KR20230171793A - Electronic apparatus and method of controlling thereof - Google Patents

Abstract

An electronic device is disclosed. The electronic device according to the present disclosure includes a memory storing at least one instruction, a display, and a processor executing at least one instruction, and the processor receives a user input inputting product information and a standard production amount for each device. , Obtain the working time and production volume of at least one device operated to produce the product, obtain representative values of the working time and production volume obtained using a clustering algorithm, and determine the operation priority and device-specific standards of the at least one device. Based on the production volume, the operation rate according to the representative value of work time or the representative value of production volume is calculated, and the display is controlled to output the calculated operation rate.

Description

Electronic device and method of controlling the same { ELECTRONIC APPARATUS AND METHOD OF CONTROLLING THEREOF }

The present disclosure relates to an electronic device and a control method thereof, and specifically to an electronic device and a control method thereof that simulate a process for producing a product.

CPPS (Cyber Physical Production Systems) is a cyber-physical production system for smart factory design and operation. It is an integrated system that integrates the real physical world and the virtual world, including production systems such as products, processes, and facilities.

When using CPPS, it is possible to simulate processes to produce defect-free products (good products) or processes to increase the operation rate of equipment.

Although the construction and use of CPPS is a key technological element for realizing a smart factory, there were difficulties in introducing CPPS at small and medium-sized manufacturing companies due to cost and design difficulties.

The present disclosure is intended to solve the above-mentioned difficulties, and the purpose of the present disclosure is to easily simulate the process for producing defect-free products (good products) or the process for increasing the operation rate of the device by collecting data from devices in the factory. To provide an electronic device and a control method thereof.

An electronic device according to an embodiment of the present disclosure includes a memory storing at least one instruction, a display, and a processor executing the at least one instruction, wherein the processor inputs product information and a standard production amount for each device. Upon receiving user input, the working time and production quantity of at least one device operated to produce the product are obtained, and representative values of the obtained working time and production quantity are obtained using a clustering algorithm, and the at least one device Based on the operation priority and the standard production amount for each device, an operation rate according to the representative value of the work time or the representative value of the production amount is calculated, and the display is controlled to output the calculated operation rate.

In addition, the processor allocates the work time of the at least one device according to the priority of the at least one device, and uses the production volume for each device while the at least one device works for the allocated work time. The operation rate can be calculated.

And, when the processor receives a user input for entering a production amount for producing the product, the processor distributes the production amount according to the user input to the at least one device based on the priority of the at least one device, Using the standard production volume for each device, the operation rate while the at least one device produces products equal to the distributed production volume can be calculated.

In addition, when the processor receives a user input for entering a production time for producing the product, the processor uses a representative value of the work time and a representative value of the production amount to operate the at least one device during the production time according to the user input. production volume can be calculated.

And, when the processor receives a user input for inputting the production amount for producing the product, the processor uses the representative value of the work time and the representative value of the production amount to set the work time for producing the product as much as the production amount according to the user input. The range can be calculated.

In addition, when the processor receives a user input for entering the production amount for producing the product, the processor uses the representative value of the work time and the representative value of the production amount to set a preset value to produce the product according to the amount of production according to the user input. The working time for the conditions can be calculated.

Meanwhile, an electronic device according to another embodiment of the present disclosure includes a memory storing at least one instruction, a display, and a processor executing the at least one instruction, where the processor performs product information and product production. Upon receiving a user input for entering a period, operation data of at least one device for producing the product is obtained, a representative value of the obtained operation data is obtained using a clustering algorithm, and a representative value of the obtained operation data is obtained. By merging representative values, a setting value for producing the product is obtained, and the display is controlled to output the obtained setting value.

Meanwhile, a method of controlling an electronic device according to another embodiment of the present disclosure includes receiving a user input of product information and a production amount for each device; obtaining operating hours and output of at least one device operated to produce the product; Obtaining representative values of the obtained work time and production volume using a clustering algorithm; and calculating an operation rate according to a representative value of the work time or a representative value of the production amount based on the operation priority of the at least one device and the production volume for each device.

Additionally, the calculating step may include distributing the work time of the at least one device according to the priority of the at least one device; and calculating an operation rate while the at least one device works for the allocated work time using the production volume for each device.

And, the calculating step includes receiving a user input of the total production amount for producing the product; distributing the total amount of production to the at least one device based on the priority of the at least one device; and calculating an operation rate while the at least one device produces products equal to the total distributed production volume using the production volume for each device.

In addition, upon receiving a user input of inputting a production time for producing the product, calculating the production volume of the at least one device using a representative value of the work time and a representative value of the production volume may be further included. there is.

