Digital twin for CNC machine tool: modeling and using strategy

CNC machine tool (CNCMT) is the mother machine of industry, which plays an important role in the coming smart manufacturing. The intelligence of CNCMT has a big significance, which will enables its self-sensing, self-prediction and self-maintenance without user concerns. In order to realize the intelligence of CNCMT, a Digital Twin (DT) modeling method for CNCMT is researched, including a multi-domain unified modeling method, a mapping method and an autonomous strategy. This paper provides a demonstration of DT modeling method for CNCMT.

The CNC machine tool is the passive executor of machining code. It cannot predict the machining accuracy during machining. If the error is found to be out of tolerance after processing, it will not only scrap the parts, but also greatly affect the processing efficiency. This phenomenon is very prominent when machining sculptured surface parts with five-axis machine tools. Therefore, this paper proposes a Digital Twin (DT) modeling method of five-axis machine tools for predicting Continuous Trajectory Contour Error (CTCE) caused by tracking errors and geometric errors. The DT consists of three parts: the Setpoints Trajectory (ST) model, the Actual Trajectory (AT) model considering tracking errors and geometric errors and the CTCE model. For a specific machine tool, according to the basic geometric information of the machine tool (tool length, kinematic chain information, etc.) and 41 geometric errors, the DT can be established. Inputting the Setpoints Positions (SPs) and the Linear Encoder Detection Positions (LEDPs), the DT can be used to predict the Tool-Tip Position Trajectory (TTPT) contour error and the Tool Orientation Trajectory (TOT) contour error. In order to verify the proposed method experimentally, the KMC400S U five-axis machine tool is selected to establish its DT by which the contour error of the S-shaped trajectory are predicted offline. Then, the DMU50 five-axis machine tool is selected to establish its DT to predict the contour error of the circular trajectory in real time. Combined with the deep motion mechanism, this paper proposes a DT modeling method for the vertical application scene of parts machining accuracy prediction, which is of great significance to developing the DT application theory and ensuring the machining accuracy of parts.

To address the problem of dynamic performance fluctuations in the feed system of CNC machine tools due to load perturbation, which in turn affects machining accuracy, this paper proposes a load prediction and compensation strategy that combines digital twin technology with the dual-drive mechanism of a data model based on a two-axis feed system. First, a digital twin mechanism model of the CNC machine tool feeding system is constructed to simulate and compensate for the load perturbation and realize the virtual mapping of the actual system behavior. Subsequently, the recursive least squares method with a variable forgetting factor combined with the GRU-gated recurrent neural network method is used to dynamically correct and compensate for the mechanism model’s load prediction and compensation results. Finally, the dynamic updating of the experimental results at the visualization level and the interaction between reality and fiction is realized by building a digital twin experimental platform. The experimental results show that the method can control the relative prediction error within 4% and the relative compensation error within 6%, which can significantly improve the quality of workpiece surface machining and the overall performance of the machine tool.

Purpose: This paper presents a multi-criteria assessment methodology to evaluate the remanufacturability of converting conventional surface grinding machines into CNC machine tools. Methodology: Conventional surface grinding machines remanufactured into CNC machine tools were analyzed and classified into five remanufacturing alternatives. A multi-criteria assessment model incorporating cost, time, accuracy, reliability, processing shape complexity, and ergonomics was developed. The importance of criteria and performance of alternatives were weighted through machine tool remanufacturing experience analysis and comparative literature review. Results: The Remanufacturability Index (RI) for remanufactured conventional surface grinding machines ranges from 0.637 to 0.999 based on the level of CNC upgrades from 2-axis to 5-axis configurations. Higher-axis remanufactured machines showed greater feasibility. Theoretical Contribution: This study provides a quantitative methodology to assess the technical, economic, and environmental feasibility of remanufacturing conventional machines into CNC machine tools. It extends the application of multi-criteria decision making to the field of machine tool remanufacturing. Practical Implications: The proposed methodology can guide small and medium-sized manufacturers in making decisions to upgrade their conventional machines to CNC through remanufacturing. It helps evaluate the benefits and risks of different upgrade configurations to support the implementation of machine tool remanufacturing in practice. Sustainable Development Goals (SDGs): SDG 9: Industry, Innovation and Infrastructure; SDG 12: Responsible Consumption and Production; SDG 8: Decent Work and Economic Growth; SDG 13: Climate Action; SDG 4: Quality Education

