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Guest Editorial

J. Manuf. Sci. Eng. 2017;140(2):020301-020301-2. doi:10.1115/1.4038639.
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Computer numerically controlled manufacturing equipment and tooling has led to process automation and significant productivity advances. Demand for high quality products and cost-effective processes continues to grow and has driven the design of new machinery, intelligent tooling, and sophisticated control and automation techniques. However, the efficiency and throughput of modern manufacturing processes still depends on the interaction of the machine and the process. This motivates research in the area of process–machine interaction. This special issue provides a platform to disseminate recent research efforts that increase our understanding of this interaction. The paper topics are wide ranging, but may be arranged by discipline.

Commentary by Dr. Valentin Fuster

Research Papers

J. Manuf. Sci. Eng. 2017;140(2):021001-021001-11. doi:10.1115/1.4036783.

Cutter runout is universal and inevitable in milling process and has a direct impact on the shape of the in-process geometry. However, most of the works on the cutter-workpiece engagement (CWE) extraction neglect the cutter runout impact, which will result in a loss of precision. In this paper, an accurate method is presented to obtain CWE boundaries in five-axis milling with a general tool integrating the cutter runout impact. First, each flute's rotary surface is analytically derived. Then, by intersecting the section circle corresponding to the current flute with each of the rotary surface formed by previous flutes, a set of candidate feasible contact arcs (CFCAs) are obtained, and the valid feasible contact arc (VFCA) is defined as the common intersection of these CFCAs. Next, by intersecting the VFCA with the workpiece surfaces, the partial arc which locates inside the workpiece volume is extracted as the engagement arc. Finally, the CWE map is plotted by mapping a set of engagement arcs to a 2D space. To validate the proposed method, the CWE maps with/without integrating the cutter runout impact in five-axis milling of an axial compressor blisk are extracted and compared. The results reveal that the shape of CWE boundaries is changed a lot owing to the cutter runout impact. A cutting force comparison experiment has been carried out to show that the proposed method will lead to higher prediction accuracy especially in the finish milling process with low immersion angle.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021002-021002-7. doi:10.1115/1.4037230.

This paper presents a proposal about a method for analytical rolling friction coefficient determination. Basis of the proposal was an assumption: rolling friction coefficient is proportional to the semi-axes of the contact ellipses. This paper shows how to compute the semi-axes of the contact ellipses. This paper shows example results of contact loads identification using finite element method (FEM) and example of experimental results of friction torque as motion resistance of an angular bearing. Comparison of analytical and experimental determination of rolling friction coefficient was examined too.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021003-021003-19. doi:10.1115/1.4037107.

In recent years, the usage of additive manufacturing (AM) provides new capabilities for component repair, which includes low heat input, small heat-affected zone, and freeform near-net-shape fabrication. Because the geometry of each worn component is unique, the automated repair process is a challenging and important task. The focus of this paper is to investigate and develop a general best-fit and shape-adaption algorithm for automating alignment and defect reconstruction for component repair. The basic principle of using features for rigid-body best-fitting is analyzed and a multifeature-fitting method is proposed to best fit the 3D mesh model of a worn component and its nominal component. The multifeature-fitting algorithm in this paper couples the least-squares method and a density-based outlier detection method. These two methods run alternately to approach the best-fit result gradually and eliminate the disturbance caused from the defect geometry. The shape-adaption algorithm is used to do cross section comparison and defect reconstruction based on the best-fitted 3D model. A “point-line-surface” fracture surface detection method is proposed to construct fracture surface and the fracture surface boundary is dilated to trim the nominal 3D model to obtain defect geometry. Illustrative examples with typical components and different kinds of defects are used to demonstrate the flexibility and capability of using multifeature-fitting and shape-adaption algorithm developed in this paper.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021004-021004-9. doi:10.1115/1.4037236.

