KR20190005315A - Method for controlling factory through data analysis acquired from smart sensor and system for the same - Google Patents

Abstract

Provided are a method for controlling a factory using data analysis acquired from a smart sensor and a system thereof. The method for controlling the factory using the data analysis acquired from the smart sensor is performed by a processor and comprises the steps of: acquiring factory information generated in the factory through the smart sensor and correcting an error through the smart sensor when the error occurs in the factory information of the factory; analyzing the factory information; predicting at least one accident expected to occur in a process or the factory through the analysis; and providing information obtained from the prediction. Therefore, the method provides early detection of an error occurring in the factory and prediction of the factory management.

Description

TECHNICAL FIELD [0001] The present invention relates to a plant control method and system for analyzing data acquired by a smart sensor,

The present invention relates to a plant control method and system, and more particularly, to a plant control method and system through data analysis obtained with a smart sensor.

Conventional factory operation and control was accomplished through experienced middle managers. An experienced middle manager can refer to a person who has long been familiar with the problems that may arise in plant operations. Through this accumulated experience, the middle manager was able to diagnose and predict possible accidents at the factory from the pre-accident stage. Therefore, it is common for the plant operator to appoint an experienced person as a mid-level manager and entrust the plant's operating authority. However, an experienced middle manager is needed in most factories, and the labor supply is not easy, so the operation of the factory by the middle manager could require a lot of labor costs. In addition, the empirical rules were not perfect, and there was a limitation that it was impossible to completely prevent an accident that may occur at a factory by only operating the plant by the middle manager.

Japanese Patent Application Laid-Open No. 10-2017-0064291,

A problem to be solved by the present invention is to construct a smart sensor and gateway platform capable of self-organizing based on open open source.

It also provides an integrated operating system for early detection, prediction, and control of abnormality occurrence in factories through MPC (Model Predictive Control) based facility / process data analysis.

The problems to be solved by the present invention are not limited to the above-mentioned problems, and other problems which are not mentioned can be clearly understood by those skilled in the art from the following description.

According to an aspect of the present invention, there is provided a method of controlling a plant through data analysis obtained by a smart sensor, the method comprising: acquiring factory information generated at a factory through the smart sensor; A factory information obtaining step of detecting an error of the smart sensor when an error occurs in a factory information value acquired through the smart sensor, the error being corrected; Analyzing the factory information; Predicting at least one of a process or an accident that may occur in the factory through the analysis; And providing information obtained through the prediction.

A factory control system for analyzing data obtained by a smart sensor according to an embodiment of the present invention for solving the above-mentioned problems, comprising: a processor; And a memory for storing at least one instruction executed by the processor, wherein the at least one instruction is for obtaining factory information that occurs at a factory via the smart sensor, Detecting an error of the smart sensor when an error occurs in the factory information value, the error obtaining factory information to be corrected, analyzing the factory information, and analyzing at least one of the processes, And to provide information obtained through the prediction.

Other specific details of the invention are included in the detailed description and drawings.

According to the present invention, it is possible to detect and predict an abnormal situation in a factory early without an intermediate manager. It also has the effect of making it easy to check the operation status of the plant at a glance.

In addition, it is possible to more easily detect defective products and to automate factory operations.

The effects of the present invention are not limited to the above-mentioned effects, and other effects not mentioned can be clearly understood by those skilled in the art from the following description.

1 is a flowchart showing a first embodiment of a factory control method using a smart sensor.
2 is a block diagram showing a first embodiment of a communication node constituting the system of the present invention.
3 is a conceptual diagram showing a second embodiment of a factory control method using a smart sensor.
4 is a conceptual diagram showing a second embodiment of the smart gateway.
5 is a conceptual diagram showing a third embodiment of the smart gateway.

BRIEF DESCRIPTION OF THE DRAWINGS The advantages and features of the present invention, and the manner of achieving them, will be apparent from and elucidated with reference to the embodiments described hereinafter in conjunction with the accompanying drawings. It should be understood, however, that the invention is not limited to the disclosed embodiments, but may be embodied in many different forms and should not be construed as limited to the embodiments set forth herein, Is provided to fully convey the scope of the present invention to a technician, and the present invention is only defined by the scope of the claims.

The terminology used herein is for the purpose of illustrating embodiments and is not intended to be limiting of the present invention. In the present specification, the singular form includes plural forms unless otherwise specified in the specification. The terms " comprises "and / or" comprising "used in the specification do not exclude the presence or addition of one or more other elements in addition to the stated element. Like reference numerals refer to like elements throughout the specification and "and / or" include each and every combination of one or more of the elements mentioned. Although "first "," second "and the like are used to describe various components, it is needless to say that these components are not limited by these terms. These terms are used only to distinguish one component from another. Therefore, it goes without saying that the first component mentioned below may be the second component within the technical scope of the present invention.

Unless defined otherwise, all terms (including technical and scientific terms) used herein may be used in a sense that is commonly understood by one of ordinary skill in the art to which this invention belongs. In addition, commonly used predefined terms are not ideally or excessively interpreted unless explicitly defined otherwise.

The terms spatially relative, "below", "beneath", "lower", "above", "upper" And can be used to easily describe a correlation between an element and other elements. Spatially relative terms should be understood in terms of the directions shown in the drawings, including the different directions of components at the time of use or operation. For example, when inverting an element shown in the figures, an element described as "below" or "beneath" of another element may be placed "above" another element . Thus, the exemplary term "below" can include both downward and upward directions. The components can also be oriented in different directions, so that spatially relative terms can be interpreted according to orientation.

Hereinafter, embodiments of the present invention will be described in detail with reference to the accompanying drawings.

The features of the processor (smart gateway) included in the system of the present invention may be as follows.

