Research Papers

J. Manuf. Sci. Eng. 2019;141(8):081001-081001-13. doi:10.1115/1.4043731.

Sensor signals acquired during the manufacturing process contain rich information that can be used to facilitate effective monitoring of operational quality, early detection of system anomalies, and quick diagnosis of fault root causes. This paper develops a method for effective monitoring and diagnosis of multisensor heterogeneous profile data based on multilinear discriminant analysis. The proposed method operates directly on the multistream profiles and then extracts uncorrelated discriminative features through tensor-to-vector projection, and thus, preserving the interrelationship of different sensors. The extracted features are then fed into classifiers to detect faulty operations and recognize fault types. The developed method is demonstrated with both simulated and real data from ultrasonic metal welding.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081002-081002-9. doi:10.1115/1.4043838.

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.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081003-081003-13. doi:10.1115/1.4043837.

Bulk metallic glasses (BMGs) are a series of metal alloys with an amorphous structure. The deformation of BMGs occurs in localized regions and is highly sensitive to the applied stress, strain rate, and temperature. This paper presents a coupled thermomechanical model to analyze the chip segmentation mechanism due to material shear localization in orthogonal cutting of Zr-BMG. The shear stress variation in the primary shear zone is modeled considering the tool-chip friction and large strain of the material. The constitutive property of BMG corresponding to the inhomogeneous deformation through shear transformation zones is modeled. The oscillations of shear stress, temperature, and free volume are simulated based on the cutting conditions. The predicted chip segmentation frequency is compared with the experimental result under different cutting speeds and uncut chip thicknesses. The developed model provides the fundamental mechanism of material deformation and chip formation in cutting Zr-BMG with an amorphous structure.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081004-081004-14. doi:10.1115/1.4043798.

The presence of various uncertainty sources in metal-based additive manufacturing (AM) process prevents producing AM products with consistently high quality. Using electron beam melting (EBM) of Ti-6Al-4V as an example, this paper presents a data-driven framework for process parameters optimization using physics-informed computer simulation models. The goal is to identify a robust manufacturing condition that allows us to constantly obtain equiaxed materials microstructures under uncertainty. To overcome the computational challenge in the robust design optimization under uncertainty, a two-level data-driven surrogate model is constructed based on the simulation data of a validated high-fidelity multiphysics AM simulation model. The robust design result, indicating a combination of low preheating temperature, low beam power, and intermediate scanning speed, was acquired enabling the repetitive production of equiaxed structure products as demonstrated by physics-based simulations. Global sensitivity analysis at the optimal design point indicates that among the studied six noise factors, specific heat capacity and grain growth activation energy have the largest impact on the microstructure variation. Through this exemplar process optimization, the current study also demonstrates the promising potential of the presented approach in facilitating other complicate AM process optimizations, such as robust designs in terms of porosity control or direct mechanical property control.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081005-081005-12. doi:10.1115/1.4043799.

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.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081006-081006-8. doi:10.1115/1.4043899.

This paper evaluates the performances of dry, minimum quantity lubrication (MQL), and MQL with nanofluid conditions in turning of the most common titanium (Ti) alloy, Ti-6Al-4 V, in a solution treated and aged (STA) microstructure. In particular, the nanofluid evaluated here is vegetable (rapeseed) oil mixed with small concentrations of exfoliated graphite nanoplatelets (xGnPs). This paper focuses on turning process that imposes a challenging condition to apply the oil or nanofluid droplets directly onto the tribological surfaces of a cutting tool due to the uninterrupted engagement between tool and work material during cutting. A series of turning experiments was conducted with uncoated carbide inserts, while measuring the cutting forces with a dynamometer under the dry, MQL and MQL with nanofluid conditions supplying oil droplets externally from our MQL device. The inserts are retrieved intermittently to measure the progress of flank and crater wear using a confocal microscopy. This preliminary experimental result shows that MQL and in particular MQL with the nanofluid significantly improve the machinability of Ti alloys even in turning process. However, to attain the best performance, the MQL conditions such as nozzle orientation and the concentration of xGnP must be optimized.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081007-081007-10. doi:10.1115/1.4043765.

The mask image projection-based stereolithography (MIP-SL) is a low-cost and high-resolution additive manufacturing (AM) process. However, the slow speed of part separation and resin refilling is the primary bottleneck that limits the fabrication speed of the MIP-SL process. In addition, the stair-stepping effect due to the layer-based fabrication process limits the surface quality of built parts. To address the critical issues in the MIP-SL process related to resin refilling and layer-based fabrication, we present a mask video projection-based stereolithography (MVP-SL) process with continuous resin flow and light exposure. The newly developed AM process enables the continuous fabrication of three-dimensional (3D) objects with ultra-high fabrication speed. In the paper, the system design to achieve mask video projection and the process settings to achieve ultrafast fabrication speed are presented. The relationship between process parameters and the surface quality of the built parts is discussed. Test results illustrate that the MVP-SL process with a continuous resin flow can build three-dimensional objects within minutes, and the surface quality of the fabricated objects is significantly improved.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081008-081008-12. doi:10.1115/1.4043836.

