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Research Papers

J. Manuf. Sci. Eng. 2018;140(11):111001-111001-19. doi:10.1115/1.4040543.

The goal of this work is to detect the onset of material cross-contamination in laser powder bed fusion (L-PBF) additive manufacturing (AM) process using data from in situ sensors. Material cross-contamination refers to trace foreign materials that may be introduced in the powder feedstock used in the process due to reasons such as poor cleaning of the machine after previous builds or inadequate quality control during production and storage of the powder. Material cross-contamination may lead to deleterious changes in the microstructure of the AM part and consequently affect its functional properties. Accordingly, the objective of this work is to develop and apply a spectral graph theoretic approach to detect the occurrence of material cross-contamination in real-time as the part is being built using in-process sensors. The central hypothesis is that transforming the process signals in the spectral graph domain leads to early and more accurate detection of material cross-contamination in L-PBF compared to the traditional delay-embedded Bon-Jenkins stochastic time series analysis techniques, such as autoregressive (AR) and autoregressive moving average (ARMA) modeling. To test this hypothesis, Inconel alloy 625 (UNS alloy 06625) test parts were made at Edison Welding Institute (EWI) on a custom-built L-PBF apparatus integrated with multiple sensors, including a silicon photodetector (with 300 nm to 1100 nm optical wavelength). During the process, two types of foreign contaminant materials, namely, tungsten and aluminum particulates, under varying degrees of severity were introduced. To detect cross-contamination in the part, the photodetector sensor signatures were monitored hatch-by-hatch in the form of spectral graph transform coefficients. These spectral graph coefficients are subsequently tracked on a Hotelling T2 statistical control chart. Instances of Type II statistical error, i.e., probability of failing to detect the onset of material cross-contamination, were verified against X-ray computed tomography (XCT) scans of the part to be within 5% in the case of aluminum contaminant particles. In contrast, traditional stochastic time series modeling approaches, e.g., ARMA, had corresponding Type II error exceeding 15%. Furthermore, the computation time for the spectral graph approach was found to be less than one millisecond, compared to nearly 100 ms for the traditional time series models tested.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111002-111002-13. doi:10.1115/1.4040872.

In five-axis milling process, the tool path generated by a commercial software seldom takes the dynamics of the machining process into account. The neglect of process dynamics may lead to milling chatter, which causes overcut, quick tool wear, etc., and thus damages workpiece surface and shortens tool life. This motivates us to consider dynamic constraints in the tool path generation. Tool orientation variations in five-axis ball-end milling influence chatter stability and surface location error (SLE) due to the varying tool-workpiece immersion area and cutting force, which inversely provides us a feasible and flexible way to suppress chatter and SLE. However, tool orientations adjustment for suppression of chatter and SLE may cause drastic changes of the tool orientations and affects surface quality. The challenge is to strike a balance between the smooth tool orientations and suppression of chatter and SLE. To overcome the challenge, this paper presents a minimax optimization approach for planning tool orientations. The optimization objective is to obtain smooth tool orientations, by minimizing the maximum variation of the rotational angles between adjacent cutter locations, with constraints of chatter-free and SLE threshold. A dedicated designed ball-end milling experiment is conducted to validate the proposed approach. The work provides new insight into the tool path generation for ball-end milling of sculpture surface; also it would be helpful to decision-making for process parameters optimization in practical complex parts milling operations at shop floor.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111004-111004-7. doi:10.1115/1.4040875.

Shear banding is a type of plastic flow instability with often adverse implications for cutting and deformation processing of metals. Here, we study the mechanics of plastic flow evolution within single shear bands in Ti- and Ni-based alloy systems. The local shear band displacement profiles are quantitatively mapped at high resolution using a special micromarker technique. The results show that shear bands, once nucleated, evolve by a universal viscous sliding mechanism that is independent of microstructural details. The evolution of local deformation around the band is accurately captured by a momentum diffusion equation based on a Bingham-type flow rule. The predicted band viscosity is very small, compared to those of liquid metals. A plausible explanation for this small viscosity and fluid-like behavior at the band, based on phonon drag, is presented.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111005-111005-9. doi:10.1115/1.4040873.