The processor can support multiple radio frequencies and self configurable multiprotocol. The processor can support and apply PLC interface stacks. The processor may be a reference structure of a gateway and IoT connection over a standard stack. The processor can support lightweight IoT middleware and gateway-to-gateway application architecture and protocols.

The processor can support the required interface standard between existing EPC-based gateways and applications (OPC-UA / SECS-GEM). The processor can support stand-alone functionality for the smart factory.

Referring to FIG. 1, a factory control method using data analysis obtained by a smart sensor can be performed by a processor included in a factory control system through data analysis obtained with the smart sensor of the present invention. The processor can acquire factory information from the factory through the smart sensor (S110)

Here, the smart sensor includes at least one of an oil level sensor, an air pressure sensor, an oil pressure sensor, a moisture sensor, an oil temperature sensor, a safety sensor, a stock sensor, an illuminance sensor, a worker sensor, . ≪ / RTI >

Factory information includes the amount of oil in the plant and the temperature of the oil in the plant, the air pressure of the machine using air compression such as air pressure, the concentration of harmful substances in the factory air, the humidity in the factory air, the physical condition of workers (body temperature, The concentration of carbon dioxide in the blood, etc.), the state of the material used in the process (temperature of the material, composition ratio of the material, etc.), illuminance, distance between objects, and position of the object.

The distance between objects can be recognized by an ultrasonic sensor. Bad product movement can be recognized through Metal Tag RFID.

The processor can detect an error in the smart sensor when an error occurs in the factory information value set by the smart sensor. The processor can correct errors caused by errors in the smart sensor to appropriate values.

For example, if the processor factory information value exceeds the expected range, the factory information value acquired through the sensor can detect that there is an error. In this case, the processor can process the factory information value as an exception value.

The processor may analyze the factory information (S120). Various parameters can be used in plant information analysis. There can be a correlation between each variable. Equipment / process conditions and causal relationships may exist. Each variable can have various types (for example, bit, category, integer). The variable state of the whole time can affect the next time. The processor may consider these features. Thus, the processor can eliminate multi-collinearity in the variables. The processor can also reduce the number of variables. The processor can also handle multivariate variables. In addition, the processor can express a non-linear relationship. The processor can determine the processing type of the various variables. The processor may reflect the temporal component of the variable. The processor can predict the outcome by reducing the dimension of the variable, or by constructing an artificial neural network related to time.

The processor may predict at least one of the process or an accident that may occur in the factory through the process information analysis (S130). A database for this analysis may be pre-populated in the system. The processor can learn and update the database on its own by using machine learning method.

The processor can control the plant environment in real time. The processor can also perform the process virtually. The processor may provide information obtained through prediction to a user (S140).

Defective items can be affixed to RFID chips by workers. The processor can check whether the defective product is carried out through the RFID reader. The processor can check the quality status of the product in real time.

In addition, in the present invention, communication between the plurality of sensors and the factory control system may be performed using a wireless communication system such as 802.11x (e.g., 802.11a, 802.11b, 802.11g, 802.11n, 802.11ac, etc.), Bluetooth, Zigbee , UWB (Ultra Wide Band), NFC (Near Field Communication), BCDMA (Binary CDMA), and Long Term Evolution (LTE) .

Referring to FIG. 2, the communication node 200 may be a system for controlling a plant through the smart sensor described in the present invention. The communication node 200 may include at least one processor 210, a memory 220, and a transceiver 230 connected to the network to perform communication. The communication node 200 may further include an input interface device 240, an output interface device 250, a storage device 260, and the like. Each component included in the communication node 200 may be connected by a bus 270 and communicate with each other.

The processor 210 may execute a program command stored in at least one of the memory 220 and the storage device 260. The processor 310 may refer to a central processing unit (CPU), a graphics processing unit (GPU), or a dedicated processor on which methods in accordance with embodiments of the present invention are performed. Each of the memory 220 and the storage device 260 may be constituted of at least one of a volatile storage medium and a nonvolatile storage medium. For example, the memory 220 may comprise at least one of read-only memory (ROM) and random access memory (RAM).

The steps of a method or algorithm described in connection with the embodiments of the present invention may be embodied directly in hardware, in software modules executed in hardware, or in a combination of both. The software module may be a random access memory (RAM), a read only memory (ROM), an erasable programmable ROM (EPROM), an electrically erasable programmable ROM (EEPROM), a flash memory, a hard disk, a removable disk, a CD- May reside in any form of computer readable recording medium known in the art to which the invention pertains.

While the present invention has been described in connection with what is presently considered to be practical exemplary embodiments, it is to be understood that the invention is not limited to the disclosed embodiments, but, on the contrary, You will understand. Therefore, it should be understood that the above-described embodiments are illustrative in all aspects and not restrictive.

Claims (2)

As a factory control method through analysis of data acquired by smart sensor,
Performed by a processor,
The method comprising the steps of: acquiring factory information generated at a factory through the smart sensor, the method comprising: detecting an error of the smart sensor when an error occurs in the factory information value acquired through the smart sensor; ;
Analyzing the factory information;
Predicting at least one of a process or an accident that may occur in the factory through the analysis; And
And providing information obtained through the prediction. As a factory control system through data analysis obtained by smart sensor,
A processor; And a memory for storing at least one instruction executed by the processor,
Wherein the at least one instruction comprises:
The method comprising the steps of: acquiring factory information generated in a factory through the smart sensor, the method comprising: detecting an error of the smart sensor when an error occurs in the factory information value acquired through the smart sensor; ,
Analyzing the factory information,
Predicting at least one of the process or an accident that may occur in the plant through the analysis, and
And to provide information obtained through the prediction.

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