KR102278761B1 - Real time smart bigdata accquisition and analysis system - Google Patents

Abstract

The present invention relates to a real-time smart big data collecting and analyzing device for improving the yield. More specifically, provided is the real-time smart big data collecting and analyzing device for improving the yield, which stores meaningful information and transmits the information to a server to prevent damage caused by a sudden failure of semiconductor production facilities.

Description

Real-time smart big data collection and analysis device for yield improvement {REAL TIME SMART BIGDATA ACCQUISITION AND ANALYSIS SYSTEM}

The present invention relates to a real-time smart big data collection and analysis apparatus for improving yield, and more particularly, to prevent damage caused by sudden failure of semiconductor production facilities, by storing meaningful information and transmitting it to a server for yield improvement It relates to a real-time smart big data collection and analysis device.

Currently, major core industries and semiconductor fields collect and analyze various operation signals generated from production facilities in real time to improve production efficiency and facility operation reliability by combining IT-based real-time failure/performance/risk management and AI. We are actively introducing predictive diagnostic technology to improve production efficiency by maintaining the best operating condition of a facility and to improve yield by reducing the defective rate of products, and also to prevent damage caused by accidental failure of facilities.

In addition, as the technology advances and the scale of production facilities increases, the damage caused by facility accidents is also increasing. With the advancement of IoT / big data-based facilities, the demand for switching from on-site method to on-line type diagnosis system is increasing. One-time accident has a huge impact on the amount of astronomical damage caused by production setbacks and yields when the production line is stopped unexpectedly, and the national and social interest in preventing and predicting safety accidents in large plants is increasing significantly.

The most problematic point while making the existing equipment was that it had a small size and many functions, but the research and development period was relatively short, so the existing commercial products were mainly used, and the multi-channel, high-precision A/D converter responsible for measurement. We focused on development and operation programs to meet the deadline.

In particular, an existing PC (intel core i5, etc.) was used as a device for overall control, UI display, and data communication with the server, and the operating system (O/S) was implemented using Windows. This has the result of making all operating programs that operate the overall control and UI display and data communication with the server subordinate to the Windows environment, so that the overall control and UI display and the equipment specialized for data communication with the server The need to develop a unique operating system (O/S) is emerging.

If you use an operating system in a Windows environment, you have to use it in an intranet environment that does not allow any connection to the outside for the security of the semiconductor manufacturing process, so there are many difficulties in connecting new sensors and updating programs. There is a problem that it takes a lot of time to apply.

Also, due to a vulnerability in the Windows operating system, there is a problem in that when abnormal program termination is repeated, such as a stop due to power cut off, rather than a normal program termination, it does not operate normally and problems occur frequently.

This can be solved with sufficient education, but improvement is urgently needed for equipment that will be operated in a special environment that cannot be repaired immediately from the outside.

Most of the manufacturing equipment operated at semiconductor-related sites depends on imports.

Currently, several companies are producing semiconductors internationally, and the equipment used for manufacturing and production is also being produced and supplied by several companies.

However, the reason that the yield of semiconductors produced while operating the same manufacturing equipment is higher than that of other manufacturing countries may be due to maintaining the best condition in operating the production equipment and the mind and skill of the workers.

In other words, equipment for monitoring and monitoring manufacturing equipment has been developed and is currently in operation, but research is required for smoother operation by solving the above-mentioned problems.

Korean Patent Registration [10-0223960] discloses a semiconductor manufacturing plant management system.

Korean Patent Registration [10-0223960] (Registration Date: July 12, 1999)

Accordingly, the present invention has been devised to solve the above problems, and an object of the present invention is to improve the yield of storing meaningful information and transmitting it to the server in order to prevent damage caused by sudden failure of semiconductor production facilities. It is to provide a real-time smart big data collection and analysis device.

The purpose of the embodiments of the present invention is not limited to the above-mentioned purpose, and other objects not mentioned will be clearly understood by those of ordinary skill in the art to which the present invention belongs from the following description. .