Friction stir scribe (FSS) welding as a recent derivative of friction stir welding (FSW) has been successfully used to fabricate a linear joint between automotive Al and steel sheets. It has been established that FSS welding generates a hook-like structure at the bimaterial interface. Beyond the hook-like structure, there is a lack of fundamental understanding on the bond formation mechanism during this newly developed FSS welding process. In this paper, the microstructures and phases at the joint interface of FSS welded Al to ultra-high-strength steel were studied using scanning electron microscopy (SEM) and transmission electron microscopy (TEM). It was found that both mechanical interlocking and interfacial bonding occurred simultaneously during the FSS welding process. Based on SEM observations, a higher diffusion driving force in the advancing side was found compared to the retreating side and the scribe swept zone, and thermally activated diffusion was the primary driving force for the interfacial bond formation in the scribe swept region. The TEM energy-dispersive X-ray spectroscopy (EDXS) revealed that a thin intermetallic compound (IMC) layer was formed through the interface, where the thickness of this layer gradually decreased from the advancing side to the retreating side owing to different material plastic deformation and heat generations. In addition, the diffraction pattern (or one-dimensional fast Fourier transform (FFT) pattern) revealed that the IMC layer was composed of Fe2Al5 or Fe4Al13 with a Fe/Al solid solution depending on the weld regions.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111006-111006-9. doi:10.1115/1.4040874.

Machining industry has been evolving toward implementation of automation into the processes for higher productivity and efficiency. Although many studies have been conducted in the past to develop intelligent monitoring systems in various application scenarios of machining processes, most of them just focused on cutting tools without considering the influence of the nonuniform hardness of workpiece material. This study develops a compact, reliable, and cost-effective tool condition monitoring (TCM) system to detect the cutting tool wear in machining of the workpiece material with hardness variation. The generated audible sound signals during the machining process are analyzed by state-of-the-art artificial intelligent techniques, support vector machine (SVM) and convolutional neural network (CNN), to predict the tool wear and the hardness variation of the workpiece. A four-level classification model is developed for the system to detect the tool wear condition based on the width of the flank wear land and the hardness variation of the workpiece. This study also involves the comparative analysis between two employed artificial intelligent techniques to evaluate the performance of the model in prediction. The proposed TCM system has shown a high prediction accuracy in detecting the tool wear from the audible sound into the proposed multiclassification wear level in end milling of the nonuniform hardened workpiece.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111007-111007-10. doi:10.1115/1.4038993.

A hybrid friction stir resistance spot welding (RSW) process is applied for joining aluminum alloy 6061 to TRIP 780 steel. Compared with conventional RSW, the applied current density is lower and the welding process remains in the solid state. Compared with conventional friction stir spot welding (FSSW) process, the welding force is reduced and the dissimilar material joint strength is increased. The electrical current is applied in both a pulsed and direct form. With the equal amount of energy input, the approximately same force reduction indicates that the electro-plastic material softening effect is insignificant during FSSW process. The welding force is reduced mainly due to the resistance heating induced thermal softening of materials. With the application of electrical current, a wider aluminum flow pattern is observed in the thermo-mechanically affected zone (TMAZ) of weld cross sections and a more uniform hook is formed at the Fe/Al interface. This implies that the aluminum material flow is enhanced. Moreover, the Al composition in the Al–Fe interfacial layer is higher, which means the atomic diffusion is accelerated.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111008-111008-8. doi:10.1115/1.4040877.

Powder bed metal additive manufacturing (AM) utilizes a high-energy heat source scanning at the surface of a powder layer in a predefined area to be melted and solidified to fabricate parts layer by layer. It is known that powder bed metal AM is primarily a thermal process, and further, heat conduction is the dominant heat transfer mode in the process. Hence, understanding the powder bed thermal conductivity is crucial to process temperature predictions, because powder thermal conductivity could be substantially different from its solid counterpart. On the other hand, measuring the powder thermal conductivity is a challenging task. The objective of this study is to investigate the powder thermal conductivity using a method that combines a thermal diffusivity measurement technique and a numerical heat transfer model. In the experimental aspect, disk-shaped samples, with powder inside, made by a laser powder bed fusion (LPBF) system, are measured using a laser flash system to obtain the thermal diffusivity and the normalized temperature history during testing. In parallel, a finite element (FE) model is developed to simulate the transient heat transfer of the laser flash process. The numerical model was first validated using reference material testing. Then, the model is extended to incorporate powder enclosed in an LPBF sample with thermal properties to be determined using an inverse method to approximate the simulation results to the thermal data from the experiments. In order to include the powder particles' contribution in the measurement, an improved model geometry, which improves the contact condition between powder particles and the sample solid shell, has been tested. A multipoint optimization inverse heat transfer method is used to calculate the powder thermal conductivity. From this study, the thermal conductivity of a nickel alloy 625 powder in powder bed conditions is estimated to be 1.01 W/m K at 500 °C.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111009-111009-10. doi:10.1115/1.4040914.

