KR102256115B1 - Intelligent system for cutting process - Google Patents

Abstract

Disclosed is an intelligent system for a cutting process. According to an embodiment of the present invention, an intelligent method for the cutting process, which is conducted by an intelligent control apparatus for a cutting process can comprise: a step in which an input unit receives processing request information including a shape information of a target article; a step in which a simulation unit generates a processing scheduling information corresponding to the processing request information based on a processing analysis algorithm based on an artificial intelligence built previously; a step in which the input unit receives a measurement value information in a cutting and processing process conducted to process the subject to be processed into the target article; a step in which a monitoring unit calculates an error information based on the measurement value information and the processing scheduling information; and a step in which a display unit displays feedback information generated based on the error information. The present invention aims to provide an intelligent system for the cutting process, which is able to monitor to see if the actual process is conducted to meet the predetermined processing scheduling information.

Description

Intelligent cutting processing system {INTELLIGENT SYSTEM FOR CUTTING PROCESS}

The present application relates to an intelligent cutting processing system. For example, the present application relates to an intelligent cutting process control device and method.

A machine tool refers to a machine used for the purpose of processing a metal or non-metal base material into shapes and dimensions using a suitable tool by various cutting or non-cutting processing methods, or adding more precise processing. For these machine tools, automation and numerical control are rapidly progressing throughout the industry, and in addition, computerized numerical control is widely introduced throughout the industry.

In such a machine tool, the processing of the base material is mainly performed by a processing program generated by an operator, and such a processing program may include the type of tool to be used during processing, the feed rate of the tool, the spindle rotational speed, and the processing path.

On the other hand, if you want to create a machining program by judging the type of tool, tool feed rate, spindle rotational speed, and machining path, or if you want to perform simple cutting manually, the operator is required to have extensive knowledge about cutting. There were difficulties.

In particular, the trend toward reducing personnel, reducing production time, improving quality, and reducing costs through automation in the process environment is becoming increasingly stronger as it approaches the modern era. In the manufacturing industry, cutting processing still takes a lot of time and cost in product production, and in addition, the need for high performance and monitoring of cutting processing conditions using various measuring equipment is increasing in machine tools that perform cutting processing.

In particular, as the cycle of products is shortened and the number of multi-kind, small-scale workpieces is increasing, the proportion of the reduction in processing time to productivity is gradually increasing, and accordingly, detailed information on the process to be performed to the operator through simulation of the operation of the cutting equipment is provided. It is required to achieve the reliability of the process and the high quality of the manufacturing elements through a condition monitoring sensor system, etc. provided in the workplace where it is accurately provided and actually processed.

The technology behind the present application is disclosed in Korean Patent Publication No. 10-1515736.

The present application is to solve the problems of the prior art described above, and automatically generates processing scheduling information based on the shape of the target workpiece, and provides it to the operator, and the previously established processing for the corresponding process based on the measured value obtained in the actual process. The object of the present invention is to provide an intelligent cutting processing device and method capable of monitoring whether the actual process is performed in accordance with the scheduling information.

However, the technical problem to be achieved by the embodiments of the present application is not limited to the technical problems as described above, and other technical problems may exist.

As a technical means for achieving the above-described technical problem, the intelligent cutting processing method performed by the intelligent cutting processing control device according to an embodiment of the present application includes an input unit receiving processing request information including shape information of a target workpiece. The step of generating processing scheduling information corresponding to the processing request information based on a processing analysis algorithm based on artificial intelligence built in advance by a simulation unit, in a cutting processing process performed by the input unit to process the workpiece into the target workpiece. Receiving the measured value information of, a monitoring unit calculating error information based on the measured value information and the processing scheduling information, and a display unit displaying feedback information generated based on the error information.

In addition, the generating the processing scheduling information may include determining a plurality of unit processes to be included in the cutting process based on the shape information, determining an execution order of the plurality of unit processes, and the plurality of units It may include the step of determining the operating conditions of the cutting means corresponding to each of the processes.

In addition, the processing request information may include drawing data representing the shape information in three dimensions.

In addition, the intelligent cutting processing method performed by the intelligent cutting processing control device according to an embodiment of the present application is, after the step of generating the processing scheduling information, the display unit is a virtual cutting processing generated in response to the processing scheduling information. The process simulation data may be overlaid on the drawing data and displayed.

In addition, the step of displaying by overlaying may include displaying a two-dimensional shape in which the simulation data is projected based on at least one projection direction.

In addition, the calculating of the error information includes generating time series data on the measured value information collected for a time period equal to or longer than a preset monitoring period, and a cutting process actually performed based on the time series data is reflected in the machining scheduling information. It may include determining whether the execution order and the operation condition are satisfied.

