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Review Article

J. Manuf. Sci. Eng. 2017;139(9):090801-090801-12. doi:10.1115/1.4036909.

This study presents detailed analyses of variant joining processes under the category of friction stir riveting (FSR) that are applied to assemble similar or dissimilar materials by integrating the advantages of both friction stir process and mechanical fastening. It covers the operating principle of FSR methods along with the insights into various process parameters responsible for successful joint formation. The paper further evaluates the researches in friction stir-based riveting processes, which unearth the enhanced metallurgical and mechanical properties, for instance microstructure refinement, local mechanical properties and improved strength, corrosion, and fatigue resistance. Advantages and limitations of the FSR processes are then presented. The study is concluded by summarizing the key analyses and proposing the potential areas for future research.

Commentary by Dr. Valentin Fuster

Research Papers

J. Manuf. Sci. Eng. 2017;139(9):091001-091001-12. doi:10.1115/1.4036908.

Additive manufacturing (AM) is rapidly becoming a local manufacturing modality in fabricating complex, custom-designed parts, providing an unprecedented form-free flexibility for custom products. However, significant variability in part geometric quality and mechanical strength due to the shortcomings of AM processes has often been reported. Presently, AM generally lacks in situ quality inspection capability, which seriously hampers the realization of its full potential in delivering qualified practical parts. Here, we present a monitoring approach and a periodic structure design for developing test artifacts for in situ real-time monitoring of the material and bonding properties of a part at fiber/bond-scale. While the production method used in current work is filament based, the proposed approach is generic as defects are always due to materials in a bonding zone and their local bonding attributes in any production modality. The artifact design detailed here is based on ultrasonic wave propagation in phononic coupons consisting of repeating substructures to monitor and eventually to assess the bond quality and placement uniformity—not only for geometry but also for defect states. Periodicity in a structure leads to the dispersion of waves, which is sensitive to geometric/materials properties and irregularities. In this proof-of-concept study, an experimental setup and basic artifact designs are described and off-line/real-time monitoring data are presented. As a model problem, the effects of printing speed on the formation of stop bands, wave propagation speeds and fiber placement accuracy in samples are detected and reported.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091002-091002-11. doi:10.1115/1.4036992.

The quality of threaded pipe connections is one of the key quality characteristics of drill pipes, risers, and pipelines. This quality characteristic is evaluated mainly by a pair of critical points, which are corresponding to the mechanical deformations formed in the pipe connection process. However, these points are difficult to detect because of nonlinear patterns generated by latent process factors in torque signals, which conceal the true critical points. To address this problem, we propose a novel three-phase state-space model that incorporates physical interpretations of connection process to detect pairwise critical points. We also develop a two-stage recursive particle filter to estimate the locations of the underlying critical points. Results of a real threaded pipe connection case show that the detection performance of the proposed method is more powerful than that of other existing methods.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091003-091003-10. doi:10.1115/1.4036910.

This paper describes in detail the deformation behavior of the rolls and strip predicted from the three-dimensional finite element analysis of skin-pass rolling. The predictions are made on the basis of the coupled analysis of elastic deformation of the rolls and elastic–plastic deformation of the strip. Predictions from the proposed finite element (FE) model are compared with experimental data from laboratory-scale cold rolling mills. Then, proposed are models for the prediction of the roll force profile and for the prediction of the residual stress profile. The prediction accuracy of the models is examined through comparison with the predictions from the FE model.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091004-091004-11. doi:10.1115/1.4036714.

Residual stress (RS) has significant impact on cutting process optimization. However, conventional process modeling approaches are limited to only single cutting pass on very short length and time scales due to the exceedingly high computational cost. This work provides a new concept of equivalent loading which enables an efficient modeling approach to predict RS in an actual machined surface by incorporating multiple cutting passes and crossing different length and time scales. The predicted residual stress profiles are validated in turning Inconel 718 superalloy under different edge geometries and process conditions.

Topics: Stress , Cutting
Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091005-091005-14. doi:10.1115/1.4036641.

