Modeling of the Thermomechanical Process Effects on Machine Tool Structures

AbstractThermally induced deviations are a key issue in the development of machine tools, especially when considering the actual trends of high performance and dry cutting. The interactions between the cutting process and the machine tool structure are significant boundary conditions for the numerical prediction of the thermomechanical machine behavior. Within this paper an approach for the holistic modeling of process effects is presented, including process heat, cutting forces and increased load on feed and main drives. The modeling approach is supported by experimental investigations on a lathe to provide empiric data for the link between cutting forces and active drive power

A Concept For The Development Of A Maturity Model For The Holistic Assessment Of Lean, Digital, and Sustainable Production Systems

Manufacturing companies today face a volatile environment with a variety of challenges. Particularly, external factors such as the climate change, the digitalization, the material scarcity, or the shortage of skilled workers can be noted. At the same time, these factors are forcing companies to take measures to remain competitive and ensure their production system's future viability. In this context, established paradigms such as Lean Production and Industry 4.0 promise optimization potentials in terms of efficiency, quality, and costs. A new paradigm has gained importance with the emergence of the topic of sustainability, which aims to improve companies' use of resources and the recyclability of their products. However, there is no transparent model that enables companies to assess the status quo of their production system regarding these three paradigms, considering the interdependencies between the paradigms, and at the same time showing the implementation potential of methods or technologies within these paradigms. To support companies in rationalizing, digitalizing, and making their production processes more sustainable, this scientific paper presents a three-stage concept for a holistic maturity model. By providing transparency about the status quo of production systems in terms of Lean Production, digitalization, and sustainability, the model contributes to ensuring the future viability of such production systems in this highly competitive environment and under the political, social, and regulatory challenges

Towards Additively Manufactured Metamaterials with Powder Inclusions for Controllable Dissipation: The Critical Influence of Packing Density

Particle dampers represent a simple yet effective means to reduce unwanted oscillations when attached to structural components. Powder bed fusion additive manufacturing of metals allows to integrate particle inclusions of arbitrary shape, size and spatial distribution directly into bulk material, giving rise to novel metamaterials with controllable dissipation without the need for additional external damping devices. At present, however, it is not well understood how the degree of dissipation is influenced by the properties of the enclosed powder packing. In the present work, a two-way coupled discrete element - finite element model is proposed allowing for the first time to consistently describe the interaction between oscillating deformable structures and enclosed powder packings. As fundamental test case, the free oscillations of a hollow cantilever beam filled with various powder packings differing in packing density, particle size, and surface properties are considered to systematically study these factors of influence. Critically, it is found that the damping characteristics strongly depend on the packing density of the enclosed powder and that an optimal packing density exists at which the dissipation is maximized. Moreover, it is found that the influence of (absolute) particle size on dissipation is rather small. First-order analytical models for different deformation modes of such powder cavities are derived to shed light on this observation

Methodology to Determine Melt Pool Anomalies in Powder Bed Fusion of Metals Using a Laser Beam by Means of Process Monitoring and Sensor Data Fusion

Additive manufacturing, in particular the powder bed fusion of metals using a laser beam, has a wide range of possible technical applications. Especially for safety-critical applications, a quality assurance of the components is indispensable. However, time-consuming and costly quality assurance measures, such as computer tomography, represent a barrier for further industrial spreading. For this reason, alternative methods for process anomaly detection using process monitoring systems have been developed. However, the defect detection quality of current methods is limited, as single monitoring systems only detect specific process anomalies. Therefore, a new methodology to evaluate the data of multiple monitoring systems is derived using sensor data fusion. Focus was placed on the causes and the appearance of defects in different monitoring systems (photodiodes, on- and off-axis high-speed cameras, and thermography). Based on this, indicators representing characteristics of the process were developed to reduce the data. Finally, deterministic models for the data fusion within a monitoring system and between the monitoring systems were developed. The result was a defect detection of up to 92% of the melt track defects. The methodology was thus able to determine process anomalies and to evaluate the suitability of a specific process monitoring system for the defect detection

Influence of process temperature on hardness of friction stir welded high strength aluminum alloys for aerospace applications

