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Research Papers

J. Manuf. Sci. Eng. 2017;139(7):071001-071001-24. doi:10.1115/1.4035676.

Many types of artifacts appear in X-ray computed tomography (CT) volume data, which influence measurement quality of industrial cone beam X-ray CT. Most of those artifacts are associated to CT scanning parameters; therefore, a good scanning parameter setting can weaken the influence to improve measurement accuracy. This paper presents a simulation method for evaluating CT scanning parameters for dimensional metrology. The method can aid CT metrology to achieve high measurement accuracy. In the method, image entropy is used as a criterion to evaluate the quality of CT volume data. For entropy calculation of CT volume data, a detailed description about bin width and entropy zone is given. The relationship between entropy values of CT volume data and error parameters of CT metrology is shown and discussed. By use of this method, mainly we focus on specimen orientation evaluation, and some other typical scanning parameters are used to evaluate the proposed method. Two typical specimens are used to evaluate the performance of the proposed method.

Topics: Entropy , Errors , Metrology
Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071002-071002-13. doi:10.1115/1.4035898.

Uncertainty quantification (UQ) is an emerging field that focuses on characterizing, quantifying, and potentially reducing, the uncertainties associated with computer simulation models used in a wide range of applications. Although it has been successfully applied to computer simulation models in areas such as structural engineering, climate forecasting, and medical sciences, this powerful research area is still lagging behind in materials simulation models. These are broadly defined as physics-based predictive models developed to predict material behavior, i.e., processing-microstructure-property relations and have recently received considerable interest with the advent of emerging concepts such as Integrated Computational Materials Engineering (ICME). The need of effective tools for quantifying the uncertainties associated with materials simulation models has been identified as a high priority research area in most recent roadmapping efforts in the field. In this paper, we present one of the first efforts in conducting systematic UQ of a physics-based materials simulation model used for predicting the evolution of precipitates in advanced nickel–titanium shape-memory alloys (SMAs) subject to heat treatment. Specifically, a Bayesian calibration approach is used to conduct calibration of the precipitation model using a synthesis of experimental and computer simulation data. We focus on constructing a Gaussian process-based surrogate modeling approach for achieving this task, and then benchmark the predictive accuracy of the calibrated model with that of the model calibrated using traditional Markov chain Monte Carlo (MCMC) methods.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071003-071003-12. doi:10.1115/1.4035794.

Gear shaping, commonly regarded as the most widely used machining method for cylindrical gear, is in fact an ideal manufacturing method for noncircular gear due to its merit of not being restricted by gear type or pitch curve in contrast to gear hobbing. However, concerning researches are mainly focused on the generation of noncircular straight external gear, paying rare attention to noncircular internal gear and noncircular helix gear. Considering that this paper, through using a three-linkage computer numerical control (CNC) shaping machine, aims to synthesize shaped noncircular gear, covering external, internal, straight, and helix gear. The mathematical model, a three-linkage model, is first established. The corresponding manufacturing process in practice is subsequently discussed. Finally, with practical shaping experiments, the correctness of the proposed model and the appropriateness of the manufacturing process are verified.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071004-071004-13. doi:10.1115/1.4035491.

One of the challenges in micromilling processing is chatter, an unstable phenomenon which has a larger impact on the microdomain compared to macro one. The minimization of tool chatter is the key to good surface quality in the micromilling process, which is also related to the milling tool and the milling structure system dynamics. Frequency response function (FRF) at micromilling tool point describes dynamic behavior of the whole micromilling machine-spindle-tool system. In this paper, based on receptance coupling substructure analysis (RCSA) and the consideration of rotational degree-of-freedom, tool point frequency response function of micromilling dynamic system is obtained by combining two functions calculated from beam theory and obtained by hammer testing. And frequency response functions solved by Timoshenko's and Euler's beam theories are compared. Finally, the frequency response function is identified as the modal parameters, and the modal parameters are transformed into equivalent structural parameters of the physical system. The research work considers the difference of theoretical modeling between the micromilling and end-milling tool and provides a base for the dynamic study of the micromilling system.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071005-071005-10. doi:10.1115/1.4035962.