The objective of this work is to develop and apply a spectral graph theoretic approach for differentiating between (classifying) additive manufactured (AM) parts contingent on the severity of their dimensional variation from laser-scanned coordinate measurements (3D point cloud). The novelty of the approach is in invoking spectral graph Laplacian eigenvalues as an extracted feature from the laser-scanned 3D point cloud data in conjunction with various machine learning techniques. The outcome is a new method that classifies the dimensional variation of an AM part by sampling less than 5% of the 2 million 3D point cloud data acquired (per part). This is a practically important result, because it reduces the measurement burden for postprocess quality assurance in AM—parts can be laser-scanned and their dimensional variation quickly assessed on the shop floor. To realize the research objective, the procedure is as follows. Test parts are made using the fused filament fabrication (FFF) polymer AM process. The FFF process conditions are varied per a phased design of experiments plan to produce parts with distinctive dimensional variations. Subsequently, each test part is laser scanned and 3D point cloud data are acquired. To classify the dimensional variation among parts, Laplacian eigenvalues are extracted from the 3D point cloud data and used as features within different machine learning approaches. Six machine learning approaches are juxtaposed: sparse representation, k-nearest neighbors, neural network, naïve Bayes, support vector machine, and decision tree. Of these, the sparse representation technique provides the highest classification accuracy (F-score > 97%).

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091006-091006-11. doi:10.1115/1.4036784.

When machining narrow grooves, corners, and other complex cavities with trochoidal milling, the irrationally large trochoidal step usually leads to chatter, while the conservative trochoidal step constrains the machining efficiency. In this paper, a stability prediction model of trochoidal milling is established to solve these problems. An approach considering trochoidal steps and spindle speeds is presented to predict stability boundary of trochoidal milling. With considering the varying cutter-workpiece engagements, the stability of trochoidal milling process is predicted by obtaining the stability lobes of different cutter location (CL) points along the trochoidal milling tool paths. Based on the proposed stability model, a trochoidal step optimization strategy is developed to improve the machining efficiency of trochoidal milling under other parameters in a given situation. Cutting experiments are performed on the machining center GMC 1600H/2 to show the effectiveness of the proposed trochoidal milling stability model. Finally, simulations are adopted to illustrate the optimization strategy.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091007-091007-9. doi:10.1115/1.4036786.

In this study, the Fickian diffusion formulation is extended to the adhesive layer of a single lap joint (SLJ) model, in order to develop a coupled peel and shear stress-diffusion model. Constitutive equations are formulated for shear and peel stresses in terms of adhesive material properties that are time- and location-dependent. Numerical solution is provided for the effect of diffusion on shear and peel stresses distribution. Detailed discussion of the results is presented.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091008-091008-10. doi:10.1115/1.4037182.

Magnesium (Mg) and its alloys are among the lightest metallic structural materials, making them very attractive for use in the aerospace and automotive industries. Recently, Mg has been used in metal matrix composites (MMCs), demonstrating significant improvements in mechanical performance. However, the machinability of Mg-based MMCs is still largely elusive. In this study, Mg-based MMCs are machined using a wide range of cutting speeds in order to elucidate both the chip morphology and chip formation mechanism. Cutting speed is found to have the most significant influence on both the chip morphology and chip formation mechanism, with the propensity of discontinuous, particle-type chip formation increasing as the cutting speed increases. Saw-tooth chips are found to be the primary chip morphology at low cutting speeds (lower than 0.5 m/s), while discontinuous, particle-type chips prevail at high cutting speeds (higher than 1.0 m/s). Using in situ high-speed imaging, the formation of the saw-tooth chip morphology is found to be due to crack initiation at the free surface. However, as the cutting speed (and strain rate) increases, the formation of the discontinuous, particle-type chip morphology is found to be due to crack initiation at the tool tip. In addition, the influences of tool rake angle, particle size, and particle volume fracture are investigated and found to have little effect on the chip morphology and chip formation mechanism.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091009-091009-8. doi:10.1115/1.4036785.

