How can CNC machine tool machining accuracy be monitored online?

As one of the core equipment of modern manufacturing, CNC machine tools play a vital role in the field of industrial manufacturing.

As product designs tend to be more complex and diversified, machine tool machining accuracy has become a key factor affecting production efficiency and product quality.

High-precision machining can enhance product market competitiveness, effectively reduce production costs, and thus improve enterprises’ economic efficiency.

However, the previous practice of relying on offline inspection to monitor machining accuracy has limitations. It cannot instantly identify and correct potential problems in the machining process. In view of this, the development of efficient online monitoring technology has become particularly urgent.

CNC machine tool machining accuracy online monitoring principle

Resistive strain gauge principle of operation

Sensors designed based on the principle of resistance change – resistance strain gauges are widely used in the field of mechanical structure stress and strain measurement.

In the application scenario of CNC machine tools, by fixing this sensor in an important position of the equipment, it is able to sense the slight deformation and then change its own resistance value.

Based on the Wheatstone bridge principle, the detected resistance change can be accurately mapped to the pressure on the workpiece during the machining process.

Due to their high sensitivity and good linearity, resistance strain gauges are ideally suited for immediate monitoring of manufacturing accuracy.

In addition, this type of sensor is easy to install and cost-effective, so it is widely used in many industrial fields.

Laser Ranging Principle

Laser ranging technology is based on the principle of time difference. It uses laser beams to measure distance accurately.

The basic principle is to transmit a laser beam to the surface of the workpiece, receive its reflected light, calculate the laser from the time of transmission to reception, and then arrive at the distance.

This technology offers unparalleled advantages in the field of CNC machine tools, especially in the pursuit of high-precision machining monitoring application scenarios.

Compared with traditional contact gauges, laser ranging provides a non-destructive means of inspection that not only avoids any form of physical damage or impact on the object being measured, but also benefits from the excellent properties inherent in lasers, such as highly high monochromaticity and coherence, which enable even subtle changes on the micron scale to be captured with precision.

Principles of Vibration and Acoustic Emission Monitoring

Vibration and acoustic emission monitoring technology can effectively assess machining accuracy and machine condition by analyzing the machine tool’s vibration patterns and acoustic emission signals during the machining process.

When the machine is in operation, any abnormal vibration or acoustic emission signals may indicate poor machining or malfunction.

Vibration sensors can capture each machine tool component’s vibration frequency, amplitude, and other information. Using spectrum analysis and other technical means, they can identify the type of potential failure, such as tool wear or machine loosening.

The acoustic emission signal can monitor the sound waves generated during the machining process in real time, and by analyzing the characteristics of the sound waves, it is possible to determine the cutting status of the material and the quality of machining.

CNC machine tool machining accuracy of online monitoring technology optimization significance

Improve production efficiency and product quality

Vibration and acoustic emission monitoring technology can effectively assess machining accuracy and equipment status by analyzing the machine tool’s vibration patterns and acoustic emission signals during the machining process.

When the machine tool is in operation, any abnormal vibration or acoustic emission signals may be processing problems or mechanical failure of the “early warning”.

Vibration sensors can collect each component’s vibration frequency, amplitude, and other relevant data. Using spectral analysis and other means, these sensors can identify problems such as tool wear or loose machine structure.

In addition, acoustic emission technology can track the acoustic changes in the machining process in real time. By analyzing these acoustic characteristics, you can further understand the material’s cutting condition and quality level.

Reduce the failure rate and maintenance costs

With the application of online monitoring technology, the processing of CNC machine tools can be tracked in real time, and data and status information can be collected and processed in a timely manner to optimize the production process.

By analyzing the instant data during machine tool operation, the staff can quickly identify potential machining process issues, such as inaccurate workpiece positioning or tool loss, and accordingly make the appropriate parameter adjustments.

This instant feedback mechanism dramatically improves productivity and reduces dwell time due to machining faults.

In addition, online monitoring strongly supports product quality assurance. Traditional offline inspection methods can only find problems after the product is manufactured, which increases the probability of defective products and wastes a lot of time and resources.

