System for optimizing power consumption relative to machining time by utilizing cutting depth data, spindle motor power data, and actual feed rate data in CNC machining, and method using same

Abstract

The present invention improves productivity and energy efficiency by performing a process with maximum feed relative to power consumption in a CNC machining process, thereby performing energy-efficient and eco-friendly machining. To this end, the present invention provides a method for utilizing a power consumption feed mapping map and an optimization function. In addition, the present invention can be utilized to configure a system capable of implementing the method.

Description

A system for optimizing power consumption relative to machining time by utilizing cutting depth data, spindle motor power data, and actual feed rate data in CNC machining, and a method using the same.

[0001] The present invention relates to a method for optimizing power consumption relative to machining time by utilizing cutting depth data, spindle motor power data, and actual feed rate data in CNC machining, and to a system using the same. Specifically, the present invention proposes a method for energy-efficient machining by utilizing data that can be obtained in a CNC machining process without performing precise measurements of cutting force and torque.

[0002] Specifically, the present invention relates to a method and system for utilizing a maximum feed rate for the same power, which is calculated by an optimization function composed of simulation data such as power data and cutting depth of a spindle motor, in order to perform an energy-efficient process in CNC equipment at a manufacturing site.

[0003] CNC machining remains a key process for flexible, low-volume, multi-variety manufacturing, maintaining its importance. However, CNC machining is also a highly energy-intensive process. Companies are increasingly developing energy-saving technologies to address environmental regulations and other challenges. Consequently, they are investing in R&D for CNC equipment components and control technologies that can improve energy efficiency.

[0004] CNC cutting processes typically analyze cutting forces during the cutting process, and based on this analysis, understand the cutting process conditions, physical phenomena, and causes of cutting. Theoretically, cutting forces and torque generated during cutting can be viewed as the pattern of physical forces generated when a single tool blade cuts a single chip. For example, a spindle with 30,000 RPM and two tool blades generates 1,000 cutting chips and torque per second. If a CNC device capable of highly precise real-time control existed, the cutting process could be analyzed and controlled at the 1 kHz speed in the example above. However, because no device with such performance exists, the physical inertia of the spindle motor and spindle axis limits the precise control of theoretical cutting forces and torque.

[0005] Korean Patent Laid-Open Publication No. 10-2016-0124333, Method and System for Predicting Power Consumption in a Milling Process, is a simulation method for predicting power consumption during milling. The method calculates power consumption by inputting cutting depth, cutting fluid volume, feed, and lubrication strategy into the prediction model. In particular, the lubrication strategy requires comprehensive milling process condition data, including cooling conditions based on the spindle motor's temperature status.

[0006] Typically, manufacturing sites use CNC equipment equipped with spindle motors capable of delivering sufficiently high torque to reliably perform cutting processes. From an energy consumption perspective, the torque of CNC equipment is sufficiently high compared to the chips being machined, so torque and the current used to control it are unnecessary. Conversely, the torque generated by the spindle motor can be used to remove even larger amounts of chips.

[0007] In CNC equipment, the spindle module, consisting of a spindle motor and bearings, provides the torque for the tool blade to cut the workpiece. To ensure the cutting of metals with high material properties and stable operation of the equipment, the spindle module is controlled and driven based on torque curves and other indicators. Servo motors, which perform precision machining through precise position control, are used in spindle modules and feed modules. When a machining load occurs, such as an increase in machining volume at a given location, the spindle servo motor driver uses feedback control to increase torque. This is achieved by increasing the current and voltage input to the servo motor.

[0008] The above machining load can be influenced by various factors. For example, if the material properties of the workpiece are strong, the machining load is large, and if the tool is subject to severe wear, the machining load increases. Furthermore, the machining load increases at machining locations with large machining volumes. Therefore, machining load data can be used to analyze the condition of the workpiece, the condition of the tool, and the machining condition at each machining section. The method of the present invention assumes that the machining process is managed in a high-quality manner, and the condition of the workpiece and tool are within the acceptable range for a high-quality machining process.