Additive manufacturing, also known as three-dimensional (3D) printing, is an approach in which a structure may be fabricated layer by layer. For 3D inkjet printing, droplets are ejected from a nozzle, and each layer is formed droplet by droplet. Inkjet printing has been widely applied for the fabrication of 3D biological gel structures, but the knowledge of the microscale interactions between printed droplets is still largely elusive. This study aims to elucidate the layer formation mechanism in terms of the formation of single lines and layers comprised of adjacent lines during drop-on-demand inkjet printing of alginate using high speed imaging and particle image velocimetry. Inkjet droplets are found to impact, spread, and coalesce within a fluid region at the deposition site, forming coherent printed lines within a layer. The effects of printing conditions on the behavior of droplets during layer formation are discussed and modeled based on gelation dynamics, and recommendations are presented to enable controllable and reliable fabrication of gel structures. The effects of gelation on droplet impact dynamics are found to be negligible during alginate printing, and interfaces are found to form between printed lines within a layer depending on printing conditions, printing path orientation, and gelation dynamics.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091010-091010-14. doi:10.1115/1.4037040.

Springback is an important issue for the application of advanced high-strength steels (AHSS) in the automobile industry. Various studies have shown that it is an effective way to predict springback by using path-dependent material models. The accuracy of these material models greatly depends on the experimental test methods as well as material parameters calibrated from these tests. The present cyclic sheet metal test methods, like uniaxial tension–compression test (TCT) and cyclic shear test (CST), are nonstandard and various. The material parameters calibrated from these tests vary greatly from one to another, which makes the usage of material parameters for the accurate prediction of springback more sophisticated even when the advanced material model is available in commercial software. The focus of this work is to compare the springback prediction accuracy by using the material parameters calibrated from tension–compression test or cyclic shear test, and to further clarify the usage of those material parameters in application. These two types of nonstandard cyclic tests are successfully carried out on a same test platform with different specimen geometries. One-element models with corresponding tension–compression or cyclic shear boundary conditions are built, respectively, to calibrate the parameters of the modified Yoshida–Uemori (YU) model for these two different tests. U-bending process is performed for springback prediction comparison. The results show, for dual phase steel (DP780), the work hardening stagnation is not evident by tension–compression tests at all the prestrain levels or by cyclic shear test at small prestrain γ = 0.20 but is significantly apparent by cyclic shear tests at large prestrain γ = 0.38, 0.52, 0.68, which seems to be a prestrain-dependent phenomenon. The material parameters calibrated from different types of cyclic sheet metal tests can vary greatly, but it gives slight differences of springback prediction for U-bending by utilizing either tension–compression test or cyclic shear test.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091011-091011-7. doi:10.1115/1.4037181.

The Zamak 2 alloy has the best mechanical properties of the Zamak alloys with respect to the tensile strength, creep resistance, and hardness. Zamak 2 is a commercial material widely used for the manufacturing of mechanical components. The presence of Cu in this alloy (3 wt. %) improves the mechanical properties through the formation of E (CuZn4) precipitates. The powder metallurgy (P/M) has an important direct advantage in the fabricated parts with respect to the finished dimensions or near net shaping due to the additional phase stabilization without heat treatment. However, there are few studies into the production of this zinc alloy via mechanical alloying and the effect of the consolidation technique in terms of the material properties; these research deficiencies led to the development of this work. The powder was analyzed during milling until achieving a steady-state, which occurred after 30 h of milling in a planetary ball mill at 400 rpm. The high-energy milling produces a Zamak 2 alloy powder with a T′ stable phase and with a greater melting point. When consolidated using hot pressing, the hardness increases compared to sintering and casting alloy.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091012-091012-8. doi:10.1115/1.4036639.

