The consideration of process-induced subsurface characteristics as an essential quality parameter of manufactured components is of primary relevance. An established means for the prediction of these characteristics such as residual stress, hardness or phase transformations is the use of finite element analysis, which can be used to model changes in the material for defined process configurations and engagement scenarios. However, due to high simulation times and in many cases limited model sizes, only selected scenarios can be evaluated. Process simulation systems which model the cutting process using empirical models and geometric representations of the tool and workpiece to predict the process forces and, e. g., deflections, offer the possibility to simulate entire machining processes efficiently. In this contribution, a methodology is presented to integrate process-induced alterations of the subsurface during milling into the workpiece model of a process simulation system. For the evaluation of these alterations, finite element analyses can be used for representative engagement and process scenarios, which have to be selected a priori based on each process. By extending the digital-twin of the workpiece with this information, the influence of complex machining operations with time-variant engagement conditions can be evaluated continuously. As a result, the presented framework thus provides a basis for predicting the resulting quality of the manufactured component with respect to subsurface characteristics. © 2022 The Authors. Published by Elsevier B.V.

Nickel-based superalloys belong to a category of material employed for extreme conditions and exhibit high strength properties at elevated temperatures that result in poor machinability. Machining such difficult-to-cut materials like Inconel 718 leads to a high rate of tool wear, and therefore trochoidal milling toolpath is used to improve productivity and tool life. The current study analyzes the evolution of the flank wear area of the tool during trochoidal milling of Inconel 718 using an image processing methodology. It is attempted by performing experimental studies until tool failure occurs at several cutting conditions. The machining is performed through several iterations on an identical cutting path, and the number of iterations to failure is recorded. The microstructural image of a flank wear area is captured upon each iteration and processed using an image processing algorithm. It is realized that the evaluation of flank wear area can be an effective parameter to analyze tool wear. Also, the image processing methodology works effectively and can be extended during real-time machining. © 2022

Rotating turbine components of an aircraft engine are subjected to high thermal and mechanical alternating loads. The occurrence of material defects can have devastating effects and can even lead to component failure. However, many of these defects are not detected until very late in the production chain. This paper focuses on the detection of defects during the turning process of nickel-based alloy DA718 based on the analysis of measured cutting forces. For this purpose, the knowledge gained from previous experiments with synthetically produced defects were validated on real defects detected on series production parts. The applied measurement setup will be discussed and evaluated with regard to a series application. © 2022 The Authors.

The machining of nickel-based superalloys such as Inconel 718 still poses a great challenge. The high strength and temperature resistance of these materials lead to poor machinability, resulting in high process forces and extensive tool wear. However, this wear is stochastic when reaching a certain point and is difficult to predict. To generate consistent wear conditions, the tool wear can be decoupled from the milling process by creating artificial wear using grinding. In this paper, a multi-axis approach for decoupling tool wear is presented and analyzed. Therefore, scanning electron microscope images of different wear states – worn and artificially worn – are analyzed. In addition, the occurring process forces of naturally and contrived worn inserts are compared in orthogonal cutting experiments as an analogy setup. Finally, a finite element analysis using a novel methodology for segmenting relevant cutting edge sections using digital microscope images provides qualitative insights on the influence of different wear conditions. © 2022

The material point method (MPM) represents an alternative discretization method for numerical simulations. It aims to combine the benefits of a Lagrangian representation of bodies and an Eulerian numerical solution approach. Therefore, especially at high material deformations the method is not prone to mesh distortions such as the finite element method (FEM). For this reason, the MPM is used to a great extent for modeling granular materials as in geo-mechanics. However, high deformations occur in many industrial processes on metallic materials. The Split-Hopkinson-Pressure-Bar (SHPB) experiment is used to characterize material properties at high deformation rates. Although widely used, this experiment is not yet standardized and shows a variety of sensitivities, e.g. to friction. Inter alia for this reason, simulations are conducted with the experiment to allow for a better evaluation of the measured data. The purpose of this work from an engineering point of view is to analyze the performance of the MPM on an SHPB experiment. In order to validate the experimental results for the material characterization under dynamic loading conditions we introduce frictional contact. We use arbitrary tri-linear brick domains in a 3D CPDI1 scheme, instead of originally used parallelepipeds. This allows for a more flexible geometry approximation using standard meshes. The results of the method are analyzed with respect to discretization sensitivity and discussed in the context of the experimental results for a 42CrMo4 steel. We were able to show that the method is capable to reproduce the SHPB experiment. Additionally the method shows convergency in the results with finer discretizations. Thus, the MPM has underlined its importance as an alternative simulation technique for problems with high deformation. © 2021, The Author(s).

The performance of machine learning algorithms depends to a large extent on the amount and the quality of data available for training. Simulations are most often used as test-beds for assessing the performance of trained models on simulated environment before deployment in real-world. They can also be used for data annotation, i.e, assigning labels to observed data, providing thus background knowledge for domain experts. We want to integrate this knowledge into the machine learning process and, at the same time, use the simulation as an additional data source. Therefore, we present a framework that allows for the combination of real-world observations and simulation data at two levels, namely the data or the model level. At the data level, observations and simulation data are integrated to form an enriched data set for learning. At the model level, the models learned from observed and simulated data separately are combined using an ensemble technique. Based on the trade-off between model bias and variance, an automatic selection of the appropriate fusion level is proposed. Our framework is validated using two case studies of very different types. The first is an industry 4.0 use case consisting of monitoring a milling process in real-time. The second is an application in astroparticle physics for background suppression. © 2022 Elsevier Ltd

The planning of machining operations for components using CAM requires careful consideration by highly trained personnel, with rising complexity in part requirements. This work proposes a novel domain-specific planning technique using Combinatory Logic Synthesis to generate a multitude of tool paths. By analyzing current state CNC path planning algorithms, motion primitives are identified and implemented in a modular representation using software components. Thus, a large variety of path planning strategies can be generated, while maintaining a multitude of different boundary constraints and productivity metrics. These solutions are subjected to geometric physically-based simulations in order to validate their ranking and compliance. © 2021 The Author(s).

The increasing demand for high-performance components is leading to a greater use of advanced alloys such as DA718, which is, e.g., used in engine parts due to its high-temperature strength. The strict quality requirements pose major challenges for the machining of engine components for aircrafts. Quality deviations along the value chain can lead to high costs due to rework and, in the worst case, rejections in order to prevent material failure within a safety-critical environment. These deviations include, e.g., an increased surface roughness, deviations in the shape tolerances as well as increased internal stresses or surface deformations. Material defects are an additional reason to reject the manufactured components. These are usually inspected only at the end of the value chain and—due to measurement limitations—only if they occur close to the surface of the workpiece. Ultrasonic testing is used in order to detect defects near the surface of the raw part. For the evaluation of the finished part, etching and optical inspection of the surface is used. However, defects inside the components cannot be detected in this way. If material defects are located in areas subjected to intense load changes and high temperatures, the components have to be rejected since engine parts require a high level of fatigue strength. Such rejects constitute a significant economic risk, as a large part of the added value has already been completed and a significant amount of machine time has been invested. Thus, an identification of material defects in an earlier stage of the manufacturing process is required. In this paper, fundamental investigations on machining artificially generated material defects in a micro-milling process and the signal analysis during the pre-turning of turbine disks made of nickel-based materials like DA718 will be presented. Based on force measurements, characteristic signals were identified that could indicate material defects during the turning process. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

The occurrence of chatter vibrations in 5-axis milling processes is a common problem and can result in part failure, surface defects and increased wear of the cutting tool and the machine tool. In order to prevent process vibrations, machining processes can be optimized by utilizing geometric physically-based simulation systems. Since the modal parameters of the machine tool are dependent on the position of the linear and rotary axes, the dynamic behavior of milling processes can change along the NC path despite constant engagement conditions. In order to model the pose-dependent modal properties at the tool tip, the frequency response functions (FRFs) were measured at different locations of the workspace of the machine tool for various poses of the rotary axis of the spindle. To take the varying compliance within the workspace of a machine tool into account in a geometric physically-based milling process simulation, different interpolation methods for interpolating FRFs or parameter values of oscillator-based compliance models (OPV) were applied. For validation, the resulting models were analyzed and compared to measured data. In OPV interpolation, the individual oscillation modes were interpolated in their respective characteristics based on the oscillator parameters (eigenfrequencies, modal masses and damping values). In FRF interpolation, however, there was no differentiation between the modes, resulting in a wrong interpolation. It can therefore provide good results when only a small shift of the eigenfrequencies is expected, as in case of the analyzed machine tool, with only small movements of the translatory axes. © 2021, The Author(s).

In order to analyze various process characteristics, grinding simulations can be used, which need accurate models of the tool and the individual grains. For this purpose, grinding tools can be digitized. To identify characteristic grains from a large number of measurements, each individual grain has to be analyzed and separated from the bond manually. Therefore, a deep learning-based methodology was developed to achieve a high segmentation accuracy of the grain boundaries efficiently. Additionally, a data augmentation approach was investigated to limit the data necessary for learning. The model transferability was quantified by analyzing different states of tool wear. © 2021 CIRP

In this research, Split-Hopkinson pressure bar tests were performed on samples made from the quenched and tempered steel 42CrMo4 in four different heat-treatment conditions. These samples were subjected to four different pressures and five different temperatures while deforming the samples at strain rates in the range of 103 s−1. Stress-strain curves and the strain rate were computed from the measured signals. The polished cross-sections of the samples were analyzed before and after testing by means of SEM, EBSD, nanoindentation, and microhardness testing. A variety of deformation characteristics were identified and correlated with the pre-test and post-test microstructure. This work focusses on the influence of the microstructure on deformation and provides a detailed understanding on the deformation of the 42CrMo4 steel over a wide range of parameter values. © 2021 Elsevier B.V.