[0009] The above current and voltage are controlled with reference to the torque diagram to ensure process reliability and stable equipment operation, and thus, they are relatively continuously changing. During CNC machining of complex three-dimensional products, the machining load increases or decreases relative to the current and voltage of the previous machining position at each machining position. This can be acquired through a torque sensor or a sensor that detects the current and voltage that control torque.

[0010] This proposal proposes a method to perform machining at the maximum machining speed relative to the power consumption of the machining process by utilizing real-time data sensed by the spindle servo motor driver for the current and voltage used to control the servo motor, thereby promoting productivity and energy savings.

[0011] The purpose of the present invention is to provide a method for optimizing power consumption relative to machining time by utilizing cutting amount data, spindle motor power data, and actual feed speed data in a CNC machining process so as to maximize productivity while simultaneously minimizing machining energy, i.e., power consumption, and a system using the same.

[0012] The system for optimizing power consumption compared to processing time of the present invention to solve the above technical problems is as follows:

[0013] A machining data extraction module that extracts machining data including feed speed, current and voltage in real time at each machining position on a machining path during an actual CNC machining process; and a cutting physics simulation module that calculates physical characteristic data of cutting depth and cutting amount along the movement trajectory of a tool on the machining path; and a mapping map creation module that creates a mapping map including power consumption and feed speed by cutting depth from the machining data and cutting physical quantities obtained from the above; and

[0014] It includes a control module that controls the maximum transfer speed in proportion to the power consumption according to the above-mentioned mapping map.

[0015]

[0016] Meanwhile, the above processing data extraction module includes a step of analyzing a processing position for mapping with simulation data according to a processing path in actual CNC processing data; and a step of extracting an actual processing feed speed and power consumption corresponding to each processing section from the actual CNC processing data.

[0017] In addition, the cutting physics simulation module includes a step of segmenting a machining path from a machining position obtained from the machining data extraction module and performing a cutting physics simulation on the same; a step of calculating a cutting depth for the segmented machining section; and a step of classifying the calculated cutting depth into an appropriate range by considering a spindle motor torque diagram.

[0018] And, the control module that controls the maximum transfer speed in relation to the power consumption is

[0019] It includes a step of calling a mapping map at a starting point of a segment section on a processing path; a step of utilizing an optimization function to set a maximum feed rate relative to power consumption in the mapping map; a step of selecting a maximum feed rate relative to an existing power consumption for each segment section based on the optimization function and controlling the segment section at the selected maximum feed rate; and a step of calculating an accumulated value of a consumption strategy and a maximum feed rate up to the corresponding segment section.

[0020] The effect of the present invention is that energy-efficient processing can be performed in terms of power consumption in performing a CNC processing process by performing a processing process at the maximum feed speed relative to power consumption.

[0021] In addition, it can be used as an eco-friendly processing technology that realizes digital transformation of CNC processing and energy savings by utilizing data acquired during the processing process using existing equipment, i.e. equipment equipped with open CNC.

[0022] Additionally, it can be applied to digital twins, which are virtual models for CNC machining, and digital manufacturing systems in the future as an implementation method that utilizes simulation data and actual processing data in parallel.

[0023] The present invention provides a method with high effectiveness in the mass production processing process because it is a method applied in the mass production processing process stage rather than the simulation processing stage, and because it can implement the maximum feed speed through real-time feed speed control in actual processing, and because the actual state of the equipment is reflected by using simulation data and torque sensing data in parallel.

[0024] Figure 1 is a flowchart of an optimal transport speed control method according to the present invention.

[0025] Figure 2 is a schematic diagram of the control system according to the present invention.

[0026] Figure 3 is an example showing segmented sections and starting points of a processing section according to the present invention.

[0027] Figure 4 illustrates a graph of the optimal transport speed calculation function of the present invention.

