Design and Development of Module Coding System Oriented on CNC Machine Tools

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.

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

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.

In this study, design and analysis of a gantry-type 5-axis CNC machine tool is presented with experimental results on a manufactured prototype. Critical points in the design of a large-scaled and heavy-duty machine tool is discussed. Moreover, FE analysis results is also presented with detailed discussion. The measurement results on structural dynamics is shown together with the FE results. Furthermore, the final performance of the machine tool is demonstrated thorough position and velocity measurements of the axes.

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.

With the continuous development of the national economy, the investment in infrastructure construction is increasing, especially for the entire society, the continuous improvement and accelerated development of its industrial level have brought huge economic development to the country. The development of industry is inseparable from the development of the real economy. Today, with the rapid development of the country, especially for the equipment manufacturing industry, earth-shaking changes have taken place. A large number of high-tech industrial enterprises have sprung up. They have left a strong mark in the history of world industrial development. The production and research of data machine tools has promoted the development of the equipment manufacturing industry. This article is based on the design of artificial intelligence-based CNC machine tools. Through a detailed introduction of its conceptual significance and related methods to strengthen the design, it aims to provide some reference and help.

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.

With the structure design and manufacture of CNC machine tool becoming more and more perfect, its geometry errors have been controlled, thermal error generated by thermal deformation of CNC machine tool is the main error, which has strongly influence on the CNC machine tool's process precision. Thermal error compensation is an important method for increasing the process precision of CNC machine tool, and the neural networks technology is the major tool in thermal error modeling and compensation. In this paper, some applications of neural networks in thermal error modeling and compensation are introduced, and they are demonstrated by examples, the results prove that researches on artificial neural networks and relative algorithms have good effects on CNC machine tool's thermal error modeling and compensation.

The highly sophisticated CNC machine tools of today, in the vast and diverse range found throughout the field of manufacturing processing, started from very humble beginnings in a number of the major industrialized countries. Some of the earliest research and development work in this field was completed in the USA and a mention will be made of the UK’s contribution to this numerical control development.

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.

Big data technology has strongly promoted the development of social productive forces, and commercial applications are continuously expanding in all walks of life. It also uses the power of Internet technology to provide strong technical support for the development of the entire industry. In terms of the production of CNC machine tools, due to the use of big data technology, CNC machine tools have been rapidly produced on a large scale, which has played an important role in the upgrading of the entire CNC machine tools and the improvement of quality and efficiency. This article takes the technology of big data acquisition bus for CNC machine tools as the topic, through researching and discussing its concept, meaning and related strategies, in order to effectively improve the production scale and reference.Chinese Library Classification number : TP23 Document Identification code : A

With the rapid development of the Internet of Things and intelligent sensing technology, the real-time collected CNC machine tool operating data presents the characteristics of massive quantity, variety, and low density. The purpose of this paper is to study the design of computer simulation operating system for CNC machine tools based on deep learning. Firstly, it summarizes the working process of CNC machine tools and CNC system, and introduces the design and implementation of the training model system module based on deep learning in this article. Secondly, the overall framework design of the virtual simulation system of CNC machine tools was launched, and the data of the simulation operating system based on SAE depth in the network training and the performance analysis of the computer simulation operating system of CNC machine tools were analyzed. The experimental results showed that with the increase of the learning rate, the error the curve becomes unstable and the convergence process becomes more and more difficult. When the learning rate reaches 0.06, the curve no longer converges.