Tool wear in machining is generally observed as early and late stage tool wear. During early stage tool wear, the tool is rapidly worn during a break-in period, followed by a stable region of tool wear. After machining more material, the tool reaches late stage tool wear. At this point, tool wear becomes unstable; tool failure occurs quickly or it may take some time. Therefore, late stage tool wear represents a bifurcation point, making it difficult to predict tool wear past this point. Tool wear is well known to be stochastically influenced. Due to this effect, it is difficult to perform studies on late stage tool wear since machining tools will be affected differently up to this point, introducing unknown variables. A novel method is presented in this research which utilized artificial wear to reach late stage tool wear. This method, termed contrived tool wear, may be capable of reducing the stochastic tool wear that occurs during early stage tool wear. As an initial investigation, machining tool inserts were worn by taking several passes over a grinding wheel with the tool rotating in reverse. Several parameters were tested in an attempt to match the natural worn state as close as possible. Subsequent to artificial wear, the inserts were used to machine IN718. The presented method of contrived wear was found to be a good approach, but could not sufficiently replicate the tool wear typically produced in IN718 machining. Future work should aim at implementing a multi-axis approach to enable grinding at various angles to the rake face of the insert. Copyright © 2021 by ASME.

Process damping in milling is a significant influencing factor in avoiding detrimental dynamic effects such as regenerative chatter vibrations, which can impair the workpiece quality and increase tool wear. In this context, the use of tools with flank face chamfers causes significant process damping effects over a wide range of spindle speeds. This way, processes with increased material removal rates due to high radial and axial tool immersions can be conducted without the occurrence of disturbing chatter vibrations. A precise prediction of the process stability is necessary to define efficient process strategies in advance. However, this is particularly challenging in the presence of process damping due to its nonlinear process behavior. This paper presents an evaluation of a new approach towards modeling dynamic forces in a geometric physically-based milling simulation for taking process damping effects caused by chamfered cutting tools into account. This model considers the vibration velocity present at the cutting edge in order to calculate a damping force caused by the dynamic tool-workpiece contact. The parameterization of the velocity-dependent force model was carried out a priori by conducting finite element simulations using an orthogonal cutting model as an analogy setup to determine the resulting force components. The proposed modeling approach was analyzed by comparing the simulation results to corresponding milling processes for validation. In contrast to established empirical force models, which calculate the process forces entirely as a function of the undeformed chip shape, the consideration of the dynamic tool-workpiece interaction led to a significant damping of the modeled process vibrations. © 2021 The Authors. Published by Elsevier B.V.

Free-formed surfaces, e.g. of dies, can be finished using 5-axis milling processes. Due to the varying tool-engagement situations and the dynamic behavior of the tool-spindle-machine system, the avoidance of chatter vibrations is challenging for these processes. Since the dynamic behavior depends on the position of the axes, the process stability can be improved by choosing beneficial tilt angles along the NC path. In this paper, a geometric physically-based process simulation was used to investigate the dependence of the calculated stability limit on the tilt angle and the speed-dependent parameters of the force model. © 2021 Society of Manufacturing Engineers (SME)

Nickel-based superalloys are often used in aerospace industry for different applications, e.g., blisks or turbine blades. Due to its high strength and corrosion resistance, materials like Inconel 718 lead to a poor machinability and, thus, to a high amount of tool wear. In this paper, the influence of different process parameter values on the tool wear is analyzed. For the fundamental investigations, the tool wear evolution was examined for two different path strategies with and without coolant. To identify suitable process parameter values, the width of flank wear land and process forces were analyzed based on a screening design of experiments. © 2021 The Authors. Published by Elsevier B.V.

The focus on the fourth industrial revolution and advancements in 3D printing has reignited the need for energy efficient manufacturing. In particular, Selective Laser Melting (SLM), an additive manufacturing process, has garnered wide attention owing to its adaptability in producing lightweight components for metal industries. Reasonable material demand along with environmental and methodical capabilities of SLM machines has opened up an intriguing possibility to examine its power consumption as well as to determine its suitability for energy efficient manufacturing. In addition, the energy demand of SLM machines along with its occupancy time in a factory floor poses challenges to energy supply grid and subsequent effects on energy flexibility. Hence, it is necessary to determine energy demand of SLM process chain. This paper provides an empirical power consumption analysis of an additive process chain and interprets the power utilized by various process steps of an SLM machine. © 2021 The Authors. Published by Elsevier B.V.

The quality and surface integrity of machined parts is influenced by residual stresses in the subsurface resulting from cutting operations. These stress characteristics can not only affect functional properties such as fatigue life, but also the process forces during machining. Especially for orthogonal cutting as an appropriate experimental analogy setup for machining operations like milling, different undeformed chip thicknesses cause specific residual stress formations in the subsurface area. In this work, the process-related depth profile of the residual stress in AISI 4140 was investigated and correlated to the resulting cutting forces. Furthermore, an analysis of the microstructure of the cut material was performed, using additional characterization techniques such as electron backscatter diffraction and nanoindentation to account for subsurface alterations. On this basis, the influence of process-related stress profiles on the process forces for consecutive orthogonal cutting strategies is evaluated and compared to the results of a numerical model. The insights obtained provide a basis for future investigations on, e. g., empirical modeling of process forces including the influence of process-specific characteristics such as residual stress. © 2021, The Author(s).

In aerospace industry surface and profile grinding processes are widely used for the manufacturing of turbine blades. Maximizing the productivity is a key factor for industry, which can be achieved by reducing the number of cuts necessary in order to remove the remaining millimeters of stock material after casting. This leads to high depth of cut values and, therefore, considerably high process forces. Turbine blades are highly flexible workpieces resulting in process induced deflections. In order to avoid mechanical damages of the workpiece during the process, a macroscopic grinding simulation is used, which is presented in this paper. For this process simulation a coupled multiphysics FE model was created using the software COMSOL Multiphysics. First, the material removal was evaluated using the deformed geometry module of the software. Based on the current material removal the process forces were calculated using an experimentally calibrated grinding force model. The forces were subsequently applied onto the grinding area allowing for a calculation of the resulting stresses and deflections. Further, the simulation was extended for profile grinding processes using an inclined grinding wheel and a fir tree profile of a turbine blade. The simulated forces were validated based on experimentally conducted grinding processes. © 2021 Elsevier B.V.. All rights reserved.

An increasing demand for products and services in the aviation industry is attended by a rising demand for aircraft engines. This requires an increased productivity combined with highest quality and safety standards. In this paper, a new approach of material defect detection is presented which is based on force and acoustic-emission measurements during machining processes. Representative synthetic defects in titanium alloy Ti6246 were investigated. In order to use scale effects, the experiments were conducted in micro-milling processes. This approach could be used for an automated, non-destructive evaluation of the manufactured components in the future and thus for reducing testing effort and related auxiliary times. © 2021 The Authors. Published by Elsevier B.V.

The machining of free-formed surfaces, e.g., dies or moulds, is often affected by tool vibrations, which can affect the quality of the workpiece surface. Furthermore, in 5-axis milling, the dynamic properties of the system consisting of the tool, spindle and machine tool can vary depending on the tool pose. In this paper, a simulation-based methodology for optimising the tool orientation, i.e., tilt and lead angle of simultaneous 5-axis milling processes, is presented. For this purpose, a path finding algorithm was used to identify process configurations, that minimise tool vibrations based on pre-calculated simulation results, which were organised using graph theory. In addition, the acceleration behaviour of the feed drives, which limits the ability of adjusting the tool orientation with a high adaption frequency, as well as potential collisions of the tool, tool chuck and spindle with the workpiece were considered during the optimisation procedure. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

The aerospace industry utilizes nickel-based super-alloys due to its high level of strength and corrosion resistance. To evaluate milling strategies regarding tool wear, the prediction of forces during these cutting operations is essential. This comprises the determination of the undeformed chip thickness. Due to the complex interdependencies of tool engagements, the determination of these thicknesses is challenging. A geometric physically-based simulation system was extended by a novel time-discrete envelope model to increase the precision of the calculated undeformed chip thicknesses. In order to take tool wear into account, digitized topographies of cutting inserts in different states of tool wear were modelled. © 2021, The Author(s).

Additive manufacturing processes, such as Selective Laser Melting (SLM), has become increasingly established in metal-processing industry offering versatile possibilities for producing individualised components or lightweight structures. SLM machines offer ecological and economical potentials due to comparatively low power and material demand. Required pre-and post-processes as sieving and milling, which are used to ensure a stable process and fulfil demands on surface quality and tolerances, are often neglected. Differentiating from this, an approach for analysing the energy demand of an additive-subtractive process chain is presented based on exemplary processes using a combination of empirical models and a geometric physically-based simulation. © 2021 The Authors. Published by Elsevier B.V.