[0028] The details related to the implementation of the present invention are described in detail below through the attached drawings and descriptions. Unless otherwise specifically defined, all terms used herein, including technical or scientific terms, have the same meaning as commonly understood by those of ordinary skill in the art to which the present invention pertains. Terms defined in commonly used dictionaries should be interpreted as having meanings consistent with their meanings within the context of the relevant technology, and shall not be interpreted in an idealized or overly formal sense unless explicitly defined herein.

[0029] A specific method for implementing the present invention is presented through Fig. 1. The present invention comprises a mapping map construction step (S 1) for constructing a mapping map between power consumption and transfer speed, and a control step (S 2) for controlling the maximum transfer speed relative to power consumption according to the mapping map.

[0030]

[0031] First, the mapping map construction step (S 1) for constructing a mapping map between the power consumption and the transfer speed of the present invention is

[0032] 1) Step of collecting processing data during actual CNC processing (S 1-1)

[0033] 2) Cutting physics simulation stage (S 1-2) and

[0034] 3) It consists of a mapping map configuration step (S 1-3).

[0035]

[0036] More specifically,

[0037] The processing data collection stage (S 1-1) is

[0038] This is a step of collecting processing data from an actual CNC processing process, and processing data including processing position, feed, current, voltage, processing load, etc. are collected in real time during processing. That is, the processing data collection step is obtained by extracting from actual processing status data including processing position, feed, current, voltage, processing load, etc. in a mass production processing process that performs high-quality CNC processing. That is, data related to the processing position and power consumption for a mapping map are extracted from the actual processing status data.

[0039]

[0040] - The step of collecting the above processing data (S 1-1) is

[0041] a) A step (S 1-1a) for calculating the machining interval to map the machining path simulation data from the actual CNC machining data; and

[0042] b) It includes a step (S 1-1b) of extracting the actual processing feed speed and power consumption from the actual CNC processing data according to the above-described calculated processing interval.

[0043]

[0044] - The above cutting physics simulation step (S 1-2) segments the machining path for machining path simulation by referring to the machining gap data extracted in ⓐ. This means calculating cutting processing-related physical quantities such as cutting depth through cutting physics-based simulation. This machining path segmentation is necessary to generate related data in the same machining section for mapping actual machining data and simulation data. In ⓑ, the cutting depth is generated in the simulation for the segmented machining section, and in ⓒ, the generated cutting depth is classified into an appropriate range by considering the spindle motor torque diagram, which has a large impact on power consumption.

[0045]

[0046] That is, the above cutting physics simulation step (S 1-2) is

[0047] a) A step of segmenting the machining path by the above machining interval and performing cutting physics simulation (S 1-2a);

[0048] b) A step (S 1-2b) of extracting cutting depth, machining position and power consumption-related data for a segmented machining section; and

[0049] c) Includes a step (S 1-2c) of classifying the calculated cutting depth into an appropriate range by considering the spindle motor torque diagram.

[0050]

[0051] - The above mapping map configuration step (S 1-3) configures a mapping map of a three-dimensional array structure including power consumption and feed rate by cutting depth classification using data obtained from the actual CNC processing data extraction step (S 1-1) and the cutting physics simulation step (S 1-2). An example of configuring a mapping map by cutting depth classification is shown in the upper right corner of Fig. 2.

[0052]

[0053] - In addition, the present invention includes a control step (S 2) for controlling the maximum transfer speed in proportion to the power consumption according to the above-mentioned mapping map.

[0054]

[0055] The present invention includes a step of calling a mapping map at each starting point of a machining path segment in S 2-1. The mapping map must be called at each starting point of a machining path segment until machining is completed. The mapping map is specifically presented in Example 1 below, with reference to FIG. 3.

[0056]

[0057] In order to select the maximum transport relative to power consumption in S 2-2, the present invention applies mapping map data to a maximum transport relative to power consumption optimization function (hereinafter referred to as the "optimization function"). The optimization function is described in detail through FIG. 3 and Example 2, and presents an optimal transport speed that simultaneously considers power consumption and transport speed.

