This paper presents a novel application of intensity-based volume registration to manufacturing using voxel-based computer-aided manufacturing (CAM) models. The introduced techniques are presented in the context of machining irregularly shaped materials by integrating volumetric imaging feedback to computer numerical control (CNC) machine tools. This requires a comparison and alignment to be performed in the software to geometrically “fit” the source design model inside a rendered starting material. The requirements differ from many typical registration applications in that the workpiece will necessarily be larger (i.e., greater in volume) than the desired final computer-aided design (CAD) file. Therefore, models need to be aligned for toolpath generation to workpiece counterparts that have been either volumetrically offset or contain additional material/volume. Intensity-based registrations are unique in that they consider only the voxel values over the entire volume. Although advancements in medical imaging have produced efficient, robust voxel registration algorithms, these techniques have not yet been applied to manufacturing. This research introduces the use of maximization of mutual information (MMI) for voxel-based CAM to drive an alignment registration for systems integrating imaging technology. A simple but novel method, which the authors have named minimization of distance variance (MDV), is also introduced. This minimizes the variance between voxel intensities to demonstrate the design of a similarity metric for a simple case in machining rough castings.

Metals such as Cu, Al, Ni, Ta, and stainless steels, despite their softness and ductility, are considered difficult to machine. This is due to large cutting forces and corresponding formation of a very thick chip during cutting, and hence, these metals are referred to as “gummy.” Their poor machinability of these materials arises because of an unsteady and highly redundant mode of plastic deformation referred to as sinuous flow. The prevailing plastic deformation mode during machining can be overcome by the application of certain coatings and chemical media on the undeformed free surface of the workpiece ahead of the cutting process. Using in situ imaging and concurrent force measurements, we present two different mechanochemical routes through which these media can improve machinability. The first route, which requires chemicals that adhere to the metal surface, such as glues and inks, improves cutting by inducing a change in the local plastic deformation mode—from sinuous flow to one characterized by periodic fracture or segmented flow. The second route, which requires chemicals that can react with the workpiece to form a low-friction layer, changes the sinuous flow mode to a smooth, laminar one. Both routes decrease cutting forces by more than 50% with order of magnitude improvement in surface texture as characterized by measured roughness and defect density. The results suggest a broad range of opportunities for improving the performance of machining processes for many difficult-to-cut gummy metals.

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

The paper presents a simulation of the Airbus A350-900 wing-to-fuselage assembly process. The latter is a complex multistage process where the compliant parts are being joined by riveting. The current research analyzes the quality of the temporary fastener arrangement. The fastener arrangement is being checked to ensure that the residual gap between joined parts is small, and the fastener loads closing the gap are calculated. The deviations of the part shape from nominal are modeled via initial gaps. A cloud of initial gaps is generated based on the statistical analysis of the available measurements assuming the stochastic nature of local gap roughness. Through the reduction of the corresponding contact problem to a quadratic programming (QP) problem and the use of efficient QP algorithms together with the task-level parallelism, the mass contact problem solving on refined grids is accomplished.

In this work, a mechano-chemical surface modification to improve cutting tool performance is proposed. We applied this surface modification via shot peening the rake faces of high-speed steel tools with a blend of Al 2 O 3 and Cu 2 S particles that serve as a plastic deformation medium and a chemical precursor, respectively. Orthogonal cutting experiments under base oil lubrication demonstrated that the proposed treatment results in a reduction of cutting and thrust forces, as well as in a reduction of built-up edge formation. These effects are explained by favorable changes in the lubricity and roughness of the rake face, and they suggest that this method has the potential to increase cutting tool life, lower energy consumption, and improve the dimensional accuracy and surface quality of a machined workpiece.

