Hybrid Additive-subtractive Manufacturing Research Articles

Hybrid additive-subtractive manufacturing of high-density copper-based flexible transparent circuits based on side-etch process

High-density flexible transparent circuits (FTCs) are widely used in 5G/6G flexible transparent antennas, wearable devices, flexible transparent electronics and other fields. However, the rapid iteration and upgrading of electronic circuits present significant challenges to the manufacturing of both high-density and high-precision circuits (especially copper-based circuits) at room temperature, in an efficient and flexible manner. Here, we employ the side-etching phenomenon, which is typically avoided, to propose a novel method for hybrid additive-subtractive fabricating high-density copper-based FTCs that combines electric field-driven (EFD) microjet printing and wet etching technology. Firstly, the customized photoresist mask was flexibly printed on the copper-clad flexible substrate by EFD microjet printing, and then the copper circuit with less than the mask resolution was obtained by the side etching process of the wet etching process. By optimizing process parameters and precisely controlling the speed of the side etching stage during the etching process, the manufacturing of high-precision copper-based FTCs with a minimum line width of 2.4 μm and a minimum pitch of 4 μm was achieved. The typical sample is manufactured with a resistivity of 4 × 10−6 Ω·cm, a sheet resistance of 3.58 Ω/sq at a transmittance of up to 87.65 % (including the substrate), and it exhibits excellent mechanical stability. The prepared high-density flexible transparent interdigital electrode has excellent sensitivity, and can detect the concentration change of dilute H2SO4 solution at a minimum of 1 nmol/L at a frequency of 100–10,000 Hz. This method provides a new solution for the fabrication of copper-based FTCs at room temperature with high efficiency and low cost, and shows a good prospect for industrial application.

Enhancing surface quality and tool life in SLM-machined components with Dual-MQL approach

Selective laser melting (SLM) can produce complex metal components with high densities, thereby surpassing the limitations of traditional machining methods. However, achieving accurate dimensions, geometries, and acceptable surface states in parts fabricated through SLM remains a concern as they often fall short compared to traditionally machined components. As a solution, a hybrid additive-subtractive manufacturing (HASM) method was developed to effectively utilize the advantages of both techniques. In this study, SLM-made 316 L stainless steel was machined under distinct cooling conditions to investigate the effects of roughness and tool wear. After a thorough investigation, the dual-MQL strategy was evaluated and compared with dry and MQL cutting strategies. The findings showed that the dual-MQL condition led to a significant reduction in flank wear by 54–56% and 29–34%, respectively, associated with dry and MQL cutting techniques, making it a highly promising key for machining SLM-made steel components. Machine learning techniques are potential tools for prediction and classification capabilities in machining processes. For milling SLM-made 316 L SS, multilayer perceptron (MLP) proved to be the most effective prediction model and for classification MLP and Random forest performed better.

The influence of deformation affected region on microstructure and mechanical property of 316L fabricated by hybrid additive-subtractive manufacturing

The hybrid of additive manufacturing and subtractive manufacturing is promising in producing high-quality and high-accuracy parts made of hard-to-machine metallic materials with complex geometries. However, few studies have been conducted to analyze the influence of responses from subtractive manufacturing, especially the plastic deformation region induced by mechanical cutting, on the following additive manufacturing processes. This paper comprehensively investigates the impact of finishing milling on the mechanical properties and quality of 316L fabricated by hybrid additive-subtractive manufacturing. The whole manufacturing process consisted of a two-stage micro selective laser melting μSLM process with three scanning speeds and one finishing milling process. Typical machining responses including phase, cutting force, surface roughness at different manufacturing stages were analyzed; the mechanisms of how the deformation-affected region induced in subtractive manufacturing process affects the microstructure, hardness, and mechanical properties after the second-stage additive manufacturing were explored. Fine grains were formed after the second-stage μSLM in the connected region, because of the lower G/R ratio and the higher G × R value, whereas the hardness in this region was lower than the bulk material consisting of coarse grains, caused by the thermal softening effect induced in mechanical cutting. The elongation rate was increased due to the existence of the grain-boundary-rich connected region.