With many industries increasingly relying on leased equipment and machinery, many original equipment manufacturers (OEMs) are turning to product-service packages where they deliver (typically lease) the physical assets. An integrated service contract will be offered for the asset. A classic example being Rolls Royce power-by-the-hour aircraft engines. Service contracts offered by original equipment manufacturers have predominantly focused on maintenance and upkeep activities for a single asset. Interestingly enough, manufacturing industries are beginning to adopt the product-service paradigm. However, one of the unique aspects in manufacturing settings is that the leased system is often not a single asset but instead a multi-unit system (e.g., an entire production line). In this paper, we develop a lease-oriented maintenance methodology for multi-unit leased systems under product-service paradigm. Unlike traditional maintenance models, we propose a leasing profit optimization (LPO) policy to adaptively compute optimal preventive maintenance (PM) schedules that capture the following dynamics: (1) the structural dependencies of the multi-unit system, (2) opportunistic maintenance of multiple system components, and (3) leasing profit savings (LPSs). We demonstrate the performance of our multi-unit maintenance policy by using a leased automotive manufacturing line and investigate its impact on leasing profits.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071006-071006-9. doi:10.1115/1.4035795.

The hybrid stereolithography (SLA) process integrates a laser scanning-based system and a mask projection-based system. Multiple laser paths are used to scan the border of a 2D pattern, whereas a mask image is adopted to solidify the interior area. By integrating merits of two subsystems, the hybrid SLA process can achieve high surface quality without sacrificing productivity. For the hybrid system, closed polygonal contours are required to direct the laser scanning, and a binary image is also needed for the mask projection. We proposed a novel image-based slicing method. This approach can convert a 3D model into a series of binary images directly, and each image is corresponding to the cross section of the model at a specific height. Based on the resultant binary image, we use an image processing method to gradually shrink the pattern in the image. Boundaries of the shrunk image are traced and then restored as polygons to direct the laser spot movement. The final shrunk image serves as the input for the mask projection. Experimental results of test cases demonstrate that the proposed method is substantially more efficient than the traditional approaches. Its accuracy is also studied and discussed.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071007-071007-9. doi:10.1115/1.4035963.

Fused deposition modeling (FDM) is currently one of the most widely utilized prototyping technologies. Studies employing statistical techniques have been conducted to develop empirical relationships between FDM process factors and output variables such as dimensional accuracy, surface roughness, and mechanical properties of the fabricated structures. However, the effects of nozzle temperature (T), nozzle-bed distance (NBD), and their interactions on strut width (SW) have not been investigated. In the present work, a two-way factorial study with three levels of T and NBD in triplicates was undertaken. A fixed-effects model with interaction was proposed and remedial measures based on the error analysis were performed to obtain correct inferences. The factor main/interaction effects were all found to be statistically significant (p < 0.05) using analysis of variance (ANOVA). Multiple comparisons were conducted between treatment means using the Tukey's method. A multiple linear regression (MLR) model (R2 = 0.95) was subsequently developed to enable the prediction of SW. The developed MLR model was verified experimentally; by (1) the fabrication of individual struts and (2) the fabrication of single-layer scaffolds with parallel raster patterns. The percentage error between the predicted and observed widths of individually fabricated struts was 3.2%, and the error between predicted and observed SW/spacing for the single-layer scaffolds was ≤ 5.5%. Results indicate that a similar statistical methodology could be potentially employed to identify levels of T and NBD that yield defined width struts using open architecture, personal or commercial FDM setups, and existing/new materials.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071008-071008-7. doi:10.1115/1.4035964.

In this paper, an additive manufacturing (AM) process, magnetic field-assisted projection stereolithography (M-PSL), is developed for 3D printing of three-dimensional (3D) smart polymer composites. The 3D-printed magnetic field-responsive smart polymer composite creates a wide range of motions, opening up possibilities for various new applications, like sensing and actuation in soft robotics, biomedical devices, and autonomous systems. In the proposed M-PSL process, a certain amount of nano- or microsized ferromagnetic particles is deposited in liquid polymer by using a programmable microdeposition nozzle. An external magnetic field is applied to direct the magnetic particles to the desired position and to form the desired orientation and patterns. After that, a digital mask image is used to cure particles in photopolymer with desired distribution patterns. The magnetic-field-assisted projection stereolithography (M-PSL) manufacturing process planning, testbed, and materials are discussed. Three test cases, an impeller, a two-wheel roller, and a flexible film, were performed to verify and validate the feasibility and effectiveness of the proposed process. They were successfully fabricated and remote controls of the printed samples were demonstrated, showing the capability of printed smart polymer composites on performing desired functions.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071009-071009-9. doi:10.1115/1.4035796.

