Aspects Of Additive Manufacturing Research Articles

Sustainability and innovation in 3D printing: Outlook and trends

<abstract> <p>The convergence of additive manufacturing (AM), sustainability, and innovation holds significant importance within the framework of Industry 4.0. This article examines the environmentally friendly and sustainable aspects of AM, more commonly referred to as 3D printing, a cutting-edge technology. It describes the fundamentals of AM in addition to its diverse materials, processes, and applications. This paper demonstrates how several 3D printing techniques can revolutionize sustainable production by examining their environmental impacts. The properties, applications, and challenges of sustainable materials, such as biodegradable polymers and recyclable plastics, are thoroughly examined. Additionally, the research explores the implications of 3D printing in domains including renewable energy component fabrication, water and wastewater treatment, and environmental monitoring. In addition, potential pitfalls and challenges associated with sustainable 3D printing are examined, underscoring the criticality of continuous research and advancement in this domain. To effectively align sustainability goals with functional performance requirements, it is imperative to address complexities within fused deposition modeling (FDM) printing processes, including suboptimal bonding and uneven fiber distribution, which can compromise the structural integrity and durability of biodegradable materials. Ongoing research and innovation are essential to overcome these challenges and enhance the viability of biodegradable FDM 3D printing materials for broader applications.</p> </abstract>

An Overview of Extensive Analysis of 3D Printing Applications in the Manufacturing Sector

3D printing (additive manufacturing) is one of the revolutionary technologies that are transforming manufacturing and industrial processes. Additive manufacturing (AM) technology is being used for extensive customization and production of all types of open-source designs in farming, medical, automotive, locomotive, aerospace, and construction industries. The advantages of 3D printing for industrial applications include little material waste, simple production, minimal human participation, minimal postprocessing, and energy efficiency. There are limited articles on the scope and future possibilities of AM technologies. This article explains numerous AM techniques, uses for technology, and substances used in the manufacturing firm. The numerous materials that may be used with every type of 3D printing process are explained in depth. The numerous settings whereby every processor kind is used are also listed in the study. The original study findings indicate that, while 3D printing technology has made great advances, there are still challenges that need to be addressed; however, the obstacles appear to vary: the cost of preprocessing and postprocessing, a restricted selection of materials, and technological constraints are the most significant 3D printing challenges. Readers will be benefitted from the new dimension added by explanation of the many aspects of additive manufacturing and the identification of potential new research fields in this review. The processes may be enhanced and modified to operate with a range of materials through further research, whereas if the range of applications for 3D printing technology components is to be increased, more effort should be made into developing economical printing procedures and supplies that function with these printers.

Sustainability aspects of additive manufacturing: Leveraging resource efficiency via product design optimization and laser powder bed fusion

Natural resource is used for producing useful components and in the process fractions of Natural resources are used for producing useful components and in the process fractions of valuable resources are lost as waste or emissions into the ecosystem. The continuous usage of natural resources causes their scarcity alongside the negative impacts. Manufacturing sectors aim to control these impacts. Industry 4.0 (I4.0) technologies including additive manufacturing (AM), simulations, internet of things and connectivity promise resource consumption, functions and sustainability improvements.Simulation-assisted design for AM boosts productivity via swift and novel product designs to achieve resource efficiency, cost effectiveness, and process efficacy. New integrated and iterative methods of creating optimized product designs enabled by I4.0 elements offer alternative route of light weighting, and digitalization. Optimized designs help control resource scarcity including efficient use of raw materials, energy efficient products, reduced waste, and pollution to achieve sustainable goals. This study aims to guide AM users on how computer design and simulation assisting tools help to digitally create optimized lightweight products, test performance, plan manufacturing without committing to physical manufacturing cost. The study using review and experimental case study shows how AM and, particularly, laser powder bed fusion (LPBF) through optimized product designs influence either component functionality, build weight or manufacturing time towards resource and energy improvements. The results of the experimental study show prospective scenarios for maximizing resource efficiency in L-PBF through combined build and optimized build orientations. This study adds to ongoing sustainability aspects of AM relating to product design optimization in support to sustainable excellence.

Is Additive Manufacturing an Environmentally and Economically Preferred Alternative for Mass Production?