In addition, in the displaying of the feedback information, if the execution order does not satisfy the processing scheduling information as a result of the determination, feedback information corresponding to the first warning level may be displayed.

In addition, in the displaying of the feedback information, if the operation condition does not satisfy the processing scheduling information as a result of the determination, feedback information corresponding to a second warning level that is more relaxed than the first warning level may be displayed.

In addition, in the displaying of the feedback information, if the execution order and the operation condition satisfy the processing scheduling information as a result of the determination, feedback information corresponding to a normal level may be displayed.

In addition, the intelligent cutting processing method performed by the intelligent cutting processing control device according to an embodiment of the present application, in the step of expressing the feedback information, the feedback information corresponding to the first warning level or the second warning level When the corresponding feedback information is displayed, the storage unit may include storing measurement information obtained for the corresponding cutting process.

On the other hand, the intelligent cutting processing control device according to an embodiment of the present application is an input unit for receiving processing request information including shape information of a target workpiece and measurement value information in a cutting process performed to process a workpiece into the target workpiece , A simulation unit that generates processing scheduling information corresponding to the processing request information based on a pre-built artificial intelligence-based processing analysis algorithm, a monitoring unit that calculates error information based on the measured value information and the processing scheduling information, and the It may include a display unit that displays feedback information generated based on the error information.

In addition, the monitoring unit generates time series data for the measurement value information collected for a time period equal to or longer than a preset monitoring period, and based on the time series data, the execution order between unit processes in which the actual cutting process is reflected in the machining scheduling information And it may be determined whether or not the operating condition for the cutting means is satisfied.

In addition, the display unit may display feedback information corresponding to the first warning level when the execution order does not satisfy the processing scheduling information based on a determination result of the monitoring unit.

In addition, the display unit may display feedback information corresponding to a second warning level that is more relaxed than the first warning level when the operation condition does not satisfy the processing scheduling information based on a determination result of the monitoring unit.

In addition, when the feedback information corresponding to the first warning level or the feedback information corresponding to the second warning level is displayed, the intelligent cutting processing control apparatus according to an exemplary embodiment of the present application is provided with measured value information obtained for the corresponding cutting process. It may include a storage unit for storing.

The above-described problem solving means are merely exemplary and should not be construed as limiting the present application. In addition to the above-described exemplary embodiments, additional embodiments may exist in the drawings and detailed description of the invention.

According to the above-described problem solving means of the present application, processing scheduling information is automatically generated and provided to the operator based on the shape of the target workpiece, and based on the measured value obtained in the actual process, it conforms to the previously established processing scheduling information for the process. It is possible to provide an intelligent cutting processing device and method capable of monitoring whether the actual process is performed.

However, the effect obtainable in the present application is not limited to the above-described effects, and other effects may exist.

1 is a schematic configuration diagram of a cutting processing system according to an embodiment of the present application.
2 is a conceptual diagram illustrating drawing data including shape information applied to an intelligent cutting processing control apparatus according to an exemplary embodiment of the present disclosure.
3 is a conceptual diagram illustrating that the intelligent cutting processing control device according to an exemplary embodiment of the present disclosure determines an execution order of a plurality of unit processes included in a cutting processing process.
4 is a schematic configuration diagram of an intelligent cutting processing control device according to an embodiment of the present application.
5 is an operation flowchart of an intelligent cutting processing method performed by the intelligent cutting processing control device according to an embodiment of the present application.
6 is a detailed operation flowchart for the step of generating processing scheduling information.

Hereinafter, embodiments of the present application will be described in detail with reference to the accompanying drawings so that those of ordinary skill in the art may easily implement the present application. However, the present application may be implemented in various different forms and is not limited to the embodiments described herein. In the drawings, parts not related to the description are omitted in order to clearly describe the present application, and similar reference numerals are attached to similar parts throughout the specification.

Throughout the present specification, when a part is said to be "connected" with another part, it is not only the case that it is "directly connected", but also "electrically connected" or "indirectly connected" with another element interposed therebetween. "Including the case.

Throughout the present specification, when a member is positioned "on", "upper", "upper", "under", "lower", and "lower" of another member, this means that a member is located on another member. This includes not only the case where they are in contact but also the case where another member exists between the two members.

In the entire specification of the present application, when a certain part "includes" a certain component, it means that other components may be further included rather than excluding other components unless specifically stated to the contrary.

The present application relates to an intelligent cutting processing system. For example, the present application relates to an intelligent cutting process control device and method.

1 is a schematic configuration diagram of a cutting processing system according to an embodiment of the present application.