Laser powder bed fusion (LPBF) has the ability to produce three-dimensional lightweight metal parts with complex shapes. Extensive investigations have been conducted to tackle build accuracy problems caused by shape complexity. For metal parts with stringent requirements, surface roughness, laser beam positioning error, and part location effects can all affect the shape accuracy of LPBF built products. This study develops a data-driven predictive approach as a promising solution for geometric accuracy improvement in LPBF processes. To address the shape complexity issue, a prescriptive modeling approach is adopted to minimize geometrical deviations of built products through compensating computer aided design models, as opposed to changing process parameters. It allows us to predict and control a wide range of shapes starting from a limited set of measurements on basic benchmark geometries. An error decomposition and compensation scheme is developed to decouple the influence from different error components and to reduce the shape deviations caused by part geometrical deviation, laser beam positioning error, and other location effects simultaneously via an integrated modeling and compensation framework. Experimentation and data collection are conducted to investigate error sources and to validate the developed modeling and accuracy control methods.

Grain depth-of-cut, which is the predominant factor determining the surface morphology, grinding force, and subsurface damage, has a significant impact on the surface quality of the finished part made of hard and brittle materials. When the existing analytical models are used to predict the gain depth-of-cut in ultra-precision grinding process of silicon wafer, the results obtained become unreasonable due to an extremely shallow grain depth-of-cut, which is inconsistent with the theory of the contact mechanics. In this study, an improved model for analyzing the grain depth-of-cut in ultra-fine rotational grinding is proposed, in which the minimum grain depth-of-cut for chip formation, the equivalent grain cutting tip radius, elastic recovery deformation in cutting process, and the actual number of effective grains are considered in the prediction of the ultrafine rotational grinding of brittle materials. The improved model is validated experimentally and shows higher accuracy than the existing model. Furthermore, the sensitivity of the grain depth-of-cut to three introduced factors is analyzed, presenting the necessity of the consideration of these factors during the prediction of grain depth-of-cut in ultrafine grinding.

Due to its high versatility and scalability, manual grinding is an important and widely used technology in production for rework, repair, deburring, and finishing of large or unique parts. To make the process more interactive and reliable, manual grinding needs to incorporate “skill-based design,” which models a person-based system and can go significantly beyond the considerations of traditional human factors and ergonomics to encompass both processing parameters (e.g., feed rate, tool path, applied forces, material removal rate (MRR)), and machined surface quality (e.g., surface roughness). This study quantitatively analyzes the characteristics of complex techniques involved in manual operations. A series of experiments have been conducted using subjects of different levels of skill, while analyzing their visual gaze, cutting force, tool path, and workpiece quality. Analysis of variance (ANOVA) and multivariate regression analysis were performed and showed that the unique behavior of the operator affects the process performance measures of specific energy consumption and MRR. In the future, these findings can be used to predict product quality and instruct new practitioners.

Recent advances in fused filament fabrication (FFF), such as five-axis printing, patching existing parts, and certain hybrid manufacturing processes, involve printing atop a previously manufactured polymer substrate. The success of these technologies depends upon the bond strength between the substrate and the newly added geometry. ANOVA and response surface methods were used to determine the effect of three process parameters on bond tensile strength: surface roughness, layer thickness, and raster angle. Experimental results indicate that the process–property relationships are not identical to those found in single, continuous FFF operations, and that the physical bonding mechanisms may also be different. Bond strength was found to be highly sensitive to surface roughness and layer thickness, and distinct optimal parameter settings exist. These results represent a first step toward understanding bond strength in such circumstances, allowing manufacturers to intelligently select process parameters for the production of both the substrate and the secondary geometry.

Ultrasonic-assisted machining, which is the application of ultrasonic vibrations to standard or “conventional” machine tools for processes such as drilling, milling, and turning, is a rapidly developing technology aimed at increasing the productivity of machining processes. While a solid foundation is being established through laboratory-based research studies, typically these processes have not yet progressed to fulfill the demanding requirements of the factory floor. The objective of the current work is to transition the ultrasonic-assisted drilling (UAD) process from the laboratory to a production system compatible with automated machining systems. This work details the design and development of an ultrasonic drilling module that has sufficient strength, stiffness, and accuracy for production demands, while maintaining powerful levels of ultrasonic vibrations that result in lowered drilling forces and faster feed rates. In addition, this work will review prior work in UAD, including the development of a module based on a vibration-isolating case using a standard tool holder. Performance of the system is shown to provide thrust force reductions, while maintaining or improving surface finish and drilling accuracy. The results from drilling several materials are presented.

