are optimized depending on whether Optimization is related to data analysis (41), facility selection (42), and result report (43), and the control unit applies these variables to the artificial intelligence model to report data analysis (41), facility selection (42), and result report (43). ) is optimized.

The control unit includes a state machine, and the state machine includes event processing, state transition, and state processing.

The state machine handles events based on key, mouse, and touch input; State transition that transitions between states in response to an event; State processing is performed to process routines for the transitioned state. The status includes data analysis (41), equipment selection (42), and result report (43), and the routine includes a data analysis routine, equipment selection routine, and result report routine.

The control unit executes a state machine for event processing, state transition, and state processing corresponding to user manipulation and data input. Event processing processes events according to manipulation and input, and status processing performs calculation, display, vibration, and alarm, and verifies the input of range, time, and level for user manipulation, data input, and random input, and user manipulation. , execute system verification according to state probability for data input and random input. System verification includes state machine verification based on sampled data.

The control unit stores the sampling data, calculates the first probability distribution by accumulating the number of occurrences for each size of the sampling data over a certain period of time, calculates the second probability distribution for another period of time, and calculates the two first and second probabilities. By calculating the distribution difference, area difference, and difference distance accumulation, sampling circuit abnormalities, data errors, and data changes can be predicted and responded to. The control unit can notify the user of the prediction result so that the user can respond, or the control unit can respond to hardware failure, data error, or data change. For example, when the area difference between the two first and second probability distributions exceeds a certain threshold, the control unit predicts sampling circuit abnormalities, data errors, and data changes, and responds to the abnormalities, errors, and changes. Responses include abnormality indication, notification, and system shutdown.

The sampling data includes data from data analysis (41), equipment selection (42), and result report (43), and the control unit responds to hardware failures, data errors, and data changes based on the sampling data.

The control unit monitors the trend of each probability distribution for a certain period of time, predicts abnormalities in the probability distribution, responds to abnormal accidents, and notifies the outside world of normal operation if the data change in the probability distribution is constant. Additionally, the control unit feeds back the data change rate to adjust a certain time interval. For example, if the data change rate is large, the certain time interval is increased, and if the data change rate is small, the certain time interval is shortened.

Figure 4 is a flowchart showing the operation of the method of providing an artificial intelligence-based decision-making service for replacing high-efficiency equipment in an industrial factory of the present invention.

The measuring equipment 32 measures physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics at industrial sites and inputs the measured data to the control unit.

The control unit inputs digital data, such as measurement data and equipment data, from the measurement equipment 32 and the keyboard 53 in the data input step (S101). Measurement data includes physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics; equipment data includes technical information such as manufacturer, model, serial number, capacity, and specifications of the equipment; Operational records of operating records, anomalies, maintenance history, and inspection schedules; sensor data measured in the facility; Includes maintenance and repair records;

The control unit performs a data analysis step of the measurement data (S102); Equipment selection step (S103) in which equipment to replace existing equipment is selected using equipment data; As a result of analyzing the measurement data, a result report step (S104) is performed to display a report of the selected equipment. The data analysis step (S102) includes data collection and preprocessing to collect measurement data, extract necessary data and convert it into an appropriate format, and remove or correct error data. Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpret and visualize data analysis results and display them in graphs, charts, and maps. The equipment selection step (S103) selects equipment to replace the existing equipment using the analysis results of the measurement data, and reviews the price, performance, maintenance cost, and reliability of the equipment; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; Select equipment by considering equipment purchase and installation. The result report step (S104) includes goal setting, result summary, visualization, result interpretation, conclusion, and suggestion, and processes the operation status of the control unit, analysis progress, and equipment report display.

The present invention is not limited to the specific preferred embodiments described above, and various modifications can be made by anyone skilled in the art without departing from the gist of the invention as claimed in the claims. Of course, such changes are within the scope of the claims.