Referring to Figure 1, the cutting processing system 100 according to an embodiment of the present application, the intelligent cutting processing control device 100 according to an embodiment of the present application (hereinafter referred to as'cutting processing control device 100). .) and cutting means 200 may be included.

The cutting process control device 100 and the cutting means 200 may communicate with each other through the network 20. The network 20 refers to a connection structure in which information exchange is possible between respective nodes such as terminals and servers. An example of such a network 20 includes a 3GPP (3rd Generation Partnership Project) network, and an LTE (Long Term Evolution) network, 5G network, WIMAX (World Interoperability for Microwave Access) network, Internet, LAN (Local Area Network), Wireless LAN (Wireless Local Area Network), WAN (Wide Area Network), PAN (Personal Area) Network), a wifi network, a Bluetooth network, a satellite broadcasting network, an analog broadcasting network, and a Digital Multimedia Broadcasting (DMB) network, but are not limited thereto.

In addition, according to an embodiment of the present application, the cutting processing control device 100 may be mounted (installed) on a user terminal (not shown) in connection with a dedicated application or program for monitoring and controlling the cutting processing process. . As another example, the cutting process control device 100 is a server device that receives a control input for a cutting process from a user terminal (not shown) and provides monitoring information on the ongoing cutting process to a user terminal (not shown) It can be implemented in a form.

User terminals (not shown) include, for example, smartphones, smart pads, tablet PCs, PCS (Personal Communication System), GSM (Global System for Mobile communication), PDC (Personal Digital Cellular), PHS (Personal Handyphone System), PDA (Personal Digital Assistant), IMT (International Mobile Telecommunication)-2000, CDMA (Code Division Multiple Access)-2000, W-CDMA (W-Code Division Multiple Access), Wibro (Wireless Broadband Internet) It can be any kind of wireless communication device, such as a terminal.

The cutting processing control apparatus 100 may receive processing request information including shape information of a target workpiece. According to an exemplary embodiment of the present disclosure, the processing request information including shape information of the target workpiece may include drawing data 1 capable of expressing the shape information of the target workpiece in three dimensions.

In addition, the cutting processing control apparatus 100 may generate processing scheduling information corresponding to the received processing request information based on a processing analysis algorithm based on artificial intelligence that is built in advance.

Here, the pre-built artificial intelligence-based processing analysis algorithm, when drawing data (1) including shape information on at least one of the target workpiece and the workpiece is input, targets the workpiece in response to the drawing data (1). In order to be processed into a workpiece, the area to be cut is identified, the machining difficulty of the area to be cut is calculated based on the location, shape, area, volume, etc. of the area to be cut, and the machining difficulty must be cut in consideration of the calculated machining difficulty. It may be learned in advance to output the order of the unit processes derived for each area and the operation condition of the cutting means 200 required in the unit process.

According to an exemplary embodiment of the present disclosure, the cutting processing control apparatus 100 may generate processing scheduling information through a supervised learning-based algorithm that receives drawing data 1 as an input.

For reference, supervised learning may refer to a method of learning in a state in which a label, which is an explicit correct answer information for data, is given. In the present application, various supervised learning algorithm models that have been previously known or developed in the future may be applied.

Specifically, according to the exemplary embodiment of the present disclosure, the apparatus 100 for controlling a cutting process may determine a plurality of unit processes to be included in the cutting process based on shape information of the target workpiece.

2 is a conceptual diagram illustrating drawing data including shape information applied to an intelligent cutting processing control apparatus according to an exemplary embodiment of the present disclosure.

Specifically, Figure 2 (a) is drawing data (1) including three-dimensional shape information of the target workpiece, and Figure 2 (b) illustrates the shape information of the virtual workpiece corresponding to the shape information of the target workpiece. It is a diagram shown as an example.

Referring to FIG. 2B, the apparatus 100 for controlling cutting processing may generate a virtual workpiece corresponding to shape information of the target workpiece. For example, the cutting processing control device 100 is formed to surround (cover) the three-dimensional shape of the target workpiece, and roughly correspond to the shape of the target workpiece, and the local characteristics of the target workpiece are not reflected in a rough form. You can create virtual workpieces. However, it is not limited thereto, and when the actual shape of the workpiece corresponding to the target workpiece is determined in advance, the cutting processing control device 100 may operate to generate a virtual workpiece corresponding to the actual shape of the workpiece. have.

In addition, according to an exemplary embodiment of the present disclosure, the apparatus 100 for controlling cutting processing may determine an execution order of the determined plurality of unit processes.

3 is a conceptual diagram illustrating that the intelligent cutting processing control device according to an exemplary embodiment of the present disclosure determines an execution order of a plurality of unit processes included in a cutting processing process.

