Micro-textures applied to cutting tool surfaces provide certain advantages such as reducing tool forces, stresses, and temperature hence overall friction between the tool-chip contact and improving chip adherence and associated tool wear. This study explores the effect of micro-texture geometry parameters fabricated on the rake face of tungsten carbide inserts that were tested in dry turning titanium alloy Ti-6Al-4V. The effects of micro-texture geometry on the cutting forces, tool stresses, tool temperatures, tool wear rate and variable friction coefficient were studied with 3D finite element (FE) simulations. The simulation model was validated comparing cutting forces predicted and measured. The results indicated some effects of micro-textured tool geometry parameters being significant and others are not as significant. The experiments reveal that the effects of micro-groove width, depth, and distance from cutting edge are found to be significant on cutting forces, but the spacing is not as much. The effect of increasing feed rate on cutting force and tool wear was significant and suppressed the advantages offered by micro-grooved texture tool geometry. The simulation results indicate that the effect of micro-texture parameters such as groove depth and distance from cutting edge are significant on tool temperature and wear rate. The variable nature of friction coefficient was emphasized and represented as functions of state variables such as normal stress and local temperature as well as micro-texture parameters.

Ultrasonic welding (USW) is one of the joining technologies that can be applied to short carbon fiber thermoplastic composites. In this study, the USW of Nylon 6 reinforced by short carbon fibers created using injection molding is used to investigate the USW process without energy directors. In addition to process parameters and performance parameters, a new category of parameters is introduced to characterize the behavior of base materials to control USW without energy directors. These parameters, named morphological parameters, are the degree of crystallinity (DoC) and the ratio of the crystalline phases of Nylon 6 (α/γ ratio). One method of controlling the morphological parameters is annealing. A design of experiments is carried out using 5 replicates and 7 annealing temperatures above the glass transition temperature (T g ) and below the melting temperature (T m ) of Nylon 6 to investigate the influence of annealing on the morphological parameters. The DoC and α/γ ratio are measured for each replicate by utilizing differential scanning calorimetry and X-ray diffraction. The results show that the DoC becomes uniform and the α/γ ratio increases after annealing. Consequently, the variation in weld strength decreases and the average weld strength increases by controlling the morphological parameters through annealing.

Computational modeling and simulation are employed to study a rotating susceptor vertical impinging chemical vapor deposition (CVD) reactor to predict GaN film deposition. Many metal-organic chemical vapor deposition reactor manufacturers use prior experience to design and fabricate CVD reactors without a fundamental basis for the process and information on the optimal conditions for the deposition. Through trial and error, they fine tune the gas flow parameters, heater temperatures, chamber pressure, and concentration of species gases for optimal growth. However, expensive raw precursor gas and time are wasted through this method. A computational model is an important step in the CVD reactor design and GaN growth prediction. It can be used to model and optimize the reactor to yield favorable operating conditions. In this paper, a simple geometry consisting of a rotating susceptor and flow guide is considered. The focus is on gallium nitride (GaN) thin films. The study shows how the computational model can benefit reactor design. It also presents comparisons between model prediction results and experimental data from a physical, practical, system. Commercially available software is used, with appropriate modifications, and the results obtained are discussed in detail.

This paper presents the effects of ultrasonic vibration assistance on shear band formation and chip segmentation mechanism in orthogonal cutting of Ti–6Al–4V. Experimental observations of chip microstructure show that the shear bands disappear when vibration assistance is applied along tangential direction at certain cutting speeds. A plastic chip flow model is developed to predict the stress and temperature variations in the primary shear zone at cutting, chip elastic recovery, and tool-chip separation periods. The simulation results show that the temperature in the primary shear zone in vibration-assisted cutting is much lower when compared with conventional cutting, therefore suppresses the generation of shear bands. The simulations of average cutting forces and pitch lengths of chip segments are compared with the experimental results. A finite element model is further developed to prove the temperature reduction when ultrasonic vibration assistance is applied.

