Material hybrid and sensor integrated lightweight machine tool components

Precision machinery has come a long way over the years. Factories that once relied on manpower now use machines, and this development has brought with it innumerable benefits including improvements to accuracy, repeatability, productivity and efficiency. Naturally, though, machines are imperfect in that precision of a batch of machines vary slightly. On top of that, machines experience wear and tear or even break-downs. These unpredictable events can be costly to manufacturers. This is why research to better understand factors that affect a machine's precision is important. This knowledge can be used to reduce the issues that occur with machine tools and thereby maximise the efficiency and quality of production. This is the goal of Dr Yum-Ji Chan, Department of Mechanical Engineering, National Chung Hsing University, Taiwan. His research on vibration engineering, structural dynamics and the dynamics of rotors is seeking to better understand machine tools and, in doing so, improve their performance. He believes more research is required to understand the behaviour of specific components in machine tools, and he is seeking to fill this gap in knowledge. This involves understanding the vibration phenomena that occur in components in machine tools and, to do so, Chan and his team are producing accurate dynamic behaviour in machine tool models. This will, in turn, enable researchers to develop virtual machine tools that can monitor the condition of machines.

The design of machine tools strongly depends on the materials chosen. Increasing requirements on machine tools require the joint optimization of material and design and thus also drive the development of new materials in this field. Digital technologies finally creating a digital shadow of the machine in development also enable the required co-development taking into consideration dynamic, thermal and long term influences and behavior, enabling state and health monitoring to increase the performance of the machine tool to the maximum possible. The choice of material for the different components of machine tools is today even more difficult than ever. The recent review paper by Möhring et al. [1] sheds light on the vast field of properties and decision opportunities of combining materials at hand with design features. In former times, cast iron was the predominant material for machine bodies and has left its footprints on the design of machine tool bodies lasting still up to now. Because massive machine bodies have been the wealth of good properties, high accuracy, stiffness, good material damping properties have been attributed to cast iron design, then with increasing strength requirements higher strength cast irons came into fashion having much less material damping and finally lead to welded frames. Today requirements of dynamics and thermal behavior change the scene again. The goal is to achieve high productivity with high accuracy, which typically is a contradiction. But increasing dynamics requires distinguishing between moving bodies and their non-moving counterparts, and opens the floor for multimaterial design. For moving parts, which have to move with high dynamics meaning, high speed, high acceleration, high jerk, light weight design prevailed with the utilization of standard materials. Because manufacturability plays a major role, the bionic structures have to be degraded to thin walled rib structures as demonstrated in Fig. 1, while in future additive manufacturing will remove that restriction and enable some real bionic structures. Furthermore material choice has a huge impact on inertia savings which opens the door for CFRP, which becomes especially interesting, when the anisotropy of this material is exploited as shown in Fig. 2. From the manufacturability truss structures then result shown in Fig. 3. For the nonmoving elements, the base body, cast iron, welded steel, polymer cast, and concrete are typical materials chosen. Also aluminium structures are discussed despite the fact that aluminium has only one third of the stiffness of steel, but it offers much better thermal conductivity equalizing temperature differences faster and thus reduces the warp of the structure, which typically causes larger errors than an isotropic thermal expansion. For the choice of materials no generalizable guideline exists. The question which material is the better choice is not answerable in generality, because design follows material, which means that a sound comparison requires completely new design approaches for the different materials, where the difference between metal and polymer concrete or CFRP is really large, offering different potentials. As an example, a design of a fast moving bridge of a gantry machine might be considered. The guiding of a support on this bridge with roller guidings imposes severe problems to the design due to the material mix and different thermal expansion coefficients. Thus the choice of CFRP for the bridge necessarily must be followed up by a decision of the guiding principle, where in this case aerostatic bearings were considered as the most promising possibility. Also the potentials for function integration into the material are of major interest for the material choice, as this is easily possible for low temperature castings like for mineral cast, CFRP, or concrete. This integration of functionalities actually is a fairly new approach and relates again the machine body design to inspiration from biology, as for instance trees or leaves are from the point of view of materials weaker than our technical materials, but have a fine integration of functionalities as transmittance of information and nourriture. Sensor integration opens the field for “feeling machines” also inspired from biology, which enables the machine to detect its embedding environment and react accordingly. Cheap and miniaturized sensors are on the other side the developments that enable this approach of machine design. In the age of compensation, Industrie 4.0 and biological transformation, this functional integration will have a huge impact on material choice. Also in terms of thermal issues in machine tools, the material choice plays a major role, as thermal elongation is a physical property which is influenced by material choice. A much larger influence comes from design as indicated already above. With growing importance of compensation besides sensor integration, especially the thermal linearity and reproducibility are of crucial importance, which makes multi material design a non-trivial design task. The discussion on the superiority of thermally fast reacting machines or thermally slow reacting machines has not come to an end yet. Problematic are machines composed of components that react fast and those that react slow. A major step in that direction is the discovery of thermal resonances in [5], which shows that temperature change frequencies can depending on the machine design lead to higher or lower thermal displacements of the TCP and therefore need to be taken into account in the design phase and are significantly influenced by the choice of materials. Restrictions and influences are also coming from the process a machine tool has to enable. The material choice must take into account the influence of different media as for instance the metal working fluids as well as the debris like hot chips etc. The aforementioned discussion is mainly a discussion of main structural parts of machine tools. It must be pointed out that a machine tool is more than the sum of its structural elements, as also covers, which typically get forgotten in all academic discussion of behaviors of machine tools, but are significant for the influence of the environment on the machine tool. Also here the material choice plays a major role. Finally material choice to a large extent decides on the costs of a machine tool, but due to the huge amount of influence factors a sound fact based decision requires a nearly full design elaboration of various material choices and the summation of costs at the end of this process. This special issue with its various individual papers elucidates different aspects of the influence of materials on the design of machine tools without being capable of offering clear rules for material choice. ===danraku===1) Isolating material to exclude environmental influences on machine tools is proposed. ===danraku===2) A new guiding system with rollers and sliding guidings is proposed and the different materials for the sliding part are investigated. ===danraku===3) Gears from bamboo fibres are proposed and the manufacturability as well as their performance are discussed. The gears offer great advantages from the environmental point of view. ===danraku===4) CFRP for spindle shafts is evaluated and CFRP spindles are compared with steel spindles within the same geometric boundary conditions. The performance increase in compliance and thermal stability is significant. ===danraku===5) A topological optimization of a grinding machine tool structure is presented and showed drastically increased performance. The difficulty to transfer it to a mass producible machine tool structure is pointed out. ===danraku===6) A design of a CFRP ram for a high speed stamping press is presented and testing procedures to ensure the ability of the ram to withstand billions of impacts are designed and carried out. ===danraku===7) CFRP can beneficially applied for the cutting tool structure and besides enhancing dynamics in terms of mass and damping the material also is a valuable basis for smart tools. There are good arguments for each of the materials, which cover the whole scope of machine tool functionality: manufacturability, stiffness, strength, specific mass, thermal properties, function integrability, reproducibility, availability, environmental friendliness, and costs.