The overall quality and efficiency of a machined part relies heavily on the tool path that is used. A more recently developed toolpath method is known as trochoidal milling, which is also known by several other terms, such as adaptive milling, circular milling, or volume clearing. In order to follow the contours of the final geometry, this path can give rise to a significant number of direction changes, which result in highly variable force directions on the tool. Chatter, or self-excited vibration that occurs at the tool or workpiece, can therefore be mitigated or avoided since periodic resonance does not have time to increase the vibration's amplitude. A randomized variation of the trochoidal path is tested in this research. Using this new proposed method, stochastic behavior of the toolpath is implemented. The toolpath consists entirely of circular arcs, which drive the tool in a pseudo-random fashion. The stability of such a path is examined in this work. A key parameter of this path is the allowable radius range of the circular arcs. It was found that the most efficient path utilized a median parameter value, illustrating an overall negative parabolic relationship between path efficiency and tool path radius. It was also discovered that smaller arcs reduced chatter. Future studies will explore the behaviors of this path for milling 3D surfaces. Copyright © 2021 by ASME

During machining operations, complex engagement situations between the tool and workpiece lead to varying amplitudes and directions of cutting forces. Correlations between material properties, process parameters and resulting forces have to be analyzed to ensure the predictability of machining processes. To model the material removal, a detailed analysis of the material behavior during the engagement is needed. In this work, a geometric physically-based simulation system is extended to take the material behavior into account for improving the prediction accuracy of process forces. A detailed analysis of the low-alloyed steel 42CrMo4 and validation experiments are presented. © 2020 The Authors.

The increasing complexity of production processes, shortening product lifecycles and rising energy costs lead to an emerging need for an efficiency optimization approach including process simulations in factory adaption planning as well as in process planning. This paper presents a method for the design of milling processes by analyzing process times, energy consumption and process stability based on process simulations. By evaluating simplified virtually conducted processes, reasonable parameter value combinations can be selected efficiently and provide flexibility by generating multiple solutions. Using detailed process simulations and conducting iterative adjustments to ensure a sufficient workpiece quality, the selected parameter sets are transferred to actual NC processes. © 2020 The Authors.

The dynamic behaviour of milling processes can be analysed using process simulations based on measured frequency response functions. However, the determination of these functions for micro-milling processes is challenging due to small tool diameters of 1 mm or less, the influence of higher spindle speeds on the dynamic behaviour, and runout errors. Therefore, an approach for analysing micro-milling tools based on an excitation using bearing balls with a diameter of 1 mm, shot by compressed air, is presented. The measured dynamic response is applied to a geometric physically-based process simulation in order to analyse tool vibrations in a micro-milling process. © 2020 CIRP

Machining operations like milling exhibit complex process kinematics, which restricts the identification and analysis of fundamental cause-effect interrelations. In order to differentiate the impact of relevant process parameters, a reduction of influencing factors is necessary. For this purpose, a cutting operation with a linear cutting motion, like orthogonal cutting, is beneficial. Such an experimental setup requires suitable tools, workpieces and measurement systems. The experimental assessment of a developed modular design is presented in this publication. In addition to orthogonal cuts, oblique cuts, which are representative for machining operations with respect to the helix angle, were investigated. To analyze process dynamics, interrupted cuts, including a specifically compliant tool system, were performed. © 2020, MM publishing Ltd.. All rights reserved.

Surface topographies resulting from grinding processes and the corresponding process forces depend on various process conditions, such as the grain shapes and the workpiece material. Geometric physically-based simulations can be used to analyze these process results, taking the individual grains on the grinding tool into account. However, the experimental calibration of the force models is time consuming and challenging since the shape of the grains changes due to wear. Finite Element Analysis (FEA) can be used to calculate the process forces of individual grain engagements with defined grain shapes based on material models, e. g., the Johnson-Cook (JC) model. In this paper, the Coupled Eulerian-Lagrangian (CEL) method is used to determine the cutting force coefficients of the empirical force model of a geometric physically-based simulation system. The workpiece model is described by an Eulerian formulation and the grain is modeled as a rigid hull comprising triangular elements. The calibrated force model is applied in a simulation of an exemplary grinding process in order to calculate the process forces for each individual grain. The simulated forces are validated by comparing the simulation results to experimental investigations. © 2019 The Authors. Published by Elsevier B.V.

During the initial sampling of injection molds, the determination of suitable process parameter values to achieve a desired quality of the resulting parts, can be a time-consuming and demanding task. This is due to the complex viscoelastic properties of injection molding processes. Conducting technological investigations and using simulation techniques are popular approaches to support the design of the regarded process. However, while the former approach can require extensive research efforts, it can be difficult to design simulations and validate their prediction accuracy, especially when few process measurements are available as a baseline. In addition, the knowledge obtained by both, simulation and technologically based approaches, is only valid for the analyzed process configurations. In contrast, models based on machine learning (ML) approaches can provide forecasts for previously unseen data and can be evaluated quickly. Unfortunately, a high amount of data is required to train such models reasonably. In this contribution, a novel ML-based methodology to predict quality characteristics of an injection molding process for different process parameter values using an intelligent combination of simulation data and measurements, is presented. © 2020 The Society of Manufacturing Engineers

The constantly increasing demand for both, higher production output and more complex product geometries, which can only be achieved using five-axis milling processes, requires elaborated analysis approaches to optimize the regarded process. This is especially necessary when the used tool is susceptible to vibrations, which can deteriorate the quality of the machined workpiece surface. The prediction of tool vibrations based on the used NC path and process configuration can be achieved by, e.g., applying geometric physically-based process simulation systems prior to the machining process. However, recent research showed that the dynamic behavior of the system, consisting of the machine tool, the spindle, and the milling tool, can change significantly when using different inclination angles to realize certain machined workpiece shapes. Intermediate dynamic properties have to be interpolated based on measurements due to the impracticality of measuring the frequency response functions for each position and inclination angle that are used along the NC path. This paper presents a learning-based approach to predict the frequency response function for a given pose of the tool center point. © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

To prevent undesirable effects during milling processes, online predictions of upcoming events can be used. Process simulations enable the capability to retrieve additional knowledge about the process, since their application allows the generation of data about characteristics, which cannot be measured during the process and can be incorporated as pre-calculated features into the analysis. Furthermore, sensor technologies were used as reasonable data sources for analyzing different monitoring scopes of milling processes. Machine learning-based models utilize data, acquired by various available data sources, to generate predictions of upcoming events in real-time. In this paper, we propose a novel approach for combining simulation data with sensor data to generate online predictions of process forces, which are influenced by tool wear, using an ensemble-based machine learning method. In addition, a methodology was developed in order to synchronize pre-calculated simulation data and streaming sensor measurements in real time. Milling experiments using ball-end milling tools with varying cutting speeds and tooth feeds showed the robustness of the approach in enhancing the prediction accuracy compared to only using one of each data source. © 2020 Elsevier Ltd

The consideration of energy efficiency of production systems is becoming increasingly important due to social, political and economic aspects. To exploit the efficiency potential available in industry, it is essential to analyze the energy requirements of factories. The basis for efficiency description is an indicator system, which can represent separate processes depending on any number of inputs and outputs. This indicator system is extended by two indicators that can describe interdependencies between processes regarding efficiency. The validation is carried out using a simulation model of a manufacturing system and shows that the interdependencies are represented qualitatively and quantitatively. © 2020 The Authors.

In this paper the idea of Self-Optimizing Machining Systems (SOMS) is introduced and discussed. Against the background of Industry 4.0, here the focus is the technological level of discrete workpiece production by mechanical machining processes utilizing related machine tools and equipment. Enabling technologies, principles, and methods are described that allow for the implementation of machining systems which are capable of adapting their parameters and settings autonomously, in order to optimize for productivity, quality, and efficiency in manufacturing. Following a description of the meaning and a definition of SOMS as well as a historical retrospection, the required elements of SOMS are discussed and exemplary approaches are presented. Based on sophisticated process planning, monitoring, adaptive control, simulation, artificial intelligence, and machine learning, strategies, state-of-the-art solutions for self-optimization in machining applications are introduced. Several examples showcase how different types of enabling technologies can be integrated synergistically, to improve the manufacturing of parts by SOMS. Finally, the future potential of SOMS as well as challenges and needs are summarized. The paper especially considers the results of the CIRP Cross-STC Collaborative Working Group on SOMS. © 2020 CIRP

This work investigates the effect of cutting on the microstructure and subsurface properties of a cut specimen, with particular focus on the influence of the sample's microstructure and its evolution. Single-pass pendulum tests were conducted with samples of 42CrMo4 steel that had been subjected to different heat treatments. The subsurface region after cutting was analyzed optically by SEM and EBSD. The strain hardened surface region was investigated by nanoindentation. It was found that a soft-annealed structure, in particular, was altered deeply by cutting, resulting in a hardness increase as well as an microstructure that is elongated and refined by high shear deformation microstructure in near-surface regions. The strain hardening behavior and potential of a microstructure had a striking influence on the subsurface alteration. Although some microstructures yielded the same forces under equal cutting conditions, the subsurface alteration was different. This type of change in microstructure was correlated with the micromechanical properties and residual stresses. General influences, such as cutting depth, on the alteration of microstructures by cutting were also taken into account. © 2020 Int. J. Mech. Eng. Rob. Res.

The use of tools with chamfered cutting edges is an essential part of high performance cutting (HPC) as a rough milling process strategy for manufacturing structural components in the aerospace industry. Due to an interaction between the chamfer and the undulated workpiece surface, tool vibrations can be damped allowing high depths of cut without the occurrence of harmful dynamic effects. Hence, a significant increase in efficiency is possible. As a result of process damping, the stability boundary predicted by linear stability analysis provided for instance by analytical or geometric physically-based simulations will generally underestimate the experimentally determined one. Consequently, the object of this procedure, namely to reduce the number of test runs until sufficient process parameter values are determined, could not be met. Therefore, the damping effect induced by chamfered tools was analysed in this paper. It is shown that the use of chamfered cutting edges leads to a significant limitation of chatter amplitudes when exceeding the stability limit. The strength of this effect depends on the cutting speed and the engagement situation, which influence the intensity and number of interactions between the chamfer and the workpiece surface and, thus, the resulting process damping. Moreover, a dynamic process damping model presented in the literature was chosen and implemented in a geometric physically-based milling simulation. An evaluation of its validity points out the challenges regarding the simulation of process damping. © 2019, German Academic Society for Production Engineering (WGP).