[0058]

[0059] The present invention selects the optimal transfer to be applied in the corresponding segment section by considering the accumulated power consumption and accumulated processing time based on the above-mentioned optimization function in S 2-3.

[0060] The present invention performs control to process the segment section at the optimal transfer speed in S 2-4.

[0061] The present invention includes the power consumption, transfer speed, and processing time of the corresponding segment section in S 2-5 in the existing accumulated value, and enables monitoring of the power consumption and processing time according to the processing progress.

[0062] And, the system configuration for systematically implementing the above invention is presented in Fig. 2, and the system can be configured including data collection and utilization HW, data processing SW, etc. That is, the present invention is provided with actual CNC equipment, and extracts and acquires processing data such as power consumption and feed speed on a processing path from the actual CNC equipment. In addition, it is provided with a cutting depth calculation module that calculates the cutting depth for each segmented section after segmenting the processing path. A power consumption and feed speed mapping map is created through the processing data extracted from the actual CNC equipment and the cutting depth calculated from the cutting physics simulation, and based on this, the maximum feed speed in relation to the power consumption can be selected, and control can be performed at the maximum feed speed selected in this way.

[0063]

[0064] [Example 1]

[0065] Example 1 is described with reference to Fig. 3. First, a mapping map is acquired based on the above-described content. Next, a method for selecting the optimal feed rate for each segment of the machining path using the acquired mapping map is described.

[0066] The mapping map shown in the upper left of Fig. 3 shows an example of a power consumption and transport mapping map, and the lower left shows a segmented section set in an example processing path.

[0067]

[0068] P(i-1): i-1th segmented machining section in the machining path

[0069] P(i): the ith segmented machining section in the machining path

[0070] P(i+1): i+1th segmented machining section in the machining path

[0071] F: Transport speed

[0072] Wi: Power consumption according to tool or material condition in the same transport

[0073]

[0074] That is, the segment sections can be set continuously, such as P(i-1), P(i), P(i+1), etc. First, when the tool of the CNC device reaches the starting point of the segment section P(i-1), the previously secured mapping map is called, and the value corresponding to or closest to the maximum feed per power consumption is selected from the called mapping map through the optimization function f(E, T) defined in the function equation below. Therefore, the feed value that can process with the maximum feed per power consumption can be found in each segment section. In the example P(i-1), F1200, 4.38W corresponds to the optimal value. In the next segment section P(i), the same method is repeated, and the optimal value through f(E, T) selects a field corresponding to the feed speed F1200 while having a processing load of 4.38 power consumption, and processes the corresponding segment section P(i-1) with F1200. Next, when the starting point of segment P(i) is reached, the method performed in the previous segment is repeated. The optimal values ​​for segment P(i) are F1000 and 6.23W, respectively. Repeating in this manner allows for improved processing speed while minimizing power consumption. CNC processing is performed to simultaneously satisfy the goals of improved productivity through reduced processing time and energy savings.

[0075]

[0076] [Example 2]

[0077] <Description of the optimization function>

[0078] The optimization function f(E, T) is composed of a processing time function f_T(F) and a power consumption function f_E(F). Each processing time function f_T(F) and power consumption function f_E(F) can be nonlinearly determined by F as a function of the feed rate F. However, it can be said that the faster the feed, the shorter the processing time, but the faster the feed, the more power consumption, which is a direct proportional relationship. Considering the above correlation, functions related to power consumption and processing time are generated, respectively. The optimization function is a combination of the two functions, and weights can be used so that the user can flexibly find the optimal value depending on the optimization objective they place importance on. The optimal feed value can be found at the minimum value of the optimization function, and the feed closest to the optimal feed is searched and used in the mapping map.