The use of online monitoring means that the quality of the product can be continuously supervised throughout the production process to ensure that it meets the expected standards, thereby improving the consistency of the finished product and the proportion of qualified.

Promote the development of intelligence and automation

Online monitoring technology can improve machining accuracy and play a vital role in promoting the development of CNC machine tools to the direction of intelligence and automation.

With the advent of Industry 4.0, intelligent manufacturing has become a mainstream trend in the development of global manufacturing.

As a key technology to achieve this goal, online monitoring technology, through integrating big data analysis, cloud computing and other cutting-edge technologies, can analyze the indicators in the production process in detail, and provide intelligent decision-making support accordingly.

With the construction of the digital production model, enterprises can realize the automatic adjustment of parameters in the manufacturing process, and then optimize the entire production process.

CNC machine tool machining accuracy of online monitoring technology development status quo

Sensor technology limitations

Although online monitoring technology plays a key role in CNC machine tool processing, but the current level of sensor technology is still facing some problems.

Firstly, the accuracy of the sensors may deteriorate as the usage time increases, thus affecting the accuracy of the collected data.

For example, under extreme conditions such as high temperatures or high humidity environments, resistance strain gauges are prone to drift phenomena, affecting the reliability of the measurement results.

Secondly, vibration and noise interference in the actual production environment are also issues that cannot be ignored. These external factors can negatively affect the sensor readings and make the data obtained inaccurate.

Data Processing and Algorithmic Challenges

The effectiveness of online monitoring technology depends not only on the sensor’s performance but also on the efficiency of data processing and algorithms. At this stage, due to the complexity of the data processing algorithms, their operation speed is relatively slow, and it is difficult to meet the demand for real-time response.

The generation and transmission of large amounts of data to the system, especially in the high-speed machining process, has imposed a considerable burden, which in turn affects overall operational efficiency.

For example, in the operation of the machine tool generates a large amount of sensor information, how to achieve rapid and accurate data analysis to instantly reflect the current machining conditions, has become a technical challenge that needs to be resolved.

System integration and compatibility issues

With the continuous development of CNC machine tools and monitoring technology, system integration and compatibility challenges have become increasingly obvious. Significant differences in interface standards and communication protocols between different manufacturers and models of CNC machine tools make seamless integration of online monitoring systems difficult.

For example, certain brands of machine tools may have unique communication protocols that make it difficult for general-purpose monitoring solutions to connect directly to them.

In addition, interoperability issues between key components such as sensors and data collection units occur, affecting the stability of the entire monitoring system and reducing its reliability.

CNC machine tool machining accuracy of online monitoring technology research

Sensor stability enhancement technology, redundancy mechanism design and fault detection

The development of advanced sensor technology is very important to enhance the accuracy and stability of the online monitoring system.

Enterprises can introduce new technical means and materials such as laser ranging, fiber optic sensing, and so on, in order to greatly improve the accuracy of data collection.

These innovative sensors are not only more sensitive, but also able to maintain excellent performance under extreme conditions.

Furthermore, the drift and accuracy degradation that occurs with conventional devices after long periods of operation can be improved through temperature compensation and environmental design to ensure that they remain stable in a variety of operating environments.

In addition, regular calibration of the sensors to ensure that they are in a long-term high-precision working condition is also an effective strategy to improve the reliability of the entire monitoring network. Finally, the design of a redundancy mechanism is also indispensable.

When a sensor fails, redundancy mechanisms are designed to ensure that the system automatically switches to a backup unit, thus ensuring the continuity and accuracy of monitoring activities.

For example, as a reference, DMG MORI of Germany, one of the world’s largest machine tool manufacturers, has introduced fiber optic sensor technology in CNC machine tool processing.

This technology uses new materials and processes to significantly enhance the sensor’s resistance to external interference and adaptability to environmental changes.

In addition, the company developed the “DMG MORI 5-Axis” system, which utilizes high-precision laser distance measurement technology to provide instant monitoring of accuracy during machining.

This includes deploying multiple redundant sensors within the machine. In the event of a sensor failure, the system automatically switches to the backup sensor, thus ensuring the continuity and accuracy of the monitoring data stream.