AbstractThe increasing application of innovative materials, such as high strength aluminum alloys, is challenging the manufacturing processes of the Aerospace and Aeronautics Industries. Despite this challenge the processes need to comply with high requirements regarding the reproducibility and the quality of the products. For this reason the adaption of conventional welding technologies to the new materials is considered to be difficult. Therefore, innovative welding technologies such as Friction Stir Welding (FSW) have been developed [1].This paper deals with the implementation of FSW into a new production process for lightweight dome structures of fuel tanks: Starting at temper condition O two AA 2219 plates are joined using FSW technology to form a larger blank. After that, the blanks are formed to shape using spinforming technology. The manufacturing process is accompanied by several steps of heat treatment to accomplish a finished tank-dome in temper condition T8.The studies presented in this paper aimed on finding a correlation between the process parameters and the properties of the welding seam, which are essential for the following spinforming process. For this purpose the experiments were conducted using design of experiments (DoE). The resulting hardness increase of the welding seam was chosen as target variable. Based on the acquired data a regression model was established and used to estimate optimal parameters for dome production

FINITE ELEMENT FORMULATION OF PRE-STRESSED BALL SCREW DRIVES

Keywords: Ball screw drive, finite element method, machine tool, mechatronic system. INTRODUCTION In the field of CNC drive technology for machine tools rotatory servo drive systems with ball screw transmission remain the predominantly used solution for generating linear feed motions, despite the increasing application of linear direct drives. Reasons for this include, in comparison to linear direct drives, their lower purchasing costs, greater feed forces in relation to the installation dimensions, higher efficiency, better heat dissipation, and reduced susceptibility to disturbance due to the thread transmission ratio. However, compliances are unavoidably given by the mechanical transmission system between the motor and the linear carriage and cause vibrations within the control path. For speed controlled servo drives, this limits the utilizable dynamic range of the control loop

Automated Identification of Linear Machine Tool Model Parameters Using Global Sensitivity Analysis

High-fidelity machine tool models are needed for condition monitoring, machine tool development, and process simulation. To accurately predict the dynamic behavior of their real counterparts, these models have to be identified, meaning that the values for the involved physical model parameters have to be found by comparing the model with measured data from its real counterpart. As of now, this can only be performed automatically for comparably simple models, which are only valid under limiting assumptions. In contrast, parameter identification for predictive high-fidelity models requires cumbersome manual effort in many intermediate steps. The present work addresses this problem by showing how to automatically identify the parameters of a complex structural dynamic machine tool model using global sensitivity analysis. The capability of the proposed approach is demonstrated in two steps for simulated reference data: first, with a model being able to perfectly replicate the reference data, and second, with a disturbed model, which can only approximate the reference because modeling is present. It is shown that, in both cases, globally valid model parameters, which lead to high conformity with the reference data, can be found, paving the way for calibrating models based on experimental reference data in future work

Process Integrated Production of WC-Co Tools with Local Cobalt Gradient Fabricated by Binder Jetting

Producing complex shaped tungsten carbide cobalt (WC-Co) tools by classical technologies is difficult and often impossible due to their high hardness and brittle fracture behavior. Additive Manufacturing (AM) is a suitable technology for creating complex structures and simultaneously shortening expensive machining processes. Binder Jetting (BJ) is an innovative AM technology that offers several advantages over laser-based processes, for example low manufacturing costs and high build-up rates. Binders with nanoparticle additives have already proven to be effective in increasing the packing density of the powder bed and improving the sintering properties. Additionally, they offer the possibility of selectively changing the material composition in the part. This paper presents a concept for the use of nanoparticles to generate gradients in the green compact, which leads to a cobalt gradient in the part after sintering. The possibility of introducing particles locally into complex structures allows local modification of the material properties.Mechanical Engineerin

The Prediction of Surface Error Characteristics in the Peripheral Milling of Thin-Walled Structures

Lightweight design is gaining in importance throughout the engineering sector, and with it, workpieces are becoming increasingly complex. Particularly, thin-walled parts require highly accurate and efficient machining strategies. Such low-rigidity structures usually undergo significant deformations during peripheral milling operations, thus suffering surface errors and a violation of tolerance specifications. This article introduces a general approach to mitigating surface errors during the peripheral milling of thin-walled aluminum workpieces. It incorporates an analytical approach to predicting surface-error characteristics based on geometrical quantities and process parameters, which is presented in detail. Milling experiments, including geometrical measurements of the samples, have been performed to verify the approach. The approach allows for a pre-selection of parameter sets that result in surface errors that can be compensated with minimal effort. Additionally, the introduced model offers a simple criterion to assess potential error mitigation by applying the respective tool-path adjustments. In doing so, the amount of costly numerical simulations or experiments is significantly reduced