Part design and process parameters directly influence the instantaneous spatiotemporal distribution of temperature in parts made using additive manufacturing (AM) processes. The temporal evolution of temperature in AM parts is termed herein as the thermal profile or thermal history. The thermal profile of the part, in turn, governs the formation of defects, such as porosity and shape distortion. Accordingly, the goal of this work is to understand the effect of the process parameters and the geometry on the thermal profile in AM parts. As a step toward this goal, the objectives of this work are two-fold. First, to develop and apply a finite element-based framework that captures the transient thermal phenomena in the fused filament fabrication (FFF) additive manufacturing of acrylonitrile butadiene styrene (ABS) parts. Second, validate the model-derived thermal profiles with experimental in-process measurements of the temperature trends obtained under different material deposition speeds. In the specific context of FFF, this foray is the critical first-step toward understanding how and why the thermal profile directly affects the degree of bonding between adjacent roads (linear track of deposited material), which in turn determines the strength of the part, as well as, propensity to form defects, such as delamination. From the experimental validation perspective, we instrumented a Hyrel Hydra FFF machine with three non-contact infrared temperature sensors (thermocouples) located near the nozzle (extruder) of the machine. These sensors measure the surface temperature of a road as it is deposited. Test parts are printed under three different settings of feed rate, and subsequently, the temperature profiles acquired from the infrared thermocouples are juxtaposed against the model-derived temperature profiles. Comparison of the experimental and model-derived thermal profiles confirms a high degree of correlation therein, with a mean absolute percentage error less than 6% (root mean squared error <6 °C). This work thus presents one of the first efforts in validating thermal profiles in FFF via direct in situ measurement of the temperature. In our future work, we will focus on predicting defects, such as delamination and inter-road porosity based on the thermal profile.

Electrically assisted forming (EAF) has been increasingly utilized as an effective auxiliary processing technology to improve the formability of hard-to-deform metals. Previous works have revealed that the phase transformation of titanium alloys subjected to electropulsing treatment (EPT) can occur at a lower temperature and in a remarkably shorter time compared with those subjected to the traditional heating treatment (THT). However, an in-depth experimental verification and further analysis is still missing so far. Therefore, to characterize the specific effects of EPT on α → β transformation process, both EPT and THT experiments were conducted on Ti–6Al–4V sheet specimens. After that, a calculation method based on the analysis of optical microscopic (OM) metallographs was developed to characterize the amount of phase transformation in EPT and THT. According to the results, it was found that the pulse current can significantly reduce the phase transus temperature and accelerate the transformation process in EPT compared with that in THT. Furthermore, the specific effects of EPT on transus temperature and phase transformation rate were investigated in detail. Based on that, the transformation kinetics of the electropulsing-induced α → β phase transformation was also analyzed using the Johnson–Mehl–Avrami model. It is revealed that the activation energies of both nucleation and growth of phase transformation are reduced by electric current. Hence, the phase transformation can start at a lower temperature and with a higher rate in EPT. The mechanism behind the effects was also discussed in detail in the present work.

Electromagnetic crimping is a solid state, high-speed, and high strain-rate joining process. Finite element analysis, as well as experimental study, was carried out on three types of field shapers, namely, tapered, taper-stepped, and stepped. In all three field shapers, the effective length, outer diameter, inner diameter, total length, and materials properties were constant. These field shapers were kept inside the same multi-turn solenoid coil for all the experiments. It was found that the taper-stepped field shaper results better regarding impact velocity, Lorentz force, temperature generation, less heating, and uniformity in crimping among the three types of field shapers.

The study is to investigate the electropolishing characteristics of 316L stainless steel in a sulfuric acid-free electrolyte of phosphoric acid and glycerol and to explore the possibility of using this eco-friendly electrolyte instead of the widely used sulfuric acid-based electrolyte. The influences of process parameters on polishing effects and the corrosion resistance of electropolished samples are investigated. The experimental results show that the electropolishing temperature and acid concentration are directly related to the mass transport mechanism in the limiting current plateau region. The grain boundaries of workpiece were electrochemically dissolved faster than the grain themselves at the beginning of the electropolishing process because they are more reactive than grains. Moreover, the conventional sulfuric—phosphoric acid electrolyte was also used to electropolish the 316L stainless steel, and the electropolished surfaces were compared with the sulfuric acid-free electrolyte proposed in this study. When the sulfuric acid-free electrolyte was used to electropolish the 316L stainless steel, the X-ray photoelectron spectroscopy (XPS) analysis shows that atomic Cr/Fe ratio of 316L stainless steel was increased from 0.802 to 1.909 after electropolishing process in the sulfuric acid-free electrolyte of phosphoric acid and glycerol. The corrosion resistance of the electropolished 316L stainless steel is studied using electrochemical analysis, and the results are verified experimentally.