[0079] The current and feed rate to be selected from the mapping map are selected through the optimization function f(E, T) as shown in Fig. 3. The optimal value through the optimization function f(E, T) is to select a field corresponding to the feed rate F1200 and a processing load of 4.38 power consumption as shown in Fig. 2, and process the corresponding segment section P(i-1) with F1200. Then, the starting point of the segment section P(i) is reached. The method performed for the previous segment section P(i-1) is repeated. In this section, the optimal values ​​through the optimization function f(E, T) are F1000 and 6.23, respectively, and the corresponding section P(i) is processed with F1000. Meanwhile, f(E, T) represents the optimization function, E represents the accumulated power consumption, and T represents the accumulated processing time.

[0080]

[0081] The above optimization function f(E, T) can calculate the optimal transport speed as shown in the graph of Fig. 4, and is explained by the following equation.

[0082] That is, the above f_T(F) is a function of the processing time (T) determined by the feed rate, and f_E(F) is a function of the power consumption (E) determined by the feed rate. And as an example, f_T(F) and f_E(F) can be expressed in a generalized manner as the functions below. Here, a, b, c, m, n, and l are arbitrary coefficients.

[0083]

[0084]

[0085] Using the above formula, an optimization function can be created as follows.

[0086]

[0087] Here, α and β are the weights for f_T(F) and f_E(F), respectively, and α+β=1.0. To obtain the optimal feed rate by giving equal weight to power consumption and processing time, set each weight to 0.5. If you want to obtain the optimal feed rate by giving weight to power consumption, set 0.5<α<1.0, and if you want to obtain the optimal feed rate by giving weight to reducing processing time, set 0.5<β<1.0.

[0088]

[0089] Therefore, when the above function f(E, T) is of minimum size, it can be said to be the optimal transfer speed that sets the maximum transfer speed compared to the power consumption proposed in the present invention.

[0090]

[0091] The present invention has industrial applicability as it enables energy-efficient processing in terms of power consumption in performing a CNC processing process by performing a processing process at the maximum feed speed relative to power consumption.

Claims

1. A machining data extraction module that extracts machining data including actual feed speed, current and voltage in real time at each machining position on a machining path during an actual CNC machining process; and a cutting physics simulation module that calculates physical characteristic data of cutting depth and cutting amount along the movement trajectory of a tool on the machining path; and a mapping map creation module that creates a mapping map including power consumption and feed speed by cutting depth from the machining data and cutting physical quantities obtained from the above; and A system for optimizing power consumption against processing time, characterized by including a control module that controls the maximum transfer speed against power consumption according to the above-mentioned mapping map.

2. In the method for optimizing power consumption using the power consumption optimization system for processing time in paragraph 1, The above processing data extraction module, A step of analyzing the machining position for mapping with simulation data according to the machining path in actual CNC machining data; A method for optimizing power consumption using a power consumption optimization system for machining time, characterized by including a step of extracting actual machining feed speed and power consumption corresponding to each machining section from the actual CNC machining data.

3. In paragraph 2, The above cutting physics simulation module is, A step of segmenting a machining path from a machining position obtained from the above machining data extraction module and performing a cutting physics simulation on the same; A step of calculating the cutting depth for the above segmented processing section; A method for optimizing power consumption against processing time, characterized by including a step of classifying the above-described calculated cutting depth into an appropriate range by considering a spindle motor torque diagram.

4. In paragraph 3, The control module that controls the maximum transfer speed in relation to the power consumption above is A step of calling a mapping map at the starting point of a segment section on a processing path; A step of utilizing the optimization function f(E, T) below to set the maximum transfer speed in relation to power consumption in the mapping map; Here, the optimization function f(E, T) is (where α and β are the weights for f_T(F) and f_E(F), respectively, and α+β=1.0) (Here, f_T(F) is a function of the processing time (T) determined by the feed rate, f_E(F) is a function of the power consumption (E) determined by the feed rate, and a, b, c, m, n, and l are arbitrary coefficients.) A step of selecting a maximum transfer speed for each segment section based on the above optimization function compared to the existing power consumption and controlling the selected maximum transfer speed; A method for optimizing power consumption against processing time, characterized by including a step of calculating accumulated values ​​of power consumption and maximum transfer speed up to the corresponding segment section.

Images