And, upon receiving a user input of inputting the total amount of production for producing the product, calculating the range of work time for producing the product using the representative value of the work time and the representative value of production volume; It can be included.

In addition, when receiving a user input of the total production amount for producing the product, calculating the working time under preset conditions for producing the product using the representative value of the working time and the representative value of the production amount; may further include.

Meanwhile, a method of controlling an electronic device according to an embodiment of the present disclosure includes receiving a user input of product information and a production period of the product; Obtaining operation data of at least one device for producing the product; Obtaining a representative value of the obtained motion data using a clustering algorithm; and merging representative values of the obtained motion data to obtain a setting value for producing the product.

1 is a block diagram for explaining the configuration of an electronic device according to the present disclosure;
2 is a flowchart for explaining an electronic device that calculates an operation rate according to an embodiment of the present disclosure;
3 is a diagram for explaining the operation rate output according to an embodiment of the present disclosure;
4 is a flowchart illustrating an electronic device for acquiring operation data of a device in a factory for producing a product under preset conditions according to an embodiment of the present disclosure;
5 is a diagram for explaining operation data displayed on an electronic device according to an embodiment of the present disclosure;
6 is a diagram illustrating operation data for producing a product with preset conditions displayed on an electronic device according to an embodiment of the present disclosure;
7 is a block diagram for explaining the configuration of an electronic device according to an embodiment of the present disclosure;
8 is a diagram for explaining a product image identified by an electronic device according to an embodiment of the present disclosure, and
Figure 9 is a flowchart for explaining a control method according to an embodiment of the present disclosure.

Terms used in this specification will be briefly described, and the present disclosure will be described in detail.

The terms used in the embodiments of the present disclosure have selected general terms that are currently widely used as much as possible while considering the functions in the present disclosure, but this may vary depending on the intention or precedent of a technician working in the art, the emergence of new technology, etc. . In addition, in certain cases, there are terms arbitrarily selected by the applicant, and in this case, the meaning will be described in detail in the description part of the relevant disclosure. Therefore, the terms used in this disclosure should be defined based on the meaning of the term and the overall content of this disclosure, rather than simply the name of the term.

Hereinafter, various embodiments of this document are described with reference to the attached drawings. However, this is not intended to limit the technology described in this document to specific embodiments, and should be understood to include various modifications, equivalents, and/or alternatives to the embodiments of this document. . In connection with the description of the drawings, similar reference numbers may be used for similar components.

In this document, expressions such as “have,” “may have,” “includes,” or “may include” refer to the existence of the corresponding feature (e.g., a numerical value, function, operation, or component such as a part). , and does not rule out the existence of additional features.

In this document, expressions such as “A or B,” “at least one of A or/and B,” or “one or more of A or/and B” may include all possible combinations of the items listed together. . For example, “A or B,” “at least one of A and B,” or “at least one of A or B” includes (1) at least one A, (2) at least one B, or (3) it may refer to all cases including both at least one A and at least one B.

Expressions such as “first,” “second,” “first,” or “second,” used in this document can modify various components regardless of order and/or importance, and can refer to one component. It is only used to distinguish from other components and does not limit the components. For example, a first user device and a second user device may represent different user devices regardless of order or importance. For example, a first component may be renamed a second component without departing from the scope of rights described in this document, and similarly, the second component may also be renamed to the first component.

Terms such as “module,” “unit,” and “part” used in this document are terms to refer to components that perform at least one function or operation, and these components are implemented in hardware or software. Alternatively, it can be implemented through a combination of hardware and software. In addition, a plurality of "modules", "units", "parts", etc. are integrated into at least one module or chip, except in cases where each needs to be implemented with individual specific hardware, and is integrated into at least one processor. It can be implemented as:

A component (e.g., a first component) is “(operatively or communicatively) coupled with/to” another component (e.g., a second component). When referred to as being “connected to,” it should be understood that any component may be directly connected to the other component or may be connected through another component (e.g., a third component). On the other hand, when a component (e.g., a first component) is said to be “directly connected” or “directly connected” to another component (e.g., a second component), It may be understood that no other component (e.g., a third component) exists between other components.

As used in this document, the expression “configured to” depends on the situation, for example, “suitable for,” “having the capacity to.” ," can be used interchangeably with "designed to," "adapted to," "made to," or "capable of." The term “configured (or set to)” may not necessarily mean “specifically designed to” in hardware. Instead, in some contexts, the expression “a device configured to” may mean that the device is “capable of” working with other devices or components. For example, the phrase "processor configured (or set) to perform A, B, and C" refers to a processor dedicated to performing the operations (e.g., an embedded processor), or by executing one or more software programs stored on a memory device. , may refer to a general-purpose processor (e.g., CPU or application processor) capable of performing the corresponding operations.