A great challenge of metal cutting modeling is the ability of the material constitutive model to describe the mechanical behavior of the work material under the deformation conditions that characterizes this process. In particular, metal cutting generates a large range of state of stresses, as well as strains and strain rates higher than those generated by conventional mechanical tests, including the Split-Hopkinson pressure bar tests. A new hybrid analytical–experimental methodology to identify the material constitutive model coefficients is proposed. This methodology is based on an in situ high-resolution imaging and digital image correlation (DIC) technique, coupled with an analytical model of orthogonal cutting. This methodology is particularly suitable for the identification of the constitutive model coefficients at strains and strain rates higher than those found in mechanical tests. Orthogonal cutting tests of nickel aluminum bronze alloy are performed to obtain the strains and strain rates fields in the cutting zone, using DIC technique. Shear forces derived from stress integrations are matched to the measured ones. Then, the constitutive model coefficients can be determined, which is performed by solving a sequential optimization problem. Verifications are made by comparing the strain, strain rate, and temperature fields of cutting zone from experiments against those obtained by finite element simulations using the identified material constitutive model coefficients as input.

Self-piercing riveting has been widely used in vehicle body manufacturing to join aluminum alloys or aluminum to steel. However, it is difficult to rivet ultrahigh strength steel (UHSS) because of its resistance to piercing of the rivet. In this paper, a thermally assisted self-piercing riveting (TA-SPR) process was proposed to improve riveting of the UHSS, through locally preheating the UHSS sheet using an induction coil prior to the traditional self-piercing riveting (SPR) process. An experimental system consisting of inductive heating apparatus, conventional self-piercing riveting equipment, and coupon transfer mechanism was established and the steps, e.g., preheating, coupons transfer, and riveting, were automatically conducted at preset schedules. Based on experiments with this system, the effects of heating current, heating time, and coil heating distance on riveting of AA6061-T6 and DP980 were examined systematically by metallurgical analyses and mechanical tests. It was found that an appropriate combination of heating current and heating time, e.g., 0.5 s at 600 A, could produce crack-free joints having 77.8% higher undercut and 24% higher lap-shear strength, compared with results obtained using a conventional SPR process.

In metal cutting processes, the use of cutting fluids shows significant effects on workpiece surface quality by reducing thermomechanical loads on cutting tool and workpiece. Many efforts are made to model these thermomechanical processes, however without considering detailed heat transfer between cutting fluid, tool, and workpiece. To account for heat transfer effects, a coupling approach is developed, which combines computational fluid dynamics (CFD) and finite element method (FEM) chip formation simulation. Prior to the simulation, experimental investigations in orthogonal cutting in dry and wet cutting conditions with two different workpiece materials (AISI 1045 and DA 718) are conducted. To measure the tool temperature in dry as well as in wet cutting conditions, a two color pyrometer is placed inside an electrical discharge machining (EDM) drilled cutting tool hole. Besides tool temperature, the cutting force is recorded during the experiments and later used to calculate heat source terms for the CFD simulation. After the experiments, FEM chip formation simulations are performed and provide the chip forms for the CFD mesh generation. In general, CFD simulation and experiment are in reasonable agreement, as for each workpiece setup the measured temperature data are located between the simulation results from the two different tool geometries. Furthermore, numerical and experimental results both show a decrease of tool temperature in wet cutting conditions, however revealing a more significant cooling effect in a AISI 1045 workpiece setup. The results suggest that the placement of drilling holes has a major influence on the local tool temperature distribution, as the drilling hole equals a thermal resistance and hence leads to elevated temperatures at the tool front.

