To send content items to your account,
please confirm that you agree to abide by our usage policies.
If this is the first time you use this feature, you will be asked to authorise Cambridge Core to connect with your account.
Find out more about sending content to .
To send content items to your Kindle, first ensure firstname.lastname@example.org
is added to your Approved Personal Document E-mail List under your Personal Document Settings
on the Manage Your Content and Devices page of your Amazon account. Then enter the ‘name’ part
of your Kindle email address below.
Find out more about sending to your Kindle.
Note you can select to send to either the @free.kindle.com or @kindle.com variations.
‘@free.kindle.com’ emails are free but can only be sent to your device when it is connected to wi-fi.
‘@kindle.com’ emails can be delivered even when you are not connected to wi-fi, but note that service fees apply.
This work focuses on the impact of the build orientation on additively manufactured waveguide-based hybrid couplers for D-band frequency range and relates it to other sources of uncertainty within the overall manufacturing process and measurement instrumentation for the D-band frequency range. The designed specimens are first printed from UV curable photopolymer resin and subsequently metal coated by an electroless silver plating process, which in turn is improved by making use of the slotted waveguide approach. Although the requirements toward geometrical precision to achieve phase errors below 10° are in an order of 0.1 mm, a desktop grade DLP printer is utilized in this work in order to point out the prospects and limitations of additive manufacturing. Furthermore, waveguide paths with bends are part of the model and their impact on the measured attenuation is estimated explicitly.
Despite this narrow field of tolerances, one specimen could have been realized, which achieves a measured output magnitude imbalance of 0.7 dB over the frequency range from 120 to 155 GHz while at the same time exhibiting a phase deviation of only <10° from the desired 90°. With these demonstrated results, the proposed approach provides suitability for future applications in the D-band frequency range.
This in situ transmission electron microscopy work presents a nanoscale characterization of the microstructural evolution in 3D-printed Inconel 718 (IN718) while exposed to elevated temperature and an associated change in the mechanical property under tensile loading. Here, we utilized a specially designed specimen shape that enables tensile testing of nano-sized thin films without off-plane deformations. Additionally, it allows a seamless transition from the in situ heating to tensile experiment using the same specimen, which enables a direct correlation of the microstructure and the mechanical property of the sample. The method was successfully used to observe the residual stress relaxation and the formation of incoherent γ′ precipitates when temperature was increased to 700°C. The subsequent in situ tensile test revealed that the exposure of the as-printed IN718 to a high temperature without full heat treatment (solutionizing and double aging) leads to loss of ductility.
Additive manufacturing offers a high degree of design freedom. When Design for Additive Manufacturing is conducted properly, lightweight potential can be exploited. This contribution introduces a novel design approach for the widespread fused layer modelling (FLM) technology when using orthotropic Fibre Reinforced Polymer filament. Its objective is to obtain stiff and strong load-path optimized FLM structures in a structured and algorithmic way. The approach therefore encompasses (1) build orientation optimization to consider weaker bonding between layers than intralayer; (2) topology optimization with orthotropic material properties to obtain favourable overall geometry and inner structure; (3) direct build path generation from optimized material orientation and alternatives to the direct generation and (4) simulation. The approach is demonstrated using a lift arm under multiple load cases and further demonstrator parts to show its general applicability. Lightweight potential of individual optimization steps and the influence of modifications contrasting general non-FLM-specific optimization are studied and discussed.
Additive manufacturing (AM) has made long strides in the recent past and rapidly evolved into a promising alternative in specific applications. The aircraft industry is not an exception to this. The true just-intime production possibility is critical for the aircraft maintenance industries, though the lack of material freedom is a major hurdle. Several fire-retardant materials were investigated for AM in the aerospace context, but mainly for fused deposition modeling (FDM). The material consolidation constraints in FDM led to the expansion to the use of selective laser sintering (SLS) to some extent. Nevertheless, the material options are still limited, proprietary, and lack scientific insights into the material consolidation mechanics. Attempts are made in this paper to fill this gap, evaluating a new fire-retardant material for processing by SLS. Experiments conducted to ascertain the material, process, structure, and consolidation relationships indicated energy density levels 0.062–0.070 J/mm2 with laser power 13 W and scan speed varied slightly around 390 mm/s to give the best laser sintering and mechanical property results in polyetherimide powders.
