Part Distortion Research Articles

A Thermo-Mechanical Analysis of Laser Hot Wire Additive Manufacturing of NAB

There is increased interest in using nickel aluminum bronze (NAB) alloys in large-scale directed energy deposition additive manufacturing (DEDAM) processes for maritime applications, but one challenge lies in the component distortion that results from residual stress generated during fabrication. This paper describes the development and evaluation of thermo-mechanical simulations for laser hot wire (LHW) DEDAM of NAB to predict part distortion. To account for the dearth of temperature-dependent properties for NAB C95800 in open literature and public databases, temperature-dependent material and mechanical properties for NAB C95800 were experimentally measured using test specimens fabricated with a variety of DEDAM processes. Autodesk’s Netfabb Local Simulation software, a commercial finite-element based AM solver, was employed but with its heat source model modified to accommodate LHW DEDAM’s oscillating laser path and additional energy input supplied by the preheated wire feedstock. Thermo-mechanical simulations were conducted using both the acquired temperature-dependent material and mechanical properties and the constant room-temperature properties to assess the impact on simulation accuracy. The usage of constant properties in the thermo-mechanical analysis resulted in significantly different predicted distortion compared to those using the temperature-dependent properties, at times even predicting substrate displacement in an opposite direction.

Intermethod Comparison and Evaluation of Measured Near Surface Residual Stress in Milled Aluminum

BackgroundWhile near surface residual stress (NSRS) from milling is a driver for distortion in aluminum parts there are few studies that directly compare available techniques for NSRS measurement.ObjectiveWe report application and assessment of four different techniques for evaluating residual stress versus depth in milled aluminum parts.MethodsThe four techniques are: hole-drilling, slotting, cos(α) x-ray diffraction (XRD), and sin2(ψ) XRD, all including incremental material removal to produce a stress versus depth profile. The milled aluminum parts are cut from stress-relieved plate, AA7050-T7451, with a range of table and tool speeds used to mill a large flat surface in several samples. NSRS measurements are made at specified locations on each sample.ResultsResulting data show that NSRS from three techniques are in general agreement: hole-drilling, slotting, and sin2(ψ) XRD. At shallow depths (< 0.03 mm), sin2(ψ) XRD data have the best repeatability (< 15 MPa), but at larger depths (> 0.04 mm) hole-drilling and slotting have the best repeatability (< 10 MPa). NSRS data from cos(α) XRD differ from data provided by other techniques and the data are less repeatable. NSRS data for different milling parameters show that the depth of NSRS increases with feed per tooth and is unaffected by cutting speed.ConclusionHole-drilling, slotting, and sin2(ψ) XRD provided comparable results when assessing milling-induced near surface residual stress in aluminum. Combining a simple distortion test, comprising removal of a 1 mm thick wafer at the milled surface, with a companion stress analysis showed that NSRS data from hole-drilling are most consistent with milling-induced distortion.

Effect of metal additive manufacturing residual stress on post-process machining-induced stress and distortion

This work represents the first investigation into the influence of residual stress (RS) from powder-based metal additive manufacturing (AM) on the post-process machining-induced stress and distortion for thin-walled components. Machined part distortion and surface residual stress pose major challenges in several industries, including for aerospace applications involving monolithic structures. However, the influence of initial RS in the bulk material on high-speed machining-induced stress and distortion is still not well understood. This is particularly true for more recent hybrid (additive and subtractive) manufactured components in which significant tensile and compressive RS develops from the rapid thermal cycles during the AM build. It is hypothesized in this work that, even for a simple thin-walled structure, the initial RS in the AM bulk material significantly influences the RS and distortion induced by high-speed machining. It is further hypothesized that the degree of influence of the initial RS on machining-induced RS and distortion varies significantly according to the specific tool path, even for the same net material removal. To test these hypotheses, a numerical modeling approach is presented considering a thin-walled directed energy deposition (DED) structure subjected to high-speed end-milling. A compatible RS field for the DED build is established using an iterative reconstruction algorithm based on limited neutron diffraction measurements, and the full reconstructed RS field is then imposed as an initial state in the end-milling simulation that follows. To assess the influence of the initial DED RS on the machining-induced stress and distortion, as well as to examine how this influence varies with machining strategy, two different tool paths are considered for the same net material removal, both with and without considering RS inherent to the DED build. The findings reveal significant influence of the DED RS on the high-speed machining-induced distortion and RS, and further, this influence is seen to vary greatly with the machining strategy. Normalized root-mean-square differences (NRMSD) of up to 25% and 29%, respectively, are observed in the machining-induced RS for the two different tool paths when DED inherent RS is considered. Likewise, maximum NRMSD of up to 44% and 40% are revealed in the post-machining distortion for the two respective machining strategies when DED RS is included. In addition, variations observed in the stress triaxiality computed during machining suggests that inclusion of the DED RS influences the localized response of the material near the tool-workpiece interface. The technical approach demonstrated can be extended beyond hybrid manufacturing to generate important scientific insights regarding distortion and machining-induced stress for conventionally manufactured monolithic components in the aerospace and other performance-critical industries.