The CNC Machine Tools with high efficiency, high precision and high stability is the inevitable trend of the modern manufacturing industry development.This development trend puts forward the extremely high request to the CNC machine tool error compensation technology. However, the error of CNC machine tools have a variety of reasons, these errors affect each other, which leads to the inevitable error. At the high efficiency processing, we must ensure the high stability and high precision of the machine tool. Which requires the error compensation function to maintain high stability and high compensation accuracy, when the CNC machine tool is under the action of high speed and dynamic load. The rapid development of computer technology provides us with more possibilities to solve error compensation. CNC machine tool error compensation technology based on computer is an important means to improve the machining accuracy in the manufacturing industry, which reduce the error in the production process and increase the production efficiency. This paper firstly analysis the error classification and error source percentage of CNC machine tools. And then it analysis the movement error when the CNC machine tools is working. Finally, it puts forward the key technique and application of error compensation based on computer.

Smart manufacturing employs embedded systems such as CNC machine tools, programable logic controllers, automated guided vehicles, robots, digital measuring instruments, cyber-physical systems, and digital twins. These systems collectively perform high-level cognitive tasks (monitoring, understanding, deciding, and adapting) by making sense of sensor signals. When sensor signals are exchanged through the abovementioned embedded systems, a phenomenon called time latency or delay occurs. As a result, the signal at its origin (e.g., machine tools) and signal received at the receiver end (e.g., digital twin) differ. The time and frequency domain-based conventional signal processing cannot adequately address the delay-centric issues. Instead, these issues can be addressed by the delay domain, as suggested in the literature. Based on this consideration, this study first processes arbitrary signals in time, frequency, and delay domains and elucidates the significance of delay domain over time and frequency domains. Afterward, real-life signals collected while machining different materials are analyzed using frequency and delay domains to reconfirm its (the delay domain’s) significance in real-life settings. In both cases, it is found that the delay domain is more informative and reliable than the time and frequency domains when the delay is unavoidable. Moreover, the delay domain can act as a signature of a machining situation, distinguishing it (the situation) from others. Therefore, computational arrangements enabling delay domain-based signal processing must be enacted to effectively functionalize the smart manufacturing-centric embedded systems.

Modular design is one of the modern design methods used for the development of CNC machine tools, which can shorten the product design and manufacturing cycle, and improve the product quality and reliability. Module coding is one of the important steps in carrying out the modular design. Aiming at the effective application and management of the module codes in the enterprise informatization, this paper studied and developed the module coding system oriented on CNC machine tools. First, this paper analyzed the purpose of the module coding and put forward the basic rules of the module coding. Then, considering the characteristics of the modular design for CNC machine tools, this paper determined the coding scheme fit to the requirements of the machine tools enterprise. Next, based on the popular B/S structure and J2EE platform, this paper completed the function design and software development of the module coding system. At last, the development environment and example interface were introduced. The application of this module coding system in one machine tools enterprise proved that it was powerful to promote the application of modular design and the realization of the enterprise informatization.

Estimation and analysis of energy consumption for machine tool is the basis of energy efficiency improvement. The existing researches of energy model focus on the static modelling of energy consumption, and a few study of dynamic energy consumption model focus on the dynamic characteristics of operating states of machine tool, the study of dynamic characteristics of energy sources, especially multi energy sources of a CNC machine tool is scarce. Based on the characteristics of CNC machine tool(e.g. multi-energy sources, dynamically changed machining tasks and process parameters), a method for modeling the dynamic energy characteristics of multi-energy sources in CNC machine tool is proposed. The dynamic characteristics of energy consumption process of machine tool are analyzed. On this basis, the colored timed object-oriented Petri net(CTOPN) integrated with virtual component method is applied to model the dynamic energy consumption of machine tool. The CTOPN model is used to describe the dynamic characteristics of operating states of machine tool and multi-energy sources. The virtual component method is used to describe the dynamic characteristics of multi energy sources which is influenced by process parameters. The virtual component model is driven by the information of activity transitions in CTOPN model. The case study shows that the proposed energy model is effective and can provide fundamental support for dynamic energy consumption forecasting, comprehensive depiction of the energy profile and quantitative analysis of influencing factors and so on during the operation of a CNC machine tool, which has significance in practice.

Increasing the productivity of high-precision manufacturing requires efficient product inspection, for example, using integrated scanning systems on CNC machine tools (MT). However, measuring the dimensional and shape accuracy of workpieces using a touch probe (TP) on MT is negatively affected by the geometric accuracy setting of the MT, thermal stability of the MT and its surroundings, type of scanning system.The aim of this paper was to examine the possibilities of assessing the capability of touch probe measurements on MT, to define the size of the permissible controlled tolerance of the workpiece and to assess the influence of the geometric accuracy of the machine on the size of the permissible tolerance parameter of the inspected workpiece. In the presented experiments, the calculation of the TP measurement capability is based on a new approach respecting the VDA5 standard extended by the minimum tolerance (TOLmin) conformity assessment procedure according to ISO 14253-1:2017.