Optimal process planning for hybrid additive–subtractive manufacturing using recursive volume decomposition with decision criteria

This paper explores the concept of hybrid manufacturing (HM), which combines two or more manufacturing processes to improve efficiency and productivity. HM can be categorized based on the combination of additive, subtractive, transformative, and assistive processes, and this study specifically focuses on widely-adopted hybrid additive–subtractive manufacturing. The potential of HM to improve productivity and manufacturability is investigated from a process planning perspective. To enable fully automated and optimized process planning, a new set of decision criteria for handling a newly devised recursive volume decomposition of 3D CAD models is introduced along with a cost and time model for optimization. An optimization scheme is developed based on these requirements, and an efficient optimization algorithm using a genetic algorithm is proposed. The experimental results demonstrate that the integration of additive and subtractive processes in HM can overcome the limitations of conventional manufacturing. The optimal solutions reduce 69% and 63% of manufacturing cost and time on average for four test cases, and statistical significance was observed for the decision criteria most of the time.

Multi-indicator evaluation and material selection of hybrid additive-subtractive manufacturing to repair automobile panel dies and molds

Multi-indicator evaluation and material selection of hybrid additive-subtractive manufacturing to repair automobile panel dies and molds

Challenges in topology optimization for hybrid additive–subtractive manufacturing: A review

Hybrid additive–subtractive manufacturing (HASM) is a revolutionary technique that fabricates complex-shaped parts in high precision. One setup to finish complicated manufacturing operations ensures high efficiency, and the interlacement of additive–subtractive operations fabricates conventionally difficult-to-process complex geometries. On the other hand, the expensive hybrid manufacturing equipment, the tedious preprocessing and extended processing time, the costly raw materials all make the utilization of HASM to process simply-designed mechanical components uneconomical. Hence, this paper is focused on design for HASM, to create the suitable mechanical structures for HASM endowed of superior functionality and light-weight features over the traditional counterpart. The performance enhancement is in general realized by expanding the geometric complexity to the level that is difficult-to-process or even unmanufacturable by traditional manufacturing techniques. HASM-oriented topology optimization is specifically focused and the state-of-the-art is reviewed and analyzed in this comprehensive paper. Starting from topology optimization for additive/subtractive manufacturing, the existing methods are thoroughly reviewed and their potentials to address design for HASM issues are carefully analyzed. Then, two critical problems: (i) topology optimization for HASM addressing residual stress/distortion constraints and (ii) process planning-assisted topology optimization for HASM addressing tool accessibility constraints, are illustrated and discussed on related technical challenges and potential solutions. At the end, the unaddressed technical issues on topology optimization for HASM are summarized to provide guidance for future research.

Friction property and milling machinability of Ni60 cladding layer in hybrid additive-subtractive manufacturing

Hybrid additive-subtractive manufacturing (HASM) is an advanced technology for parts repairing. However, the complex process and difficult to machine characteristics of cladding formed materials limit its applications. The microstructure, friction property, and milling machinability of the single-pass laser cladding layer (LCL) are investigated using laser cladding and milling experiments. The results show that Ni60-based LCL has a good forming quality on the Cr12MoV die steel. The average micro-hardness of LCL is 1.38 times that of substrate and the wear mechanism is mainly the mixture of oxidation wear and abrasive wear. Furthermore, the results of multi-zone milling experiment show that the saw-tooth chips have been appeared at the milling speed of 75.4 m/min. On the other hand, the results of single-zone milling experiment show that the middle zone has the lowest average value of and fluctuate of milling force, and has the best machined surface quality. Moreover, the micro-hardness after milling in the middle zone can reach to 57 HRC, and its wear resistance is 20.93 % better than that of substrate. Therefore, the middle zone of LCL has the best machinability, and the subsequent processing is eager to be carried out in this zone. A guiding concept of cladding parameters selection is proposed based on the machinability and machining position. It is of great significant to improve the machining efficiency and machining quality of HASM process.

A framework for hybrid manufacturing cost minimization and preform design

This paper describes preform design optimization in hybrid additive-subtractive manufacturing. In hybrid manufacturing, the question of what form and what geometry the additive preform should take has largely been a matter of intuition and experience, or trial and error. The choice of a more optimal preform depends on the target parameters, such as stiffness, cost, or lead time. We demonstrate a framework for preform optimization using static stiffness, and then the combined cost of additive and subtractive manufacturing, while respecting stable cutting conditions for the tool-part combination. The procedure is illustrated by comparing three preform geometries for a thin wall.