3, the cutting process control device 100 is based on a virtual simulation for processing a virtual workpiece that is primarily roughly generated to correspond to the shape information of the target workpiece to be closer to the shape of the target workpiece. The order of performing a plurality of unit processes to be included in the cutting process may be determined.

Specifically, referring to FIG. 3, in the process of processing the virtual workpiece shown in FIG. 2(b) to match the shape of the target workpiece shown in FIG. 2(a), In order to shape the 4 pillars of the required upper end, each of the processes of cutting the areas ① to ④ can be determined as a unit process. For reference, the numbering of areas ① to ④ may mean the order of unit processes. In other words, it may be that the order between unit processes is determined so that, after performing the cutting process on the ① area in Fig. 3, in sequence ② cutting on the area, ③ cutting on the area, and ④ cutting on the area are performed. have.

In this regard, since the shape of the virtual workpiece shown in FIG. 3 is a cylindrical shape that is generally symmetric with respect to the central axis, it may have the same degree of difficulty in area processing ① to ④, but depending on the shape of the object to which the present application is applied. , The degree of difficulty required to process (cutting) each area may be different from each other. Therefore, the cutting processing control device 100 considers location information, area information, volume information, etc. of an area to be cut in order for the shape of the virtual workpiece generated based on the shape information of the target workpiece to be processed in conformity with the target workpiece. Thus, the difficulty level of each area to be cut may be evaluated, and an order between unit processes may be determined based on the calculated difficulty level. In particular, the cutting process control device 100 considers the movement line (movement displacement, etc.) of the cutting means 200, which is inferred based on the calculated degree of difficulty and the positional proximity of each area to be cut. Can act to determine.

In addition, according to the exemplary embodiment of the present disclosure, the cutting processing control apparatus 100 may determine an operating condition of the cutting means 200 corresponding to each of a plurality of unit processes.

According to an embodiment of the present application, the operating condition of the cutting means 200 is a relative initial position (arrangement) of the cutting means 200 with respect to the workpiece, and the rotational speed of the spindle rotating the cutting blade in the cutting means 200 , Motor rotation speed, power information for rotating the cutting blade, and the moving line of the cutting blade may be widely included.

In summary, the machining scheduling information generated by the cutting process control device 100 is the type of cutting process required to match the shape of the target workpiece with the generated virtual workpiece corresponding to the shape of the target workpiece, List the number, etc., determine the order between the unit processes in the list in consideration of the difficulty of each unit process and the movement of the cutting means 200, and include the operating conditions of the cutting means 200 corresponding to each of the unit processes. It may be created to be.

In addition, the cutting processing control device 100 is generated in response to processing scheduling information determined to include an operation condition of the cutting means 200 corresponding to each of the plurality of unit processes and the execution order of the plurality of unit processes and the plurality of unit processes. The resulting virtual cutting process simulation data can be overlaid on the drawing data 1 and displayed.

According to an embodiment of the present application, the virtual cutting process simulation data refers to a shape in which the shape of the virtual workpiece generated to correspond to the shape of the target workpiece changes as a unit process according to the virtual scheduling information is sequentially applied. It may be expressed so that the (worker) can visually check before the actual work. For example, in the virtual cutting process simulation data, from the shape of the virtual workpiece, which is primarily generated to correspond to the shape of the target workpiece, the unit processes according to the virtual scheduling information are each performed from the first unit process to the Nth process according to the execution order. Assuming that the unit process is included, the shape of the virtual workpiece changed by applying the first unit process, and the shape of the virtual workpiece changed by applying to the second unit process may be sequentially displayed.

In this regard, the cutting processing control device 100 receives a user input for selecting a unit process that the user (worker, etc.) wants to check, and the shape of the virtual workpiece in a state in which a unit process corresponding to the user input is performed. Can be operated to display as virtual cutting process simulation data.

In addition, according to an embodiment of the present application, the cutting process control device 100 overlays the generated virtual cutting process simulation data on the drawing data 1 by projecting a two-dimensional shape projected based on at least one projection direction. Can be expressed.

In addition, the cutting process control apparatus 100 may receive information on a measurement value in a cutting process performed to process a workpiece into a target workpiece.

According to an embodiment of the present application, the cutting process control device 100 uses the cutting means 200 and the acoustic information that can be generated while the cutting process is being sensed by an acoustic sensor (not shown) disposed adjacent to the cutting means 200 as measured value information. You can receive it.

In addition, according to an exemplary embodiment of the present disclosure, the cutting processing control apparatus 100 may receive current measurement information associated with driving of the cutting means 200 as measurement value information. For example, the current measurement information may be measured in connection with a motor that provides power to rotate the cutting blade of the cutting means 200.