The conception of the comprehensive thermal error of servo axes is given. Thermal characteristics of a preloaded ball screw on a gantry milling machine is investigated, and the error and temperature data are obtained. The comprehensive thermal error is divided into two parts: thermal expansion error ((TEE) in the stroke range) and thermal drift error ((TDE) of origin). The thermal mechanism and thermal error variation of preloaded ball screw are expounded. Based on the generation, conduction, and convection theory of heat, the thermal field models of screw caused by friction of screw-nut pairs and bearing blocks are derived. The prediction for TEE is presented based on thermal fields of multiheat sources. Besides, the factors influencing TDE are analyzed, and the model of TDE is established based on the least square method. The predicted thermal field of the screw is analyzed. The simulation and experimental results indicate that high accuracy stability can be obtained using the proposed model. Moreover, high accuracy stability can still be achieved even if the moving state of servo axis changes randomly, the screw is preloaded, and the thermal deformation process is complex. Strong robustness of the model is verified.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021005-021005-9. doi:10.1115/1.4037237.

Single point incremental sheet forming (SPISF) technique is an emerging process for die less forming. It has wide applications in many industries viz. automobile and medical bone transplants. Among several key parameters, toolpath planning is one of the critical aspects of SPISF. Also, formability and geometric accuracy have been the two major limitations in SPISF. Spiral and constant incremental toolpaths and their variants have been investigated in detail by several researchers. Fractal-based toolpath planning is also an attempt to improve the process of SPISF. Formability is measured in terms of thickness distribution and maximum forming depth achieved. This paper investigates a fractal geometry-based incremental toolpath (FGBIT) strategy to form a square cup using incremental sheet forming (ISF). Fractal toolpath is a space-filling toolpath which is developed by the fractal geometry theory. A comparison-based study is conducted to observe the benefits of using FGBIT over traditional toolpaths (spiral and constant Z). Better formability, stress, and thickness distribution have been observed by adopting the proposed toolpath strategy. This toolpath strategy is new in its kind and has not been investigated in the metal forming domain. Experiments and simulations are conducted to validate the concept with reasonable accuracy.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021006-021006-14. doi:10.1115/1.4037631.

Direct digital manufacturing (DDM) is the creation of a physical part directly from a computer-aided design (CAD) model with minimal process planning and is typically applied to additive manufacturing (AM) processes to fabricate complex geometry. AM is preferred for DDM because of its minimal user input requirements; as a result, users can focus on exploiting other advantages of AM, such as the creation of intricate mechanisms that require no assembly after fabrication. Such assembly free mechanisms can be created using DDM during a single build process. In contrast, subtractive manufacturing (SM) enables the creation of higher strength parts that do not suffer from the material anisotropy inherent in AM. However, process planning for SM is more difficult than it is for AM due to geometric constraints imposed by the machining process; thus, the application of SM to the fabrication of assembly free mechanisms is challenging. This research describes a voxel-based computer-aided manufacturing (CAM) system that enables direct digital subtractive manufacturing (DDSM) of an assembly free mechanism. Process planning for SM involves voxel-by-voxel removal of material in the same way that an AM process consists of layer-by-layer addition of material. The voxelized CAM system minimizes user input by automatically generating toolpaths based on an analysis of accessible material to remove for a certain clearance in the mechanism's assembled state. The DDSM process is validated and compared to AM using case studies of the manufacture of two assembly free ball-in-socket mechanisms.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021007-021007-18. doi:10.1115/1.4038371.

A general calibration method of cutter runout and specific cutting force coefficients (SCFCs) for flat-end cutter is proposed in this paper, and a high accuracy of cutting force prediction during peripheral milling is established. In the paper, the cutter runout, the bottom-edge cutting effect, and the actual feedrate with limitation during large tool path curvature are concerned comprehensively. First, based on the trochoid motion, a tooth trajectory model is built up and an analytical instantaneous uncut chip thickness (IUCT) model is put forward for describing the cutter/workpiece engagement (CWE). Second, a noncontact identification method for cutter runout including offset and inclination is given, which constructs an objective function by using the cutting radius relative variation between adjacent teeth, and identifies through a numerical optimization method. Thirdly, with consideration of bottom-edge cutting effect, the paper details a three-step calibration procedure for SCFCs based on an enhanced thin-plate milling experiment. Finally, a series of milling tests are performed to verify the effectiveness of the proposed method. The results show that the approach is suitable for both constant and nonconstant pitch cutter, and the generalization has been proved. Moreover, the paper points out that the cutter runout has a strong spindle speed-dependent effect, the milling force in cutter axis direction exists a switch-direction phenomenon, and the actual feedrate will be limited by large tool path curvature. All of them should be considered for obtaining an accurate milling force prediction.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021008-021008-7. doi:10.1115/1.4037427.