The manufacturing sector accounts for a large percentage of global energy use and greenhouse gas emissions, and there is growing interest in the potential of additive manufacturing (AM) to reduce the sector's environmental impacts. Across multiple industries, AM has been used to reduce material use in final parts by 35-80%, and recent publications have predicted that AM will enable the fabrication of customized products locally and on-demand, reducing shipping and material waste. In many contexts, however, AM is not a viable alternative to traditional manufacturing methods due to its high production costs. And in high-volume mass production, AM can lead to increased energy use and material waste, worsening environmental impacts compared to traditional production methods. Whether AM is an environmentally and economically preferred alternative to traditional manufacturing depends on several hidden aspects of AM that are not readily apparent when comparing final products, including energy-intensive and expensive material feedstocks, excessive material waste during production, high machine costs, and slow rates of production. We systematically review comparative studies of the environmental impacts and costs of AM in contrast with traditional manufacturing methods and identify the conditions under which AM is the environmentally and economically preferred alternative. We find that AM has lower production costs and environmental impacts when production volumes are relatively low (below ∼1,000 per year for environmental impacts and below 42-87,000 per year for costs, depending on the AM process and part geometry) or the parts are small and would have high material waste if traditionally manufactured. In cases when the geometric freedom of AM enables performance improvements that reduce environmental impacts and costs during a product's use phase, these can counteract the higher production impacts of AM, making it the preferred alternative at larger production volumes. AM's ability to be environmentally and economically beneficial for mass manufacturing in a wider variety of contexts is dependent on reducing the cost and energy intensity of material feedstock production, eliminating the need for support structures, raising production speeds, and reducing per unit machine costs. These challenges are not primarily caused by economies of scale, and therefore, they are not likely to be addressed by the increasing expansion of the AM sector. Instead, they will require fundamental advances in material science, AM production technologies, and computer-aided design software.

Additive Manufacturing Technologies of High Entropy Alloys (HEA): Review and Prospects

Additive manufacturing (AM) technologies have gained considerable attention in recent years as an innovative method to produce high entropy alloy (HEA) components. The unique and excellent mechanical and environmental properties of HEAs can be used in various demanding applications, such as the aerospace and automotive industries. This review paper aims to inspect the status and prospects of research and development related to the production of HEAs by AM technologies. Several AM processes can be used to fabricate HEA components, mainly powder bed fusion (PBF), direct energy deposition (DED), material extrusion (ME), and binder jetting (BJ). PBF technologies, such as selective laser melting (SLM) and electron beam melting (EBM), have been widely used to produce HEA components with good dimensional accuracy and surface finish. DED techniques, such as blown powder deposition (BPD) and wire arc AM (WAAM), that have high deposition rates can be used to produce large, custom-made parts with relatively reduced surface finish quality. BJ and ME techniques can be used to produce green bodies that require subsequent sintering to obtain adequate density. The use of AM to produce HEA components provides the ability to make complex shapes and create composite materials with reinforced particles. However, the microstructure and mechanical properties of AM-produced HEAs can be significantly affected by the processing parameters and post-processing heat treatment, but overall, AM technology appears to be a promising approach for producing advanced HEA components with unique properties. This paper reviews the various technologies and associated aspects of AM for HEAs. The concluding remarks highlight the critical effect of the printing parameters in relation to the complex synthesis mechanism of HEA elements that is required to obtain adequate properties. In addition, the importance of using feedstock material in the form of mix elemental powder or wires rather than pre-alloyed substance is also emphasized in order that HEA components can be produced by AM processes at an affordable cost.