Terms used in this document are merely used to describe specific embodiments and may not be intended to limit the scope of other embodiments. Singular expressions may include plural expressions, unless the context clearly indicates otherwise. Terms used herein, including technical or scientific terms, may have the same meaning as commonly understood by a person of ordinary skill in the technical field described in this document. Among the terms used in this document, terms defined in general dictionaries may be interpreted to have the same or similar meaning as the meaning they have in the context of related technology, and unless clearly defined in this document, have an ideal or excessively formal meaning. It is not interpreted as In some cases, even terms defined in this document cannot be interpreted to exclude embodiments of this document.

Below, with reference to the attached drawings, embodiments of the present disclosure will be described in detail so that those skilled in the art can easily practice them. However, the present disclosure may be implemented in many different forms and is not limited to the embodiments described herein. In order to clearly explain the present disclosure in the drawings, parts that are not related to the description are omitted, and similar parts are given similar reference numerals throughout the specification.

In this disclosure, the term user may refer to a person using an electronic device or a device (eg, an artificial intelligence electronic device) using an electronic device.

In the present disclosure, the device within the factory may refer to all devices located within the factory as well as devices used to produce goods in the factory. For example, in-factory devices may include in-factory production devices, quality detection devices, packaging devices, as well as movement devices, ventilation devices, drainage devices, soundproofing devices, communication devices, or sensors.

Hereinafter, an embodiment of the present disclosure will be described in more detail with reference to the attached drawings.

1 is a block diagram for explaining the configuration of an electronic device according to the present disclosure.

As disclosed in FIG. 1, the electronic device 100 includes a memory 110, a display 120, and a processor 130.

The memory 110 is a component for storing various programs and data necessary for the operation of the electronic device 100. At least one instruction for the processor 130 to operate the electronic device 100 is stored in the memory 110 .

The memory 110 may store operation data of devices within the factory. Here, operation data represents the elements and their values that change when the equipment in the factory is operated to produce products, and includes the temperature of the equipment (e.g., temperature of the cylinder in the equipment), current, power, RPM, etc. can do.

Additionally, the memory 110 may store work data of devices within the factory. At this time, the work data may include the work time required for the device in the factory to produce the product, product production volume (or production weight), etc.

The memory 110 may be implemented as non-volatile memory (eg, hard disk, solid state drive (SSD), flash memory), volatile memory, etc. Meanwhile, the memory 110 may be implemented as a memory that is physically separate from the processor 130. In this case, the memory 110 may be implemented as a memory embedded in the electronic device 100 or as a memory detachable from the electronic device 100 depending on the data storage purpose.

For example, the memory 110 may include volatile memory (e.g., dynamic RAM (DRAM), static RAM (SRAM), or synchronous dynamic RAM (SDRAM), etc.), non-volatile memory (e.g., OTPROM ( one time programmable ROM), programmable ROM (PROM), erasable and programmable ROM (EPROM), electrically erasable and programmable ROM (EEPROM), mask ROM, flash ROM, flash memory (such as NAND flash or NOR flash, etc.), hard drive , or a solid state drive (SSD), memory card (e.g., compact flash (CF), secure digital (SD), micro secure digital (Micro-SD), mini secure digital (Mini-SD) , xD (extreme digital), MMC (multi-media card), etc.), external memory that can be connected to a USB port (for example, USB memory), etc.

Additionally, the memory 110 may be implemented as internal memory such as ROM (eg, electrically erasable programmable read-only memory (EEPROM)) or RAM included in the processor 130.

The display 120 is a component for outputting a user interface (UI) for user input or various data.

The display 120 may display a user interface for entering product information or product production period. Here, product information refers to information that can identify the product, such as product code and product number, as well as the product name.

The display 120 may include a user interface for inputting the standard production amount for each device. Here, the standard production volume per device refers to the weight of the product that one device can produce.

The display 120 may provide a user interface for selecting output data items. Specifically, display 120 may display a user interface for selecting output data items, such as device production volume, production time, uniform operation rate, or sequential operation rate.

The display 120 can display various output data. Specifically, the display can output and display various data, such as device production volume, production time, uniform operation rate or sequential operation rate, and device operation data.

The display 120 may be implemented as various types of displays, such as Liquid Crystal Display (LCD), Organic Light Emitting Diodes (OLED) display, Plasma Display Panel (PDP), Wall, Micro LED, etc. The display 120 may also include a driving circuit and a backlight unit that may be implemented in the form of a-si TFT, low temperature poly silicon (LTPS) TFT, or organic TFT (OTFT). Meanwhile, the display 120 may be implemented as a touch screen combined with a touch sensor, a flexible display, a 3D display, etc.