1: processor
2: memory
3: Input/output device
4: Operating system
5: Control unit
6: Terminal
7: Authentication server
8: web
9: DB
11: Library
12: Cloud
14: Container
16: Department of Communications
31: Compressor
32: Measuring equipment
33: data input unit
41: Data analysis
42: Equipment selection
43: Result report

Claims (5)

Measuring equipment (32) that measures physical quantities or characteristics of length, mass, temperature, pressure, electricity, environment, and optics in industrial settings and inputs the measured data;
a data input unit 33 for inputting digital data such as measurement data and equipment data from the measurement equipment 32 and the keyboard 53; and
data analysis of measurement data (41); Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; It includes a control unit that performs a result report 43 that displays the analysis results of the measurement data and a report of the selected equipment,
The data analysis 41 includes data collection and preprocessing to collect measurement data, extract the data, convert the format, and remove or correct error data; Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpreting and visualizing the data analysis results and displaying them in graphs, charts, and maps; the equipment selection 42 selects equipment to replace the existing equipment using the analysis results of the measurement data; , equipment review of price, performance, maintenance cost, and reliability of equipment; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; equipment purchase and installation; the result report 43 includes purpose setting, result summary, visualization, result interpretation, conclusion and suggestion, and processes operation status, analysis progress, and equipment report display. do,
The control unit includes a state machine, and the state machine includes event processing, state transition, and state processing,
The state machine includes event processing to process events according to key, mouse, and touch input; State transition that transitions between states in response to an event; State processing to process routines for transitioned states; The state includes data analysis (41), equipment selection (42), and result report (43), and the routines include data analysis routine, equipment selection routine, and result. Contains report routines,
The control unit executes a state machine for event processing, state transition, and state processing corresponding to user manipulation and data input. Event processing processes events according to manipulation and input, and state processing performs calculation, display, vibration, and alarm. Verifies input of range, time, and level for user operation, data input, and random input. System verification is performed according to state probability for user operation, data input, and random input. System verification is performed on sampling data. Includes state machine verification based on
The control unit stores the sampling data, calculates a first probability distribution by accumulating the number of occurrences for each size of the sampling data over a certain period of time, calculates a second probability distribution for another period of time, and calculates the two first and second probability distributions. Calculate the area difference of the probability distribution to predict and respond to sampling circuit abnormalities, data errors, and data changes. Notify the user of the prediction results so that the user can respond or respond to hardware failures, data errors, and data changes. 1. When the area difference of the second probability distribution exceeds a certain threshold, it predicts sampling circuit abnormalities, data errors, and data changes, and responds to abnormalities, errors, and changes. Responses include abnormal display, notification, and system stop;
The sampling data includes data from data analysis (41), equipment selection (42), and result report (43), and the control unit responds to hardware failure, data error, and data change based on the sampling data. , An artificial intelligence-based decision-making service provider for high-efficiency equipment replacement in industrial plants. delete data analysis of measurement data (41); Equipment selection (42), which uses equipment data to select equipment to replace existing equipment; A terminal (6) including a control unit that performs a result report (43) that displays a report of the selected equipment as a result of analysis of the measurement data;
Integrated control of multiple terminals (6), storing sensor values received from the terminal (6) and monitoring them over time, processing operation errors of the terminal (6), and sending error messages to other terminals (6) ) and a cloud 12 that controls switching of the terminal 6 that is the control target; and
Receive a kit value from the terminal 6, receive the kit value and user information from the terminal 6 through a duplicated data channel, compare the kit value of the terminal 6 with the user information, and match the user information to the An authentication server (7) that processes authentication for use of the system by the terminal (6) and transmits the authentication result to the terminal (6) to authorize the user's use of the system;
The control unit includes a state machine, and the state machine includes event processing, state transition, and state processing,
The state machine includes event processing to process events according to key, mouse, and touch input; State transition that transitions between states in response to an event; State processing to process routines for transitioned states; The state includes data analysis (41), equipment selection (42), and result report (43), and the routines include data analysis routine, equipment selection routine, and result. Contains report routines,