Effects of Different Process Strategies on Surface Quality and Mechanical Properties of 316L Stainless Steel Fabricated via Hybrid Additive-Subtractive Manufacturing

Effects of Different Process Strategies on Surface Quality and Mechanical Properties of 316L Stainless Steel Fabricated via Hybrid Additive-Subtractive Manufacturing

Effect of Porosity on Tool Wear During Micromilling of Additively Manufactured Titanium Alloy

Abstract Porosity is a major quality issue in additively manufactured (AM) materials due to improper selection of raw material or process parameters. While porosity is kept to a minimum for structural applications, parts with intentional (engineered) porosity find applications in prosthetics, sound dampeners, mufflers, catalytic converters, electrodes, heat exchangers, filters, etc. During postprocessing of additive manufactured components using secondary machining to obtain required dimensional tolerance and/or surface quality, part porosity could lead to fluctuating cutting forces and reduced tool life. The machinability of the porous AM material is poor compared to the homogenous wrought material due to the intermittent cutting and anisotropy of AM materials. This paper investigates the tool wear progression and underlying mechanisms in relation to the porosity of AM material during their machining. Micromilling experiments are carried out on AM Ti6Al4V alloy with different porosity levels. Insights into tool-workpiece interaction during micromachining are obtained in cases where pore sizes could be comparable to the cutting tool diameter. Findings of this research could be helpful in developing efficient hybrid additive-subtractive manufacturing technologies with improved tool life and reduced costs.

Densification, mechanical behaviors, and machining characteristics of 316L stainless steel in hybrid additive/subtractive manufacturing

Directed energy deposition (DED) is capable of manufacturing high-density and complex metal components, whereas traditional machining methods are limited in these regards. Nevertheless, the fabrication of parts with DED that have accurate dimensions and geometries as well as acceptable surface states is a concern, as these factors are inferior to those of traditionally machined components. Therefore, the application of parts fabricated with DED is restricted. Thus, the hybrid additive/subtractive manufacturing (HASM) method has been exploited to comprehensively utilize the advantages of both. In this paper, the HASM method was used to fabricate bulk parts with four different scanning strategies (alternating the orientation of subsequent layers by 0°, 45°, and 90° and island scanning are referred to as an X-scan, a Rot-scan, an XY-scan, and an Island-scan, respectively) followed by subtractive milling to gain a smooth surface with a determined thickness for the next scanning and deposition period until the parts were completely finished. The influence of the scanning strategy on the densification level and mechanical behavior of the specimens fabricated with HASM was studied. The results show that the specimens fabricated with the 7 × 7 mm2 island scan with short scan vector lengths showed a higher densification than the specimens fabricated using long scan vector lengths (the three methods mentioned above). Finally, to obtain a fine surface finish, the influence of the feed per tooth (fz) on the surface quality of a 316L stainless steel during the milling process that occurs during the HASM process was also investigated. The result shows a fz of 0.25 mm yielding the minimum surface roughness value among the samples observed herein, which implies that the surface quality was better than that of the other studied conditions.

Feature extraction and process planning of integrated hybrid additive-subtractive system for remanufacturing.

Discussion regarding hybrid manufacturing has dominated research in recent years. By synergistically integrating additive and subtractive manufacturing within a single workstation, the relative benefits of each manufacturing strategy are leveraged. The ability to add, remove feature flexibly enables remanufacturing end-of-life components into a "new" part with new features and functionalities. However, in the remanufacturing context, the process planning for hybrid additive-subtractive manufacturing is still an unsolved research topic. In general, a hybrid remanufacturing process is signified by an alternating sequence of additive and subtractive operations that alternatively add and remove materials on a used part, which results in a non-unique process planning. For determining an optimal sequence for hybrid remanufacturing, a quantitative evolution mechanism is demanded. Moreover, the constraints in process planning are required to be considered. For example, the collision avoidance between the workpiece and the material-dispensing nozzle is one of the most critical limitations that affect the alternating sequence. To fill the gap, automated feature extraction and cost-driven process planning method for hybrid remanufacturing are proposed in this paper. The feature extraction, developed under the level set framework, can extract optimal and collision-free additive-subtractive features. Then, the hybrid process planning task is formulated into an integer programming model with cost estimations. A case study is conducted, and the results confirm the correctness and effectiveness of the proposed method.