Detecting the event of a single photon loss on quantum signals

We design a scheme for detecting a single photon loss from multi-modal quantum signals transmitted via a fiber or in free space. This consists of a special type of unitary coding transformation, the parity controlled-squeezing, applied prior to the transmission on the signal composed by information and ancilla modes. At the receiver, the inverse unitary transformation is applied—decoding, and the ancilla mode is measured via photon detection. The outcome reveals whether a photon loss has occurred. Distortion of the information part of the signal caused by an ancilla photon loss can be corrected via unitary transformation while loss of a photon from the information part of the signal can be detected with the probability exponentially close to unity but cannot be corrected. In contrast to the schemes of decoherence free subspaces and quantum error correction protocols, this method allows one to make use in principle of entire Hilbert space dimensionality. We discuss possible ways of synthesizing the required encoding–decoding transformation.

Prediction of part distortion in Fused Deposition Modelling (FDM) of semi-crystalline polymers via COMSOL: Effect of printing conditions

Residual stresses and warpage adversely affect the dimensional accuracy and performance of 3D-printed semi-crystalline polymers in Fused Deposition Modelling (FDM). One of the main challenges in FDM is to understand and relate the impact of printing conditions on part distortion for optimizing the 3D-printing process to achieve good print quality. Hence, the effect of various printing parameters, particularly print bed temperature, layer bonding, layer thickness and raster pattern, on built-up residual stresses and warpage is simulated in this work, by building a relationship between the crystallisation kinetics, viscoelastic and thermo-mechanical properties of the polymer in relation to changes in temperature during FDM using element activation in COMSOL. To the best of our knowledge, this is a novel approach for quantitative prediction of part distortion in FDM of semi-crystalline polymers under various printing conditions. Based on the simulation results, it is observed that a decrease in layer thickness from 0.5 mm to 0.1 mm results in an 89% drop in warpage and a reduction in residual stress of 24%. Applying a line raster pattern reduces warpage and residual stresses by 16% and 36%, respectively in comparison with a zigzag raster pattern. Very good agreement is observed between simulation and experimental results for warpage under various printing conditions. The results of this study can be used to predict and/or minimise part distortion in a semi-crystalline, 3D-printed polymer by simulating the effect of printing parameters on residual stresses during FDM.

Effective residual stress prediction validated with neutron diffraction method for metal large-scale additive manufacturing

Metal Big Area Additive Manufacturing (MBAAM), an additive manufacturing based on wire-arc process, is progressively evolving from rapid prototyping to the industrial scale production. In MBAAM, the height of printed part can easily reach eight feet, and the printing can last for hours or days. For such large printed structures, distortion and residual stress management are primary challenges in production process. Although transient thermo-mechanical simulations with very small time increments have resulted in accurate process predictions on small parts, such time resolutions are not computationally feasible for large components. Hence, the time increment in thermo-mechanical simulations of large structures needs to be evaluated with respect to simulation accuracy and computational feasibility. In this work, two thin walls were printed using MBAAM, and temperature and process parameters were recorded and used to calibrate and validate the model results. The part distortion and residual stresses were measured before and after stress relaxation by neutron beam diffraction in High Flux Isotope Reactor (HFIR). These measurements were compared to the predicted simulation results. In this work, we investigated the robustness of the computational model and the effects of time increment magnitude on the large-scale MBAAM simulations in terms of accuracy and model efficiency. We found that a coarse time increment of 20 s effectively captured the overall part distortion, but the model was not able to capture the development of residual stresses in the base plate. We determined a combination of fine and coarse time increments that offers an optimal computational efficiency and accuracy for residual stress prediction. A fine time increment of 1 s can be used to resolve the thermal interactions between the wall and base plate during the printing of the first few layers, as well as for other transitions in the geometry or process conditions. These findings provide general guidelines for selection of simulation time increments and offer a general understanding of the effect of time increments on computational efficiency and accuracy in prediction.