Addressing Thermal Distortion in Additive Manufacturing of Topology Optimized Structures Through Reverse Shape Morphing

Design of light weight structures is an important aspect in the aircraft industry, since minimizing the weightof components improves the overall aircraft performance. However, conventional manufacturing methods work on standard geometries and shapes, and often lead to overdesigning of parts. Additive Manufacturing (AM) overcomes these issues by allowing more design freedom. The present study focuses on two aspects of AM: (1) part consolidation through topology optimization, and (2) addressing thermal distortion through reverse shape morphing. An assembly of two load bearing brackets is first amalgamated into a single Topology Optimized (TO) part, which satisfies the displacement and stress requirements of the original design. After a series of optimization iterations, the final TO part (278 g) weighs 69 % lesser than the original assembled design (909 g), still meeting the design constraints. The TO part thus eliminates the need of fasteners to join both the brackets, thereby, making the design simpler yet effective. Moreover, a homogeneous stress distribution in the optimized part allows for efficient material utilization. In order to overcome thermal distortion that results during the AM process, the shape of the TO part is transformed in a sense opposite to the distortions produced. This is achieved through reverse shape morphing technique, that reduces thermal distortions in the printed part to sub-micron levels, and the morphed TO part conforms to the requirements meeting the design constraints. Therefore, the implementation of topology optimization along with reverse shape morphing makes the design simple and efficient having reduced distortion. This is achieved without any need of modifications in the manufacturing system or equipment, and such a strategy can be replicated and implemented at industrial scale as well.

Strengthening the Sustainability of Additive Manufacturing through Data‐Driven Approaches and Workforce Development

The additive manufacturing (AM) industry is rapidly developing and expanding, thereby becoming an important and integral component of the digital revolution in manufacturing practices. While the engineering aspects of AM are under intensive research, there still remain many chances to strengthen the sustainability of additive manufacturing (SAM). Cogently increasing the AM community's attention to SAM is vital for developing the AM industry sustainably from the bottom up. The digital nature of AM provides new opportunities for acquiring, storing, and utilizing data to strengthen SAM through data‐driven approaches. Herein, spotlight on SAM is shone upon and it is placed on a more concrete footing. The corresponding advances in data‐driven methods that can strengthen SAM are featured, such as optimizing designs for AM, reducing material waste, and developing databases. How the AM workforce can be developed and grown as a collaboration between the industry, government, and academia to extensively harness the full potential of AM as well as mitigate its adversarial social impact is discussed. Finally, several critical digital techniques that have the potential to further strengthen SAM in the factory of the future, including hybrid manufacturing, Internet of Things, and machine learning and artificial intelligence, are highlighted.

Data‐Driven Approaches Toward Smarter Additive Manufacturing

The latest industrial revolution, Industry 4.0, is driven by the emergence of digital manufacturing and, most notably, additive manufacturing (AM) technologies. The simultaneous material and structure forming in AM broadens the material and structural design space. This expanded design space holds a great potential in creating improved engineering materials and products that attract growing interests from both academia and industry. A major aspect of this growing interest is reflected in the increased adaptation of data‐driven tools that accelerate the exploration of the vast design space in AM. Herein, the integration of data‐driven tools in various aspects of AM is reviewed, from materials design in AM (i.e., homogeneous and composite material design) to structure design for AM (i.e., topology optimization). The optimization of AM tool path using machine learning for producing best‐quality AM products with optimal material and structure is also discussed. Finally, the perspectives on the future development of holistically integrated frameworks of AM and data‐driven methods are provided.

Systematic review of sourcing and 3D printing: make-or-buy decisions in industrial buyer\u2013supplier relationships

Additive manufacturing (AM) is regarded as a technology that has transformative and disruptive potential in nearly all industries. However, AM is not only about new production equipment and processes. Given the decreasing degree of vertical integration in many companies, suppliers add significant value to the finished product. AM might lead to the redesign of production networks, including a scenario in which the buyer uses AM to produce parts with data provided by suppliers. Overall, AM could have a major impact on the ways in which buyers and suppliers collaborate in the future. Nevertheless, research on AM in the field of industrial procurement remains scarce. This is surprising, given that AM is not only changing traditional procurement categories and creating new ones (comprising printers, powder raw materials, data and the associated engineering services) but AM’s widely discussed potential for decentralisation might also restructure the logistical aspects (transport, stocks) of supply chains. In addition, AM may resurrect the old procurement question of ‘make or buy’. Current research focuses on the logistical aspects of AM and concerns such issues of decentralisation (such as the diminishing need for transportation and the design of transport networks). In contrast, this research addresses the question of whether AM demands new answers to strategic sourcing questions. For this purpose, academic journal literature concerning procurement and AM search strings is reviewed. Selected articles are analysed using a fine-grained analytical framework of procurement strategies. The findings show that existing research lacks theoretical approaches and a systematic view of the topic. Specifically, the analysis reveals a number of distinct knowledge gaps, which present several potential directions for future research.