In order to further improve the processing performance of rotary ultrasonic machining (RUM), a novel longitudinal–torsional-coupled (LTC) vibration was applied to the RUM. An experimental study on quartz glass was performed to access the feasibility of the LTC-RUM of a brittle material. The LTC-RUM was executed through the addition of helical flutes on the tool of conventional longitudinal RUM (Con-RUM). The experimental results demonstrated that the LTC-RUM could reduce the cutting force by 55% and the edge chipping size at the hole exit by 45% on an average, compared to the Con-RUM. Moreover, the LTC-RUM could also improve the quality of the hole wall through the reduction of surface roughness, in particular, when the spindle speed was relatively low. The mechanism of superior processing performance of LTC-RUM involved the corresponding specific moving trajectory of diamond abrasives, along with higher lengths of lateral cracks produced during the abrasives indentation on the workpiece material. The higher edge chipping size at the hole entrance of LTC-RUM indicated a higher length of lateral cracks in LTC-RUM, due to the increase in the maximum cutting speed. Furthermore, the effect of spindle speed on the cutting force and surface roughness variations verified the important role of the moving trajectory of the diamond abrasive in the superior processing performance mechanism of LTC-RUM.

Ball burnishing is a process used to smooth rough surfaces. For not rotational symmetric parts, the process is typically conducted on milling machines. Since it is an incremental process, it is relatively time consuming. Therefore, a rolling tool is developed, which superposes the rotation of the milling spindle with the feed of the machine to increase the rolling velocity. In order to achieve constant rolling forces, hydrostatic ball-burnishing tools are used. Within this work, the influence of this tool concept on the processing time as well as on the leveling of surface irregularities is investigated. This is achieved by a comparison with a conventional ball-burnishing process. Finally, the rotating tool is used to investigate the influence of high rolling speeds on the leveling of the surface. All experiments were carried out with thermally coated specimens. A model for calculating the strain rates at the roughness peaks during ball burnishing is derived. For the experiments carried out with the rotating rolling tool, rolling velocities of 50,000 mm/min were realized. Calculations with the developed model showed that this results in local strain rates at the roughness peaks of up to 1384 s −1 . In addition, the flow stresses at the roughness peaks were calculated. Compared with quasi-static experiments, the flow stress drops to less than the half under high velocities. This results in a better leveling of the surface for rolling velocities between 10,000 mm/min and 25,000 mm/min. A further rise of the rolling speed increases the flow stress again and thereby reduces the possible leveling.

This paper deals with the identification of an empirical equation for predicting free surface roughness evolution. The equation has been proposed elsewhere, and, in contrast to widely used equations, assumes that the evolution of free surface roughness is controlled by two kinematic variables, the equivalent strain, and the logarithmic strain normal to the free surface. Therefore, an experimental program is designed to account for the effect of the mode of deformation on free surface roughness evolution. Thin sheets of aluminum alloy A5052-O and pure copper C1220P-O alloys are used to conduct the experimental program. In addition, numerical simulation is performed to calculate the evolution of free surface roughness under the same conditions. Comparison of experimental and numerical results shows that the accuracy of the numerical results is good enough. Then, numerical simulation is extended to the domain in which no experimental results are available. Discrete functions so found are fitted to polynomials. As a result, continuous functions that represent the empirical equation for predicting free surface roughness evolution for A5052-O and C1220P-O alloys are determined. These equations can be used in conjunction with solutions to boundary value problems in plasticity for predicting the evolution of free surface roughness in metal forming processes.