In addition, according to an embodiment of the present application, the cutting processing control apparatus 100 may receive rotation information associated with the rotation of the cutting means 200 as measured value information. For example, the rotation information may mean rotation information of a cutting blade of the cutting means 200 or a spindle associated with the cutting blade. For example, the rotation information may be rotation angular velocity information.

In addition, according to an exemplary embodiment of the present disclosure, the apparatus 100 for controlling cutting processing may receive image information on the cutting means 200 as measured value information. For example, the image information may be obtained by a camera module (not shown) in which a photographing view is determined to include a cutting blade of the cutting means 200 and an area of a workpiece cut by the cutting blade.

In other words, the cutting process control apparatus 100 may receive (obtain) at least one of acoustic information, current measurement information, rotation information, and image information as measurement value information.

In addition, the cutting processing control apparatus 100 may calculate error information based on the received measurement information and processing scheduling information generated in advance. Specifically, the cutting processing control apparatus 100 according to an exemplary embodiment of the present disclosure may generate time series data on the measurement value information collected during a time period equal to or longer than a preset monitoring period. In addition, the cutting processing control device 100 may determine whether the actual cutting process actually performed based on the time series data satisfies the execution order and operating conditions reflected in the processing scheduling information, and generates error information based on the determination result. have.

According to an embodiment of the present application, the cutting processing control apparatus 100 may determine processing scheduling information based on the similarity between the actual time series data for the received measurement information and the virtual time series data generated in advance to correspond to the previously generated processing scheduling information. It can be determined whether the actual process is performed accordingly.

Exemplarily, the cutting processing control device 100 predicts time series data after the time period in which the measured value information is secured by applying a deep learning-based time series analysis algorithm to actual time series data for the received measurement value information, and predicts the predicted time series data. May be comparing the similarity of the virtual time series data generated in advance with a pattern in a corresponding time zone.

According to an embodiment of the present application, the cutting processing control device 100 is a deep learning-based time series analysis algorithm applied to time series data for measured value information, and may utilize at least one of an LSTM algorithm, an attention algorithm, a Transformer algorithm, and a BERT algorithm. have.

Specifically, the LSTM (Long-Short Term Memory) algorithm is one of the artificial recursive neural network (RNN) architectures used in the field of deep learning, and unlike feed forward neural networks, there is a feedback connection. Therefore, according to the LSTM algorithm, it is possible to learn and process not only a single data point but also an entire data sequence.

This LSTM algorithm is suitable for classifying, processing, and predicting predictions based on time series data, and LSTM has the advantage of solving the Vanishing Gradient problem that may occur in training through traditional RNNs.

The attention algorithm is a technique that improves the performance of the model by making the deep learning model pay attention to a specific vector, and can be understood as an algorithm implemented to focus only the important part of the model in the learning process. In other words, the Attention algorithm allows the decoder to focus different parts of the input sequence at each step when generating the output, and instead of encoding it into a single fixed context vector, it creates a context vector for each step of the output. You can learn how to do it. This can be understood as determining which part of the model to focus on in subsequent learning based on the input sequence and the result generated so far, and determining the part to focus on can be performed through Softmax.

The Transformer algorithm may include an encoder-decoder structure that receives an input sequence from an encoder and outputs an output sequence from a decoder, like a conventional seq2seq architecture. However, unlike the conventional seq2seq architecture, a plurality of encoders and decoders may be provided. In addition, the above-described attention algorithm determines which of the hidden states of the encoder to focus on and uses it for decoder calculation, whereas the Transformer algorithm does not connect the encoder and the decoder and uses the attention algorithm only internally, and is not an RNN such as LSTM or GRU. It has the characteristic that it consists only of attention neural network.

The BERT (Bidirectional Encoder Representations from Transformers) algorithm is an algorithm that performs transfer learning with labeled data having a specific task after pre-training a model with large unlabeled data. The architecture of BERT uses some of the Transformer algorithm described above, but transfer learning can be made easy by partially different architectures of the pre-training stage and the fine-tuning stage. It is recommended to use only the encoder part of the structure of the transformer algorithm described above. It is characterized.

In addition, the cutting processing control apparatus 100 may generate feedback information based on the generated error information. In addition, the cutting processing control device 100 may display the generated feedback information through a display. Here, the display on which the feedback information is expressed may be provided in a form included in the cutting processing control device 100 as described later, but is not limited thereto, and is provided separately from the cutting processing control device 100. (For example, a form mounted on a user terminal (not shown), etc.) By receiving feedback information from the cutting process control device 100 through the network 20, the received feedback information is sent to the cutting process control device 100 It may be provided to output independently. As another example, the display may be installed with respect to the cutting means 200. As another example, the display on which the feedback information is displayed may be provided in both the cutting process control device 100 and the cutting means 200.