The processor 130 is electrically connected to the memory 110 and can control the overall operation and functions of the electronic device 100. For example, the processor 130 can control hardware or software components connected to the processor 130 by running an operating system or application program, and can perform various data processing and calculations. Additionally, the processor 130 may load and process commands or data received from at least one of the other components into volatile memory and store various data in non-volatile memory.

To this end, the processor 130 is a dedicated processor (e.g., embedded processor) or a general-purpose processor (e.g., CPU (Central)) capable of performing the operations by executing one or more software programs stored in a memory device. It can be implemented as a processing unit or application processor.

In the present disclosure, the processor may consist of one or multiple processors. At this time, one or more processors may be a general-purpose processor such as a CPU, AP, or DSP (Digital Signal Processor), a graphics-specific processor such as a GPU or VPU (Vision Processing Unit), or an artificial intelligence-specific processor such as an NPU. One or more processors control input data to be processed according to predefined operation rules or artificial intelligence models stored in memory. Alternatively, when one or more processors are dedicated artificial intelligence processors, the artificial intelligence dedicated processors may be designed with a hardware structure specialized for processing a specific artificial intelligence model.

When the processor 130 receives user input of product information and the standard production amount for each device, it can calculate the operation rate of the device that produces the product.

Specifically, when the processor 130 receives user input for entering product information and the standard production amount for each device, the processor 130 obtains the work time and production amount of at least one device operated to produce the product, and obtains them using a clustering algorithm. Representative values of working time and production volume can be obtained. At this time, the representative values of work time and production volume refer to the median value of work time and the median value of production volume derived using a clustering algorithm.

Additionally, the processor 130 may calculate an operation rate based on a representative value of work time and a representative value of production volume based on the operation priority of the device and the standard production amount for each device. At this time, the operation priority of the device may be preset or may be set by user input.

The operation rate calculated here may be a uniform operation rate or a sequential operation rate. The equal operation rate refers to the operation rate of each device when work hours are equally distributed to multiple devices, and the sequential operation rate refers to the operation rate of each device when production is equally distributed to multiple devices equal to the standard production amount for each device.

This will be explained in more detail in FIGS. 2 and 3.

When receiving user input for product information and product production period, the processor 130 obtains operation data of a device for producing a product under preset conditions, and controls the display 120 to display the obtained operation data. can do.

Specifically, when the processor 130 receives user input for entering product information and the production period of the product, the processor 130 obtains operation data of at least one device for producing the product, and obtains operation data of at least one device for producing the product, and uses the clustering algorithm to obtain operation data. Representative values can be obtained. At this time, the representative value of the operation data refers to the median value of the operation data derived as a result of clustering the operation data using a clustering algorithm.

The processor 130 may acquire a setting value for producing a product by merging representative values of the acquired operation data, and control the display 120 to output the obtained setting value.

This will be explained in detail in FIGS. 4 to 6.

FIG. 2 is a flowchart illustrating an electronic device that calculates an operation rate according to an embodiment of the present disclosure.

The processor 130 may receive user input for entering product information and the standard production amount for each device (S210). Specifically, the processor 130 controls the display 120 to display a user interface for receiving product information and the standard production amount for each device, and receives user input for entering product information and the standard production amount for each device through the user interface. can do.

Additionally, the processor 130 may receive a user input for selecting an output data item. For example, the processor 130 controls the display 120 to display output data items such as production volume, production time, uniform operation rate for each facility, and sequential operation rate for each facility, and when at least one item among the displayed output data items is selected, the selected Items and corresponding values can be output. As described above in FIG. 1, in the present disclosure, the uniform operation rate refers to the operation rate of each device when work time is equally distributed to a plurality of devices, and the sequential operation rate refers to the production rate of the plurality of devices being equalized by the standard production amount for each device. When distributed, it refers to the operation rate of each device.

The processor 130 may obtain work time and production data of at least one device operated to produce the product upon receiving a user input of product information and production amount for each device (S220).

Specifically, the processor 130 may obtain work time and production data of at least one device operated to produce a product during a specific period. At this time, the specific period may be a period entered by the user, or may be a preset period.

The processor 130 may derive the maximum and minimum values of the data by excluding outliers in the obtained work time data and production data (S230).

Specifically, the processor 130 may identify data that is outside a preset range value among the acquired work time data and production data as outliers, and exclude data including the identified outliers. For this purpose, the range of work time data and production data may be preset.

Additionally, the processor 130 may analyze the data excluding outliers and derive the maximum and minimum values of the data.