Finite Element-Based Simulation of Metal Fused Filament Fabrication Process: Distortion Prediction and Experimental Verification

Building end-use functional metal parts by metal fused filament fabrication (MF3) is an emerging topic in additive manufacturing. MF3 involves extrusion of polymer filaments that are highly filled with metal powder to print three-dimensional parts, followed by debinding and sintering to eliminate the polymer binder and get a fully dense metal part, respectively. Material properties, part design and processing conditions have a significant influence on the quality of MF3 printed parts. Part distortion and dimensional variations are significant quality challenges that hinder the acceptance of printed parts in potential functional applications. Trial-and-error experiments to find the best conditions are commonly used for defect avoidance, though they are time-consuming and expensive. Hence, computational simulation and design solutions are required for MF3 to enable a virtual analysis of the process outcome and reduce dependency on experimental methods. This paper investigates the applicability of a thermo-mechanical model for finite element simulation of the MF3 printing process. The quantitative influence of material properties on MF3 printed part quality was estimated using a simulation platform. The simulation results of two materials, a Ti-6Al-4V filled polymer and an unfilled ABS copolymer, were compared to experiments. It was determined that the unfilled polymer showed greater shrinkage and warpage than the Ti-6Al-4V filled polymer in simulations and experiments. Further, the trend in the distribution of warpage was consistent between experiments and simulation results for both materials. Finally, warpage compensation algorithms showed improvement in dimensional control for both materials in simulations and were consistent with experimental results.

The Technology of Distortion-Free Quenching in a Magnetic Field of Thin-Walled Details of the Ring Form

During heat treatment of machine parts and tools, besides the usual task of ensuring a high complex of mechanical and operational properties, there is a problem of distortion of products in the process of heat treatment and the need for editing operations (which are carried out manually and require significant labor costs). The known methods do not solve the problem of removing distortion for thin-walled parts of the ring shape completely. This paper shows the technical possibility of using the energy of a constant magnetic field for the "internal" straightening of products during heat treatment in the temperature range of super-plasticity of transformation. The use of special equipment makes it possible to eliminate virtually the distortion of thin-walled parts of the ring shape and to improve their mechanical properties.

Effect of clad height, substrate thickness and scanning pattern on cantilever distortion in direct metal deposition

In metal additive manufacturing, moving heat sources cause spatial and time-dependent variations of temperature and strain that can lead to part distortions. Distortion prediction and optimized deposition parameters can increase the dimensional accuracy of the generated components. In this study, an analytical approach for modeling the effect of clad height and substrate thickness is experimentally validated. Additionally, the influence of the scanning pattern as a function of clad height and substrate thickness is determined experimentally. The analytical model is based on the cool-down phase mechanism and assumes the formation of constant thermal shrinking forces for each deposited layer. The model accurately predicts longitudinal cantilever distortion after experimental calibration when compared with similar experimental conditions. For multi-layer deposition, the scanning pattern has the largest influence on distortion for thin-walled substrates. An optimized deposition strategy with longitudinal scanning vectors leads to a distortion reduction of up to 86%. The results highlight the potential of mechanical modeling and scanning strategy optimizations to increase the shape accuracy for industrial applications in the field of additive manufacturing.

Reduced order modeling of selective laser melting: from calibration to parametric part distortion

Additive manufacturing is an appealing solution to produce geometrically complex parts, difficult to manufacture using traditional technologies. The extreme process conditions, in particular the high temperature, complex interactions and couplings, and rich metallurgical transformations that this process entails, are at the origin of numerous process defects. Therefore, the numerical simulation of the process is gaining the interest of both the scientific and the industrial communities. However, simulating that process demands impressive computational resources, limiting high resolution simulations to the microscopic and mesoscopic scales. This paper proposes a thermo-mechanical modeling framework at the process scale as well as its associated reduced order simulation counterpart, enabling the parametric evaluation of the part distortion. It deeply addresses the process calibration using a high-resolution computational procedure based on the use of an in-plane-out-of-plane separated representation at the heart of the so-called Proper Generalized Decomposition (PGD), as well as the analysis of the transient thermal effects, defining the conditions in which the thermal and mechanical analyses can be decoupled.