Exemplarily, when the display on which the feedback information is displayed is provided in both the cutting process control device 100 and the cutting means 200, among the resolution and standard (size) of the first display provided in the cutting process control device 100 The expression type of the feedback information in the cutting process control device 100 is determined based on at least one, and the cutting means 200 is based on at least one of the resolution and the standard (size) of the second display provided in the cutting means 200. ), the expression type of the feedback information may be determined.

In addition, according to an embodiment of the present application, the cutting process control device 100 determines whether the actual cutting process satisfies the execution order reflected in the machining scheduling information, if the execution order does not meet the machining scheduling information, Feedback information corresponding to the first warning level may be displayed.

In addition, according to an embodiment of the present application, the cutting process control apparatus 100 determines whether the actual cutting process satisfies the operation condition reflected in the machining scheduling information, if the operation condition does not meet the machining scheduling information, Feedback information corresponding to the second warning level, which is more relaxed than the first warning level, may be displayed.

In addition, according to an embodiment of the present application, as a result of determining whether the actual cutting process corresponds to the machining scheduling information, the cutting process control device 100 generates an execution order and operating conditions in the actual cutting process in advance. When it is determined that the processed scheduling information is satisfied, feedback information corresponding to the normal level may be displayed.

For example, the feedback information may be output as sound information. In this regard, the feedback information corresponding to the normal level may correspond to a state in which no sound is output. In addition, the first warning level and the second warning level are sounds corresponding to an alarm sound, a beep sound, etc., but the sound corresponding to the first warning level may be recognized as having higher urgency than the sound corresponding to the second warning level. It may be selected as a sound that is present.

As another example, the feedback information may be output as visual information. In this regard, the feedback information corresponding to the normal level may correspond to a light source (eg, an LED device, etc.) blinking in green. In addition, the first warning level and the second warning level may correspond to light sources blinking in red and yellow, respectively. As another example, the feedback information is a guide text such as'Operation sequence and work conditions are normal' corresponding to the normal level, guidance text such as'The work order is not correct' corresponding to the first warning level, and the second information. It may be output in the form of a guide text such as'The working condition is not correct' corresponding to the warning level. In this case, the feedback information output in the form of the guide text may include a sound corresponding to the corresponding guide text together.

In addition, when the feedback information corresponding to the first warning level or the feedback information corresponding to the second warning level is displayed, the cutting processing control apparatus 100 may store measured value information obtained for a corresponding actual cutting processing process. Accordingly, the cutting process control device 100 stores measurement value information when the cutting process is out of a process sequence or process execution condition reflected in the previously generated machining scheduling information, and uses the stored measurement value information to generate machining scheduling information. Learning can be made so that the processing analysis algorithm optimizes and generates processing scheduling information in a form that is more suitable for actual processing convenience by providing it to a processing analysis algorithm based on artificial intelligence that is built in advance.

4 is a schematic configuration diagram of an intelligent cutting processing control device according to an embodiment of the present application.

Referring to FIG. 4, the cutting processing control apparatus 100 may include an input unit 110, a simulation unit 120, a monitoring unit 130, a display unit 140, and a storage unit 150.

The input unit 110 may receive processing request information including shape information of the target workpiece.

In addition, the input unit 110 may receive measurement value information in a cutting process performed to process a workpiece into a target workpiece.

The simulation unit 120 may generate processing scheduling information corresponding to the processing request information based on a processing analysis algorithm based on artificial intelligence that is built in advance.

The monitoring unit 130 may calculate error information based on the received measurement information and pre-generated processing scheduling information.

Specifically, the monitoring unit 130 may generate time series data on the measured value information collected during a time period equal to or longer than a preset monitoring period. In addition, the monitoring unit 130 may determine whether the actual cutting process satisfies the execution order between unit processes reflected in the machining scheduling information and the operating conditions for the cutting means 200 based on the generated time series data. have.

The display unit 140 may display feedback information generated based on the error information.

Specifically, the display unit 140 displays the feedback information corresponding to the first warning level when the execution order of the actual process performed based on the determination result of the monitoring unit 130 does not satisfy the previously generated processing scheduling information. can do. In addition, if the operation condition of the process actually performed based on the determination result of the monitoring unit 130 does not meet the previously generated processing scheduling information, the display unit 140 is Corresponding feedback information can be displayed.