Energy consumption of numerical control (NC) machine tools is one of the key issues in modern industrial field. This study focuses on reducing the energy consumed by a five-axis machining center by changing only the workpiece setting position. Previous studies show that the movements along each axis in five-axis machining centers depend on the workpiece setting position, regardless of whether the same operation is performed. In addition, the energy consumptions required for the movements are different along each axis. From these considerations, an optimum workpiece setting position that can minimize the energy consumed during these motions is assumed to exist. To verify this assumption, in this study, the energy consumed by the feed drive systems of an actual five-axis machining center is first measured and then estimated using the proposed model in this study. The model for estimating the energy consumption comprises the friction, motor, and amplifier losses along each axis. The total energy consumption can be estimated by adding the energy consumptions along each axis. The effect of the workpiece setting position on the energy consumption is investigated by employing the cone-frustum cutting motion with simultaneous five-axis motions. The energy consumption that depends on the workpiece setting position is first measured and then estimated. The results confirm that the proposed model can estimate the energy consumption accurately. Moreover, the energy consumption is confirmed to depend on the workpiece setting position; the minimum energy consumption is found to be 20% lower than the maximum one.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021009-021009-6. doi:10.1115/1.4038499.

A new cutting force simulator has been developed to predict cutting force in ball end milling. In this simulator, uncut chip thickness is discretely calculated based on fully voxel models representing both cutting edge and instantaneous workpiece shape. In the previous simulator, a workpiece voxel model was used to calculate uncut chip thickness under a complex change of workpiece shape. Using a workpiece voxel model, uncut chip thickness is detected by extracting the voxels removed per cutting tooth for the amount of material fed into the cutting edge. However, it is difficult to define the complicated shape of cutting edge, because the shape of cutting edge must be defined by mathematical expression. It is also difficult to model the voxels removed by the cutting edge when tool posture is nonuniformly changed. Therefore, a new method to detect uncut chip thickness is proposed, one in which both cutting edge and instantaneous workpiece shape are fully represented by a voxel model. Our new method precisely detects uncut chip thickness at minute tool rotation angles, making it possible to detect the uncut chip thickness between the complex surface shape of the workpiece and the particular shape of the cutting edge. To validate the effectiveness of our new method, experimental five-axis milling tests using ball end mill were conducted. Estimated milling forces for several tool postures were found to be in good agreement with the measured milling forces. Results from the experimental five-axis milling validate the effectiveness of our new method.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021010-021010-8. doi:10.1115/1.4037553.

In high-speed cutting processes, late replacement of defective tools may lead to machine breakdowns and badly affect the product quality, which subsequently lead to scrap parts and high process costs. Accurate tool condition detection is essential to achieve high level of competitiveness via increasing process productivity and standardizing the quality of the produced parts. Therefore, tool condition monitoring (TCM) systems have been widely emphasized as an important principle to achieve these industrial demands. Several studies for TCM were carried out to capture tool failure using complex conventional and artificial intelligence (AI) techniques. However, these studies suffer from the absence of standardization and generalization. Hence, this paper presents a robust and reliable processing technique for the cutting process signals to extract generalized features in time and frequency domains. The proposed technique masks the effects of the cutting conditions on the extracted features and accentuates the tool condition effect. Characterization and statistical analysis of the processed features were performed to examine their sensitivity to the tool condition. The results revealed the processing technique capability to separate the features extracted from the spindle motor current signals into two mutually exclusive clusters according to their tool condition. The statistical analysis results were employed to optimize the tool condition detection approach using linear discrimination analysis (LDA) model. The results indicate the capability of the processing technique to minimize the system learning effort and to detect tool wear above the threshold level with accuracy above 90%.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021011-021011-8. doi:10.1115/1.4037598.