To cope with the increasingly competitive and demanding markets, CNC machine tool company needs a new form of development that focuses on two core competency factors: ‘process’ and ‘knowledge’. This study presents a knowledge-centric process management framework for the CNC machine tool design and development (D&D) with the integration of process and knowledge. Requirements for the framework are generated based primarily on the nature of the machine tool design practice. The proposed framework consists of process integration model, process simulation, process execution and knowledge objects management modules. Each of these modules is elaborated to support the knowledge-centric machine tool development process management. Finally, the prototype development is presented. Results of this study facilitate the knowledge integration in CNC machine tool D&D, and thus increase machine tool development capability, reduce development cycle time and cost, and ultimately speed up the effectiveness and ensure the excellent machine tool development.

As structural damage patterns and service environments become increasingly complex, digital twin (DT)-based structural health monitoring, with its unique advantages, can compensate for the limitations of data-driven methods regarding data dependency and model interpretability. However, it still faces challenges in modeling complexity, simulation accuracy, and the discrepancies between real and virtual features. This study proposes a balanced fidelity DT for structural damage monitoring based on Lamb wave multilevel feature enhancement and adaptive space interaction. Firstly, multilevel refined features are extracted from few-shot guided wave signals obtained in physical and digital space, and the adversarial synthetic balancing algorithm is proposed for feature enhancement. Additionally, the learning phase of the damage monitoring model based on the feature-mapping convolutional network is driven by virtual samples of readily accessible balanced fidelity in digital space. To reduce the feature distribution difference between the two spaces, an interactive transfer strategy is introduced to establish a shared DT feature space. The model is further updated by accurate but elusive experimental data from the physical space, making it adaptable for damage diagnosis tasks of real structures in the shared space. This method reduces the dependence on experimental data and the cost of simulations, without compromising prediction accuracy. The case study shows that the damage localization accuracy of this DT system is increased by 22.67–30.55% and the quantification accuracy by 14.23–17.11% compared to a single space. Overall, this study provides a feasible technique to enhance the accessibility and generalizability of DTs for real engineering structures.

Research on Morphology and Semantics of Industrial Design for CNC Machine Tools

In the process of thermal error modeling of machine tools, the error information is not transparent and the data characteristics are not comprehensive. The Dijkstra algorithm provides an optimization for the classical algorithm, and improving the accuracy of machine tools is an important issue in advanced manufacturing technologies. In this paper we study two methods of error avoidance and error compensation. For CNC machine tools, computer real-time error compensation technology is an economical and effective basic approach. The application of the folded Dijkstra algorithm to realize the compensation technology of the full error model of geometrical machine tool including geometric error and thermal error is put forward. The practical results show the geometric error and thermal error are compensated on 3-axis and 4-axis CNC machine tools, and the accuracy of the error model and the practicality of the compensation method.

With the continuous development and application of digital technology, CNC machine tools have become the main production equipment in the manufacturing industry. CNC machine tools are developed on the basis of the theory of CNC technology, but it is necessary to design the system with some computer-aided design to achieve automatic management. This paper analyzes the computer aided technology and numerical control technology applied in the numerical control machine tool error analysis of the practical application of, and by using multiple regression analysis method for the computation of the efficiency and quality of application of computer aided technology and numerical control technology of CNC machine tool error analysis on the efficiency and quality of data with 15% and 45% respectively than traditional CNC machine analysis, proves that computer aided technology and numerical control technology for numerical control machine tool error analysis plays an important role.

Slide level impacts the CNC machine tool performance. The deterioration of slide level will result in the torsional vibration of a feed-axis control system and lower the CNC machine tool control precision. It is necessary to investigate the rapid evaluation technology for the slide level of a CNC machine tool. In this paper, a new type of rapid evaluation method for machine tool slide level is proposed, which uses the linear scale, motor encoder, and AC servo motor current/output torque. To acquire level information, the built-in sensors test principle is profoundly investigated, and the mathematical model between the slide level and the measured data is established. In addition, two different level identification methods are comparatively analyzed. The analysis results of experiments show that it is simple, rapid, feasible, and reliable to use built-in sensors information for evaluating slide level.