The design of typical CNC machine tools has remained relatively static over the last thirty years, and gradual improvements can be classified as being evolutionary. The emerging concept of a dematerialised CNC machine tool extenuates from the need to reduce machine tool raw material use in terms of mass by up to 60%. An important requirement for this concept is a detailed catalogue of machine tool parts that links individual components, their attributes and functionalities to ensure that all mass in a machine tool adds value. This article describes DEMAT machine tools and presents research pertaining to the development of a data model and a novel information-sharing platform (ISP) that supports and enables the design of a dematerialised machine tool. It provides a unique approach to design and life cycle monitoring of machines. An experimental software system has been developed using UML machine tool data models implemented as Java classes, and an SQL database is used to store machine tool component data. The database has been populated with typical machine tool components to demonstrate the functionality of the prototype ISP, when developing DEMAT machine tools.

This paper deals with machine tool components for use in a small machine tool for micro machining. The goal is an automated manufacturing process and to reduce manual handling by the operator as far as possible. This includes a miniaturized clamping device for fixing a test workpiece via freezing of water. Using the Finite Element Method, the thermal deformation of the test workpiece made of 100Cr6 could be analyzed as well as the static stiffness and dynamic behavior of the clamping device. Additionally, an automated workpiece supply using electromagnets and a pneumatic cylinder is presented. For extraction of chips, an adapted extraction hood was developed. The paper presents first results of performed Computational Fluid Dynamic simulations regarding velocity and streamlines of particles. Furthermore, a demonstrator of the micro machine tool shows the current installation space, enabled with the developed machine tool components. Here, the machine tool frame is made of CFRP due to its thermal stability.