The control unit executes a state machine for event processing, state transition, and state processing corresponding to user manipulation and data input. Event processing processes events according to manipulation and input, and state processing performs calculation, display, vibration, and alarm. Verifies input of range, time, and level for user operation, data input, and random input. System verification is performed according to state probability for user operation, data input, and random input. System verification is performed on sampling data. Includes state machine verification based on
The control unit stores the sampling data, calculates a first probability distribution by accumulating the number of occurrences for each size of the sampling data over a certain period of time, calculates a second probability distribution for another period of time, and calculates the two first and second probability distributions. Calculate the area difference of the probability distribution to predict and respond to sampling circuit abnormalities, data errors, and data changes. Notify the user of the prediction results so that the user can respond or respond to hardware failures, data errors, and data changes. 1. When the area difference of the second probability distribution exceeds a certain threshold, it predicts sampling circuit abnormalities, data errors, and data changes, and responds to abnormalities, errors, and changes. Responses include abnormal display, notification, and system stop;
The sampling data includes data from data analysis (41), equipment selection (42), and result report (43), and the control unit responds to hardware failure, data error, and data change based on the sampling data. , an artificial intelligence-based decision-making service provision system for high-efficiency equipment replacement in industrial plants. The control unit inputs digital data, such as measurement data and equipment data, from the measurement equipment 32 and the keyboard 53 in the data input step (S101),
Data analysis step of measurement data (S102); Equipment selection step (S103) in which equipment to replace existing equipment is selected using equipment data; As a result of the analysis of the measurement data, a result report step (S104) is performed to display a report of the selected equipment,
The data analysis step (S102) includes data collection and preprocessing to collect measurement data, extract the data, convert the format, and remove or correct error data. Once data collection and preprocessing are completed, data analysis using statistical analysis, machine learning, deep learning, and natural language processing technologies; Interpreting and visualizing the data analysis results and displaying them in graphs, charts, and maps; performing the equipment selection step (S103) to select equipment to replace the existing equipment using the analysis results of the measurement data. and review of equipment price, performance, maintenance cost, and reliability; Cost-effectiveness of equipment life cycle, maintenance costs and productivity; Equipment is selected taking into account equipment purchase and installation, and the result report step (S104) includes purpose setting, result summary, visualization, result interpretation, conclusion and suggestion, operation status, analysis progress, and equipment report display. Process it,
The control unit includes a state machine, and the state machine includes event processing, state transition, and state processing,
The state machine includes event processing to process events according to key, mouse, and touch input; State transition that transitions between states in response to an event; State processing to process routines for transitioned states; The state includes data analysis (41), equipment selection (42), and result report (43), and the routines include data analysis routine, equipment selection routine, and result. Contains report routines,
The control unit executes a state machine for event processing, state transition, and state processing corresponding to user manipulation and data input. Event processing processes events according to manipulation and input, and state processing performs calculation, display, vibration, and alarm. Verifies input of range, time, and level for user operation, data input, and random input. System verification is performed according to state probability for user operation, data input, and random input. System verification is performed on sampling data. Includes state machine verification based on
The control unit stores the sampling data, calculates a first probability distribution by accumulating the number of occurrences for each size of the sampling data over a certain period of time, calculates a second probability distribution for another period of time, and calculates the two first and second probability distributions. Calculate the area difference of the probability distribution to predict and respond to sampling circuit abnormalities, data errors, and data changes. Notify the user of the prediction results so that the user can respond or respond to hardware failures, data errors, and data changes. 1. When the area difference of the second probability distribution exceeds a certain threshold, it predicts sampling circuit abnormalities, data errors, and data changes, and responds to abnormalities, errors, and changes. Responses include abnormal display, notification, and system stop;
The sampling data includes data from data analysis (41), equipment selection (42), and result report (43), and the control unit responds to hardware failure, data error, and data change based on the sampling data. , A method of providing artificial intelligence-based decision-making services for replacing high-efficiency equipment in industrial plants. delete

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