Robotic applications in aerospace manufacturing and aircraft assembly today are limited. This is because most of the aircraft parts are relatively crowded and have complex shapes that make tasks like robotic drilling and fastening more challenging. These challenges include tool accessibility, path, and motion planning. In this paper, a process methodology was developed to overcome the tool accessibility challenges facing robotic drilling and riveting for aircraft parts that are located in crowded work environments. First, the tool accessibility was analyzed based on the global accessibility area (GAA) and the global accessibility volume (GAV) to determine the accessible boundaries for parts with zero, one, and two surfaces curvatures. Then, the path for the tool was generated while taking in consideration the approachability planning. This approach generates a number of intermediate points that enable the tool to maneuver around obstacles to reach the final target points if they are accessible. Last, a software application was developed to simulate the drilling and riveting tasks, and to validate the proposed process. The results of the simulation confirmed the proposed methodology and provided a numerical feedback describing the level of crowdedness of the work environment. The accessibility percentage can then be used by the design team to reduce the design complexity and increase the level of tool accessibility.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091013-091013-14. doi:10.1115/1.4036834.

As an important component of gas turbine engines, a blisk (or an axial compressor) is complex in shape. The pressure and suction surfaces of the blisk blades are designed with free-form surfaces, and the space (or the channel) between two adjacent blades varies significantly. Thus, some blade patches can be machined with large-diameter cutters, and some patches have to be cut with small-diameter cutters. Usually, the blisk's material is high-strength stainless steel, titanium alloy, or difficult-to-cut material. The cutting force and temperature in roughing the blisks are high, and thus, the machine tool should be rigid and the cutters should be as large as possible. Therefore, the best industrial practice of rough-machining the blisks is to use multiple largest solid and indexable end-mills to cut them patch by patch on a four-axis computer numerically controlled (CNC) machine. The reasons are (a) four-axis CNC machines are more rigid than five-axis CNC machines, (b) multiple largest cutters are used for higher cutting speeds and feed rates and for less machining time and longer tool life, and (c) if indexable end-mills can be used, the tooling costs are further reduced. For the blisk finishing, a small cutter is often used on a five-axis CNC machine, which is not a topic of this work. However, due to complex shape of the blades, it is quite difficult to automatically optimize the blade surface partition so that each surface patch can be cut with a largest cutter in four-axis blisk rough machining. In the conventional way, numerically controlled (NC) programmers often employ small-diameter solid end-mills and plan their paths to cut the blades layer by layer in four-axis milling. Unfortunately, the machining efficiency of this way is low, and the end-mills wear out quickly. This work establishes a theoretical and completed solution. A simplified optimization model of the largest allowable diameter of the theoretical cutter at a cutter contact (CC) point is established, and an efficient and reliable solver is proposed. The blade surfaces are automated partitioned for largest cutters to the surfaces patch by patch in four-axis rough machining. This approach is efficient and reliable, and it is viable in theory and practical in industry.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091014-091014-13. doi:10.1115/1.4037039.

Tadeusz Rut (TR) forging is a widely used forging method to create heavy, solid crankshafts for marine or power-generating engines. The preform of a TR forging is forged into a crank throw by simultaneously applying both a vertical and a horizontal deformation. It is necessary to optimize the preform design, since a conventional analytical design for the preform gives various choices for the geometric variables. The purpose of the current study is to optimize the preform design in TR forging for heavy crankshafts in order to improve the dimensional accuracy of a forged shape using a limited material volume. A finite element (FE) model for TR forging was developed and validated by comparing with experimental results. Parametric FE analyses were used to evaluate the effects of the geometric variables of the preform on the final dimensions of the forged product. The geometric variables of the preform were optimized by a response-surface method (RSM) to obtain the results of parametric FE analyses. The volume allocation between the pin and the web of the preform is the dominant factor that affects the desirability of the final forged shape. A multi-objective optimization is employed to consider the mutually exclusive changes of local machining allowances of the final forged product. Optimization using a response-surface method is a useful tool to reach the large and uniform machining allowances that are required for the preform necessary for a TR forging.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091015-091015-8. doi:10.1115/1.4037231.