Laser-assisted laser peen forming (LALPF) is proposed as a hybrid process to combine laser heating and laser peening to improve the bending capability of laser peen forming (LPF) effectively. To predict LALPF-induced bending deformation and mechanism of bending capability improvement, a sequentially coupled modeling approach is established by integrating three models, i.e., a thermoelastic-plastic model to predict the temperature, a dynamic model to obtain the eigenstrain of laser shock, and an eigenstrain model to predict the bending deformation. The effects of temperature, thermal stress, and thermal plastic strain of laser heating and the coupling effects on the bending deformation were investigated. The results show that the interaction of temperature and thermal stress are the dominant factors contributing to the improvement of bending capability.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111010-111010-8. doi:10.1115/1.4040915.

In this study, the friction stir welding (FSW) of aluminum alloy 6061-T6511 to TRIP 780 steel is analyzed under various process conditions. Two FSW tools with different sizes are used. To understand the underlying joining mechanisms and material flow behavior, nano-computed tomography (nano-CT) is applied for a 3D visualization of material distribution in the weld. With insufficient heat input, steel fragments are generally scattered in the weld zone in large pieces. This is observed in a combined condition of big tool, small tool offset, and low rotating speed or a small tool with low rotating speed. Higher heat input improves the material flowability and generates a continuous strip of steel. The remaining steel fragments are much finer. When the volume fraction of steel involved in the stirring nugget is small, this steel strip can be in a flat shape near the bottom, which generally corresponds to a better joint quality and the joint would fracture in the base aluminum side. Otherwise, a hook structure is formed and reduces the joint strength. The joint would fail with a combined brittle behavior on the steel hook and a ductile behavior in the surrounding aluminum matrix.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111011-111011-8. doi:10.1115/1.4040728.

The rapid development of modern science and technology brings with it a high demand for manufacturing quality. The surface integrity of a machined part is a critical factor which needs to be considered in the selection of the appropriate machining processes. Surface integrity is also tightly linked with tool wear. Tool wear is one of the most significant and necessary parameters to be considered for machining sustainability. By monitoring and predicting tool wear, it is possible to improve sustainability by reducing the scrap rate due to poor surface integrity. In this work, data-dependent systems (DDS), a stochastic modeling and analysis technique, was applied to study the power of spindle motor during a hard milling operation. The objective was to correlate the spindle power to tool wear conditions using DDS analysis. The spindle power was monitored, and the time series trends were decomposed to study the frequency variation with different severities of tool wear conditions and processing parameters. Analysis of variance (ANOVA) was also used to determine factors significant to the power by a spindle motor. Experiments indicate that low-level frequency of spindle power is correlated with the amount of tool wear, cutting speed, and feed per tooth. The results suggest that effective tool wear monitoring may be achieved by focusing on low-level frequencies highlighted by DDS methodology.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111012-111012-12. doi:10.1115/1.4040617.

Milling exhibits forced vibrations at tooth passing frequency and its harmonics, as well as chatter vibrations close to one of the natural modes. In addition, there are sidebands, which are spread at the multiples of tooth passing frequency above and below the chatter frequency, and make the robust chatter detection difficult. This paper presents a novel on-line chatter detection method by monitoring the vibration energy. Forced vibrations are removed from the measurements in discrete time domain using a Kalman filter. After removing all periodic components, the amplitude and frequency of chatter are searched in between the two consecutive tooth passing frequency harmonics using a nonlinear energy operator (NEO). When the energy of any chatter component grows relative to the energy of forced vibrations, the presence of chatter is detected. The proposed method works in discrete real time intervals, and can detect the chatter earlier than frequency domain-based methods, which rely on fast Fourier Transforms. The method has been experimentally validated in several milling tests using both microphone and accelerometer measurements, as well as using spindle speed and current signals.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111013-111013-11. doi:10.1115/1.4040983.

The complexity in weld profile caused by abrupt change in polarity in square waveform welding is investigated through the development of a model capable to accurately predict weld profile. A semi-analytical model is conceived wherein characteristic attributes of a composite parabolic–elliptic function, which represent the weld profile, are obtained through nonlinear regression (NLR). The proposed model is demonstrated for its efficacy in the prediction of weld profile over a wide range of welding parameters, vis-à-vis, welding current, frequency, electrode negative (EN) ratio, and welding velocity. The investigation suggests that the center and outer cores of welding arc remains more active during positive and negative polarity, respectively, that leads to distinct macroscopic zones in weld cross section and thus, necessitates a composite profile for representation of weld profile. The intersection of the zones forms a metallurgical notch which the investigation offers a method to estimate and thus control. Unlike the convention continuous arc welding, the waveform arc welding caters welding at higher velocity without compromising the weld penetration and almost abolishing the metallurgical notch as well.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111014-111014-9. doi:10.1115/1.4041180.