The production characteristic of job-shop industry at which products have wide variety but small amounts causes every machine tool will be shared to conduct production process with dynamic load. Its dynamic condition operation directly affects machine tools component reliability. Hence, determination of maintenance schedule for every component should be calculated based on actual usage of machine tools component. This paper describes study on development of monitoring system to obtaining information about each CNC machine tool component usage in real time approached by component grouping based on its operation phase. A special device has been developed for monitoring machine tool component usage by utilizing usage phase activity data taken from certain electronics components within CNC machine. The components are adaptor, servo driver and spindle driver, as well as some additional components such as microcontroller and relays. The obtained data are utilized for detecting machine utilization phases such as power on state, machine ready state or spindle running state. Experimental result have shown that the developed CNC machine tool monitoring system is capable of obtaining phase information of machine tool usage as well as its duration and displays the information at the user interface application.

The accurate health condition evaluation of the functional components in computer numerical control (CNC) machine tools is an important prerequisite for predictive maintenance and fault warning. The vibration signals of the functional components in CNC machine tools often contain substantial noise, impeding the extraction of relevant health condition information from the vibration signals. This work presents an approach that leverages the variational mode decomposition (VMD) enhanced by the Artificial Hummingbird Algorithm (AHA) alongside the Light Gradient Boosting Machine (LightGBM) optimised through particle swarm optimisation (PSO) to evaluate the health condition of the functional components in CNC machine tools amidst pervasive noise. Initially, the AHA optimised the penalty factor (α) and the decomposition layer (K) within the VMD. This optimised VMD was subsequently applied to denoise the original vibration signals. After this denoising process, PSO was employed to optimise the learning rate and maximum tree depth within LightGBM. Health condition evaluation experiments were executed on the feed system and spindle of the CNC machine tool to validate the proposed methodology. Comparative analysis indicates that the proposed method attains paramount accuracy and computational efficiency, which are crucial for accurately evaluating the health condition of the functional components in CNC machine tools.

The rapid progression of emerging technologies like the Internet of Things (IoT) and Big Data analytics for manufacturing has driven innovation across various industries worldwide. Production data are utilized to construct a model for quality evaluation and analysis applicable to components processed by machine tools, ensuring process quality for critical components and final product quality for the machine tools. Machine tool parts often encompass several quality characteristics concurrently, categorized into three types: smaller-the-better, larger-the-better, and nominal-the-better. In this paper, an evaluation index for the nominal-the-better quality characteristic was segmented into two single-sided Six Sigma quality indexes. Furthermore, the process quality of the entire component product was assessed by n single-sided Six Sigma quality indexes. According to numerous studies, machine tool manufacturers conventionally base their decisions on small sample sizes (n), considering timeliness and costs. However, this often leads to inconsistent evaluation results due to significant sampling errors. Therefore, this paper established fuzzy testing rules using the confidence intervals of the q single-sided Six Sigma quality indices, serving as the fuzzy quality evaluation model for components of machine tools.

Demands for high precision machine tools have been increased as technology advances. Such demands require higher position control to allow the machine tools to produce higher precision end products. To facilitate the position control, magnetic and optical encoders are been widely used in the machine tools. Due to its advantage in withstanding hard environment such as oil, grease and dust over an optical encoder, along with its wide applications in industrial position control, a magnetic encoder has become a desirable choice for machine tools. The objective of this study is to develop a polarity changeable magnetizer for manufacturing coding patterns in a rotary encoder which is used to monitor runout errors for rotating components in machine tools. As opposed to commonly used capacitive pulse magnetizer in which significant amount of energy is required for its electromagnets that potentially causes high energy hazard, in this study, a polarity changeable permanent magnet is proposed and investigated through parameter studies to overcome such issue with the aim placed on producing sufficient magnetization on a thin silicon steel plate to produce desirable coding patterns on the rotary encoders.

Reducing machine tool energy consumption is critical for the manufacturing industry to achieve sustainable development. An improved energy consumption model is proposed based on the classification of computer numerical control (CNC) machine tool components. The model can be applied in various machine tools and express the machine tool operations flexibly and accurately. To facilitate the application of the model in the workshop, a corresponding procedure is proposed including data acquisition experiment, coefficient estimation, and numerical control (NC) program interpretation. The implementation of the method (i.e., the model and the procedure together) is illustrated in a grinder and a vertical machining center. The results show that the method has a good performance in predicting the power trend of machine tools during their working period. The energy consumption predictive accuracy is more than 96% in the two cases, which demonstrates the high robustness of the method.