The high quality demand for machined functional surfaces of forming tools, entail extensive investigations for the adjustment of the manufacturing process. Since the surface quality depends on a multitude of influencing factors in face micromilling, a complex optimization problem arises. Through analytical and simulative approaches, the scope of the experimental investigation to meet the requirements for surface roughness can be significantly reduced. In this contribution, both analytical and simulation-based approaches are presented in the context of predicting the roughness of a machined surface. The consideration of actual tool geometry and shape deviations are used in a simulation system to achieve the agreement with experimental results. © 2019 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

Dynamic customer demands require efficient and effective adaptations of factory systems and processes. Due to rising energy prices and consumption in manufacturing industries, energy efficiency is increasingly respected during adaptation planning. An empirical model of the power consumption of machine tools is validated and combined with a geometric physically-based process simulation. The model is experimentally validated and applied to selected processes for analyzing the effect of chatter on the power consumption. An approach for an application within the factory adaptation planning is presented giving the opportunity to simulate and optimize milling processes in order to support planning processes. © 2019 The Author(s).

In the context of digitization and industry 4.0, the production-related disciplines developed powerful simulation models with different scopes and varying levels of detail. As these simulation systems are usually not built in a compatible way, the models cannot be combined easily. Co-simulation techniques provide a promising basis for combining these models into one superordinate model and utilizing it for planning new factories, adapting existing ones or for production planning. However, today’s co-simulation systems do not benefit from the inherent flexibility of the represented production systems. Simulation-based optimization is carried out inside each discipline’s simulation system, which means that interdisciplinary, global optima are often impossible to reach. Additionally, the aspect of human interaction with such complex co-simulation systems is often disregarded. Addressing these two issues, this paper presents a concept for combining different simulation models to interdisciplinary multi-level simulations of production systems. In this concept, the inherent flexibilities are capitalized to enhance the flexibility and performance of production systems. The concept includes three hierarchical levels of production systems and allows human interaction with the simulation system. These three levels are the Process Simulation level, the Factory Simulation level, and the Human Interaction level, but the concept is easily extendable to support additional levels. Within the multi-level structure, each simulation system carries out a multi-objective optimization. Pareto-optimal solutions are forwarded to simulations on higher hierarchical levels in order to combine them and meet flexibly adaptable objectives of the entire production system. The concept is tested by means of a simplified production system, to optimize it in terms of throughput time and electric energy consumption. Results show that the presented interdisciplinary combination of heterogeneous simulation models in multi-level simulations has the potential to optimize the productivity and efficiency of production systems. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

The advancing digitalization of industrial processes offers new possibilities for improving monitoring and control of factory systems. To enhance the monitoring of energy efficiency, an indicator system was developed that displays the efficiency depending on relevant physical inputs and outputs. These Process Status Indicators can characterize single processes either time-discretely or time continuously. The behavior of the indicators is analyzed regarding an energy converting process. Exemplarily, the generation of compressed air and the influence of using waste heat are observed. The results of the simulative investigation depict that the time continuous indicators can represent the efficiency regarding all considered characteristics. © 2019 The Author(s).

For various industrial applications, e.g., the manufacturing of forming tools for the automotive sector, surface structures of functional areas play a decisive role. NC grinding processes on machining centers represent a flexible solution for finishing the free-form surfaces of forming tools. However, the surface topographies are influenced by several factors like the distribution of the grains and the wear of the tools. In this paper, a geometric physically-based simulation system is applied to predict the surface structures for different multi-stage grinding strategies. Point clouds were used for modeling the individual grains, which allows the simulation of different states of tool wear and the resulting influence on the surface topographies and process forces. Due to the high number of grains on the grinding tools, a stochastic model for the grain distributions and a database of different grain shapes were created based on representative measurements. The simulated surfaces are compared to experimental results in order to validate this approach. © 2019 The Authors. Published by Elsevier B.V.

The runout of milling tools results in uneven effective tooth radii and affects the occurrence of tool wear in machining processes. The load and, thus, the specific wear of teeth with increased effective radii is higher. In processes with small undeformed chip thicknesses, e.g., the finishing of titanium alloys, the runout error could even be greater than the undeformed chip thickness. In this case, at least one cutting edge does not remove any material. In this paper, the influence of the runout on wear effects is analyzed for an exemplary finishing process using cutting force measurements and a geometric physically-based process simulation. © 2019 The Author(s).

Trochoidal milling is an alternative path planning strategy with the potential of increasing material removal rate per unit of tool wear and therefore productivity cost while reducing cutting energy and improving tool performance. These characteristics in addition to low radial immersion of the tool make trochoidal milling a desirable tool path in machining difficult-to-cut alloys such as nickel-based superalloys. The objective of this work is to study the dynamic stability of trochoidal milling and investigate the interaction of tool path parameters with stability behavior when machining IN718 superalloy. While there exist a few published works on dynamics of circular milling (an approximated tool path for trochoidal milling), this work addresses the dynamics of the actual trochoidal tool path. First, the chip geometry quantification strategy is explained, then the chatter characteristic equation in trochoidal milling is formulated, and chatter stability lobes are generated. It is shown that unlike a conventional end-milling operation where the geometry of chips remains constant during the cut (resulting in a single chatter diagram representing the stability region), trochoidal milling chatter diagrams evolve in time with the change in geometry (plus cutter entering and exiting angles) of each chip. The limit of the critical depth of cut is compared with conventional end milling and shown that the depth of cut can be increased up to ten times while preserving stability. Finally, the displacement response of the cutting tool is simulated in the time domain for stable and unstable cutting regions; numerical simulation and theoretical results are compared. © 2019, Springer-Verlag London Ltd., part of Springer Nature.

Due to their flexibility to also build up highly complex geometries, Additive Manufacturing (AM) processes are increasingly applied. Although near net-shape components can be manufactured using, for example, the Selective Laser Melting (SLM) process, the required surface quality can often not be achieved. In order to manufacture contact areas or functional surfaces, subsequent machining processes can be used to achieve the required accuracy in shape and dimension as well as the desired surface quality. In order to reduce the experimental effort during process design and optimization, simulation systems that are able to efficiently model both processes are required. In this paper, an empirical geometry-based model for SLM and milling processes will be presented. Due to the usage of an empirical model, based on the analysis of a set of reference structures, the simulation of macroscopic geometries can be achieved and used in subsequent milling simulations. Furthermore, an experimental validation of the combination of the two simulation models will be presented. © 2018, German Academic Society for Production Engineering (WGP).

Geometric physically-based simulation systems can be used for analyzing and optimizing complex milling processes, for example in the automotive or aerospace industry, where the surface quality and process efficiency are limited due to chatter vibrations. Process simulations using tool models based on the constructive solid geometry (CSG) technique allow the analysis of process forces, tool deflections, and surface location errors resulting from five-axis machining operations. However, modeling complex tool shapes and effects like runout is difficult using CSG models due to the increasing complexity of the shape descriptions. Therefore, a point-based method for modeling the rotating tool considering its deflections is presented in this paper. With this method, tools with complex shapes and runout can be simulated in an efficient and flexible way. The new modeling approach is applied to exemplary milling processes and the simulation results are validated based on machining experiments. © 2018, Shanghai University and Springer-Verlag GmbH Germany, part of Springer Nature.

Due to the increasing demands on surface quality of machined surfaces, deviations of the feed velocity, which can occur in complex 5-axis milling processes and are caused by the insufficient acceleration and deceleration behaviour of the machining centre, have to be avoided. This is crucial in the case of surface structuring by means of high-feed milling. The high-feed rate can be used to generate quasi-deterministic surface structures on forming tools. Applying surface structures for forming processes, the friction can be tailored to improve the form filling of small cavities. However, in order to generate homogeneous surface structures, it is important to ensure a constant feed per tooth during the milling process. In this work, a novel approach for the predicting surface structures using a geometric physically-based simulation system is shown. Furthermore, an empirical model was developed which represents the acceleration and deceleration behaviour of the used machining centre for predicting the deviations of the feed rate. Therefore, it is possible to take the alternating feed rate into account when simulating the milling process. In addition, a control approach, for adapting the spindle speed online, is used to keep the tooth feed constant. © 2018 Inderscience Enterprises Ltd.

The worldwide increase in energy prices and energy consumption in recent years have led to a redirected and increased focus on energy efficiency in the industries. This paper analyses the distribution of the electrical power consumption of the components of different milling machines. Previous experiments showed that auxiliary components like cooling and control use a major share of the total electrical energy input. In an attempt to optimise the machining process, an approach to model the power input of machining centres using an empirically generated database of the basic load and a geometric, physically based model for depicting the cutting power is presented. © 2017 The Authors.

Process simulations are increasingly applied to analyze machining processes regarding process stability and the resulting surface quality of the workpiece. Due to their computational time, these simulations are inappropriate for real-time applications. Using Machine Learning approaches, monitoring systems for milling processes can be realized. Unfortunately, a huge amount of experimental data is necessary to train such models. A novel Machine Learning framework, which generates reliable predictions of the process stability, is presented in this paper. The model is designed based on results of a geometric physically-based simulation with varied process parameter values and refined using an active learning approach. © 2018 The Authors. Published by Elsevier B.V.