When the feedback information corresponding to the first warning level or the feedback information corresponding to the second warning level is displayed through the display unit 140, the storage unit 150 may store measurement information obtained for a corresponding cutting process. have.

Hereinafter, based on the details described above, the operation flow of the present application will be briefly described.

5 is an operation flowchart of an intelligent cutting processing method performed by the intelligent cutting processing control device according to an embodiment of the present application.

The intelligent cutting processing method shown in FIG. 5 may be performed by the cutting processing control device 100 described above. Therefore, even if omitted below, the description of the cutting processing control device 100 may be equally applied to the description of the intelligent cutting processing method.

Referring to FIG. 5, in step S11, the input unit 110 may receive processing request information including shape information of a target workpiece.

Next, in step S12, the simulation unit 120 may generate processing scheduling information corresponding to the received processing request information based on an artificial intelligence-based processing analysis algorithm built in advance.

Next, in step S13, the input unit 110 may receive measurement value information in an actual cutting process performed to process the workpiece into a target workpiece.

Next, in step S14, the monitoring unit 130 may calculate error information based on the measurement value information and processing scheduling information.

In addition, in step S14, the monitoring unit 130 may generate time series data for measurement information collected during a time longer than a preset monitoring period.

In addition, in step S14, the monitoring unit 130 may determine whether the actually performed cutting process satisfies the execution order and operating conditions reflected in the previously generated machining scheduling information based on the generated time series data.

Next, in step S15, the monitoring unit 130 may generate feedback information based on the error information calculated in step S14. In addition, in step S15, the display unit 140 may display the generated feedback information.

In addition, in step S15, the display unit 140 may display feedback information corresponding to the first warning level if the actual execution order does not satisfy the processing scheduling information as a result of determining the error information calculated in step S14. .

In addition, in step S15, when the determination result of the error information calculated in step S14, if the actual operating condition does not satisfy the processing scheduling information, the display unit 140 corresponds to the second warning level, which is more relaxed than the first warning level. Feedback information can be expressed.

In addition, in step S15, when the determination result of the error information calculated in step S14, the actual execution order and actual operating conditions satisfy the processing scheduling information, the display unit 140 may display feedback information corresponding to the normal level. have.

In the above description, steps S11 to S15 may be further divided into additional steps or may be combined into fewer steps, depending on the embodiment of the present application. In addition, some steps may be omitted as necessary, or the order between steps may be changed.

6 is a detailed operation flowchart for the step of generating processing scheduling information.

The step of generating the processing scheduling information shown in FIG. 6 may be performed by the cutting processing control apparatus 100 described above. Therefore, even if the contents are omitted below, the contents described with respect to the cutting processing control apparatus 100 may be equally applied to the description of FIG. 6.

Referring to FIG. 6, in step S121, the simulation unit 120 may determine a plurality of unit processes to be included in the cutting process based on shape information of the target workpiece.

Next, in step S122, the simulation unit 120 may determine an execution order of the determined plurality of unit processes.

Next, in step S123, the simulation unit 120 may determine an operating condition of the cutting means corresponding to each of the plurality of unit processes.

In the above description, steps S121 to S123 may be further divided into additional steps or may be combined into fewer steps, according to an embodiment of the present disclosure. In addition, some steps may be omitted as necessary, or the order between steps may be changed.

The intelligent cutting processing method according to an exemplary embodiment of the present disclosure may be implemented in the form of a program command that can be executed through various computer means and recorded in a computer-readable medium. The computer-readable medium may include program instructions, data files, data structures, and the like alone or in combination. The program instructions recorded on the medium may be specially designed and configured for the present invention, or may be known and usable to those skilled in computer software. Examples of computer-readable recording media include magnetic media such as hard disks, floppy disks, and magnetic tapes, optical media such as CD-ROMs and DVDs, and magnetic media such as floptical disks. -A hardware device specially configured to store and execute program instructions such as magneto-optical media, and ROM, RAM, flash memory, and the like. Examples of program instructions include not only machine language codes such as those produced by a compiler, but also high-level language codes that can be executed by a computer using an interpreter or the like. The hardware device described above may be configured to operate as one or more software modules to perform the operation of the present invention, and vice versa.

In addition, the above-described intelligent cutting processing method can also be implemented in the form of a computer program or application executed by a computer stored in a recording medium.

The foregoing description of the present application is for illustrative purposes only, and those of ordinary skill in the art to which the present application pertains will be able to understand that it can be easily modified into other specific forms without changing the technical spirit or essential features of the present application. Therefore, it should be understood that the embodiments described above are illustrative and non-limiting in all respects. For example, each component described as a single type may be implemented in a distributed manner, and similarly, components described as being distributed may also be implemented in a combined form.