Bending 3D free form metal plates is a common process used in many heavy industries such as shipbuilding. The traditional method is the so-called line heating method, which is not only labor intensive but also inefficient and error-prone. This paper presents a new incremental bending method based on minimum energy principle and model-less control. First, the sheet metal is discretized into a number of strips connected through virtual springs. Next, by applying the minimum energy principle, the punching and supporting points are calculated for the strip. Then, the bended shape of the strip is computed based on the beam bending theory. This process is continued until the final shape is reached. To compensate the bending error, the computer vision-based model-less control is applied. The computer vision detects the bending error based on which additional bending steps are calculated. The new method is tested in a custom build incremental bending machine. Different metal plates are formed. For a metal plate of 1000 × 800 × 5 mm3, the average bending error is less than 3 mm. In comparison with the existing methods, the new method has a number of advantages, including simple, fast, and highly energy efficient.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071010-071010-9. doi:10.1115/1.4036126.

A low concentrated polystyrene (PS) additive to epoxy is used, since it is able to reduce the curing reaction rate but not at the cost of increasing viscosity and decreasing glass transition temperature of the curing epoxy. The modified epoxy is cocured with a compatible thermoplastic interleaf during the vacuum assisted resin transfer molding (VARTM) to toughen the interlaminar of the composites. Using viscometry, the solubilities of thermoplastics (TPs) polycarbonate (PC), polyetherimide (PEI), and polysulfone (PSU) are determined to predict their compatibility with epoxy. The diffusion and precipitation process between the most compatible polymer PSU and epoxy formed semi-interpenetration networks (semi-IPN). To optimize bonding adhesion, these diffusion and precipitation regions were studied via optical microscopy under curing temperatures from 25 °C to 120 °C and PS additive concentrations to epoxy of 0–5%. Uniaxial tensile tests were performed to quantify the effects of diffusion and precipitation regions on composite delamination resistance and toughness. Crack paths were observed to characterize crack propagation and arrest mechanism. Fracture surfaces were examined by scanning electron microscopy (SEM) to characterize the toughening mechanism of the thermoplastic interleaf reinforcements. The chemically etched interface between diffusion and precipitation regions showed semi-IPN morphology at different curing temperatures. Results revealed deeper diffusion and precipitation regions increase energy required to break semi-IPN for crack propagation resulting in crack arrests and improved toughness.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071011-071011-10. doi:10.1115/1.4036127.

Various methods of toughening the bonding between the interleaf and laminate glass fiber reinforced polymer (GFRP) have been developed due to the increasing applications in industries. A polystyrene (PS) additive modified epoxy is used to improve the diffusion and precipitation region between polysulfone (PSU) interleaf and epoxy due to its influence on the curing kinetics without changing glass transition temperature and viscosity of the curing epoxy. The temperature-dependent diffusivities of epoxy, amine hardener, and PSU are determined by using attenuated total reflection–Fourier transfer infrared spectroscopy (ATR–FTIR) through monitoring the changing absorbance of their characteristic peaks. Effects of PS additive on diffusivity in the epoxy system are investigated by comparing the diffusivity between nonmodified and PS modified epoxy. The consumption rate of the epoxide group in the curing epoxy reveals the curing reaction rate, and the influence of PS additive on the curing kinetics is also studied by determining the degree of curing with time. A diffusivity model coupled with curing kinetics is applied to simulate the diffusion and precipitation process between PSU and curing epoxy. The effect of geometry factor is considered to simulate the diffusion and precipitation process with and without the existence of fibers. The simulation results show the diffusion and precipitation depths which match those observed in the experiments.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071012-071012-10. doi:10.1115/1.4035586.