Towards rapid, in situ characterization for materials-on-demand manufacturing

Recent hybrid additive-subtractive manufacturing platforms can usher a materials-on-demand manufacturing paradigm where the materials, along with geometry and surface morphology, are designed to meet the functionality. While in situ measurement systems have advanced to monitor geometric and morphological variations, microstructure and phase characterization methods remain slow, impeding this vision. Towards addressing this issue, we present an approach to characterize the material concurrently during fabrication by associating in situ sensor measurements with the microstructures. Analysis of sensor data from machining of 316L steel suggests that the microstructural variations under different process parameters can be predicted in real time with 93% accuracy.

Topology optimization of continuum structures under hybrid additive-subtractive manufacturing constraints

Additive manufacturing (AM) makes it possible to fabricate complicated parts that are otherwise difficult to manufacture by subtractive machining. However, such parts often require temporary support material to prevent the component from collapsing or warping during fabrication. The support material results in increased material consumption, manufacturing time, and clean-up costs. The surface precision and dimensional accuracy of the workpieces from AM are far from the engineering requirement due to layer upon layer manufacturing. Subtractive machining (SM), by contrast, can fabricate parts to satisfy the requirements of surface precision and dimensional accuracy. Nevertheless, the components need to be relatively uncomplicated for subtractive manufacturing. Thus, hybrid additive-subtractive manufacturing (HASM) is gaining increasing attention in order to take advantages of both processes. There is little research on the topological design methodology for this hybrid manufacturing technology. To address this issue, a method based on geometry approach for topology optimization of continuum structure is proposed in this paper. Both additive manufacturing and subtractive machining constraints are simultaneously considered in each topology optimization iteration. The topology optimization is performed by the bi-directional evolutionary structural optimization (BESO) method. The effectiveness of the proposed method is demonstrated by several 3D compliance minimization problems.

Geometric simulation of 5-axis hybrid additive-subtractive manufacturing based on Tri-dexel model

5-axis hybrid additive-subtractive manufacturing is a new and promising technology for many industrial applications. Because of its complexity, the machining simulation is very important to verify the effectiveness of tool path. However, most simulation methods are proposed for subtractive manufacturing and additive manufacturing separately. This paper presents a novel geometric simulation technique for the 5-axis hybrid additive-subtractive manufacturing, which is based on Laser Engineered Net Shaping (LENS) and milling. In the proposed method, 5-axis additive swept volume elements are represented with Tri-dexel models and then converted into triangular meshes for visualization. Workpiece after additive manufacturing can be then used as a workblank for subtractive manufacturing simulation. Finally, a geometric simulation module is developed based on SIEMENS NX software to demonstrate the feasibility of the proposed simulation method.

Theoretical modelling and prediction of surface roughness for hybrid additive–subtractive manufacturing processes

ABSTRACTHybrid additive–subtractive manufacturing processes are becoming increasingly popular as a promising solution to overcome the current limitations of Additive Manufacturing (AM) technology and improve the dimensional accuracy and surface quality of parts. Surface roughness, as one of the most important surface quality measures, plays a key role in the fit of assemblies and thus needs to be thoroughly evaluated at the design and manufacturing stages. However, most of the studies on surface roughness modelling and analysis employ empirical approaches, and only consider the effect of a single manufacturing process. In particular, the existing surface roughness models are not applicable to hybrid additive–subtractive manufacturing processes in which a secondary process is involved. In this article, analytical models are established to predict the surface roughness of parts fabricated by AM as well as hybrid additive–subtractive manufacturing processes. A novel surface profile representation scheme is also proposed to increase the prediction accuracy. Case studies are performed to validate the effectiveness of the proposed models. An average of 4.25% error is observed for the AM case, which is significantly smaller than the prediction error of the existing models in the literature. Furthermore, in the hybrid case, an average of 91.83% accuracy is obtained.