Processor 130 may identify the range of work time data and production data by deriving maximum and minimum values.

The processor 130 may obtain representative values of work time and production data using a clustering algorithm (S240). As described above, the representative value of the work time data and the representative value of the production volume data mean the intermediate value of the work time data and production volume data obtained using the clustering algorithm.

Meanwhile, the clustering algorithm of the present disclosure may vary depending on the embodiment. For example, the clustering algorithm may be the K-medois algorithm, but is not necessarily limited to this, and may include various algorithms that obtain the median value of data.

Additionally, the processor 130 may confirm that the median value obtained through the kernel density estimation graph is the median value (or optimal value) within the cluster.

The processor 130 can calculate the range of work time according to the amount of production input by the user (S250). Specifically, the processor 130 receives the total product production amount input from the user, and uses the representative value of the work time and the representative value of the production amount obtained in step S240 to determine the range of work time for producing the total product production amount entered by the user. can be calculated.

When the processor 130 receives a user input of inputting the production amount to produce a product, the processor 130 uses the representative value of the work time and the representative value of the production amount to calculate the range of work time to produce the product by the amount of production according to the user input. can do.

Specifically, the processor 130 can calculate the range of work time by calculating the minimum work time and maximum work time using Equation 1 below.

Alternatively, when the processor 130 receives a user input of inputting the production amount for producing a product, the processor 130 uses the representative value of the work time and the representative value of the production amount to set preset conditions for producing the product by the amount according to the user input. Working time can be calculated. Here, the working time under preset conditions may mean the median value of the working time required to produce the product.

Specifically, the processor 130 can use Equation 2 below to calculate the work time under preset conditions for producing a product equal to the production volume according to the user input.

Meanwhile, the processor 130 can calculate the production amount according to the production time entered by the user (S260).

When the processor 130 receives a user input for entering a production time for producing a product, the processor 130 uses a representative value of the work time and a representative value of the production amount to set up at least one device that produces the product during the production time according to the user input. Production volume can be calculated.

Specifically, the processor can use Equation 3 below to calculate the production volume of at least one device that produces a product during the production time according to the user input.

In this way, the processor 130 can calculate work time or production volume using the relationship between production volume and work time according to user input or the relationship between production time and production volume according to user input.

The processor 130 may calculate the operation rate based on the priority of the device and output the calculated operation rate (S270).

Specifically, the processor 130 may calculate the uniform operation rate or sequential operation rate based on the priority of the device.

The processor 130 can allocate the work time of at least one device according to the priority of the at least one device, and calculate the operation rate while at least one device works for the allocated time using the standard production amount for each device. there is. The operation rate at this time may be the uniform operation rate.

The processor 130 may also calculate the sequential operation rate.

Specifically, when the processor 130 receives a user input for inputting the production amount for producing a product, the processor 130 sequentially distributes the production amount according to the user input to at least one device based on the priority of the at least one device, and Using the standard production volume per star, the operation rate while at least one device produces products equal to the distributed production volume can be calculated.

Accordingly, the processor 130 can calculate the uniform operation rate or the sequential operation rate, and control the display 120 to display the calculated operation rate.

Figure 3 is a diagram for explaining the operation rate output according to an embodiment of the present disclosure.

Table 300 in FIG. 3 represents the operation rate of devices in the factory displayed on the display 120 as a result of execution according to the flowchart in FIG. 2.

For example, if there are devices (e.g., kneader machines) 1, 2, 3, and 4 in the factory, the processor 130 uses a clustering algorithm to determine the working time based on the work time data and production volume data of the devices in the factory. Representative values and representative values of production can be obtained. At this time, the representative value of the work time may correspond to the standard time in the table 300.

When the processor 130 receives 999.7 kg as the production amount of devices 1, 2, 3, and 4 from the user, the range of work time for producing 999.7 kg of product using Equation 1 and Equation 2 of FIG. 2 can be calculated.

Specifically, the processor 130 can obtain the minimum work time or maximum work time through Equation 1, which may correspond to the minimum work time or maximum work time in the table 300. Additionally, the processor 130 can calculate the work time under preset conditions through Equation 2, which may correspond to the optimal work time in the table 300.

Additionally, the processor 130 can calculate the operation rates of devices 1, 2, 3, and 4 in the factory. The operation rate in table 300 represents the sequential operation rate when the standard production volume for each device of devices 1 to 4 is 250 kg. Specifically, in order to produce a production volume of 999.7 kg, based on the priorities of devices 1 to 4, 250 kg corresponding to the standard production amount for each device is sequentially distributed to devices 1 to 3 and 249.7 kg is distributed to device 4. Indicates the sequential operation rate for each device.