A review on machine learning in 3D printing: applications, potential, and challenges

Additive manufacturing (AM) or 3D printing is growing rapidly in the manufacturing industry and has gained a lot of attention from various fields owing to its ability to fabricate parts with complex features. The reliability of the 3D printed parts has been the focus of the researchers to realize AM as an end-part production tool. Machine learning (ML) has been applied in various aspects of AM to improve the whole design and manufacturing workflow especially in the era of industry 4.0. In this review article, various types of ML techniques are first introduced. It is then followed by the discussion on their use in various aspects of AM such as design for 3D printing, material tuning, process optimization, in situ monitoring, cloud service, and cybersecurity. Potential applications in the biomedical, tissue engineering and building and construction will be highlighted. The challenges faced by ML in AM such as computational cost, standards for qualification and data acquisition techniques will also be discussed. In the authors’ perspective, in situ monitoring of AM processes will significantly benefit from the object detection ability of ML. As a large data set is crucial for ML, data sharing of AM would enable faster adoption of ML in AM. Standards for the shared data are needed to facilitate easy sharing of data. The use of ML in AM will become more mature and widely adopted as better data acquisition techniques and more powerful computer chips for ML are developed.

Effect of material form on deposition characteristics in micro-plasma transferred arc additive manufacturing process

This paper presents study on influence of different forms (i.e. powder, wire, and combined powder-wire) of Stellite-6 deposition material on arc interaction and deposition characteristics in μ-plasma transferred arc additive manufacturing (μ-PTAAM) process. It was found that (i) width of μ-plasma arc remains almost constant throughout its length for the powdered form, but it varies for wire and combined powder-wire form; (ii) the wire form resulted in the highest deposition efficiency (94.9%), substrate temperature (114.7°C) and surface roughness (202μm) whereas the powder form gave the highest average value of dilution (10.3%) and microhardness (588 HV), lowest substrate temperature (70.9°C) and surface roughness (125μm), and smallest grain size (3μm); (iii) combined powder-wire form gave the lowest dilution (8.66%) and microhardness (534 HV), and largest grain size (7μm); (iv) elemental composition analysis found highest inclusion of iron for the powder form; (v) phase analysis revealed that different forms of deposition material yielded same crystalline phases. This study proves that different forms of the deposition material can be used in μ-PTAAM process and combined powder-wire form the deposition material narrows the existing gaps between the wire and powder forms for various aspects of additive manufacturing.

Analysis of Shape Deformation from Densification of Additive Manufacturing Parts in Selective Laser Sintering

Additive Manufacturing (AM) has recently attracted huge attentions as a technology for the next generation of industry. Particularly for the manufacturing purposes, various aspects of AM are being studied and applied, such as prototypes for assembly tests, jig production, and actual parts manufacturing. Selective Laser Sintering (SLS) using polyamide is easy to apply to various industries, such as its superior mechanical properties and higher design freedom, but design that takes into account variation in dimensions after manufacture often leads to costly and time-consuming problems. As a way to reduce deformation in the production process, previous studies approached experimentally about the effects of thermal deformation or residual stress on deformation. This is difficult to apply to a specimen of various shapes and sizes and also has limitations as a common solution to dimensional inaccuracies. To propose a solution for mitigating shape deformation of AM part, this paper focused on the effect of phase change of material among various processing parameters that cause shape deformation and tries to present an analytic model. Modeling on the melting and sintering phenomena of powder was presented using Euler-Bernui beam equation. The proposed model was verified by measuring the density variation of manufactured AM components and analyzing the correlation between the degree of contraction and the energy density. Factors such as layer thickness, part thickness, and part placement height were identified to have significant effects on the actual deformation. It is also confirmed that dimensional accuracy of parts that show large deformation by bending has increased by 64.2% when a calibration model is applied through manufacturing of actual parts. Time and cost can be saved for industrial application of AM by applying this proposed calibration model. In addition, by using this model more efficiently in the CAD design process, dimensional accuracy can be enhanced.