Grinding processes can be optimized by simulating the influence of individual grains on process forces and surface topographies. However, the process results are significantly influenced by tool wear. Simulating this effect allows, e.g., the prediction of necessary tool changes when manufacturing large forming tools. Therefore, a new point-based approach for modeling arbitrarily shaped grains in different states of tool wear was developed. Based on a small amount of representative wear investigations, a flexible tool model was defined, which can be used for various tool shapes without further experiments. This model can be applied for grinding processes with varying engagement situations. © 2018

Dynamic models of machine tools can be used to predict their dynamic behavior in machining simulations. In a geometric-physical simulation a dynamic model comprising damped harmonic oscillators can be used to represent the frequency response functions (FRF) of the machine. The axis positions of milling machines change during machining and, thus, the FRFs vary. Therefore, the FRFs have to be determined at different locations in the workspace. Due to practical reasons, the number of measurement positions is limited. A method for interpolating the modal parameter values of the dynamic model is applied and evaluated. © 2017 The Authors. Published by Elsevier B.V.

Milling is a machining process in which material removal occurs due to the rotary motion of a cutting tool relative to a typically stationary workpiece. In modern machining centers, up to and exceeding six degrees of freedom for motion relative to the tool and workpiece are possible, which results in a very complex chip and force formation. For the process layout, simulations can be used to calculate the occurring process forces, which are needed, e.g., for the prediction of surface errors of the workpiece, or for tool wear and process optimization examinations. One limiting factor for the quality of simulation results is the parametrization of the models. The most important parameters for milling simulations are the ones that calibrate the force model, as nearly every modeled process characteristic depends on the forces. This article presents the combination of a milling simulation with the Broyden-Fletcher-Goldfarb-Shanno (BFGS) optimization algorithm for the fast determination of force parameters that are valid for a wide range of process parameters. Experiments were conducted to measure the process forces during milling with different process parameters. The measured forces serve as basis for tests regarding the quality of the determined force parameters. The effect of the tool runout on the optimization result is also discussed, as this may have significant influence on the forces when using tools with more than one tooth. The article ends with a conclusion, in which some notes about the practical application of the algorithm are given. © 2016 by ASME.

Geometric physically-based simulation systems for milling processes can provide the possibility to analyze and predict characteristically behaviors of a certain process. The parametrization of the simulation models is a crucial task when optimizing the quality of the simulation prediction. In order to determine tool load, process forces have to be calculated. Thus, the parametrization of the cutting force model that is mainly subject to the processed material and tool characteristics has a versatile impact on the simulation results. However, the tool state is expected to be constant within common milling simulations and therefore tool state variations like several tool wear effects are not represented. The tool state is defined through the geometric constitution of the cutting edges of the tool. This paper aims to analyze tool wear effects by re-calibrating the parameter values of the force model within the simulation system. To validate the simulation system, several milling experiments were conducted. In order to induce a fast change of the tool state within the process and to provoke high tool loads, the powder metallurgic high speed steel 1.3344 was machined. Advanced surrogate modeling techniques from the design and analysis of computer experiments (DACE) were applied to analyze the contribution of the force model parameter values. The fitting of the surrogate model is performed by means of sequential design of experiments. This allows the retrieval of sets of fitting parameter combinations for each tool state with a relatively small amount of simulation runs compared to genetic algorithms or gradients based methods. The surrogate models are exploited to analyze the behavior of the force model parameter values over the varying tool states. Approaches for further research are recommended and potential practical applications are discussed. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

Sheet-Bulk Metal Forming (SBMF) allows the manufacture of complex parts with integrated functional form elements, such as teeth and thickened areas. Therefore, bulk forming operations are applied to sheets with initial thicknesses of 2 or 3 mm. The design and functionality of the tools are as important as the process itself. Therefore, the working group "Tools" of the Transregional Collaborative Research Centre on Sheet-Bulk Metal Forming (CRC/TR73) focuses on the optimization of the technical tool design. By varying topographies or applying tailored coatings, the friction behavior is changed to achieve a better form filling and to reduce process forces during the forming operations. In this paper, the potential of different tailored surfaces is validated by simulations and experimental studies. The tribological behavior of 14 surface microstructures is evaluated using a half-space model in order to select structures suitable for application. Those were characterized experimentally by ring-compression and pin-extrusion tests. The determined friction factors were used in a forming simulation to predict the form filling of small cavities in a flow forming operation. Furthermore, special attention is paid to the utilization of the anisotropic behavior of specific structures. The results were validated by an incremental gear forming process. © 2016, German Academic Society for Production Engineering (WGP).

WC-W2C iron based cermet coatings are widely used in the field of wear protection. In surface engineering, machine hammer peening (MHP) is a novel surface treatment technology, which enhances the surface properties, especially for surfaces in tribological contact. In this study, the wear behavior of peened WC-W2C FeCrCMnSi arc sprayed coatings is characterized and compared to conventional coatings under as-sprayed conditions. The resulting strain hardening effects were measured by mechanical response using nanoindentation. In addition, residual stresses at the surfaces were determined using X-ray diffraction and the sin2ψ method. © 2016 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

Fixtures are an essential element of the machining system, being part of the precision path and force flux between process and machine tool. Intelligent fixtures enable the identification of critical process conditions, a compensation of error influences and the minimization of defective parts. At first, this contribution presents a study in which the influence of the clamping setup and of the workpiece characteristics at various steps of the machining process is analyzed. Experimental and theoretical results regarding the dynamic process behavior reveal the relevance of these influences with respect to machining performance and workpiece quality. Secondly, the European research project INTEFIX is introduced. Representative approaches of intelligent fixtures, reducing workpiece vibrations and distortions, and improving workpiece alignment, are described and prototypes are shown. In a third part, two examples of intelligent fixtures are presented and discussed more in detail. The first example concerns a fixture for the identification and active mitigation of chatter in milling of thin walled workpieces. The second example is related to the compensation of workpiece distortions which occur in machining of large thin walled structural parts. © 2016 The Authors.

In milling of impellers and blisks, critical workpiece vibrations of thin-walled blade structures occur due to the excitation by the process forces and the dynamic compliance of the sensitive elements of the parts. Workpiece vibrations lead to an inacceptable waviness and chatter marks on the blade surfaces and thus to the production of defective parts. Also, these vibrations provoke an increased tool wear progress. Within the European collaborative research project INTEFIX, fixture solutions are developed which enable the detection and compensation of chatter vibrations during machining of thin-walled workpiece elements. With respect to the machining of impeller blades, a challenging task is to identify critical vibrations by means of sensors which are integrated into the structure of the fixture or the contact surface between the workpiece and clamping system. This contribution introduces the integration and application of piezo patch transducers which are embedded in CFRP fixture components. The sensory CFRP sub-structure is located directly at the workpiece and pre-stressed by the clamping. Tests show the functionality and performance of the sensor system. In addition, the sensor integrated fixture is investigated in machining analyses. (C) 2016 The Authors. Published by Elsevier Ltd.

Milling processes for the manufacturing of parts for aerospace applications can be influenced by various effects. When machining structural parts with high material removal rates, the stiffness of the machine tool can be a limiting factor because chatter vibrations. Additionally, vibrations of thin-walled structures, e.g., the blades of impellers or turbines, can lead to chatter vibrations and surface location errors. Thermo-mechanical deformations are another cause for violations of given shape tolerances. Geometric physically-based process simulations can be used to analyze milling processes with regard to these effects in order to optimize the process parameters. In this paper, an overview of several applications of a geometric physically-based simulation system for analyzing different effects during milling processes is presented. Depending on the relevant effects, process forces, the dynamic behaviour of the tool-spindle-machine system, vibrations of workpieces and fixture systems, as well as thermo-mechanical deformations are calculated. (C) 2016 The Authors. Published by Elsevier B.V.

The mechanical wear behavior of forming tools is the limiting factor during an incremental gear-forming process. These forming tools with a simply shaped geometry are exposed to high forming forces. Additionally, the necessary workpiece chambering, which is characteristic for this incremental process restricts the dimensioning of the tools. Thereby, the geometrical design of the forming tools is limited, which leads to a decreased lifetime. Functional structures on the tool surfaces can influence the occurring loading and wear behavior by reducing the contact area, the supply of lubricant pockets, and by a controlled influence and adjustment of the occurring material flow. For the extension of the tool's lifetime, different surface concepts and combinations with CrAlN PVD-coatings are investigated. To offer conditions with a high tool load, the investigations are focused on an incremental gear forming process with a simple one-wedge forming tool. The results show abrasive and adhesive wear characteristics, as well as outbreaks, and crack formations. The crack propagation on the flank leads to a chipping of the tool tip, hence limiting the tool life. Compared to the reference tool, a surface structure combined with a PVD-coating provides a significant increase of the tool life of 84%. © 2016 Elsevier Ltd

The selection of process parameter values for homing operations is challenging since their effect on the resulting surface characteristics is difficult to predict. With the right settings, the finishing operations can reduce surface roughness values, enhance the shape accuracy of bores and shafts, and create surface topographies with improved functional properties. In this paper, a model for honing operations based on microscopic scans of tool topographies is presented. The model allows the simulation of material removal during the process by taking force-controlled honing operations into account. © 2014 The Authors. Published by Elsevier B.V.

In 2011, a round robin test was initiated within the group of CIRP Research Affiliates. The aim was to establish a platform for linking interdisciplinary research in order to share the expertise and experiences of participants all over the world. This paper introduces a testpart which has been designed to allow an analysis of different manufacturing technologies, simulation methods, machinery and metrology as well as process and production planning aspects. Current investigations are presented focusing on the machining and additive processes to produce the geometry, simulation approaches, machine analysis, and a comparison of measuring technologies. Challenges and limitations regarding the manufacturing and evaluation of the testpart features by the applied methods are discussed. © 2014 The Authors. Published by Elsevier B.V.