The high-efficiency utilization of cutting tool resource is closely related to the flexible decision of tool life criterion, which plays a key role in manufacturing systems. Targeting a flexible method to evaluate tool life, this paper presents a data-driven approach considering all the machining quality requirements, e.g., surface integrity, machining accuracy, machining stability, chip control, and machining efficiency. Within the context, to connect tool life with machining requirements, all patterns of tool wear including flank face wear and rake face wear are fully concerned. In this approach, tool life is evaluated systematically and comprehensively. There is no generalized system architecture currently, and a four-level architecture is therefore proposed. Workpiece, cutting condition, cutting parameter, and cutting tool are the input parameters, which constrain parts of the independent variables of the evaluation objective including first-level and second-level indexes. As a result, tool wears are the remaining independent variables, and they are calculated consequently. Finally, the performed processes of the method are experimentally validated by a case study of turning superalloys with a polycrystalline cubic boron nitride (PCBN) cutting tool.

Topics: Wear , Machining , Cutting
Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):091016-091016-14. doi:10.1115/1.4037235.

There is a need for the development of lumped-parameter models that can be used for real-time control design and optimization for laser-based additive manufacturing (AM) processes. Our prior work developed a physics-based multivariable model for melt–pool geometry and temperature dynamics in a single-bead deposition for a directed energy deposition process and then validated the model using experimental data from deposition of single-bead Ti–6AL–4V (or Inconel®718) tracks on an Optomec® Laser Engineering Net Shaping (LENS) system. In this paper, we extend such model for melt–pool geometry in a single-bead deposition to a multibead multilayer deposition and then use the extended model on melt–pool height dynamics to predict part height of a three-dimensional build. Specifically, the extended model incorporates temperature history during the build process, which is approximated by super-positioning the temperature fields generated from Rosenthal's solution of point heat sources, with one heat source corresponding to one bead built before. The proposed model for part height prediction is then validated using builds with a variety of shapes, including single-bead thin wall structures, a patch build, and L-shaped structures, all built with Ti–6AL–4V using an Optomec® LENSTM MR-7 system. The model predictions on average part height show reasonable agreement with the measured average part height, with error rate less than 15%.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Manuf. Sci. Eng. 2017;139(9):094501-094501-7. doi:10.1115/1.4037108.

Owing to the contaminations in the small discharge gap of micro-electro-discharge machining (μEDM), generation of nonuniform nature of discharge pulses is more significant than in macro-EDM. To address the contribution in material removal of workpiece by each of these pulses, a pulse discriminating (PD) system which discriminates them into contributing and noncontributing types is generally used. Developing a PD system in μEDM is a time-consuming process that requires an availability of continuously running machine. Such requirement could be eliminated if virtual signals, similar to the actual once, are made available and provided continuously to the PD system developer. An innovative idea of generating such virtual signals, based on ni multisim, is, therefore, proposed and a robust PD system based on these signals is developed and validated. The strategy for discriminating the pulses in various types is developed through virtual instrumentation in ni labview. The robustness is validated in terms of its applicability over a wide range of parametric settings, acquisition length, and time.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(9):094502-094502-12. doi:10.1115/1.4036994.

Subsurface deformation of the cutting process has attracted a great deal of attention due to its tight relationship with subsurface hardening, microstructure alteration, grain refinement, and white layer formation. To predict the subsurface deformation of the machined components, an analytical model is proposed in this paper. The mechanical and thermal loads exerted on the workpiece by the primary and tertiary shear zones are predicted by a combination of Oxley's predictive model and Fang's slip line field. The stress field and temperature field are calculated based on contact mechanics and the moving heat source theory, respectively. However, the elastic–plastic regime induced by the material yielding hinders the direct derivation of subsurface plastic deformation from the stress field and the work material constitutive model. To tackle this problem, a blending function of the increment of elastic strain is developed to derive the plastic strain. In addition, a sophisticated material constitutive model considering strain hardening, strain rate sensitivity, and thermal softening effects of work material is incorporated into this analytical model. To validate this model, finite element simulations of the subsurface deformation during orthogonal cutting of AISI 52100 steel are conducted. Experimental verification of the subsurface deformation is carried out through a novel subsurface deformation measurement technique based on digital image correlation (DIC) technique. To demonstrate applications of the subsurface deformation prediction, the subsurface microhardness of the machined component is experimentally tested and compared against the predicted values based on the proposed method.

Commentary by Dr. Valentin Fuster

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