With the 2011 launch of Industrie 4.0, a German project aiming to promote the computerization of manufacturing, the integration of physical or actual manufacturing systems with cyber-physical systems (CPS) using various technologies, such as the Internet of things (IoT), industrial Internet of things (IIOT), and artificial intelligence, is considered to be more important than ever before. One of the goals of the Industrie 4.0 is to realize smart factories or smart manufacturing using advanced digital technologies. However, the core component in the manufacturing systems is still machine tools. This special issue, composed of eleven excellent research papers, focuses on the latest research advances in machine tools and manufacturing processes. It covers various topics, including machine tool control, tool path generation for multi-axis machining, and machine tool components. Furthermore, this special issue includes innovative machining technologies, including not only cutting and grinding processes but also the EDM process and burnishing process connected effectively with force control techniques. All the research contributions were presented at IMEC2018, a joint event with JIMTOF2018, held in Tokyo, Japan in 2018. The editors would like to sincerely thank the authors for their dedication and for their well written and illustrated manuscripts. We are also profoundly grateful for the efforts of all the reviewers who ensured their quality. Finally, we sincerely hope that studies on machine tools and related manufacturing technologies will further contribute to the development of our global society.

The rapid technological developments in the manufacturing industry and an increasing demand for more and more complex and individual products has led to the development of modern machine tools from simple tools to highly automated technical products. The trend towards cyber physical production systems will intensify this development in the machine tool sector in context with the so-called fourth industrial revolution. In particular, the increasing quantity of mechatronic components in machine tools has led to a high amount of different functions that need to be controlled by the user. Empirical research has shown that user oriented Human-Machine-Interface-design (HMI-design) reduces error rates and cognitive load for the machine operator and can lead to an increase in effectiveness and efficiency with regard to the interaction. In this paper we introduce a study which points out the impact of user centered design by analyzing the differences of workflow-oriented and function-oriented HMIs. The results of the study show that work task performance can be enhanced by workflow-oriented HMI by improving the time needed and diminishing the number of clicks and errors for specific work tasks.

Machining vibrations and dynamic instability of machine tools is an important consideration in machining systems. Common approaches for improving their dynamic performance target either the process, or intelligent, yet complex control systems with actuators. Given that machine tools’ dynamic characteristics are largely defined by the characteristics of the joints, this article proposes a novel concept, attempting to create a new paradigm for improving the dynamic behaviour of machine tools—introducing modular machine tools components (Joint Interface Modules—JIMs) with joints deliberately designed for increasing dynamic stiffness and enhancing damping with the use of viscoelastic materials. Through a systematic model-based design process, a prototype replicating a reference tool holder was constructed exploiting viscoelastic materials and the dynamic response of the machining system was improved as a result of its introduction; in machining experiments, the stability limit was increased from around 2 mm depth of cut to 4 mm depth of cut, without compromising the rigidity of the system or changing the process parameters. The article also includes the results of investigations regarding the introduction of such prototypes in a machine tool and discusses the shortcomings of the stability lobe diagrams as a method for evaluating the performance of machine tool components with viscoelastically treated joints.

Power losses in machine tools, e.g. during the standby, idle-, and manufacturing process, are converted into heat energy. This causes the machine frame and other machine components to heat up. As a result, the Tool Centre Point (TCP) of the machine tools is moved. The accuracy of the machine is thus reduced during manufacturing. The current cooling system design of machine tools is based on a centrally fixed pump supply that provides a constant cooling volume flow for cooling all the machine tool components. This does not correspond to the individual temperature development of the components, after all, the high temperature fluctuation arises and causes the thermo-elastic deformation of machine tools. The main objective of this paper is to highlight the deficit of the current concept of cooling systems and to present a simulative study on the different controls concepts of cooling systems for machine tools. The results depict that the new concepts under consideration have a large potential for better thermal behaviour and lower hydraulic performance compared to the current cooling system design. The simulation results show a stability of the components’ temperature profile as well as a decreased energy consumption of the cooling system.

Post-process updating of model parameters to approximate thermal errors of machine tools operating in different configurations

Structural components of large lightweight machine tools with serial kinematics, travelling column and Gantry-type machine tools, feature a pose-dependent dynamic behavior. Conducting vibration reduction methods at these structures demands information on the precise current dynamic behavior. Determining this, an approach is presented, where the parameters of a simple rigid multi-body model of a lightweight travelling column machine tool structure are adapted online to the current dynamic behavior of the structure using a recursive least-squares estimator. Inherent control signals and additional acceleration sensor signals are used for the parameter updating. These signals are conditioned using Kalman and lowpass filters. The model as well as the online parameter identification algorithms are validated at a laboratory prototype of a lightweight travelling column machine tool. Experiments show that the model parameters quickly converge to a stable state after impulse excitation of the laboratory prototype with fixed axis. The parametrized model exactly represents the measured dynamic behavior of the laboratory prototype in a frequency range until 50 Hz. For moving axis the estimated parameters consistently change according to the movement of the axis.