The prediction of the grinding process result, such as the workpiece surface quality or the state of the edge zone depending on the used grinding wheel is still a great challenge for today's manufacturers and users of grinding tools. This is mainly caused by an inadequate predictability of force and temperature affecting the process. The force and the temperature strongly depend on the topography of the grinding wheel, which comes into contact with the workpiece during the grinding process. The topography of a grinding wheel mainly depends on the structure of the grinding wheel, which is determined by the recipe-dependent volumetric composition of the tool. So, the structure of a grinding tool determines its application behavior strongly. As result, the knowledge-based prediction of the grinding wheel topography and its influence on the machining behavior will only be possible if the recipe-dependent grinding wheel structure is known. This paper presents an innovative approach for modeling the grinding wheel structure and the resultant grinding wheel topography. The overall objective of the underlying research work was to create a mathematical-generic grinding tool model in which the spatial arrangement of the components, grains, bond, and pores, is simulated in a realistic manner starting from the recipe-dependent volumetric composition of a grinding wheel. This model enables the user to determine the resulting grinding wheel structure and the grinding wheel topography of vitrified and synthetic resin-bonded cubic boron nitride (CBN) grinding wheels depending on their specification and thus to predict their application behavior. The originality of the present research results is a generic approach for the modeling of grinding tools, which takes into account the entire grinding wheel structure to build up the topography. Therefore, original mathematical methods are used. The components of grinding wheels are analyzed, and distribution functions of the component's positions in the tools are determined. Thus, the statistical character of the grinding wheel structure is taken into account in the developed model. In future, the presented model opens new perspectives in order to optimize and to increase the productivity of grinding processes.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021012-021012-11. doi:10.1115/1.4037242.

A wear characterization study was performed to determine the useful lifetime of polycrystalline cubic boron nitride (PCBN) tooling for the friction stir welding (FSW) of stainless steel samples in support of a nuclear repair welding research and development program. In situ and ex situ laser profilometry were utilized as primary methods of monitoring tool geometry degradation, and volumetric defects were detected through both nondestructive and destructive techniques, as repeated welds of a standard sample configuration were produced. These combined methods of characterization allowed for the successful correlation of defect formation with tool condition. Additionally, the spectral content of weld forces was examined to search for indications of evolving material flow conditions, caused by significant tool wear, that would result in the formation of defects; this analysis established the basis for a system that would automatically detect these conditions. To demonstrate this type of system, an artificial neural network was trained and evaluated, and a 95.2% classification rate of defined defect states in validation was achieved. This performance constituted a successful demonstration of in-process monitoring of tool wear and weld quality in FSW of a high melting temperature, high hardness material, with implications for remote monitoring capabilities in the specific application of nuclear repair welding.

Commentary by Dr. Valentin Fuster
J. Manuf. Sci. Eng. 2017;140(2):021013-021013-7. doi:10.1115/1.4037601.

The objectives of this work are to demonstrate the use of multiscale curvature tensor analysis for characterizing surfaces of stainless steel created by micro-electrical discharge machining (μEDM), and to study the strengths of the correlations between discharge energies and resulting surface curvatures (i.e., principal, Gaussian, or mean curvatures) and how they change with scale. Surfaces were created by μEDM techniques using energies from 18 nJ to 16,500 nJ and measured by confocal microscope. The curvature tensor T is calculated using three proximate unit vectors normal to the surface. The multiscale effect is achieved by changing the size of the sampling interval for the estimation of the normals. Normals are estimated from regular meshes by applying a covariance matrix method. Strong correlations (R2 > 0.9) are observed between calculated principal maximal and minimal as well as mean and Gaussian curvatures and discharge energies. This method allows detailed analysis of the nature of surface topographies and suggests that different formation processes governed the creation of surfaces created by higher energies.

Commentary by Dr. Valentin Fuster

Technical Brief

J. Manuf. Sci. Eng. 2017;140(2):024501-024501-6. doi:10.1115/1.4038370.

The simulation and experimental methods are used to determine the parameters of a tailored tempering process for a lab-scale B-pillar that is made from CSC-15B22 high-strength steel. The finite element software, DEFORM-3D, is used to simulate the tailored tempering process. A segmented hot stamping tool is developed for testing. Results demonstrate that the cooling and heating systems are successful. On the cooled side of the tooling, the cooling rate for the sheet is more than 30 °C/s. The material structure of the sheets is entirely a martensite structure, which results in an ultra-high strength material. The average hardness is measured as HV423, which translates to a tensile strength of 1350 MPa. On the heated side of the tooling, the cooling rate for the sheet is less than the critical cooling rate, the microstructure of the material is ferrite and pearlite, and the average hardness is measured at HV205, which translates to a tensile strength of approximately 660 MPa. The study demonstrates that a tailored tempering process allows production using integrated tooling and produces sheets that have different mechanical properties.

Commentary by Dr. Valentin Fuster

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