Although only the sequential operation rate is shown in FIG. 3, the processor 130 may calculate the uniform operation rate using the method described above in FIG. 2.

FIG. 4 is a flowchart illustrating an electronic device that acquires operation data of a device in a factory for producing a product under preset conditions according to an embodiment of the present disclosure.

In this disclosure, a product with preset conditions refers to a product with no defects or defects.

First, the processor 130 may receive user input for entering product information and the production period of the product (S410). Specifically, the processor 130 controls the display 120 to display a user interface for receiving product information and the production period of the product, and receives user input for entering product information and the standard production amount for each device through the user interface. can do.

When the processor 130 receives a user input of product information and a product production period, the processor 130 may obtain operation data of at least one device for producing a product corresponding to the product information entered by the user (S420). .

As described above in FIG. 2, operation data represents elements and their values that change when a device in a factory is operated to produce a product, including temperature of the device (e.g., temperature of the cylinder in the device), current, power, This may include RPM, etc.

The processor 130 may acquire operation data of at least one device for producing a product corresponding to product information among the operation data stored in the memory 110, or may obtain operation data from an external device (not shown).

The processor 130 may preprocess the acquired operation data. Specifically, the processor 130 may identify and remove data with duplicate values or incorrect data values from the acquired operation data.

The processor 130 may remove outliers from the operation data. The processor 130 may identify data that is outside a preset range among the operation data as outliers and exclude data including the identified outliers.

The processor 130 may determine the range of operation data excluding outliers. Specifically, the processor 130 may obtain the maximum, minimum, or average value of the operation data.

Additionally, the processor 130 preprocessed operation data may be sorted in ascending time order.

The processor 130 may obtain representative values of operation data using a clustering algorithm (S430). Here, the representative value of the operation data refers to the median value of the operation data obtained when the operation data is clustered using a clustering algorithm.

The clustering algorithm may be the K-medois algorithm, but is not necessarily limited to this, and may include various algorithms that obtain the median value of the data.

The processor 130 may confirm that the median value obtained through a kernel density estimation (KDE) graph is the median value (or optimal value) within the cluster.

The processor 130 may merge representative values of operation data of at least one device. For example, if a representative value of the operation data of device A, a representative value of the operation data of device B, and a representative value of the operation data of device C exist for one product, the processor 130 may determine the representative value of the operation data of device A for one product. The representative value of the operation data of , the representative value of the operation data of device B, and the representative value of the operation data of device C can be merged.

The processor 130 may visualize the operation data obtained in step S420 (S440).

Specifically, the processor 130 may control the display 120 to display operation data including the maximum, minimum, and average values of the operation data.

In this regard, FIG. 5 is a diagram for explaining operation data displayed on an electronic device according to an embodiment of the present disclosure.

As shown in FIG. 5, the processor 130 can visualize device operation data using a boxplot image.

For example, if temperature data, current data, and RPM data exist as the operation data of device A, the processor 130 displays the maximum, minimum, and average values of each of the temperature data, current data, and RPM data of device A in a boxplot image (610 , 620, and 630).

Meanwhile, only the operation data for device A is shown in FIG. 5, but operation data for other devices can also be visualized using a boxplot image in the same way.

In this way, by visualizing the operation data using a boxplot image, the user can more clearly recognize the range of the operation data.

Returning again to FIG. 4, the processor 130 may output a representative value of the operation data obtained in step S430 (S450).

Specifically, the processor 130 may control the display 120 to output representative values of operation data of at least one device.

In this regard, referring to FIG. 6, representative values of operation data displayed on the display 120 are shown.

As shown in FIG. 6, the processor 130 may control the display 120 to merge operation data of at least one device and display it.

For example, RPM data, temperature data and current data of device A that produces the product, temperature data of cylinder 1, temperature data of cylinder 2 and temperature data of cylinder 3, temperature data of pipe 1 and temperature data of pipe 2 of device B. , if representative values for the temperature data of tube 3 and the temperature data of tube 4 exist, the display 120 can be controlled to merge them and display them in one table.

Meanwhile, in another embodiment, the processor 130 may obtain representative values for the weight of materials in addition to devices used to produce products.

Specifically, the processor 130 may obtain a representative value for the weight of the material in a method similar to the flowchart of FIG. 4. The processor 130 may acquire weight data of materials used to produce a product and obtain a representative value for the weight data using a clustering algorithm.

Additionally, the processor 130 may control the display 120 to display the obtained representative value. In this case, the processor 130 may control the display 120 to display together representative values of device operation data and representative values of material weight data, as shown in FIG. 6 .