Aerosol jet printing (AJP) is a direct write technology that enables fabrication of flexible, fine scale printed electronics on conformal substrates. AJP does not require the time consuming mask and postpatterning processes compared with traditional electronics manufacturing techniques. Thus, the cycle time can be dramatically reduced, and highly personalized designs of electronics can be realized. AJP has been successfully applied to a variety of industries, with different combinations of inks and substrates. However, the quality of the printed electronics, such as resistance, is not able to be measured online. On the other hand, the microscopic image sensors are widely used for printed circuit boards (PCBs) quality quantification and inspection. In this paper, two widely used quality variables of printed electronics, resistance and overspray, will be jointly modeled based on microscopic images for fast quality assessment. Augmented quantitative and qualitative (AUGQQ) models are proposed to use features of microscopic images taken at different locations on the printed electronics as input variables, and resistance and overspray as output variables. The association of resistance and overspray can be investigated through the AUGQQ models formulation. A case study for fabricating silver lines with Optomec® aerosol jet system is used to evaluate the model performance. The proposed AUGQQ models can help assess the printed electronics quality and identify important image features in a timely manner.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071013-071013-16. doi:10.1115/1.4036124.

The structural dynamics of thin-walled parts vary as the material is removed during machining. This paper presents a new, computationally efficient reduced order dynamic substructuring method to predict the frequency response function (FRF) of the workpiece as the material is removed along the toolpath. The contribution of the removed mass to the dynamics of the workpiece is canceled by adding a fictitious substructure having the opposite dynamics of the removed material. The equations of motion of the workpiece are updated, and workpiece FRFs are evaluated by solving the hybrid set of assembled equations of motion in frequency domain as the tool removes the material between two consecutive dynamics update steps. The orders of the initial workpiece structure and the removed substructures are reduced using a model order reduction method with a newly introduced automatic master set selection criterion. The reduced order FRF update model is validated with peripheral milling tests and FRF measurements on a plate-shaped workpiece. It is shown that the proposed model provides ∼20 times faster FRF predictions than the full order finite element (FE) model.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071014-071014-8. doi:10.1115/1.4036122.

Finite element modeling (FEM) of machining-induced residual stresses (RS) takes place over two consecutive steps: a cutting step and a relaxation step. In the latter, the workpiece is left to cool down after deactivating all external loads. The current work focuses on the relaxation step, and how different strain components, material plasticity, and workpiece edge deflections affect the final state of different RS components. First, a two-dimensional arbitrary-Lagrangian–Eulerian (ALE) plane strain thermomechanical explicit model was used to simulate dry orthogonal cutting. After that, the relaxation process was modeled using three approaches: (1) the classical approach, (2) a new approach that is first presented here, and (3) a modified approach that was developed earlier by the current author. In the classical approach, the same exact machined workpiece is relaxed, considering all stress/strain components and material plasticity. On the other hand, the new approach uses a pure elastic one-dimensional thermal relaxation model, in the cutting direction, and assumes that the workpiece edges normal to the cutting direction remain so. The differences between the RS predicted by the new and classical approaches reflected the combined effects of the examined parameters. The role of each parameter was isolated using three different versions of the modified approach. The current findings confirmed that for orthogonal cutting, the stress relaxation process can be considered as a one-dimensional pure elastic thermal relaxation process. Also, the workpiece edges normal to the cutting direction deflect during relaxation, contributing to the final state of RS.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071015-071015-10. doi:10.1115/1.4036224.

Sliding guideways are often used as the foundation for linear motion in computer numerical control (CNC) machine tools due to their high damping capabilities especially for heavy duty machining applications. However, the traditional manufacturing process with grinding is time-consuming, and the product’s sliding performance has not been optimized nor clearly understood. In order to increase productivity, a machining center based manufacturing method with cubic boron nitride (CBN) milling tools was introduced and tested by researchers. While greatly reducing manufacturing time and cost, a rougher milled surface, in comparison to traditional grinding, is a possible concern for the performance as well as the life of sliding guideways. In this study, a novel planar honing process was proposed as a postprocess of CBN milling to create a finish surface on hardened cast iron sliding guideways used for CNC machine tools. A design of experiment (DOE) was conducted to statistically understand significant factors in the machining process and their relationship with surface topography. Effective planar honing conditions were discovered and analyzed with three-dimensional (3D) and two-dimensional surface parameters.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071016-071016-9. doi:10.1115/1.4036123.