The approaches to design and manufacturing of large-sized marine machinery parts by direct laser deposition

This article shows several aspects of additive manufacturing via direct laser deposition of machinery parts. The redesigning methods of product manufactured by conventional technologies are considered, taking into account the stress-strain state of a sample manufactured by the DLD-method. Besides modeling methods allow obtaining a product of required geometry, the experience of applying the topological optimization method of structure is demonstrated. The product with optimized design has reliability characteristics close to the original solid version. The differences in the product microstructure obtained by the DLD-method from the structure after casting and thermomechanical processing are shown. The mechanical properties of built-up material are comparable to the same properties after casting and rolling. Economic evaluation of DLD introduction was held. A criterion of advisability replacement to DLD-method of manufacturing is determined. The results prove attractiveness of digital laser technologies application in shipbuilding.

On the potential of integrating building information modelling (BIM) for the additive manufacturing (AM) of concrete structures

PurposeAdditive manufacturing (AM) and building information modelling (BIM) are emerging trends for which it has been claimed that both increase both efficiency and productivity in the construction industry. This study aims to synthesise and aggregate the literature addressing BIM integration in the AM of concrete structures and to exploit the joint value creation potential.Design/methodology/approachThis study firstly applies a mixed-review method to achieve mutual corroboration and interdependency between quantitative and qualitative research approaches. Bibliometric mapping is applied to identify, map and synthesise the relevant literature. Scoping review is used to examine the extent, gap, range and nature of the research activity. Afterward, a cross-situational analysis, the threats, opportunities, weaknesses and strengths2 matrix, is proposed and applied to exploit the joint value creation potential of different aspects of AM and BIM.FindingsThe study reveals a substantial interest in this field. However, progress in terms of integration is slow compared to the rapid development in interest in the two trends individually. The literature discusses or conceptualises such integration at building-scale, while prototyping or proof-of-concept processes are only rarely used. The study identified 12 joint value creation potentials through the integration of BIM in AM for concrete structures, which can create value by enabling more optimised designs, automated construction processes and data analytics that can apply throughout the building life-cycle process.Originality/valueThe advancements of BIM integration in the AM of concrete structures are analysed and joint value creation potentials are proposed. The study proposes a cross-situation analysis that can be applied to structure joint value creation potentials from the multi-dimensional integration of different factors and topics, especially for emerging technologies.

An overview of information technology standardization activities related to additive manufacturing

As Additive manufacturing (AM) technologies and connected machines are ever more widespread across most industries, there is a need for a better understanding about the standardization activities related to information technology (IT) within the scope of AM. The purpose of this paper is to provide an overview of existing standardization activities related to IT aspects of AM, including but not limited to data transfer and exchange. The paper covers the IT standardization activities in organizations, including ISO TC261, ASTM International, ISO TC 184, ISO/IEC JTC 1, Web3D Consortium, IEC committees, IEEE committees, 3MF Consortium and Khronos, which have the most active and ongoing projects. From this study, it can be observed that the manufacturing sector has generated the majority of standardization work, followed by industry R&D areas and the medical field. This paper also discusses two future IT standards for AM service platforms and for the medical industry.

Toward Feedback Control for Additive Manufacturing Processes Via Enriched Analytical Solutions

Additive manufacturing (AM) enables the fabrication of objects using successive additions of mass and energy. In this paper, we explore the use of analytic solutions to model the thermal aspects of AM, in an effort to achieve high computational performance and enable “in the loop” use for feedback control of AM processes. It is shown that the utility of existing analytical solutions is limited due to their underlying assumption of a homogeneous semi-infinite domain. These solutions must, therefore, be enriched from their exact form in order to capture the relevant thermal physics associated with AM processes. Such enrichments include the handling of strong nonlinear variations in material properties, finite nonconvex solution domains, behavior of heat sources very near boundaries, and mass accretion coupled to the thermal problem. The enriched analytic solution method (EASM) is shown to produce results equivalent to those of numerical methods, which require six orders of magnitude greater computational effort. It is also shown that the EASM's computational performance is sufficient to enable AM process feedback control.