Carbon fiber-reinforced plastics (CFRPs) are sustainable materials compared to others due to their distinctive properties and light weight. On the other hand, producing CFRP products with minimum manufacturing costs and high quality can be quite challenging. This research aims to formulate a mathematical model that determines the optimum manufacturing process/processing parameters and takes into consideration the effect of the selected processes on the quality of panels and the environmental impact surface roughness and percentage of voids are used as metrics to assess the desired quality level of the finished product. Energy consumption is used to quantify the environmental cost. Design of experiment (DOE) was performed to study the effect of varying the process parameters, namely application method, pressure, and temperature on the response variables. Regression models were used to model the response variables. A generalized model was developed and validated both numerically and experimentally. Results signify the need for a systematic approach to determine optimum manufacturing processes without resorting to trial and error.

The application of cutting fluid in grinding operations is crucial to control temperature levels and prevent thermal damage to the workpiece. Water-based (emulsions and solutions) coolants are used in grinding operations owing to their excellent cooling capability and relatively lower cost compared to neat oils. However, the cutting fluid efficiency is not only dependent on its type, but also on other parameters including its concentration and flow rate. In this context, this work aims to analyze the influence of the coolant concentration and flow rate on the grinding process. Two different workpiece materials for the production of plastic injection moulds were machined: VP80 and VPATLAS steel grades. Six grinding conditions (combinations of depth of cut values of 5, 15, and 25 μ m with coolant concentration of 3% and 8%, respectively) were employed in the former, while two grinding conditions were used for the latter. The output parameter used to assess the influence of coolant concentration and flow rate on the grinding operation focused on the integrity of the workpiece materials (surface roughness and microhardness below the ground surface). The results showed that the surface integrity of VP80 after grinding was more sensitive to depth of cut than to cutting fluid concentration. Furthermore, the highest coolant concentration outperformed the lowest one when grinding under more severe conditions. With regard VPATLAS steel, no influence of the coolant flow rate on surface roughness was observed.

This paper reports an experimental study on grinding of chromium carbide coatings using electroplated diamond wheels. The work was motivated by machining carbide coatings in gas turbine engine applications. The objective is to explore the process conditions and parameters satisfying the ground surface quality requirements. Surface grinding experiments were conducted with water-based grinding fluid on chromium carbide coated on flat surfaces of aluminum blocks for rough grinding at a fixed wheel speed v s = 30 m/s, and finish grinding at v s = 30, 60 m/s. The effects of depth of cut and workspeed on grinding power, forces, and surface roughness were investigated for each of the wheel speeds. Material removal rate Q = 20 mm 3 /s for rough grinding at a grinding width b = 101.6 mm was achieved. It was found that the maximum material removal rate achievable in rough grinding was restricted by chatters, which was mainly due to the large grinding width. The specific energy ranged from 27 to 59 J/mm 3 under the tested conditions. Surface roughness R a = 3.5–3.8 μ m were obtained for rough grinding, while R a = 0.6–1.5 μ m were achieved for finish grinding. Surface roughness was not sensitive to grinding parameters under the tested conditions, but was strongly dependent on the diamond grain sizes. Imposing axial wheel oscillations to the grinding motions reduced surface roughness by about 60% under the tested condition. It was proved that it is feasible to grind the chromium carbide coating with electroplated diamond wheels.