A real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention for achieving the above object includes: a sensor connection unit 100 connected to a sensor installed in a semiconductor production facility; a digital conversion unit 200 for converting information obtained from a sensor connected to the sensor connection unit 100 into a data format for transmission to a server; a storage unit 300 for storing information to be transmitted to the server; a processing unit 500 for storing meaningful information among the information converted from the digital conversion unit 200 in the storage unit 300; and a monitoring unit 900 that displays information requiring notification among the information stored in the storage unit 300 .

In addition, the real-time smart big data collection and analysis apparatus for improving the yield is characterized in that it communicates with an external device using Generic Equipment Model (GEM) communication.

In addition, the real-time smart big data collection and analysis apparatus for improving the yield is characterized by using an embedded operating system.

In addition, the real-time smart big data collection and analysis apparatus for improving the yield includes an FM receiver 600 for receiving FM radio broadcasts; Including, wherein the processing unit 500 detects the time signal information among the information received from the FM receiving unit 600, characterized in that it adjusts the on-time of the internal clock.

In addition, the real-time smart big data collection and analysis apparatus for improving the yield includes an FM transmitter 700 that transmits information on an FM radio frequency, and the processing unit 500 sends the alarm information to the FM transmitter 700 It is characterized in that it is transmitted.

According to the real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention, by storing meaningful information and transmitting it to the server, it is possible to prevent damage due to unexpected failure of semiconductor production facilities. .

In addition, by using GEM communication, it is possible to obtain information faster.

In addition, by using the embedded operating system, there is an effect that can solve the problem that occurred in the Windows operating system.

In addition, by correcting the internal clock using the radio time signal, there is an effect of correcting the deviation of the reference time of the internal clock.

In addition, by transmitting the alarm information on the FM radio frequency, there is an effect that the information transmission is not disturbed by external interference.

1 is a conceptual diagram for explaining a measurement method using a conventional sensor.
2 is a conceptual diagram of a real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention.
3 is a conceptual diagram for explaining a measurement method using a real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention.
4 is a conceptual diagram of a real-time smart big data collection and analysis apparatus for improving yield according to another embodiment of the present invention.
5 is a conceptual diagram of a real-time smart big data collection and analysis apparatus for improving yield according to another embodiment of the present invention.

Since the present invention can have various changes and can have various embodiments, specific embodiments are illustrated in the drawings and described in detail. However, this is not intended to limit the present invention to specific embodiments, and should be understood to include all modifications, equivalents, and substitutes included in the spirit and scope of the present invention.

When a component is referred to as being “connected” or “connected” to another component, it is understood that the other component may be directly connected or connected to the other component, but other components may exist in between. it should be

On the other hand, when it is mentioned that a certain element is "directly connected" or "directly connected" to another element, it should be understood that the other element does not exist in the middle.

The terms used herein are used only to describe specific embodiments, and are not intended to limit the present invention. The singular expression includes the plural expression unless the context clearly dictates otherwise. In the present application, terms such as “comprise” or “have” are intended to designate that a feature, number, process, operation, component, part, or combination thereof described in the specification exists, but one or more other features It is to be understood that this does not preclude the existence or addition of numbers, processes, operations, components, parts, or combinations thereof.

Unless defined otherwise, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs. Terms such as those defined in a commonly used dictionary should be interpreted as having a meaning consistent with the meaning in the context of the related art, and should not be interpreted in an ideal or excessively formal meaning unless explicitly defined in the present application. does not

Hereinafter, the present invention will be described in more detail with reference to the accompanying drawings. Prior to this, the terms or words used in the present specification and claims should not be construed as being limited to conventional or dictionary meanings, and the inventor should properly understand the concept of the term in order to best describe his invention. Based on the principle that can be defined, it should be interpreted as meaning and concept consistent with the technical idea of the present invention. In addition, if there is no other definition in the technical terms and scientific terms used, it has the meaning commonly understood by those of ordinary skill in the art to which this invention belongs, and the summary of the present invention in the following description and accompanying drawings Descriptions of known functions and configurations that may be unnecessarily obscure will be omitted. The drawings introduced below are provided as examples in order to sufficiently convey the spirit of the present invention to those skilled in the art. Accordingly, the present invention is not limited to the drawings presented below and may be embodied in other forms. Also, like reference numerals refer to like elements throughout. It should be noted that the same components in the drawings are denoted by the same reference numerals wherever possible.