Reduced order modeling of selective laser melting: from calibration to parametric part distortion

Reduced order modeling of selective laser melting: from calibration to parametric part distortion

Reduced order modeling of selective laser melting: from calibration to parametric part distortion

Reduced order modeling of selective laser melting: from calibration to parametric part distortion

Experimental investigation into the effect of supports and overhangs on accuracy and roughness in laser powder bed fusion

Overhangs are one of the most critical features in the design of parts for Powder Bed Fusion. In particular, accuracy and roughness of these geometrical elements are the main concerns while designing for this process. Support structures are the most common solutions adopted to preserve the quality of overhangs and ensure the appropriate completion of the whole process.This work aims to correlate geometrical parameters of overhangs and supports to the distortion and roughness of parts. For this purpose, an experimental campaign is carried out on specimens manufactured via a powder bed fusion of stainless steel. Appropriate process parameters have been chosen thanks to preliminary experimental tests.Both displacement and roughness are measured using optical and contact systems. The two methods show considerable differences that are examined in the light of process features.The analysis of results highlights that the design of support structures has to be carried out in accordance with the thickness and inclination of the overhangs in order to minimise distortions. Local defects occurring on the edges are also highlighted by comparing contact with optical measurements. An upward warping of all the geometries is observed after annealing.Roughness underlines the fact that the inclination of surfaces is the only influential factor, since the support design can efficiently dissipate the thermal energy from the overhangs.Comparative analysis of contact and optical measurements also highlights the limitations of the first type of measurements in detecting small surface defects.

Fast additive manufacturing distortion prediction using backward interpolation

Powder Bed Fusion Additive Manufacturing (PBFAM) processes have emerged as important industrial processes that are capable of manufacturing complicated part features, such as hollow designs, lattice structure and other unique design structures. The current state of computing technology requires significant time to predict the part distortion formed during the PBFAM build process. In this paper, a novel Backward Interpolation (BI) model is presented for fast estimation of part distortion based on build process parameters. In the Backward Interpolation approach, we propose the concept of distortion factor that represents the distortion contribution of unit forces on the node to all other nodes that have equal or lower height in the FEM mesh. To start with, the CAD model is meshed in a layer by layer manner and the FEM model is voxelized and sliced for calculating the distortion factor. Next, the as-built distortion before cutoff from the substrate is calculated based on distortion factors and the internal forces generated by the inherent strain of the voxel. Subsequently, the spring back distortion is calculated, and the total part distortion is then finally determined as the summation of part distortion and the spring back distortion. An experimental validation of the methodology was conducted, and the predicted distortion results appeared to agree well with the distortion obtained from the built part. The comparison of distortion obtained from Backward Interpolation and distortion data from published work was further used to validate this algorithm. The computational efficiency of the proposed Backward Interpolation method was evaluated using an example part and demonstrated that the part distortion values were obtained within a few minutes using a desktop computer, confirming the significant decrease in computing time using this approach.

Improving radiographic image contrast using multi layers of histogram equalization technique

&lt;span id="docs-internal-guid-43432eef-7fff-9949-6deb-865191ff0740"&gt;&lt;span&gt;Usually, X-ray image has distortion in many parts because it is focusing on bones rather than other, However, when dentist needs to make decision analysis, he does that by using X-ray and many opinions can be judged by looking closely on it like (inflammation, infection, tooth nerve, root of the tooth…). This paper proposes on new suggested technique by applying multilayers of histogram equalization (HE) and contrast limited adaptive histogram equalization (CLAHE) in order to make high contrast of X-ray, this technique provides very satisfied results and smooth intensity which leads to high clear X-ray image, by using Python3 and OpenCV.&lt;/span&gt;&lt;/span&gt;

Towards a comprehensive understanding of distortion in additive manufacturing based on assumption of constraining force

ABSTRACT Additive manufacturing has shown giant potential in advanced manufacturing industry. However, distortion of additive-manufactured parts may interrupt the printing process and decrease manufacturing precision, causing a significant waste of time and money. Distortion, a common problem in additive manufacturing, has not been sufficiently researched. In this study, we provide a comprehensive understanding of distortion in additive manufacturing based on assumption of constraining force. A quantitative model was established to illustrate inconsistent shrinkage during the additive process. A qualitative model was then built for showing the distortion caused by inconsistent shrinkage. It can be founded that inconsistent shrinkage accumulated during the additive process drives the final distortion of part. We concluded most influencing factors of distortion together, forming towards a comprehensive understanding of distortion in additive manufacturing. This study not only links micro melting-solidification process and macro structural mechanics in science, but also provides systematic solutions for decreasing the distortion in additive manufacturing for engineering.