Grinding is an abrasive process mostly used in finishing operations to provide low roughness and narrow limits of form and dimensioning to the workpiece. Due to the large amount of heat generated by friction between the abrasive and the workpiece in this process, the use of large volumes of coolant is encouraged to avoid thermal damage, such as burning and hardness variation caused by subsurface damage. On the other hand, environmental impacts and human health problems caused by coolants have been a key issue toward sustainable manufacturing, mainly because of the chemistry behind them. Thus, is important to seek for strategies to reduce the volume of fluids and their risks as well as guarantee grinding efficiency. One machining strategy is the minimum quantity of lubricant (MQL) technique, which is well consolidated over the past 25 years and one that uses low volumes of fluid mixed with compressed air flow, as well as provides less waste. However, it has generally been reported that sludge formed during grinding is forced into the wheel pores, consequently clogging its pores, thereby reducing the wheel cutting potential and its performance. A possible solution for this problem is to use an auxiliary compressed air system to clean the grinding wheel surface during machining, since the MQL conventional system is not able to clean it. In this context, this work evaluated the performance of the MQL technique with an auxiliary cleaning of the grinding wheel cutting surface in relation to the conventional cooling techniques (flood cooling) during a cylindrical plunge grinding of N2711 steel. N2711 steel is widely employed in manufacturing of molds for plastic injection processes and is one of steels more susceptible to grinding burn. The following output parameters were used to assess the performance: surface roughness, roundness, microhardness, grinding power, and grinding wheel wear. The results showed that the MQL technique, in addition to the environmental and economic advantages achieved, provided superior workpiece quality, and lower power consumed compared to the flood technique. The MQL technique proved to be an alternative method compared to the conventional technique under the conditions investigated. Also, the Malkin’s model was used to predict the grinding ratio (G-ratio) based on the experimental data obtained in this work. After regression analysis, the model predicted the G-ratio from the specific material removal rate and the cutting speed with a satisfactory accuracy of approximately 92%.

With the rising trend of miniaturization in modern industries, micro manufacturing processes have made a significant position in the manufacturing domain. Demands of high precision along with super finish of the final machined product have started rising. Grinding, being largely considered as a finishing operation, has large potential to cater to such requirements of micro manufacturing. However, stochastic nature of the grinding wheel topography results in a high degree of variation in the output responses especially in the case of microgrinding. With an aim to obtain a good and predictable surface finish in brittle materials, the current study aims at developing a surface generation model for wall grinding of hard and brittle materials using a microgrinding tool. Tool topographical features such as grit protrusion height, intergrit spacing, and grit distribution on the tool tip of a microgrinding pin have been calculated from the known mesh size of the grits used during tool manufacturing. Kinematic analysis of surface grinding has been extended to the case of wall grinding and each grit trajectory has been predicted. The kinematic analysis has been done by taking into consideration the effect of tool topographical features and the process parameters on the ground surface topography. Detailed analysis of the interaction of the grit trajectories is done to predict the final surface profile. The predicted surface roughness has been validated with the experimental results to provide an insight to the surface quality that can be produced for a given tool topography.

Textured functional surfaces are finding applications in the fields of bioengineering, surface energy, hydrodynamics, lubrication, and optics. Electrical discharge machining (EDM), which is normally used to generate smoother surface finish on various automotive components and toolings, can also generate surfaces of rough finish, a desirable characteristic for texturing purposes. There is a lack of modeling efforts to predict the surface textures obtained under various EDM operating conditions. The aim of the current work is to capture the physics of the electrical discharge texturing (EDT) on a surface assuming random generation of multiple sparks with respect to (i) space, (ii) time, and (iii) energy. A uniform heat disk assumption is taken for each individual spark. The three-dimensional (3D) texture generated is utilized to evaluate a 3D roughness parameter namely arithmetic mean height, S a . Surface textures obtained from the model are validated against experimentally obtained ones by comparison of distribution of R a values taken along parallel sections along the surface. It was found that the distribution of simulated R a values agrees with that of experimental R a values.

This paper proposes an integrated approach to determine optimal build orientation for powder bed fusion by laser (PBF-L), by simultaneously optimizing mechanical properties, surface roughness, the amount of support structure (SUPP), and build time and cost. Experimental data analysis has been used to establish the objective functions for different mechanical properties and surface roughness. Geometry analysis of the part has been used to estimate the needed SUPP and thus evaluate the build time and cost. Normalized weights are assigned to different objectives depending on their relative importance allowing solving the multi-objective optimization problem using a genetic optimization algorithm. A study case is presented to demonstrate the capabilities of the developed system. The major achievements of this work are the consideration of multiple objectives and the establishment of objective function considering different load direction and heat treatments. A user-friendly graphical user interface was developed allowing to control different optimization process factors and providing different visualization and evaluation tools.