Cutting tool rotation errors have significant influence on the machined surface quality, especially in micromilling. Precision metrology instruments are usually needed to measure the rotation error accurately. However, it is difficult to directly measure the axial error of micromilling tools due to the small diameters and ultra-high rotational speed. To predict the axial error of high speed milling tools in the actual machining conditions and avoid the use of expensive metrology instruments, a novel method is proposed in this paper to quantify the cutting tool error in the axial direction based on the tool marks generated on the machined surface. A numerical model is established to simulate the surface topography generation, and the relationship between tool marks and the cutting tool axial error is then investigated. The tool axial errors at different rotational speeds can be detected by the proposed method. The accuracy and the reliability of the proposed method are verified by machining experiments.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111015-111015-12. doi:10.1115/1.4040959.

Over the past decade, laser forming has been effectively used to bend various metal foams, opening the possibility of applying these unique materials in new engineering applications. The purpose of the study was to extend laser forming to bend sandwich panels consisting of metallic facesheets joined to a metal foam core. Metal foam sandwich panels combine the excellent shock-absorption properties and low weight of metal foam with the wear resistance and strength of metallic facesheets, making them desirable for many applications in fields such as aerospace, the automotive industry, and solar power plants. To better understand the bending behavior of metal foam sandwich panels, as well as the impact of laser forming on the material properties, the fundamental mechanisms that govern bending deformation during laser forming were analyzed. It was found that the well-established bending mechanisms that separately govern solid metal and metal foam laser forming still apply to sandwich panel laser forming. However, two mechanisms operate in tandem, and a separate mechanism is responsible for the deformation of the solid facesheet and the foam core. From the bending mechanism analysis, it was concluded on the maximum achievable bending angle and the overall efficiency of the laser forming process at different process conditions. Throughout the analysis, experimental results were complemented by numerical simulations that were obtained using two finite element models that followed different geometrical approaches.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111016-111016-10. doi:10.1115/1.4040938.

This paper presents a methodology to compensate the tooltip position errors caused by the geometric errors of a three-axis gantry type micromill integrated with a six degree-of-freedom (6DOF) rotary magnetic table. A geometric error-free ideal forward kinematic model of the nine-axis machine has been developed using homogenous transformation matrices (HTMs). The geometric errors of each linear axis, which include one positioning, two straightness, pitch, roll, and yaw errors, are measured with a laser interferometer and fit to quintic polynomial functions in the working volume of the machine. The forward kinematic model is modified to include the geometric errors which, when subtracted from the ideal kinematic model, gives the deviation between the desired tooltip position with and without geometric errors. The position commands of the six degree-of-freedom rotary magnetic table are modified in real time to compensate for the tooltip deviation using a gradient descent algorithm. The algorithm is simulated and verified experimentally on the nine-axis micromill controlled by an in-house developed virtual/real-time open computer numerical controlled (CNC) system.

Topics: Errors , Kinematics
Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2018;140(11):111019-111019-12. doi:10.1115/1.4040544.

In this paper, both traditional Inconel 718 parts and WC/Inconel 718 composites were fabricated by selective laser melting (SLM). The size of WC particles was observed to play a crucial role in determining the microstructural evolution, distortion, and microcracks around the WC particles, which inturn also affected the effective mechanical properties of WC/Inconel 718 composites. The use of the 5.25 μm diameter WC particles resulted in fine dendrites at the interface between the WC particle and the Inconel 718 matrix. This was attributed to the formation of an annular heat flow and radially arranged temperature gradient directions around the WC particle that increased the contact area between the matrix and the particle, thereby also improving the interfacial bonding. A sound metallurgical bonding at the interface was achieved with negligible distortion and microcracks due to a relatively uniform temperature distribution and temperature gradient (4.7 × 103 °C/mm) at the interface. This also explains the generation of dense and smooth interfacial bonding, which yielded a low average friction coefficient of 0.21. The wear properties were improved since grooves and spallation were reduced with the decrease of the WC size.

Commentary by Dr. Valentin Fuster

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