Uncut chip geometry determination for cutting forces prediction in orthogonal turn-milling operations considering the tool profile and eccentricity

The cutting forces generated in machining are responsible for the tool deflection, part distortion, and features as chatter; therefore, their accurate estimation is fundamental to defining stable and safe working conditions to increase workpiece accuracy and productivity. Turn-milling is a conventional milling operation while the workpiece is simultaneously rotating. These operations enable manufacturing pieces with bosses or eccentricities; particularly, in large-sized industries such as aeronautics, naval power, and nuclear energy. Despite its wide use, relatively few studies are available regarding cutting forces and their implication in the process. Then, the effects of some cutting parameters over the process are not well detailed, for example, the tool profile and eccentricity. The numerical model presented in this research covers the cases of tool eccentricity and tool profile, such as torus and spherical end mills in orthogonal turn-milling operations. The model accurately determines the uncut chip geometry, validated theoretically against a CAD representation of the chip with errors below 3%. Furthermore, a set of milling trials was proposed to compare the chip mass and the cutting forces estimated by the model with those measured from the trials in torus and spherical profiles. The experimental validation results correlate in both tests presenting in the case of the mass errors below 3.5% and the cutting-forces errors around 12%. The validated model allows exploring a wider scenario of simulations where the eccentricity and the tool profile are the studied variables. The main findings drawn from the experiments and simulations are that the tool profile and the eccentricity affect the material removal rate. Its wrong selection reduces the chip volume and leaves material where it is supposed to be removed; then, the geometrical errors force to reprocess the workpiece, negatively impacting manufacturing productivity.

Cyber-physical approach toward semiautonomous postprocessing of additive manufactured parts and components

Additive manufacturing (AM), often referred to as 3D printing, is a generic term describing the layered build-up of material in near net shape frequently attributed with a freedom of design that cannot be achieved otherwise. AM focuses basically on the fabrication of parts for different fields in complex high-tech applications. Examples include components for jet engines, turbines blades, and implants in the medical sector. This is often justified with tool cost savings, shorter lead-time, and overcoming the “design for manufacture” paradigm. On the other hand, a machining allowance is frequently required to counteract the inherent surface roughness and the widespread challenge of part distortion due to residual stresses. At this point, geometrical complexity and small batch sizes transform into strong cost drivers compared to conventional subtractive processing. In fact, these parts are simply hard-to-clamp and hard-to-probe. Moreover, iterative processing is frequently required due to remaining residual stresses in order to reach the target geometry; even the part envelope changes unintentionally. The current paper explores the novel approach of semiautonomous postprocessing of AM parts and components based on flexible clamping, geometry acquisition in the as-clamped position using cooperating laser profile sensors, and an adaptive milling path planning strategy to counteract unforeseen change of the part envelope.

A digital twin strategy for major failure detection in fused deposition modeling processes

Part distortion during additive manufacturing (AM) may lead to catastrophic failure and significant waste of resources. Existing work often focuses on identification and detection of individual root causes such as melt pool geometries or extruder clogging to prevent part failures. Since the end-effect of major print failures can be the result of multiple error sources (including unknowns), relying on detection of individual root causes may misclassify some failed prints as successful. Instead, detecting end-effects or part distortion could provide early warning of major failures regardless of potential error sources. Distortion detection, however, currently involves computationally expensive simulation and analysis of sensing data. One promising solution is to adopt digital twin strategy to quickly compare model prediction to features extracted from in situ sensing data. This study extends the digital twin strategy to major distortion detection by developing (1) a multi-view optical sensing system for movable print beds and (2) failure detection methods by analyzing multi-view of part images layer by layer. Since the digital twin of actual prints at specific layers are generated offline, delay can be reduced to determine if a significant enough quality departure has occurred to justify termination of the print. In the experimental evaluation of this approach for a FDM machine with a moving print bed, failure was rapidly detected in two of the three test prints, while in the remaining print, failure was successfully detected after a short delay.

Investigation on the scale effects of initial bulk and machining induced residual stresses of thin walled milled monolithic aluminum workpieces on part distortions: experiments and finite element prediction model

Thin walled monolithic milled aluminum workpieces are commonly used in the aerospace industry, because of their good properties such as a high overall strength-to-weight ratio. After machining those parts distortions occur. Residual stresses (RS) are the main driver for those distortions. Two types of RS, the initial bulk residual stresses (IBRS) and the machining induced residual stresses (MIRS), contribute to the part distortion. In this study, the scale effects of each RS type and their combined effects on the distortion of milled thin walled aluminum workpieces are evaluated for different wall thicknesses, different IBRS conditions and different MIRS. In this context a finite element model (FEM) is developed to predict the distortion due to the measured RS. A 3D linear elastic model, considering both types of RS as input is presented. The simulation outcome is validated by experiments.It was found that both RS types contribute to part distortion. For parts containing high IBRS, those IBRS dominate the distortion. For stress relieved parts, containing low IBRS, the MIRS dominate the distortion. The investigations showed that the shear RS induced by machining are crucial for the distortion. The developed FEM model is able to predict the distortion due to both RS types.