1 is a conceptual diagram for explaining a measurement method using a conventional sensor, FIG. 2 is a conceptual diagram of a real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention, and FIG. 3 is an embodiment of the present invention It is a conceptual diagram for explaining a measurement method using a real-time smart big data collection and analysis device for yield improvement according to an embodiment, and FIG. 4 is a real-time smart big data collection and analysis device for yield improvement according to another embodiment of the present invention. 5 is a conceptual diagram of a real-time smart big data collection and analysis apparatus for improving yield according to another embodiment of the present invention.

As shown in FIG. 1 , the conventional measurement method using a sensor measures a value measured by a sensor selected according to the server's request and sends it to the server.

This conventional measurement method has a problem in that the measurement period of the selected sensor is short, and events occurring at times other than the selected and measured period cannot be measured.

That is, there is a problem that sensor 1 cannot measure an event that occurs during a time when the server requests a measurement from sensor 2 to sensor n (a natural number) and receives the measured value.

Therefore, while other sensors such as sensor 2 are being measured, if an event that can be detected by sensor 1 occurs during the time when other sensors such as sensor 2 are being measured, sensor 1 cannot measure it, so the server does not check the occurrence of an important event. There was a problem that it was difficult to maintain the production facilities in the best condition.

In order to solve this problem, as shown in FIG. 2 , a real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention includes a sensor connection unit 100 , a digital conversion unit 200 , and a storage unit. 300 , a processing unit 500 , and a monitoring unit 900 .

The sensor connection unit 100 is connected to a sensor installed in a semiconductor production facility.

Various sensors such as vibration sensor, temperature sensor, humidity sensor, light sensor, UV sensor, fine dust sensor, RPM sensor, voltage sensor, current sensor, pressure sensor, vibration sensor, and open/close sensor can be used as sensors installed in semiconductor production facilities. and works all the time.

The sensor connection unit 100 can be connected to various communication methods such as RS-232C, RS-422, and RS-485 communication.

The digital conversion unit 200 converts the information obtained from the sensor connected to the sensor connection unit 100 into a data format for transmission to the server.

The digital conversion unit 200 may include at least one selected from an A/D converter, a counter, a digital input (D/I) and a digital output (D/O).

The storage unit 300 stores information to be transmitted to the server.

The storage unit 300 may be a random access memory (RAM).

The processing unit 500 stores meaningful information among the information converted from the digital conversion unit 200 in the storage unit 300 .

The processing unit 500 serves to overall control the real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention.

Significant information means information that is out of the normal state or information that needs to be notified to the manager.

For example, when the voltage of the steady state is 12 to 14V, if the voltage of 17V is sensed, the voltage of 17V corresponds to meaningful information.

For example, when the voltage in the steady state is 12 to 14V, if a voltage of 15V to 17V is detected, the average value of the voltage out of the steady state corresponds to meaningful information, or the voltage of 17V, which is the maximum value, corresponds to meaningful information. can

For example, when a voltage of 12 to 14 V in a steady state is detected, an average value of the sensed voltage may correspond to meaningful information.

That is, the processing unit 500 may be said to have added a data analysis function.

The monitoring unit 900 displays information requiring notification among the information stored in the storage unit 300 .

The information that needs to be notified may be a finally-confirmed sensed value or may be meaningful information.

Real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention, a sensor operates in real time, stores meaningful data, and receives a request for a measurement value from a server, when the previous measurement value is transmitted Meaningful data is processed and transmitted to the server during the period from the time the measurement value is received from the server to the time when the request is received.