Using the representative value calculated in this way, the electronic device 100 can provide the user with operation data for producing a product with no defects or defects.

Meanwhile, according to another embodiment of the present disclosure, an electronic device can identify products with defects or defects.

In this regard, Figure 7 is a block diagram for explaining the configuration of an electronic device according to an embodiment of the present disclosure.

As shown in FIG. 7 , the electronic device 100 may include a memory 110, a display 120, a processor 130, and a camera 140. Regarding the memory 110, display 120, and processor 130, content that overlaps with the content described in FIG. 2 will be omitted.

The memory 110 may include an artificial intelligence model according to various embodiments of the present disclosure.

The artificial intelligence model stored in the memory 110 may be an artificial intelligence model learned to determine whether a defect or defect exists in the product based on the image of the product captured by the camera 140.

The display 120 is configured to display images captured by the camera 140.

Specifically, the display 120 may display images including normal products and images including products with defects or defects (hereinafter referred to as defective products) among images captured by the camera 140.

The camera 140 can photograph products produced in a device within a factory from various angles.

The camera 140 can capture various images of a product at one location while varying brightness conditions such as illuminance and brightness of the lens or adjusting the focal length of the lens.

The processor 130 may acquire an image of the product captured by the camera 140 and convert the acquired image of the product into a hue saturation value (HSV) image or a LAB image.

In addition, the processor 130 can identify whether a defective product exists in the obtained product image using an artificial intelligence model learned to determine whether a defect or defect exists in the product.

If a defective product is included in an image captured by the camera 140, the processor 130 may distinguish the image from an image containing a normal product.

Additionally, the processor 130 may control the display 120 to display images containing normal products and images containing defective products separately.

FIG. 8 is a diagram illustrating a product image identified by an electronic device according to an embodiment of the present disclosure.

As shown in FIG. 8, the processor 130 may control the display 120 to display images containing normal products and images containing defective products.

Meanwhile, according to one embodiment, the processor 130 may control the display 120 to display defective products or areas where defects or defects exist within an image including defective products.

Figure 9 is a flowchart for explaining a control method according to an embodiment of the present disclosure.

The electronic device 100 may receive user input for entering product information and the standard production amount for each device (S910). Specifically, a user interface for receiving product information and the standard production amount for each device may be displayed, and user input for entering product information and the standard production amount for each device may be received through the user interface.

Additionally, the working time and production volume of at least one device operated to produce the product can be obtained (S920).

At this time, work time and production data of at least one device operated to produce a product during a specific period can be obtained. At this time, the specific period may be a period entered by the user, or may be a preset period.

By excluding outliers in the obtained work time data and production data, the maximum and minimum values of the data can be derived. And, by analyzing the data excluding outliers, the maximum and minimum values of the data can be derived.

Additionally, representative values of work time and production data can be obtained using a clustering algorithm (S930). At this time, it can be confirmed that the median value obtained through the kernel density estimation graph is the median value (or optimal value) within the cluster.

In addition, based on the operation priority of at least one device and the standard production amount for each device, an operation rate according to a representative value of work time or a representative value of production volume can be calculated (S940).

The work time of at least one device can be distributed according to the priority of the at least one device, and the operation rate while at least one device works for the allocated time can be calculated using the standard production amount for each device. The operation rate at this time may be the uniform operation rate.

When receiving a user input for inputting the production amount for producing a product, the production amount according to the user input is sequentially distributed to at least one device based on the priority of the at least one device, and the production amount according to the user input is sequentially distributed to at least one device using the standard production amount for each device. The operation rate while the equipment produces products equal to the allocated production volume can be calculated.

Various operations described above as being performed through the electronic device 100 may be performed through one or more electronic devices in the form of a control method or operation method of a system including an electronic device.

Meanwhile, the various embodiments described above may be implemented in a recording medium that can be read by a computer or similar device using software, hardware, or a combination thereof.

According to hardware implementation, the embodiments described in this disclosure include application specific integrated circuits (ASICs), digital signal processors (DSPs), digital signal processing devices (DSPDs), programmable logic devices (PLDs), and field programmable gate arrays (FPGAs). ), processor, controller, micro-controllers, microprocessor, and other electrical units for performing functions.

Meanwhile, computer instructions for performing processing operations on a user device or administrator device according to various embodiments of the present disclosure described above may be stored in a non-transitory computer-readable medium. You can. The computer instructions stored in such a non-transitory computer-readable medium, when executed by a processor of a specific device, cause the specific device to perform processing operations of the user device and/or the administrator device according to the various embodiments described above.