In this study, a heat transfer model of machining of Ti–6Al–4V under the application of atomization-based cutting fluid (ACF) spray coolant is developed to predict the temperature of the cutting tool. Owing to high tool temperature involved in machining of Ti–6Al–4V, the model considers film boiling as the major heat transfer phenomenon. In addition, the design parameters of the spray for effective cooling during machining are derived based on droplet–surface interaction model. Machining experiments are conducted and the temperatures are recorded using the inserted thermocouple technique. The experimental data are compared with the model predictions. The temperature field obtained is comparable to the experimental results, confirming that the model predicts tool temperature during machining with ACF spray cooling satisfactorily.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071017-071017-11. doi:10.1115/1.4036349.

Error motion of an ultraprecision axis of rotation has great influences on form error of machined parts. This paper gives a complete error analysis for the measurement procedure including nonlinearity error of capacitive displacement probes, misalignment error of the probes, eccentric error of artifact balls, environmental error, and error caused by different error separation methods. Nonlinearity of the capacitive displacement probe targeting a spherical surface is investigated through experiments. It is found that the additional probe output caused by lateral offset of the probe relative to the artifact ball greatly affects the measurement accuracy. Furthermore, it is shown that error motions in radial and axial directions together with eccentric rotation of the artifact lead to lateral offset. A novel measurement setup which integrates an encoder and an adjustable artifact is designed to ensure measurement repeatability by a zero index signal from the encoder. Moreover, based on the measurement setup, once roundness of the artifact is calibrated, roundness of the artifact can be accurately compensated when radial error motion is measured, and this method improves measurement efficiency while approaches accuracy comparable to that of error separation methods implemented alone. Donaldson reversal and three-probe error separation methods were implemented, and the maximum difference of the results of the two methods is below 14 nm. Procedure of uncertainty estimation of radial error motion is given in detail by analytical analysis and Monte Carlo simulation. The combined uncertainty of radial error motion measurement of an aerostatic spindle with Donaldson reversal and three-probe methods is 14.8 nm and 13.9 nm (coverage k = 2), respectively.

Topics: Errors , Probes , Uncertainty
Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071018-071018-9. doi:10.1115/1.4036350.

Manufacturers have faced an increasing need for the development of predictive models that predict mechanical failures and the remaining useful life (RUL) of manufacturing systems or components. Classical model-based or physics-based prognostics often require an in-depth physical understanding of the system of interest to develop closed-form mathematical models. However, prior knowledge of system behavior is not always available, especially for complex manufacturing systems and processes. To complement model-based prognostics, data-driven methods have been increasingly applied to machinery prognostics and maintenance management, transforming legacy manufacturing systems into smart manufacturing systems with artificial intelligence. While previous research has demonstrated the effectiveness of data-driven methods, most of these prognostic methods are based on classical machine learning techniques, such as artificial neural networks (ANNs) and support vector regression (SVR). With the rapid advancement in artificial intelligence, various machine learning algorithms have been developed and widely applied in many engineering fields. The objective of this research is to introduce a random forests (RFs)-based prognostic method for tool wear prediction as well as compare the performance of RFs with feed-forward back propagation (FFBP) ANNs and SVR. Specifically, the performance of FFBP ANNs, SVR, and RFs are compared using an experimental data collected from 315 milling tests. Experimental results have shown that RFs can generate more accurate predictions than FFBP ANNs with a single hidden layer and SVR.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;139(7):071019-071019-8. doi:10.1115/1.4036290.

The advance in computational science and engineering allows people to simulate the additive manufacturing (AM) process at high fidelity, which has turned out to be a valid way to model, predict, and even design the AM processes. In this paper, we propose a new method to simulate the melting process of metal powder-based AM. The governing physics is described using partial differential equations for heat transfer and Laminar flow. Level set methods are applied to track the free surface motion of the molten metal flow. Some fundamental issues in the metal-based AM process, including free surface evolution, phase transitions, and velocity field calculation, are explored, which help us gain insight into the metal-based AM process. The convergence problem is also examined to improve the efficiency in solving this multiphysics problem.

Commentary by Dr. Valentin Fuster

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