Enriched analytical solutions for additive manufacturing modeling and simulation

Recent developments in additive manufacturing (AM) technologies involving heat and mass deposition have exposed the need for computationally efficient modeling of thermal field histories. This is due to the effect of such histories on resulting morphologies and quantities of interest, such as micro- and meso-structure, residual strains and stresses, as well as on material and structural properties and associated functional performance at the macro-scale. Limiting undesirable manifestations of these phenomena has motivated the development of both feed-forward and feedback loop control methodologies. However, up to now the computational cost of existing methods for predicting thermal fields and associated aspects, have allowed only feed-forward control methods. Consequently, in this paper, analytic solutions are enriched and then used to model the thermal aspects of AM, in a manner that demonstrates both high computational performance and fidelity required to enable “in the loop” use for feedback control of AM processes. It is first shown that the utility of existing analytical solutions is limited due to their underlying assumptions, some of which are their derivation based on a homogeneous semi-infinite domain and temperature independent material properties among others. These solutions must therefore be enriched in order to capture the actual thermal physics associated with the relevant AM processes. Enrichments introduced herein include the handling of strong nonlinear variations in material properties due to their dependence on temperature, finite non-convex solution domains, behavior of heat sources very near domain boundaries, and mass accretion coupled to the thermal problem. The enriched analytic solution method (EASM) that implements these enrichments is shown to produce results equivalent to those of numerical methods (such as Finite Elements and Finite Differences) that require six orders of magnitude greater computational cost.

A Study of Design Fixation Related to Additive Manufacturing

This study aims to understand the effect of additive manufacturing (AM) on design fixation. Whereas previous research illustrates the positive aspects of AM, the overarching hypothesis of this work is that it might also have negative effects with respect to conventional manufacturability. In this work, participants from two groups, a design for conventional manufacturing (DfCM) group, and a design for additive manufacturing (DfAM) group, were asked to design a basic product. Then, a second iteration of the design asked both groups to design for conventional processes, and to include subtractive and formative methods like machining and casting, respectively. Findings showed that the DfAM fixated on nonproducible manufacturing features and produced harder to conventionally manufacture designs, even when told specifically to DfCM. There was also evidence that the complex designs of the DfAM group limited their modeling success and seemed to encourage them to violate more design constraints. This study draws attention to the negative effect of AM knowledge on designers and provides motivation for treatment methods. This is important if AM is used in prototyping or short run production of parts that are slated for conventional manufacturing later. The issue of design fixation is not a problem if AM is the final manufacturing method—a more common practice nowadays. This work suggests that one should consider the possibility of fixation in design environments where AM precedes larger volume conventional manufacturing.

The Role of Additive Manufacturing in the Era of Industry 4.0

The latest industrial revolution, Industry 4.0, is encouraging the integration of intelligent production systems and advanced information technologies. Additive manufacturing (AM) is considered to be an essential ingredient in this new movement. In this paper, a comprehensive review on AM technologies is presented together with both its contributions to Industry 4.0. The review focusses on three important aspects of AM: recent advances on material science, process development, and enhancements on design consideration. The main objective of the paper is to classify the current knowledge (and technological trends) on AM and to highlight its potential uses.

Additive Manufacturing of Biomedical Constructs with Biomimetic Structural Organizations.

Additive manufacturing (AM), sometimes called three-dimensional (3D) printing, has attracted a lot of research interest and is presenting unprecedented opportunities in biomedical fields, because this technology enables the fabrication of biomedical constructs with great freedom and in high precision. An important strategy in AM of biomedical constructs is to mimic the structural organizations of natural biological organisms. This can be done by directly depositing cells and biomaterials, depositing biomaterial structures before seeding cells, or fabricating molds before casting biomaterials and cells. This review organizes the research advances of AM-based biomimetic biomedical constructs into three major directions: 3D constructs that mimic tubular and branched networks of vasculatures; 3D constructs that contains gradient interfaces between different tissues; and 3D constructs that have different cells positioned to create multicellular systems. Other recent advances are also highlighted, regarding the applications of AM for organs-on-chips, AM-based micro/nanostructures, and functional nanomaterials. Under this theme, multiple aspects of AM including imaging/characterization, material selection, design, and printing techniques are discussed. The outlook at the end of this review points out several possible research directions for the future.