A non-transitory readable medium refers to a medium that stores data semi-permanently and can be read by a device, rather than a medium that stores data for a short period of time, such as registers, caches, and memories. Specifically, the various applications or programs described above may be stored and provided on non-transitory readable media such as CD, DVD, hard disk, Blu-ray disk, USB, memory card, ROM, etc.

In addition, although preferred embodiments of the present invention have been shown and described above, the present invention is not limited to the specific embodiments described above, and the technical field to which the invention pertains without departing from the gist of the present invention as claimed in the claims. Of course, various modifications can be made by those skilled in the art, and these modifications should not be understood individually from the technical idea or perspective of the present invention.

100: electronic device 110: memory
120: display 130: processor

Claims (14)

In electronic devices,
a memory storing at least one instruction;
display; and
Including a processor executing the at least one instruction,
The processor,
Upon receiving user input entering product information and the standard production amount for each device,
Obtain the operating hours and output of at least one device operated to produce the product,
Obtain representative values of the obtained work time and production volume using a clustering algorithm,
An electronic device for calculating an operation rate according to a representative value of the work time or a representative value of the production amount based on the operation priority of the at least one device and the standard production amount for each device, and controlling the display to output the calculated operation rate. Device.
According to paragraph 1,
The processor,
Distributing the work time of the at least one device according to the priority of the at least one device,
An electronic device that calculates an operation rate while the at least one device works for the allocated work time using the standard production amount for each device.
According to paragraph 1,
The processor,
Upon receiving user input for entering the production quantity to produce the product,
sequentially distributing the production amount according to the user input to the at least one device based on the priority of the at least one device,
An electronic device that calculates an operation rate while the at least one device produces a product equal to the distributed production volume using the standard production volume for each device.
According to paragraph 1,
The processor,
Upon receiving user input inputting the production time for producing the product,
An electronic device that calculates the production volume of the at least one device during the production time according to the user input using the representative value of the work time and the representative value of the production volume.
According to paragraph 1,
The processor,
Upon receiving user input for entering the production quantity to produce the product,
An electronic device that calculates the range of work time for producing a product equal to the amount of production according to the user input, using the representative value of the work time and the representative value of the production amount.
According to paragraph 1,
The processor,
Upon receiving user input for entering the production quantity to produce the product,
An electronic device that uses the representative value of the work time and the representative value of the production amount to calculate the work time under preset conditions for producing a product as much as the amount of production according to the user input.
In electronic devices,
a memory storing at least one instruction;
display; and
Including a processor executing the at least one instruction,
The processor,
Upon receiving user input entering product information and the production period for the product,
Obtaining operation data of at least one device for producing the product,
Obtain representative values of the obtained operation data using a clustering algorithm,
An electronic device that acquires a setting value for producing the product by merging representative values of the obtained operation data, and controls the display to output the obtained setting value. In a method of controlling an electronic device,
Receiving a user input of product information and a standard production amount for each device;
obtaining operating hours and output of at least one device operated to produce the product;
Obtaining representative values of the obtained work time and production volume using a clustering algorithm;
calculating an operation rate according to a representative value of the work time or a representative value of the production amount based on the operation priority of the at least one device and the standard production amount for each device; and
A control method comprising: outputting the calculated operation rate.
According to clause 8,
The calculating step is,
distributing work time of the at least one device according to the priority of the at least one device; and
A control method including; calculating an operation rate while the at least one device works for the allocated work time using the standard production amount for each device.
According to clause 8,
The calculating step is,
Receiving a user input inputting a production quantity for producing the product;
sequentially distributing the production amount according to the user input to the at least one device based on the priority of the at least one device; and
A control method including; calculating an operation rate while the at least one device produces products equal to the distributed production volume using the standard production volume for each device.
According to clause 8,
Upon receiving a user input for entering a production time for producing the product, calculating the production volume of the at least one device during the production time according to the user input using a representative value of the work time and a representative value of the production volume. A control method further comprising ;.
According to clause 8,
When receiving a user input for entering the total production amount to produce the product, the representative value of the work time and the representative value of the production volume are used to calculate the range of work time to produce the product as much as the production amount according to the user input. A control method further comprising a step.
According to clause 8,
When receiving a user input for inputting the production volume for producing the product, the representative value of the work time and the representative value of the production volume are used to calculate the work time under preset conditions for producing the product according to the production volume according to the user input. A control method further comprising:
In a method of controlling an electronic device,
Receiving user input entering product information and a production period of the product;
Obtaining operation data of at least one device for producing the product;
Obtaining a representative value of the obtained operation data using a clustering algorithm;
Obtaining a set value for producing the product by merging representative values of the obtained operation data; and
A control method comprising: outputting the obtained setting value.

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