The performance of technological surfaces can be optimized via tailored characteristics according to their specific field of usage. These high performance surfaces are needed for the new technology of Sheet-Bulk Metal Forming (SBMF), which is a combination of sheet metal and bulk forming operations. Due to the high surface loads of bulk forming operations, tool surfaces need to be capable to withstand high stress states. Additional to a high wear resistance, the friction coefficient of these surfaces is an important criterion for the material flow of the sheet material. Surface characteristics can be adjusted by using technologies such as high-feed and micromilling processes resulting in different friction coefficients optimizing functional performance of the tools. In dependency of these different manufacturing processes, different residual stresses are induced into the subsurface of the forming tool. Reliability of residual stress measurements via X-ray diffractometry for microstructured surfaces produced through high-feed milling and micromilling is investigated. © Carl Hanser Verlag GmbH & Co. KG.

During grinding processes, numerous grains interact with the workpiece material producing mechanical and thermal loads on the surface. In the field of thermal simulation of grinding processes, a widely used approach is to substitute numerous cutting edges by a single moving distributed heat source of a specific geometrical shape referring to the theory of Carslaw and Jaeger. This heat source is then moved across the modelled workpiece according to the specific kinematics of the grinding process. The geometrical shape of the substituted heat source can usually be determined using different approaches, e. g., predefined distribution functions or, more precisely, based on measurements of the shear stress within the contact zone. Referring to the state of the art, it is not possible to measure the shear stress within the contact zone during internal traverse grinding with roughing and finishing zone because of its very complex engagement conditions and the non-rectangular shape of its contact zone. In this work, a novel approach to determining a heat source distribution based on a geometric-kinematic simulation for internal traverse grinding is presented. This simulation identifies the ideal geometrical interaction of workpiece and grinding wheel. For this purpose, the specific material removal rate for each grain is calculated and accumulated with respect to the contact zone resulting in a three-dimensional thermal load distribution. This heat source can be used in finite element simulations to determine the thermal load on the workpiece. © 2015 The Authors. Published by Elsevier B.V.

Forming of near-net-shaped and load-adapted functional components, as it is developed in the Transregional Collaborative Research Centre on Sheet-Bulk Metal Forming SFB/TR 73, causes different problems, which lead to non-optimal manufacturing results. For these high complex processes the prediction of forming effects can only be realized by simulations. A stamping process of pressing eight punches into a circular blank is chosen for the considered investigations. This reference process is designed to reflect the main aspects, which strongly affect the final outcome of forming processes. These are the orthotropic material behaviour, the optimal design of the initial blank and the influences of different contact and friction laws. The aim of this work is to verify the results of finite element computations for the proposed forming process by experiments. Evaluation methods are presented to detect the influence of the anisotropy and also to quantify the optimal blank design, which is determined by inverse form finding. The manufacturing accuracy of the die plate and the corresponding roughness data of the milled surface are analysed, whereas metrological investigations are required. This is accomplished by the help of advanced measurement techniques like a multi-sensor fringe projection system and a white light interferometer. Regarding the geometry of the punches, micromilling of the die plate is also a real challenge, especially due to the hardness of the high-speed steel ASP 2023 (approx. 63 HRC). The surface roughness of the workpiece before and after the forming process is evaluated to gain auxiliary data for enhancing the friction modelling and to characterise the contact behaviour. © 2015 Trans Tech Publications, Switzerland.

Due to friction and material deformation in the shear zone, workpieces in NC-milling processes are subjected to heat input and thermal loading. Ongoing geometric changes as well as time-varying contact and cutting conditions result in an inhomogeneous temperature field that is constantly in flux. Such thermally loaded workpieces often exhibit complex and transient thermomechanical deformations, which may result in erroneous material removal with respect to the desired shape. In order to meet critical manufacturing tolerances, it is therefore necessary to avoid and compensate these effects. Predicting the deformation exhibited by a thermally loaded workpiece is a problem of linear thermoelasticity, which can be solved by use of the finite element (FE) method. A prerequisite to this is the accurate calculation of the temperature field that results within the workpiece material during the course of the milling process. Although the FE method may be used for this as well, the practical application to realistic milling processes is limited due to the required computational resources. This paper presents a fast geometric process simulation for the prediction of cutting forces, heat input and thermal loading in dry NC milling. The temperature field of the workpiece is continuously updated, such that it is possible to determine the temperature of any material point at any point in time of the milling process. Individual models comprising the simulation system are described in detail, along with the experiments that are required to calibrate them. The accuracy of the geometric process simulation is validated by comparison with experimental data for a non-trivial milling process. © 2015, German Academic Society for Production Engineering (WGP).

The increasingly investigated and applied production process sheet-bulk metal forming (SBMF) has novel requirements for the forming tools, e.g., the need of an adaptive material flow at different areas of the tool for an adequate form filling. One new method to realize different, defined tribological conditions are tailored surfaces (TS). During the design of forming tools, it is imperative to have profound knowledge about the tribology between the tool and the workpiece. This article introduces structuring with high-feed milling tools as one possibility for influencing the material flow during forming processes and presents a ring-compression test for the quantification of the tribological conditions, which is adapted for SBMF. On the basis of various machined structures, surface parameters are analyzed to identify a correlation with the friction coefficient to gain knowledge about the mechanisms of TS and to be able to choose structures according to the needs of SBMF processes. © 2014, German Academic Society for Production Engineering (WGP).

In the machining of large structural components such as those used in the construction of airplanes, most of the material is removed, while at the same time, a large amount of heat is inserted into the workpiece. During roughing operations in dry milling, the thermal load can lead to workpiece distortions that result in a violation of the manufacturing tolerances of the finished part. Although the variation of process parameter values and milling strategies can influence and significantly reduce the thermal loading, effects such as chatter or limitations of the machine also have to be taken into account. In this paper, the interrelation between process parameter values and dynamic tool behavior is investigated, as both have a large influence on the thermal loading of the workpiece. Milling with a high material removal rate typically results in a lower heat input into the workpiece, but this approach is limited and may lead to process instabilities, manifested in chatter of the tool. In this paper, a basic experimental analysis for the influencing process parameters feed per tooth fz, axial immersion ap, radial immersion ap, and spindle speed n is conducted, and the effects of chatter on the thermal loading of the workpiece is analyzed by experiment. A geometric simulation of the milling process is utilized in order to reduce the experimental effort, as well as to to increase the knowledge of the heat input mechanisms. The simulation system is able to calculate the transient dynamic behavior of the tool with high accuracy and can therefore be used to predict the process stability in advance. Additionally, a thermal model is used to simulate the temperature of the workpiece material during the dry milling process. © 2015 Authors. Published by Elsevier B.V.

In this chapter, applications of computational intelligencemethods in the field of production engineering are presented and discussed. Although a special focus is set to applications in machining, most of the approaches can be easily transferred to respective tasks in other fields of production engineering, e.g., forming and coating. The complete process chain of machining operations is considered: The design of the machine, the tool, and the workpiece, the computation of the tool paths, the model selection and parameter optimization of the empirical or simulation-based surrogate model, the actual optimization of the process parameters, the monitoring of important properties during the process, as well as the posterior multicriteria decision analysis. For all these steps, computational intelligence techniques provide established tools. Evolutionary and genetic algorithms are common networks. Fuzzy logic represents an intuitive way to formalize expert knowledge in automated decision systems. © Springer-Verlag Berlin Heidelberg 2015.

Honing operations are primarily applied to enhance tribologically loaded surfaces. In order to reduce the experimental effort during process design and optimization, a prediction of the specific surface topography resulting from a particular honing operation is necessary. Therefore, a high-resolution geometric process model for force-controlled honing operations was developed, which utilizes numerical data of tools and workpieces from topographic scans. In this paper, the modeling approach is presented and applied to a micro-finishing process with different process parameter values. The simulation results are also compared to surface topographies generated in experiments in order to validate the simulation model. © 2015 CIRP.

Simulation systems are used to optimize milling processes by analyzing surface location errors, which can be predicted by combining various modeling techniques in a multi-scale way. In order to visualize surface location errors, a multi-dexel representation of the workpiece can be used. The application of a triangle mesh representation of the tools to cut the workpiece model is presented, which results in a higher accuracy of the predicted surface location errors in comparison to a Constructive-Solid-Geometry-(CSG)-based approach. Both models are evaluated by simulating a milling process and the simulation results are validated by comparing them to experimental results. © 2015 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license.

In this work, we focus on the computational bridging between the meso- and macro-scale in the context of the hybrid modelling of Internal Traverse Grinding with electro-plated cBN wheels. This grinding process satisfies the manufacturing industry demands for a high rate of material removal along with a high surface quality while minimising the number of manufacturing processes invoked. To overcome the major problem of the present machining process, namely a highly concentrated thermal load which can result in micro-structural damage and dimension errors of the workpiece, a hybrid simulation framework is currently under development. The latter consists of three components. First, a kinematic simulation that models the grinding wheel surface based on experimentally determined measurements is used to calculate the transient penetration history of every grain intersecting with the workpiece. Secondly, an h-adaptive, plane-strain finite element model incorporating elasto-plastic work hardening, thermal softening and ductile damage is used to simulate the proximity of one cBN grain during grinding and to capture the complex thermo-mechanical material response on a meso-scale. For the third component of the framework, the results from the preceding two simulation steps are combined into a macro-scale process model that shall in the future be used to improve manufacturing accuracy and to develop error compensation strategies accordingly. To achieve this objective, a regression analysis scheme is incorporated to approximate the influence of the several cutting mechanisms on the meso-scale and to transfer the homogenisation-based thermo-mechanical results to the macro-scale. © 2015, German Academic Society for Production Engineering (WGP).