A novel 6-axis hybrid additive-subtractive manufacturing process: Design and case studies

Additive manufacturing has been employed in numerous areas owing to its advantages of fabricating complex geometries and creating less material waste. Nevertheless, parts manufactured by additive manufacturing processes tend to have poor surface quality and low dimensional accuracy. To overcome the limitations of additive manufacturing technologies, the favorable capabilities of subtractive manufacturing, i.e., high surface quality, can be integrated to form a hybrid process. A novel 6-axis hybrid additive-subtractive manufacturing process is proposed and developed in this paper. The hybrid process is realized using a six degrees of freedom (DOF) robot arm, equipped with multiple changeable heads and an integrated manufacturing platform. Based on the obtained results from different case studies, the hybrid additive-subtractive process has shown to have potentials in reducing production time, fabricating parts with better surface quality by removing the staircase error, manufacturing high quality freeform surfaces through the dynamic adjustment of tool axis direction, and eliminating the need for support structure because of the 6-DOF flexibility.

Hybrid Ants: A New Approach for Geometry Creation for Additive and Hybrid Manufacturing

This research presents a novel and disruptive approach to the simultaneous design and structural refinement of parts manufactured using purely additive, purely subtractive and hybrid additive-subtractive manufacturing processes (HASPs). This research is responding to the increasing need to be able to state with confidence that a particular part design can be manufactured by a particular process. This is viewed as a major barrier to the profitable exploitation of additive and hybrid manufacturing processes. By describing the known part constraints and the mechanisms (limitations) of constituent manufacturing processes, parts are designed using a bio-inspired multi-agent system called ‘Hybrid Ants’. By abstracting manufacturing processes into a set of rules that limit how and where material can be processed, all part geometries created by the Hybrid Ants are inherently ‘manufacturable’ under the current description of the manufacturing capability. The possibility that new knowledge may be elicited from this system is an exciting new paradigm, which could change the way design for additive (or hybrid) manufacturing processes is developed in the future. As will be shown throughout this paper, Hybrid Ants is a closed-loop system, which generatively creates part geometries and then appraises these geometries for structural performance using the finite element method. Stress values are then used in the next loop iteration to refine the geometry ad infinitum. This system is akin to ant (or termite) nest morphogenesis, where nest layouts are optimised for thermoregulation and ventilation. In this research, thermoregulation is analogously exchanged for stress for structural optimisation of engineering components.

Topology optimization for hybrid additive-subtractive manufacturing

Hybrid additive-subtractive manufacturing is gaining popularity by making full use of geometry complexity produced by additive manufacturing and dimensional accuracy derived from subtractive machining. Part design for this hybrid manufacturing approach has been done by trial-and-error, and no dedicated design methodology exists for this manufacturing approach. To address this issue, this work presents a topology optimization method for hybrid additive and subtractive manufacturing. To be specific, the boundary segments of the input design domain are categorized into two types: (i) Freeform boundary segments freely evolve through the casting SIMP method, and (ii) shape preserved boundary segments suppress the freeform evolvement and are composed of machining features through a feature fitting algorithm. Given the manufacturing strategy, the topology design is produced through additive manufacturing and the shape preserved boundary segments will be processed by post-machining. This novel topology optimization algorithm is developed under a unified SIMP and level set framework. The effectiveness of the algorithm is proved through a few numerical case studies.

Gemini: Engaging Experiential and Feature Scales Through Multimaterial Digital Design and Hybrid Additive–Subtractive Fabrication

Abstract Gemini is a chaise lounge constructed using hybrid fabrication involving 3D printing of a textured polymeric skin combined with CNC milling of a wooden chassis. The texture of the chaise was inspired by the seed geometry of the Ornithogalum dubium flower and designed using a computational implementation of an inhomogeneous Poisson process. The 3D-printed texture was informed by the weight distribution of a person with the goal of delivering structural support and comfort on the one hand and maximizing the absorption of sound emanating from exterior sources of noise on the other. Gemini is the first functional object produced using the Stratasys Objet500 Connex3 color multimaterial 3D printer including the Tango+ soft material. It represents one of the first cases of a hybrid additive–subtractive manufacturing approach, which combines the strength of both of these techniques.