In addition, in order to maintain the high performance of these sensors over time, DMG MORI has established a regular calibration program as a way to guarantee the proper operation of the deployment.

Building a real-time monitoring system with data caching and pre-processing in conjunction with data algorithms

Developing an efficient real-time monitoring system is essential for improving the machining accuracy of CNC machine tools. The system includes data collection, transmission, analysis and feedback to ensure that the monitoring process is efficient and accurate.

In this regard, the use of adaptive filtering technology and machine learning algorithms can significantly improve the speed and accuracy of data processing.

The algorithm specially designed for monitoring the machining accuracy of CNC machine tools can further optimize the data analysis results and reduce the influence of external noise on the measurement results.

Furthermore, by constructing a distributed system architecture and dispersing the computational tasks to be executed on different nodes, the system’s concurrent processing capability can be greatly enhanced to meet the data processing requirements during rapid machining.

In addition, to strengthen the system’s immediate response characteristics, a buffering mechanism in the data acquisition stage allows preliminary cleaning of the raw signals in advance, such as noise removal and filtering operations. This not only reduces the amount of data to be transmitted but also speeds up the system’s response.

Taking Japan’s Mitsubishi Electric as a reference, Mitsubishi Electric has deployed a real-time online monitoring system in CNC machine tool machining. This system effectively improves the speed and accuracy of data processing by utilizing adaptive filtering technology and machine learning algorithms.

Mitsubishi’s “MELFA Robot” system not only realizes real-time data acquisition, but also designs special algorithms for monitoring the machining accuracy of CNC machine tools.

During operation, to optimize data flow management, Mitsubishi introduced a caching mechanism at the acquisition stage and carried out preliminary cleaning of the acquired basic information, such as filtering and noise reduction, thus reducing the amount of information to be transmitted and accelerating response speed.

In addition, the company has adopted a distributed architecture design that allows different computing tasks to be assigned to multiple nodes in the network for execution, further enhancing the entire system’s parallel processing capability.

Promote standardization and modular design to build an open monitoring platform

In the field of CNC machine tool machining accuracy monitoring systems, implementing standardization and a modular design concept is one key method to enhance system compatibility and improve integration efficiency.

Establishing consistent interface standards and protocol specifications can simplify the connection process between different brands and models of CNC machine tools and monitoring systems.

This not only reduces the time required for system integration, but also significantly reduces the frequency of problems caused by interface mismatches.

In addition, rigorous compatibility testing in the early stages of system integration is conducive to detecting and dealing with possible compatibility problems in advance, thus ensuring the system’s smooth operation.

At the same time, the flexibility of the entire system can be further enhanced by equipping various types of equipment with corresponding adapters or conversion interfaces.

Finally, establishing an open monitoring platform and inviting external developers to join the system’s design and improvement process will help form an ecosystem that promotes a virtuous cycle of technological innovation and development, thus promoting the continuous progress of online monitoring technology for CNC machine tools.

The United States Haas Automation (Haas Automation) has made remarkable progress in standardizing and modularizing the design of CNC machine tool machining accuracy monitoring systems.

Haas Automation has developed a unified interface standard and protocol specification to facilitate the seamless integration of different types of machine tools and monitoring systems.

To accomplish this, the company performs rigorous compatibility testing to identify and resolve any mismatches.

At the same time, Haas Automation developed a series of adapters and conversion interfaces to ensure stable system operation by building an open monitoring platform.

In the development process, Haas Automation actively invites external developers to participate in developing and improving the platform, thus forming an ecosystem conducive to technological progress and application expansion.

Summary

In summary, the use of online monitoring technology for CNC machine tool machining accuracy in modern manufacturing fields has become increasingly common.

With the continuous improvement of product complexity and precision requirements, traditional non-real-time detection means have been difficult to adapt to the current production requirements. Therefore, there is an urgent need to develop a more efficient online monitoring program.

However, at this stage, online monitoring technology faces several major challenges, such as sensor performance issues, data processing difficulties, and compatibility challenges encountered during system integration.

To cope with these obstacles, companies need to adopt redundancy design strategies, optimize real-time monitoring architecture, implement standardization and modular design concepts, and take a series of measures to promote the development of related technologies.