Conventionally, since the data is processed only in the measurement section and transmitted to the server, the section measured by each sensor is short (there is a time when the sensor is deactivated) and there may exist a case of missing meaningful data, but as shown in FIG. As described above, when the real-time smart big data collection and analysis device for yield improvement according to an embodiment of the present invention is used, each sensor operates at all times and identifies meaningful data and then sends the sensor to the server at the time the sensor is selected. By transmitting meaningful data, it is possible to prevent the loss of meaningful data.

In addition, the processing unit 500 may determine a criterion for determining meaningful information for each sensor.

In addition, when an event occurs, the processing unit 500 makes a highlight display so as to be visually highlighted on the monitoring unit 900, or transmits the highlighting information to the server to increase the efficiency of information collection in the server. can be done with

Real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention may be characterized in that it communicates with an external device using Generic Equipment Model (GEM) communication.

GEM designates the operation scenario of equipment according to the function, and selects the necessary SECS-II message according to this scenario and uses it as a standard.

Therefore, data communication with other semiconductor equipment can be facilitated by using GEM communication as the basis for communication.

In addition, by standardizing the external hardware interface, interfaces of other manufacturers can be integrated and managed.

Through this, it is possible to improve the speed of collecting and transmitting various signals generated during the semiconductor production process.

In the prior art, which did not support GEM communication, the maximum data transmission time/0.3 seconds can be reduced to the maximum data transmission time/0.1 second while supporting GEM communication.

The real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention may be characterized by using an embedded operating system.

Through this, compared to the prior art using Windows, it is possible to solve the delay problem at the time of first booting, the update problem that occurs during equipment operation, and the security problem by securing complete independence from the external network.

An embedded operating system is an operating system that is usually embedded in hardware, and is usually used in small information devices such as electronic products, PDAs, mobile phones, and digital cameras and automobiles. In general, portable information devices are characterized by a small memory capacity, a slow central processing unit, and a limited battery capacity, but it is gradually expanding to include various functions supported by personal computers.

4, the real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention includes an FM receiver 600 for receiving FM radio broadcasts, and the processing unit 500 includes It may be characterized in that the time signal information is sensed among the information received from the FM receiver 600 to set the on-time of the internal clock.

The real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention may include an internal clock. However, in a state in which communication with the outside is cut off so that Internet access is impossible, an error occurs in the internal clock as time elapses, resulting in a deviation of the reference time in which a difference from the standard time occurs. If the deviation of the reference time exceeds a certain amount of time, the collected data becomes unreliable.

In order to solve this problem, the FM receiver 600 receives an FM radio broadcast, and the processor 500 corrects the deviation of the reference time of the internal clock based on the radio time signal.

A time signal is a signal or a reminder of an accurate time. Various methods have been used since ancient times as a way to tell the exact time. As the number of clocks using electronic and mechanical devices increases, the meaning of the hour has faded as it is now possible to accurately observe 1 minute and 1 second. However, radio in Korea broadcasts the provided time signal every hour on the hour unless there is a special reason. have.

The FM radio broadcasting band is generally used worldwide between 87.5 and 108.0 MHz.

As shown in FIG. 5, the real-time smart big data collection and analysis apparatus for yield improvement according to an embodiment of the present invention includes an FM transmitter 700 that transmits information on an FM radio frequency, and the processing unit 500 ) may be characterized in that the alarm information is transmitted to the FM transmitter 700 .

Alarm information is information transmitted to the process operator when an emergency situation occurs, and when the processing unit 500 determines that an emergency situation has occurred, the alarm information can be delivered to the process operator through the FM transmitter 700 .

Alarm information can be delivered to the mobile terminal of the process operator through the server, but there is often a problem that the alarm information is not delivered, so the real-time smart big data collection and analysis device for improving the yield according to an embodiment of the present invention is directly Alarm information can be transmitted to the mobile terminal of the process operator.