In this investigation, the superalloy IN718 has been prepared by additive manufacturing (AM) following a selective laser melting technique, and the post-AM heat treatments have been optimized. The microstructure of additively manufactured (AM) IN718 is characterized by the presence of dendritic and cellular features with large spatial heterogeneity along and across the build plane. Along the build direction, the 〈100〉 fiber texture dominates. Heat treatment involving two-step solution treatment, and subsequently, two-step aging treatment was specifically designed to facilitate the precipitation of δ phase at the grain boundaries to make the material resistant to grain boundary sliding (GBS). The AM IN718 showed dynamic strain aging (DSA) at three different temperatures, while the critical strain for the onset of serration was extended to a higher value after the heat treatment.
Metal additive manufacturing (AM) provides a platform for microstructure optimization via process control, but establishing a quantitative processing-microstructure linkage necessitates an efficient scheme for microstructure representation and regeneration. Here, we present a deep learning framework to quantitatively analyze the microstructural variations of metals fabricated by AM under different processing conditions. The principal microstructural descriptors are extracted directly from the electron backscatter diffraction patterns, enabling a quantitative measure of the microstructure differences in a reduced representation domain. We also demonstrate the capability of predicting new microstructures within the representation domain using a regeneration neural network, from which we are able to explore the physical insights into the implicitly expressed microstructure descriptors by mapping the regenerated microstructures as a function of principal component values. We validate the effectiveness of the framework using samples fabricated by a solid-state AM technology, additive friction stir deposition, which typically results in equiaxed microstructures.
The disruptive potential of additive manufacturing (AM) relies on its ability to make customized products with considerable weight savings through geometries that are difficult or impossible to produce by conventional methods. Despite its versatility, applications of AM have been restricted due to the formation of columnar grains, resulting in solidification defects and anisotropy in properties. To achieve fine equiaxed grains in AM, alloy design and solidification conditions have been optimized in various alloy systems. In this review paper, the microstructure of high-entropy alloy (HEA) parts produced by selective laser melting and powder-based directed energy deposition is investigated. Solidification maps based on laser process parameters (as opposed to most commonly used solidification velocity and temperature gradient) are constructed by compiling available literature for single-phase face-centered cubic, body-centered cubic, and multiphase HEAs. These maps could guide printing of HEAs and provide an insight into the design of novel HEAs for AM.
This contribution investigates how methods for functional modeling support designers with additive manufacturing. Therefore, two methods for functional modeling are examined. In this contribution a study with 32 participants is presented. The participants solved two consecutive design tasks, in which some participants were supported by functional modeling methods in the second task. The study shows that students have the most difficulties in dealing with the geometric restrictions of Laser Beam Melting (LBM). Furthermore, the support value of functional modeling was not able to be assessed.
Lightweight design (LWD) is partly reaching its limits. New technologies must not only be used to make products more functional, but also to make LWD more efficient. Here additive manufacturing (AM) should be named. Potentials of the use in LWD are not yet clear. In this work, existing LWD strategies and their location in the design process are presented. Criteria are worked out which influence the design process and the use of LWD strategies. The use of AM in (hybrid) LWD will be investigated in order to overcome design trade-offs and what influence its use could have on the design process.
With the broader industrial application of Additive Manufacturing (AM), designers are facing new challenges in conceptual design for AM. To better understand the problematic, the authors organised a design workshop with six experts in AM. The paper presents the results of the conducted design workshop and discusses the current and future trends in research on the conceptual design for AM.
Current geometrical modelling approaches are unable to handle complex geometrical objects such as heterogeneous lattice structures. In this work, a framework for a novel bio-inspired geometric modelling method is proposed. The method can potentially support geometric modelling of heterogeneous lattice structures. The method utilises discretisation algorithms that are based on cell division processes encountered in nature. The method is verified on two 2D use-cases.