The objective of this work is to fabricate thermocouples directly on the rake face of a commercially available tungsten carbide cutting insert for accurately measuring the tool–chip interface temperature during metal cutting. The thermocouples are sputtered onto the cutting insert using micromachined stencils, are electrically isolated with layers of Al 2 O 3 , and receive a top coating of AlTiN for durability. The result is a nonsacrificial thermocouple junction that is approximately 1.3 µm below the rake face of the tool and 30 µm from the cutting edge. Experimental and numerical characterization of the temperature measurement accuracy and response time are presented. The instrumented cutting tool can capture the tool–chip interface temperature transients at frequencies of up to 1 MHz, which enables the observation of serrated chip formation and adiabatic shear events. Temperature measurements from oblique machining of 4140 steel are presented and compared with three-dimensional, transient numerical simulations using finite element analysis, where cutting speed and feed are varied. This method of measuring the tool–chip interface temperature shows promise for future research and smart manufacturing applications.

This paper studies how to control boundary slope of optimized parts in density-based topology optimization for additive manufacturing (AM). Boundary slope of a part affects the amount of support structure required during its fabrication by additive processes. Boundary slope also has a direct relation with the resulting surface roughness from the AM processes, which in turn affects the heat transfer efficiency. By constraining the minimal boundary slope, support structures can be eliminated or reduced for AM, and thus, material and postprocessing costs are reduced; by constraining the maximal boundary slope, high-surface roughness can be attained, and thus, the heat transfer efficiency is increased. In this paper, the boundary slope is controlled through a constraint between the density gradient and the given build direction. This allows us to explicitly control the boundary slope through density gradient in the density-based topology optimization approach. We control the boundary slope through two single global constraints. An adaptive scheme is also proposed to select the thresholds of these two boundary slope constraints. Numerical examples of linear elastic problem, heat conduction problem, and thermoelastic problems demonstrate the effectiveness and efficiency of the proposed formulation in controlling boundary slopes for additive manufacturing. Experimental results from metal 3D printed parts confirm that our boundary slope-based formulation is effective for controlling part self-support during printing and for affecting surface roughness of the printed parts.

A widespread use of lasers in additive manufacturing is to induce a given temperature and a phase transformation in materials deposited onto a substrate. For a laser to induce a phase transformation in the material, the power intensity must be sufficiently high to induce melting and, in all cases, stay below a vaporization or burn-off temperature of the target material. Oftentimes, there is variability in the laser input to the target zone. For a process designer, a central question is to determine the uncertainty of the resulting target state, i.e., temperature and state (solid or melted), due to uncertainty in the energy (laser) input. This motivates the present work, which integrates relatively fundamental heat transfer models that describe the thermal effects due to (a) laser irradiation, (b) heat conduction into the surface of deposition, (c) infrared radiation outwards into the surroundings, (d) convection due to an exhaust apparatus to control the cooling of the system, and (e) phase transformations, for a dry Nylon 6 powder as a sample material. One key advantage of this framework is that it is amenable to a sensitivity and uncertainty analysis with respect to any of its parameter inputs. Accordingly, uncertainty quantification studies are also undertaken to ascertain the relationship between variation in laser input to variation in the processed material state. Examples will be presented to illustrate the thermal behavior of the numerical model. Due to its simplicity, this framework is designed to be computationally implemented in a straightforward fashion. The model allows for rapid computation and sensitivity analyses, which are provided as numerical examples. Extensions are also given to include mass transport (losses) due to ablation of the target material.

Additive manufacturing (AM) is a novel fabrication technique capable of producing highly complex parts. Nevertheless, a major challenge is the quality assurance of the AM fabricated parts. While there are several ways of approaching this problem, how to develop informative process signatures to detect part anomalies for quality control is still an open question. The objective of this study is to build a new layer-wise process signature model to characterize the thermal-defect relationship. Based on melt pool images, we propose novel layer-wise key process signatures, which are calculated using multilinear principal component analysis (MPCA) and are directly correlated with the layer-wise quality of the part. The resultant layer-wise quality features can be used to predict the overall defect distribution of a fabricated layer during the build. The proposed model is validated through a case study based on a direct laser deposition experiment, where the layer-wise quality of the part is predicted on the fly. The accuracy of prediction is calculated using three measures (i.e., recall, precision, and F-score), showing reasonable success of the proposed methodology in predicting layer-wise quality. The proposed quality prediction methodology enables online process correction to eliminate anomalies and to ultimately improve the quality of the fabricated parts.