In this case, the transmission of information on the FM radio frequency is to transmit alarm information using a non-jamming signal, so that information transmission is not disturbed by external interference.

In this case, the real-time smart big data collection and analysis apparatus for improving yield according to an embodiment of the present invention may be designed with the following specifications.

Operating system: O/S for embedded

Processor : Intel i5

Memory : 8G

Monitor: 7"

A/D Converter : 24Bit, 21Channel

A/D Converter : 10Bit, 21Channel

16Bit Counter : 21Channel

D/I D/O : 21Channel

External communication: Tcp/ip, RS485, RS232C, USB

A/D Converter: 24Bit can be used to secure more precise data from sensors such as vibration, temperature, humidity, light, UV, and fine dust. Slower than 10Bit, but with higher precision than 10Bit.

A/D Converter: 10Bit can be used to secure lower precision data from sensors such as vibration, temperature, humidity, light, UV, and fine dust. Faster than 24Bit, but less precise than 24Bit.

16Bit Counter can be used in connection with a sensor that measures the number of motor rotations and vibrations.

D/I D/O can be used to collect on/off signals of doors and valves.

TCP/ip communication can be used to connect to the server.

RS485 communication and RS232C communication can be used to connect with compatible sensors.

USB communication can be used to connect to a USB-compatible sensor, or to connect to another USB when updating.

The present invention is not limited to the above-described embodiments, and various modifications can be made without departing from the gist of the present invention as claimed in the claims.

100: sensor connection part
200: digital conversion unit
300: storage
500: processing unit
600: FM receiver
700: FM transmitter
900: monitoring unit

Claims (5)

a sensor connection unit 100 connected to a sensor installed in a semiconductor production facility in a state in which communication with the outside is cut off so that Internet access is impossible;
a digital conversion unit 200 for converting information obtained from a sensor connected to the sensor connection unit 100 into a data format for transmission to a server;
a storage unit 300 for storing information to be transmitted to the server;
a processing unit 500 for storing meaningful information among the information converted from the digital conversion unit 200 in the storage unit 300;
a monitoring unit 900 for displaying information required to be notified among the information stored in the storage unit 300;
FM receiver 600 for receiving FM radio broadcast; and
FM transmitter 700 for transmitting information on an FM radio frequency;
includes,
The processing unit 500 is
It is characterized in that by detecting the time signal information among the information received from the FM receiver 600, and adjusting the time of the internal clock,
The processing unit 500 is
It is characterized in that the alarm information is transmitted to the FM transmitter 700,
The storage unit 300 stores meaningful data of the sensor operating in real time,
When the processing unit 500 receives a request for a measurement value from the server, it is characterized in that it transmits meaningful data to the server during the period from the time when the previous measurement value is transmitted to the time when the measurement value is received from the server,
The processing unit 500 is
Real-time smart for improving yield, characterized in that when an event occurs, highlighting is displayed so as to be visually emphasized on the monitoring unit 900 or transmitted to the server including highlighting information to increase the efficiency of information collection in the server Big data collection and analysis device.
According to claim 1,
The real-time smart big data collection and analysis device for improving the yield is
Real-time smart big data collection and analysis device for yield improvement, characterized in that it communicates with an external device using GEM (Generic Equipment Model) communication.
According to claim 1,
The real-time smart big data collection and analysis device for improving the yield is
Real-time smart big data collection and analysis device for yield improvement, characterized by using an embedded operating system.
According to claim 1,
The real-time smart big data collection and analysis device for improving the yield is
FM receiver 600 for receiving FM radio broadcast;
includes,
The processing unit 500
Real-time smart big data collection and analysis apparatus for improving yield, characterized in that by detecting time signal information among the information received from the FM receiver (600) and adjusting the time of the internal clock.
According to claim 1,
The real-time smart big data collection and analysis device for improving the yield is
FM transmitter 700 for transmitting information on an FM radio frequency;
includes,
The processing unit 500
Real-time smart big data collection and analysis device for improving yield, characterized in that it transmits alarm information to the FM transmitter (700).

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