Additive Manufacturing is doing its first steps in the production of spare parts. Usually the spares belong to legacy systems, and the tooling to produce them is no longer available. Re-designing spares that are designed for a previous industry mindset can be sometimes challenging. In this study a rather classic design approach is compared to a functional driven approach. Four case studies from different clients are reported, remarking the benefits and drawbacks of using design for additive manufacturing practices in Laser Powder Bed Fusion.
The recent interest in human-robot interaction requires the development of new gripping solutions, compared to those already available and widely used. One of the most advanced solutions in nature is that of the human hand, and several research contributions try to replicate its functionality. Technological advances in manufacturing technologies and design tools are opening possibilities in the design of new solutions. The paper reports the results of the design of an underactuated artificial robotic hand, designed by exploiting the benefits offered by additive manufacturing technologies.
This paper presents an algorithm that contributes to an automatic decomposition of a mechanical part based on geometric features and methods of unsupervised machine learning. For the development of the algorithm, existing techniques of 3D shape segmentation, especially surface-based part segmentation procedures are reviewed and important areas of activities are revealed. The developed multi-step approach results in an abstract product model. This representation leads to a new way of designing and redesigning parts for the novel hybrid manufacturing concept Incremental Manufacturing (IM).
In modular products conflicting objectives may occur. This leads to characteristics as component-dependent oversizing and undersizing as well as increased complexity of the interfaces. These conflicts can be resolved using the potentials of AM processes. For the best use possible, the potentials are systematically considered in the early design phases as part of an extended procedure. The extended procedure improves the benefit-effort ratio of modular respectively individual products and a further optimization of the product architecture and consideration of synergy effects is achieved.
The topic of support structure design in the Design for Additive Manufacturing (DfAM) field is not addressed with the same relevance as the topic of part design. Therefore, this contribution investigates parameters for both the manufacturing and support structure design for the Laser Powder Bed Fusion (L-PBF) process. Matrices for cause-effect-relations of manufacturing and design parameters on build properties as well as correlations of them are presented. Based on these, recommendations for actions for experimental procedures are derived following the Design of Experiments method.
This paper describes an approach for designing lightweight components produced through additive manufacturing (AM). Lightweight design is often done through topology optimization (TO). However, the process of manually interpreting mesh-based and imprecise results from a TO into a geometry that fulfils all requirements is complex. To aid in this process, this paper suggest an approach based on combining overhang-constrained TO with lattice-based TO to automate complex tasks, retain parametric control, and to minimize manufacturing cost. The approach is validated through a benchmark part.
Function and constraints modelling are implemented to design two gridded ion thrusters for additive manufacturing (AM). One concept takes advantage of AM design freedom, disregarding AM limitations and is not feasible. The other concept considers AM limitations and is manufacturable and feasible. Constraints modelling highlights AM capabilities that can be improved, showing where future investment is needed. Constraints representation can also support the creation of technology development roadmaps able to identify areas of AM technologies that must be improved.
The multidisciplinary nature and lack of comprehensive ‘materials-product-manufacturing’ knowledge of Functionally Graded Additive Manufacturing (FGAM) require training to support the future Additive Manufacturing experts. INEX-ADAM, an EU funded project is building a transnational platform to promote FGAM. Brunel University London conducted two-day workshop on FGAM at the University of Zagreb in Croatia with academics and industry professionals. The workshop will strengthen the research capabilities to harness the potential of the FGAM and mitigate the constraints to industrial applications.
Mass-personalization (MP) presents an opportunity to meet diversifying customer needs in consumer products market with a near mass-production efficiency. Traditional product development methodologies fall short to guide design for MP and a dedicated systematic methodology is essential. The proposed approach bases on a dynamic product template that automatically adapts with user input and produces a reliable output. This paper presents the workflow towards mass-personalization of saxophone mouthpieces with focus on design automation.