The scope of the present application is indicated by the claims to be described later rather than the detailed description, and all changes or modified forms derived from the meaning and scope of the claims and their equivalent concepts should be interpreted as being included in the scope of the present application.

10: cutting processing system
100: intelligent cutting processing control device
110: input unit
120: simulation unit
130: monitoring unit
140: display unit
150: storage unit
200: cutting means
20: network
1: drawing data

Claims (12)

In the intelligent cutting processing method performed by the intelligent cutting processing control device,
Receiving, by an input unit, processing request information including shape information of the target workpiece;
Generating processing scheduling information corresponding to the processing request information based on a processing analysis algorithm based on artificial intelligence built in advance by a simulation unit;
Receiving, by the input unit, measurement value information in a cutting process performed to process a workpiece into the target workpiece;
Calculating error information based on the measured value information and the processing scheduling information by a monitoring unit; And
Displaying feedback information generated based on the error information by a display unit,
Including,
The step of generating the processing scheduling information,
Determining a plurality of unit processes to be included in the cutting process based on the shape information;
Determining an execution order of the plurality of unit processes based on a processing difficulty of each of the unit processes evaluated in consideration of location information, area information, and volume information of a cutting area corresponding to each of the plurality of unit processes; And
Determining an operating condition of the cutting means corresponding to each of the plurality of unit processes,
Including,
The step of calculating the error information,
Generating time series data on the measured value information collected during a time period greater than or equal to a preset monitoring period; And
Whether the cutting process actually performed based on the similarity between the time series data and the virtual time series data generated in advance to correspond to the machining scheduling information satisfies the order of execution between the unit processes reflected in the machining scheduling information and an operating condition for the cutting means The step of judging,
Including,
The step of expressing the feedback information,
As a result of the determination, if the execution order does not satisfy the processing scheduling information, feedback information corresponding to the first warning level is displayed, and
As a result of the determination, if the operation condition does not satisfy the machining scheduling information, feedback information corresponding to a second warning level that is more relaxed than the first warning level is displayed. delete The method of claim 1,
The processing request information includes drawing data representing the shape information in three dimensions,
After the step of generating the processing scheduling information,
Displaying, by a display unit, the virtual cutting processing simulation data generated in response to the processing scheduling information by overlaying it on the drawing data,
That further comprises a cutting method. The method of claim 3,
The step of overlaying and expressing,
Expressing a two-dimensional shape projected based on at least one projection direction of the simulation data,
That containing, cutting processing method. delete delete The method of claim 1,
The step of expressing the feedback information,
As a result of the determination, when the execution order and the operation condition satisfy the machining scheduling information, feedback information corresponding to a normal level is displayed. The method of claim 1,
In the step of displaying the feedback information, when the feedback information corresponding to the first warning level or the feedback information corresponding to the second warning level is displayed, storing the measured value information obtained for the corresponding cutting process by the storage unit ,
That further comprises a cutting method. In the intelligent cutting processing control device,
An input unit for receiving processing request information including shape information of a target workpiece and measurement value information in a cutting process performed to process a workpiece into the target workpiece;
A simulation unit that generates processing scheduling information corresponding to the processing request information based on a processing analysis algorithm based on artificial intelligence built in advance;
A monitoring unit that calculates error information based on the measured value information and the processing scheduling information; And
A display unit that displays feedback information generated based on the error information,
Including,
The simulation unit,
Based on the shape information, a plurality of unit processes to be included in the cutting process are determined, and each of the unit processes evaluated in consideration of location information, area information, and volume information of a cutting area corresponding to each of the plurality of unit processes Determining an execution order of the plurality of unit processes based on the processing difficulty, determining an operating condition of the cutting means corresponding to each of the plurality of unit processes,
The monitoring unit,
Time series data on the measured value information collected during a time period greater than or equal to a preset monitoring period is generated, and the actual cutting process is performed based on the similarity between the time series data and the virtual time series data generated in advance to correspond to the machining scheduling information. Determine whether the execution order between unit processes reflected in the scheduling information and operation conditions for the cutting means are satisfied,
The display unit,
If the execution order does not satisfy the processing scheduling information based on the determination result of the monitoring unit, feedback information corresponding to the first warning level is displayed, and
If the operation condition does not satisfy the processing scheduling information based on a determination result of the monitoring unit, feedback information corresponding to a second warning level that is more relaxed than the first warning level is displayed. delete delete The method of claim 9,
When the feedback information corresponding to the first warning level or the feedback information corresponding to the second warning level is displayed, a storage unit that stores measurement information obtained for a corresponding cutting process,
That further comprises a cutting process control device.

Images