The synergistic effect of combining different modification methods was investigated in this study to improve the interlaminar toughness and delamination resistance of fiber reinforced polymers (FRP). Epoxy-compatible polysulfone (PSU) was end-capped with epoxide group through functionalization, and the fiber surface was chemically grafted with an amino functional group to form a micron-size rough surface. Consequently, the long chain of PSU entangles into cross-linked thermoset epoxy network, additionally, epoxide group on PSU further improves the bonding through chemical connection to the epoxy network and amino group on the fiber surface. The combined modification methods can generate both strong physical and chemical bonding. The feasibility of using this method in vacuum-assisted resin transfer molding was determined by rheometer. The impact of formed chemical bonds on the cross-linking density was examined through glass transition temperatures. The chemical modifications were characterized by Raman spectroscopy to determine the chemical structures. Synergistic effect of the modification was established by mode I and mode II fracture tests, which quantify the improvement on composites delamination resistance and toughness. The mechanism of synergy was explained based on the fracture mode and interaction between the modification methods. Finally, numerical simulation was used to compare samples with and without modifications. The experiment results showed that synergy is achieved at low concentration of modified PSU because the formed chemical bonds compensate the effect of low cross-linking density and interact with the modified fiber.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081009-081009-9. doi:10.1115/1.4043839.

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.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081010-081010-15. doi:10.1115/1.4043900.

Ultrasonic welding has been widely used in joining plastic parts since it is fast, economical, and suitable for automation. It also has great potential for joining thermoplastic composite structures in the aerospace and automotive industries. For a successful industrial application of ultrasonic composite welding, it is necessary to have effective weld quality prediction technology. This paper proposes a model for weld quality prediction by establishing a correlation between ultrasonic wave transmission and welding process signatures. The signatures, welding power, and force are directly related to the weld quality. This model is used to predict the weld quality with three contact conditions and validated by experiments. The results show that the quality model performs well when a centralized and consistent contact condition is achieved. The model provides a process physics-based solution for the online weld quality prediction in ultrasonic welding of carbon fiber composite.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081011-081011-7. doi:10.1115/1.4043980.

Injection molding of plastic optical lenses prevails over many other techniques in both efficiency and cost; however, polymer shrinkage during cooling, high level of uneven residual stresses, and refractive index variations have limited its potential use for high precision lens fabrication. In this research, we adopted a newly developed strong graphene network to both plano and convex fused silica mold surfaces and proposed a novel injection molding with graphene-coated fused silica molds. This advanced injection molding process was implemented in the molding of polymer-based plano-concave lenses resulting in reduced polymer shrinkage. In addition, internal residual stresses and refractive index variations were also analyzed and discussed in detail. Meanwhile, as a comparison of conventional injection mold material, aluminum mold inserts with the same shape and size were also diamond machined and then employed to mold the same plano-concave lenses. Finally, a simulation model using moldex3d was utilized to interpret stress distributions of both graphene and aluminum molds and then validated by experiments. The comparison between graphene-coated mold and aluminum mold reveals that the novel injection molding with carbide-bonded graphene-coated fused silica mold inserts is capable of molding high-quality optical lenses with much less shrinkage and residual stresses with a more uniform refractive index distribution.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081012-081012-11. doi:10.1115/1.4043981.

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.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081013-081013-12. doi:10.1115/1.4043898.

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.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2019;141(8):081014-081014-8. doi:10.1115/1.4043983.

Production of functionally graded materials (FGMs, i.e., a gradual transition from one material to another) and components is challenging using conventional manufacturing techniques. Additive manufacturing (AM) provides a new opportunity for producing FGMs. However, current metal AM technologies including powder-bed fusion are limited to producing single material components or vertical FGM parts, i.e., a different material composition in different layers but not within the same layer, and in situ changing materials is challenging. In this paper, we demonstrate the fabrication of horizontal and 3D 316L/Cu10Sn components with FGM within the same layer and in different layers, via a proprietary multiple selective powder delivery array device incorporated into a selective laser melting system that allowed the deposition of up to six different materials point by point. The manufactured component macrostructure, microstructure, microhardness, and phases were examined. Smooth transition from one material to the other was realized. Also, an interesting phenomenon was found that the maximum hardness was at 50% 316L and 50% Cu10Sn. The work would open up a new opportunity for the manufacturing of true 3D functionally graded components using additive manufacturing and for the rapid development of new metal alloy systems.

Commentary by Dr. Valentin Fuster

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