In dry NC milling, a significant amount of heat is introduced into the workpiece due to friction and material deformation in the shear zone. Time-varying contact conditions, relative tool–workpiece movement and continuous geometric change of the workpiece due to material removal lead to a perpetually changing inhomogeneous temperature distribution within the workpiece. This in turn subjects the workpiece to ongoing complex thermomechanical deformations. Machining such a thermally loaded and deformed workpiece to exact specifications may result in unacceptable shape deviations and thermal errors, which become evident only after dissipation of the introduced heat. This paper presents a hybrid simulation system consisting of a geometric multiscale milling simulation and a finite element method kernel for solving problems of linear thermoelasticity. By combination and back-coupling, the described system is capable of accurately modeling heat input, thermal dispersion, transient thermomechanical deformation and resulting thermal errors as they occur in NC milling processes. A prerequisite to accurately predicting thermomechanical errors is the correct simulation of the temperature field within the workpiece during the milling process. Therefore, this paper is subjected to the precise prediction of the transient temperature distribution inside the workpiece. © 2014, German Academic Society for Production Engineering (WGP).

An established concept adjusting tribological properties and for increasing the wear resistance is presented by coatings. In addition to the material adaption of surfaces, there are efforts of applying structures on tool active parts in order to allow a further adjustment on the property profile. For this reason, the presented article investigates the influence of bionic and technologically textured surfaces on the friction and wear behavior with and without near-net shaped wear-resistant PVD coatings. Based on the example of nature, a honeycombed surface structure discovered on the head of scarab beetles as well as a dimple structure optimized for the manufacturing time were transferred on HSS steel by means of micro-milling. The analyses focus on the influence of the surface structures, the effects of PVD coatings and their interactions on the friction and wear behavior. The investigations show that the tribological properties depend on each surface structure and the material pairing. Both the technological and the bionic structures show a reduction of the friction coefficient in combination with the material pairing 100Cr6 and WCCo compared to polished samples. Furthermore, it is shown that the CrAlN coating has no influence on the friction behavior, but rather leads to the desired increase in the wear resistance. © 2015 Wiley-VCH Verlag GmbH & Co. KGaA, Weinheim.

Surface modification by means of textured structures can largely enhance the tribological and wear behavior of components and tools under various environmental conditions. Continuous developments in machining processes, such as the micromilling technology, can be used to manufacture fine-scaled structures on hardened steel tool surfaces. Thus, the adjusted friction behavior, which can affect the tendency of a material to adhere to the surface, is compensated by the small number of contact points between the friction partner and the surface. Accordingly, anisotropic friction properties of such structures can lead to a locally different wear behavior. In this study, a NiCrBSiFe self-fluxing alloy is thermally sprayed onto specimens made of AISI M2 high-speed steel (HSS). Technological and bionic surface structures were applied on thermally sprayed and laser remelted substrates. Based on ball-on-disk tests, the coefficient of friction was determined and compared for different high velocity oxy fuel (HVOF) sprayed NiCrBSiFe coatings and surface textures. These experiments show that functional structures can reduce the coefficient of friction. The bio-inspired surface shows a friction reduction of approximately 35% compared to the as-sprayed and polished sample, and a reduction of 25% when compared to the remelted and smoothened surface. Moreover, the analyzed surface conditions lead to a different wear behavior than the bio-inspired structure, which possesses areas with a reduced oxidational wear and less adhesion when compared to the other surface conditions. © 2015 Elsevier B.V.

The abrasive-wear resistance and the lifetime of tribologically stressed free-formed surfaces of forming tools can be increased by thermally sprayed tungsten carbide coatings. In order to improve the surface quality and the shape accuracy, the workpieces must be machined prior to industrial application. A suitable machining process is NC grinding on five-axis machining centers using abrasive mounted points. However, the high hardness of the applied coatings and the small diameter of the utilized tools pose a great challenge for the process design. In order to optimize the grinding process and predict the resulting surface topography, a geometric-kinematic simulation based on the modelling of individual grains using Constructive Solid Geometry techniques was developed. In this paper, the results of fundamental investigations on grinding tungsten carbide coatings and the developed process simulation are presented. © (2014) Trans Tech Publications, Switzerland.

Thermally sprayed coatings and tribological surfaces are a point of interest in many industrial sectors. They are used for better wear resistance of lightweight materials or for oil retention on surfaces. Lightweight materials are often used in the automotive industry as a weight-saving solution in the production of engine blocks. For this, it is necessary to coat the cylinder liners to ensure wear resistance. In most cases, the coating is sprayed directly onto the surface. Previous research has shown that it is possible to transfer these coatings inversely onto other surfaces [1]. This was achieved with plasma sprayed coatings which were transplanted onto pressure-casted surfaces. These transplanted surfaces exhibited better adhesive strength, smoother surfaces, and lower form deviation compared to directly coated surfaces. Additionally, it was shown that even microstructures of a surface coated by plasma spraying can be transferred to pressure-casted surfaces. This paper presents the development and micromilling of different microstructures for transferring thermally sprayed coatings onto pressure-casted surfaces. In the development process, microstructures with different shapes and aspect ratios as well as thin tribological surfaces are designed in order to evaluate the advantages and limitations of the transplantation process. In subsequent experiments, the micromilling process and a simulation of the coating transplantation are presented and analyzed. © 2014 Published by Elsevier B.V.

The abrasive wear resistance of tribologically stressed free-formed surfaces can be increased with thermally sprayed tungsten carbide coatings. In order to improve the surface topographies and shape accuracies, the workpieces must be finished prior to industrial application. A suitable machining process is NC grinding on five-axis machining centres using abrasive mounted points. However, the high hardness of the applied coatings and the small diameter of the utilized tools pose a great challenge for the process design. In this paper both, the results of fundamental investigations on the grinding of tungsten carbide coatings as well as a process optimization for the finishing of a coated forming tool are presented. This includes the heat transfer into the coating and the tool wear during the grinding process as well as the wear behaviour of the coating in dependence of the generated surface topography. In order to achieve a smooth surface, elastic-bonded diamond tools were used during polishing in a multi-stage machining process. © 2014 German Academic Society for Production Engineering (WGP).

Deep drawing tools are used in various production processes. In order to increase the life cycle of these tools, thermally sprayed abrasive-wear resistant WC-Co hard material coatings can be applied. With respect to the shape accuracy and surface quality of the forming tools, the coated surfaces have to be finished. A suitable machining process to meet these conditions is grinding on machining centers. In this paper, a geometric simulation model for this grinding process based on the modeling of individual grains with constructive solid geometry techniques is presented. The workpiece is represented by poisson-disk sampled dexels. Validation experiments show a good match of the simulated and measured process forces in different engagement situations. © 2014 CIRP.

In case of manufacturing miniaturized products with 3D features, micromachining is a suitable technology. By using a five-axis process, it is possible to produce complex products with high material removal rates. Further benefits are, for example, higher tool stiffness due to the possibility of utilizing tools with shorter cantilever lengths and higher surface qualities, which can be achieved by avoiding cutting with the center of the tool when using ball-end milling cutters. A tool inclination can not only be used to avoid the center cut in the five-axis process, but also to achieve better cutting conditions. In this paper, the influence of the tool inclination is analyzed for micromilling hardened high-speed steel (S6-5-2, 63 HRC). The presented results show the possibility of reducing tool wear and achieving better surface qualities by applying a specific tool inclination. This knowledge can be used to generate optimized NC programs for the five-axis micromilling of hardened steels. © 2014 Published by Elsevier B.V.

Due to the time- and position-dependent dynamic behavior of the workpiece, the prediction of process dynamics during the five-axis milling of thin-walled free-formed surfaces is a challenge from the modeling point of view. In this paper, three different techniques for modeling workpiece deflections and their integration into a system for simulating the NC milling process will be discussed by means of analyzing the machining of a turbine blade. © 2013 CIRP.

The wear-resistance of sheet metal forming tools can be increased by thermally sprayed coatings. However, without further treatment, the high roughness of the coatings leads to poor qualities of the deep drawn sheet surfaces. In order to increase the surface quality of deep drawing tools, grinding on machining centers is a suitable solution. Due to the varying engagement situations of the grinding tools on free-formed surfaces, the process forces vary as well, resulting in inaccuracies of the ground surface shape. The grinding process can be optimized by means of a simulative prediction of the occurring forces. In this paper, a geometric-kinematic simulation coupled with a finite element analysis is presented. Considering the influence of individual grains, an additional approximation to the resulting topography of the ground surface is possible. By using constructive solid geometry and dexel modeling techniques, multiple grains can be simulated with the geometric-kinematic approach simultaneously. The process forces are predicted with the finite element method based on an elasto-plastic material model. Single grain engagement experiments were conducted to validate the simulation results. © 2014 German Academic Society for Production Engineering (WGP).

This paper presents an overview of recent developments in simulating machining and grinding processes along the NC tool path in virtual environments. The evaluations of cutter-part-geometry intersection algorithms are reviewed, and are used to predict cutting forces, torque, power, and the possibility of having chatter and other machining process states along the tool path. The trajectory generation of CNC systems is included in predicting the effective feeds. The NC program is automatically optimized by respecting the physical limits of the machine tool and cutting operation. Samples of industrial turning, milling and grinding applications are presented. The paper concludes with the present and future challenges to achieving a more accurate and efficient virtual machining process simulation and optimization system. © 2014 CIRP.