This study investigates the prediction of maraging steel C250 microgrinding forces by incorporating phase transformation effects with the manufacturing process mechanics. The results could consequently increase the accuracy of the prediction and better understand the influence of phase evolution on the materials processing. Based on a detailed analysis of microgrinding mechanics and thermodynamics, an iterative blending scheme integrating phase transformation kinetics and material genome analysis is developed. The physical-based formulation, experimental validation, and computational configuration are presented herein for the microgrinding forces, quantifying phase transformation effects. According to the results, the implementation of the iterative blending scheme can help achieve a higher prediction accuracy of microgrinding forces. Besides, the iterative blending would enable the consideration of the interactive relation between process mechanics and microstructure evolution through materials genome analysis.

In this research, we propose a coupled thermomechanical modeling method for predicting grinding residual stress based on randomly distributed grains. In order to deal with the problem that the nominal grinding force is too small to generate the plastic deformation, we hold the opinion that grinding residual stress is totally derived from three factors: thermal stress, the nominal grinding force (pressure) over the entire grinding zone, and the equivalent plowing force just under the bottom of the abrasive wheel. Finite element model (FEM) simulation of the single-grain grinding (SGG) is conducted to obtain the critical plowing depth and the SGG force at an arbitrary cutting depth. Based on the randomly distributed abrasive grains, the equivalent grinding heat source model, the equivalent SGG plowing force model, and the equivalent nominal pressure model are all established. A 2D coupled thermomechanical model is established to simulate the grinding process for temperature fields and grinding residual stress fields. In addition, verification tests are conducted to validate the model. It turns out that the coupled model can accurately predict the multiphysical fields on both temperature and residual stress. Based on the simulation results of the model, the generation mechanism of grinding residual stress is quantitatively studied. This research provides a promising pathway to residual stress control of grinding.

Tailored blanks characterized by variable thickness were friction stir welded (FSWed) with the aim to obtain constant joint properties along the weld seam, regardless of the thickness change. To pursue this goal, the heat input was kept constant by in-process control of tool rotation. A dedicated numerical model of the process was used to determine the tool rotation values as a function of the sheet thickness. The mechanical properties and the microstructure of the FSWed joints, produced with varying process parameters, were studied. It was found that the proposed approach can produce joints with uniform properties along the weld line in terms of stress–strain curve shape, joint strength, elongation at failure, and microstructure.

A new adaptive disturbance feedforward control strategy of the strip thickness in a hot strip rolling mill with online parameter estimation is proposed. The feedforward control strategy makes use of the measured strip temperature and strip entry thickness. To avoid that these disturbances cause a nonuniform strip exit thickness, the Sims’ roll gap model and a linear mill stand deflection model are used to compute control inputs, which compensate for these disturbances. By minimizing the difference between the expected roll force from the model and the measured roll force, uncertain parameters of the model and also errors of the strip tracking are estimated in real time. The estimated parameters are immediately used in the adaptive feedforward controller. Experimental results of the proposed control approach obtained from an industrial hot strip rolling mill show a significant improvement of the strip thickness accuracy compared to the existing standard controllers. The proposed adaptive feedforward control strategy is now in permanent operation at the considered rolling mill.

Prediction of temperature in the tool, chip, and workpiece surface is important to study tool wear, residual stresses in the machined part, and to design cutting tool substrates and coating. This paper presents a finite difference method-based prediction of temperature distribution in the tool, chip, and workpiece surface for transient conditions. The model allows inclusion of anisotropic materials such as coating or different material properties. The energy is created in the primary shear zone where the metal is sheared, the secondary deformation zone where the chip moves on the tool rake face with friction, and the tertiary zone where the flank face of the tool rubs against the finished part surface. The model allows both sticking and sliding friction contact of the moving chip on the rake face of the tool. The distribution of temperature is evaluated by meshing chip, workpiece surface zone, and tool into small discrete elements. The heat transfer among the elements is modeled, and the temperature is predicted at the center of each element. The heat transfer to the tool, workpiece, and chip is iteratively evaluated. The predicted temperature values are compared against the experimental measurements collected with coated tools in turning.