Polymer composites of self-reinforced fibres and a matrix composed of the same plastic material display an outstanding mechanical performance and an excellent recyclability. Hence, these materials are suitable for many practical applications. One disadvantage, however, is the narrow processing window that is caused by a strong pressure and temperature sensitivity of the self-reinforced fibres. In this paper, an approach to efficiently model the spatial and temporal temperature evolution is presented. Advanced empirical modelling techniques from the design and analysis of computer experiments are fitted to experimental data. It is shown that only a small set of experiments has to be performed in order to predict the temperatures with the desired accuracy. The required enhancements with respect to the design of experiments and the empirical models are presented.

Thermally sprayed coatings offer a promising approach as efficient method to increase the wear-resistance of sheet metal forming tools. However, the roughness of thermally sprayed surfaces is quite high. The use of these coatings for deep drawing tools results in poor sheet surface qualities and low drawing ratios. Because it is suspected that high friction is the reason for the low drawability, hard metal coatings (WC-12Co), deposited by high velocity oxygen fuel flame-spraying, were machined by grinding and ball burnishing to improve their friction behavior and the accuracy of the tool shape. The investigation was conducted by plane strip drawing tests. Strips of high strength steel were mated with these novel and effective coatings at different normal contact pressures and drawing velocities. Uncoated friction elements made of C60 steel were considered as reference during the analysis. The results revealed that coated but unmachined friction elements showed high friction values, which led to scratch marks on the sheet surface after drawing. Applying the finishing processes, the friction coefficient could be reduced significantly. Additionally, deep drawing tests were carried out to determine the drawing ratio for coated, unmachined as well as for processed, coated dies. Thermally sprayed and ball burnished as well as thermally sprayed and ground coatings are feasible for deep drawing. Due to the post treatment, the drawing ratio β = 1.8 was increased to 2.0. This is consistent to the results of the friction tests. © 2013 German Academic Society for Production Engineering (WGP).

The dynamic process behavior during milling often leads to vibrations or even chatter and, thereby, to surface location errors. In this paper, a multi-scale simulation system is presented, which can predict these errors efficiently by combining a dexel-based workpiece representation with a CSG-based process model and an oscillator-based system for the process dynamics. The different modeling techniques are described, and the run-time of the combined system is compared to a single-scale system in which the CSG-based model is used for every process step. Furthermore, the simulation is validated by examining the generated surface of a micromachined workpiece.

Sheet-bulk metal forming is an innovative process with a high potential to generate load-adapted parts with high precision. Bulk forming processes of sheet metals especially require high process forces, resulting in an intense contact pressure and, thus, in a very high abrasive and adhesive wear. As a method to reduce or avoid these common wear phenomena, even hardened or coated tool surfaces are not sufficient. The objective of this paper is to show an improvement of the tool resistance during an incremental forming process by an adapted tool design and the application of structured tool surfaces combined with coatings. For the tool surface the structure of the scarabaeus beetle serves as the basis for a bionic structure. This structure was manufactured by micromilling. Despite the high hardness of the tool material and the complex geometry of the forming tools, very precise patterns were machined successfully using ball-end milling cutters. The combination of bionic structures with coating techniques like physical vapor deposition (PVD) on plasma nitrided tool surfaces is very promising. In this work, the influence of process parameters (workpiece material, lubrication, tool design, stepwise infeed) on the tool resistance during the forming operation was analyzed experimentally. The results of the optimized forming tools were compared to conventional, unstructured, uncoated, and only plasma nitrided forming tools. The different tools were applied to 2 mm thick metal sheets made of aluminum (AlMg3) and steel (nonalloy quality steel DC04). As a result, the process forces could be reduced by a modified shape and surface of the tools. Thus, the lifetime of the tools can be enhanced. Copyright © 2013 Trans Tech Publications Ltd.

Oscillator models provide an efficient approach for simulating the dynamic behaviour of the machine, tool, or workpiece. In their application, however, these models are usually limited to describing the vibration behaviour at one specific position since they do not contain any information about the structure of the machine tool or the workpiece. Additionally, the variation in time dependent parameters caused by the material removal process is not taken into account. In this paper, an adapted model, which takes the position- and time-dependent modal parameters during NC milling into account, is presented and its experimental validation with respect to the machining of thin-walled components is discussed. © 2013 German Academic Society for Production Engineering (WGP).

The main goal in the design of milling processes for components in the aerospace industry is the optimization of productivity while maintainig process stability. These two goals can be conflicting, especially if long tools are required, which are particularly susceptible to vibrations. In order to reduce the number of costly experiments, simulation-based approaches can be used to evaluate generated NC programs beforehand. In this paper, a modeling approach for the detailed simulation of engagement conditions, process forces, and dynamic tool behavior is used to detect instable process conditions. Additionally, an algorithm is presented to change the axial immersion in order to avoid regenerative chatter during milling. To demonstrate the effectiveness of the simulation approach and of the compensation strategy, a comparison is shown between experimental and simulated results and between the workpiece generated by the original and the optimized NC programs.

During roughing in NC milling, heat is introduced into the workpiece. For the manufacturing of large structural components, a constantly changing temperature field is created due to the rapid movement and the varying contact conditions between tool and workpiece. Therefore, significant deformations can cause form errors that lead to rejects in the production process. In this paper, a simulation system for the prediction of transient workpiece temperatures is presented. In order to calibrate the system, simple experiments have been conducted, and a model for the introduction of energy into the workpiece via cutting has been developed. The newly developed cutting-energy input model makes it possible to perform fast simulations. Therefore, it can be used to perform simulations of the thermoelastic workpiece deformations during milling of complex shaped parts. Copyright © 2013 Elsevier B.V.

Due to the characteristics of the milling process, modeling workpiece dynamics during the machining of freeform surfaces is a challenge: The relative movement between the milling tool and the workpiece leads to a variation of the excitation position, and the material removal process results in changing modal parameters of the workpiece. In this paper, an ongoing work is discussed dealing with different modeling techniques for the prediction of workpiece deflections: a finite element model, a particle-based approach, and an oscillator-based technique. These three methods and their integration into a simulation system for the modeling of NC milling are presented and discussed by simulating the machining of a turbine blade. c- 2012 Published by Elsevier B.V. Selection and/or peer-review under responsibility of Dr. Ir. Wessel W. Wits. © 2012 Published.

During the machining of thin-walled components, the dynamic behavior of the workpiece has a significant influence on the machining process and on the quality of the machined surfaces. In this article, a hybrid simulation concept for modeling regenerative workpiece vibrations is presented, which couples a geometric workpiece model with sets of decoupled harmonic oscillators to take the workpiece dynamics into account. © 2012 Copyright Taylor and Francis Group, LLC.

During the grinding of hard materials using cylindrically and spherically shaped mounted points - like for the machining of complex forming tools with abrasive-wear-resistant coatings - the process force is an important factor influencing the accuracy of the machining outcome. A simulation-based prediction of these forces could be used to adapt the tool path and, thereby, to keep the grinding forces at a low level. In this paper, a simulation system based on the modeling of each grain of the grinding tool and the validation of this simulation model are presented. © 2012 The Authors.

During the micromachining of hardened materials, the low stiffness of the milling tool results in an increased tool deflection which has a great influence on the shape and dimensional accuracy of the machined components. In order to compensate these deflections, an optimization method is presented in this paper. Based on measured form errors of the machined workpieces, the NC programs are optimized iteratively to reduce the shape deviations. To verify this method, experimental investigations were carried out by milling pockets in hardened steel. The results show a significant reduction of the tool deflection after the optimization. © 2012 The Authors.

The layout of temperature control systems for moulds is decisive for the performance and stability of the production process. A design and optimisation approach for temperature control systems is introduced, coping with geometric constraints and complex thermal dependencies and allowing a significant reduction of manufacturing costs. Five-axis milling processes are increasingly used for the production of moulds in order to achieve high surface qualities and low manufacturing times. The CAM-programming required for the milling of free-formed surfaces in this field is complex and error-prone. An approach is shown, which automatically generates five-axis NC-paths from existing error-free three-axis paths. Copyright © 2011 Inderscience Enterprises Ltd.

Workpiece vibrations have a significant influence on the machining process and on the quality of the resulting workpiece surface, particularly when milling thin-walled components. In this paper a simulation system, consisting of an FE model of the workpiece coupled with a geometric milling simulation for computing regenerative workpiece vibrations during the five-axis milling process, is presented. Additionally, a modeling method for visualizing the resulting surface is described. In order to validate the simulation model, turbine blades were machined and the experimental results were compared to the simulation results. © 2010 CIRP.

During the milling process of flexible structures, such as thin-walled profiles manufactured for the aerospace industry, the dynamic behavior of the workpieces can become a key factor that limits the productivity of the machining process. Therefore, knowledge of the dynamic characteristics of the components prior to the milling process is important and provides the possibility to choose appropriate values for the process parameters. The experimental modal analysis is an adequate procedure to study the dynamic properties of components under vibrational excitation. In this process, the response of the structure is measured at defined points under controlled conditions when the structure is artificially excited by an input force. In case of thin-walled components, the response should be measured in a contactless way using laser systems to avoid the disturbance of the moving sensor mass. In order to design this process to be manageable, a device was designed connecting the laser system to the spindle of the milling machine. In this paper, the device, the experimental setup, and the software developed for programming corresponding NC paths are presented. The practicability of the system is also demonstrated analyzing the dynamic behavior of a turbine blade on a five-axis milling machine. © 2010 Springer-Verlag France.