Hybrid Additive Manufacturing Technologies – An Analysis Regarding Potentials and Applications

Additive manufacturing (AM) has recently been accorded considerable interest by manufacturers. Many manufacturing industries, amongst others in the aerospace sector, are already using AM parts or are investing in such manufacturing methods. Important material properties, such as microstructures, residual stress, and surface topography, can be affected by AM processes. In addition, a subtractive manufacturing (SM) process, such as machining, is required for finishing certain parts when accurate tolerances are required. This finish machining will subsequently affect the surface integrity and topography of the material. In this research work, we focused on the surface integrity of Ti-6Al-4V parts manufactured using three different types of AM and finished using an SM step. The aim of this study was to gain an understanding on how each process affects the resulting surface integrity of the material. It was found that each AM process affects the materials’ properties differently and that clear differences exist compared to a reference material manufactured using conventional methods. The newly generated surface was investigated after the SM step and each combination of AM/SM resulted in differences in surface integrity. It was found that different AM processes result in different microstructures which in turn affect surface integrity after the SM process.

Comparative study on life cycle assessment of components produced by additive and conventional manufacturing process

PurposeMaterial extrusion (MEX) is a class of additive manufacturing (AM) process based on MEX principle. In the viewpoint of Industry 4.0 and sustainable manufacturing, AM technologies are gaining importance than conventional manufacturing route (subtractive manufacturing). Because of the ease of use and lesser operation skills, MEX had wide popularity in industry for product and prototype development. This study aims to analyze energy consumption of MEX-based AM process and its influencing factors.Design/methodology/approachA group of factors were identified pertaining to MEX-based AM process. In this viewpoint, this study presents the configuration of a structural model using interpretive structural modeling (ISM) to depict dominant factors in MEX-based AM process. A total of 18 influencing factors are identified and ranked using ISM methodology for MEX process. The Impact Matrix Cross-reference Multiplication Applied to a Classification analysis was done to categorize influencing factors into four groups for MEX-based AM process.FindingsThe derivation of structural model would enable AM practitioners to systematically analyze the factors and to derive key factors which enable comprehensive energy modeling and energy assessment studies. Also, it facilitates the development of energy efficient AM system.Originality/valueThe development of structural model for analysis of factors influencing energy consumption of MEX-based AM is the original contribution of the authors.

Additive manufacturing (AM) has gained notoriety for offering advantages over traditional manufacturing methods, such as increased design complexity and flexibility. However, it has not found widespread use beyond rapid prototyping. One hindrance to the acceptance of AM processes in industry is the time and cost of fabrication per component. While metal AM by itself can be inexpensive, extra manufacturing steps in the form of subtractive manufacturing (SM) may need to be performed to reach final part tolerances, leading to hybrid additive-subtractive manufacturing (HASM) of a part, which increases time and cost. A potential area to reduce cost is through increasing the efficiency of the HASM process by conducting additive and subtractive manufacturing simultaneously. Usually, HASM is performed in a process where AM is completed in one machine or cell and transferred to another machine or cell for SM in a sequential assembly line process. This efficiency decreases part cost, but high aspect ratio parts or parts with internal geometry that require interleaved additive deposition and machining cannot be produced. One unexplored solution to simultaneous HASM that allows for interleaved operations is to operate the deposition head and machining spindle concurrently within the same machine envelope, known as concurrent HASM (CHASM). In this type of process, both AM and SM occur simultaneously on a batch of small parts or a single large part, maintaining a high efficiency without sacrificing the full range of complex geometries that AM allows for. A potential approach to the single-machine method could be to combine a robot and mill within the same envelope. A challenge to this approach, however, is control of both systems. Most machine controllers have limited external communication or, if a robot has been integrated, only offer movement of either the robot or mill at any given time. As a result, systems must pause either the AM or SM process to switch between them rather than working simultaneously. The present work investigates the positional accuracy of such a CHASM system comprised of a robotic arm and a 3-axis mill. Open-loop tests with limited communication between machines are performed on the system to verify positional error during concurrent robot-mill movements. Under certain conditions, it is demonstrated that position error can stay within 2 mm for the duration of a single layer; however, these tests show that, generally, the open-loop positioning performance of the system is inadequate for CHASM without part-specific hand-tuning of parameters. Based on these results, a set of requirements for successful robot-CNC CHASM is proposed for future integrations.

This study was aimed at preparing zirconia samples via additive manufacturing (AM) and subtractive manufacturing (SM) and testing the following aspects: (1) the manufacturing accuracy of the zirconia samples and (2) the bond strength of porcelain to zirconia to evaluate the applicability of the zirconia fabricated by AM in dental clinics. We used three milling machines for SM (AR, K5, and UP) and a 3D printer for AM (AO). The manufacturing accuracy of the zirconia specimen in the internal and marginal areas was evaluated by superimposing techniques to calculate the root mean square (RMS) values. The bond strengths of porcelain to zirconia prepared via SM and AM were measured using a universal testing machine. The internal and marginal RMS values of the zirconia prepared by AM (AO) were within the range of those of the zirconia prepared by SM (AR, K5, and UP). Moreover, the bond strength value of the zirconia prepared by AM (35.12 ± 4.09 MPa) was significantly higher than that of the zirconia prepared by SM (30.26 ± 5.20 MPa). Therefore, AM technology has significant potential for applications in dentistry.

The additive manufacture (AM) of plastic components can be accomplished by a variety of methods which are classified according to how material layers are consolidated layer-by-layer to create physical objects from digital data. Two of the most widely used methods include Material Extrusion (MEX) and Vat Photopolymerization (VP). These methods include a range of commercialized AM processes often referred to by various trademarked terms such as Fused Deposition Modelling (FDM) and Stereolithography (SLA). Compared to conventional subtractive or formative manufacturing process, MEX and VP are able to manufacture complex parts with high ability for customization, as they impose few constraints on part geometry, and require low setup effort with no custom tooling. Furthermore, MEX and VP are both well-established additive manufacturing processes and through ongoing refinement have achieved compatibility with a broad range of materials and part geometries, and comparatively low operating costs. Due to their high versatility, MEX and VP have been widely used in a broad range of industries including applications in chemical sciences, biotechnology, aerospace, defense, and automotive engineering. However, despite their high versatility, AM processes such as MEX and VP are subject to unique technological characteristics associated with the manufacturing process, the material properties, part design and suitable application areas. This chapter provides an overview of MEX and VP processes characteristics critical to the effective application of these additive manufacturing technologies to high performance products.KeywordsAdditive manufacturingDesign for additive manufactureMaterial extrusionPhotopolymerizationPolymersThermoplasticsVat photopolymerization

Additive manufacturing (AM) is a cutting-edge technology that provides up to 100% of material efficiency and significant weight reduction which will positively impact aircraft fuel consumption in addition to high design freedom. Consequently, many aerospace companies are considering implementing AM thanks to these benefits. Therefore, the aim of this research is to assist aerospace organisations with a selection among different AM technologies. To enable this, primary data from (8) experts in the field of AM was collected through semi-structured interviews and cross-referenced with secondary data to identify the key factors for consideration in the selection of AM equipment for aerospace applications. Four AM technologies laser powder bed fusion (LPBF), electron beam powder bed fusion (EBPBF), wire arc AM (WAAM) and laser metal deposition (LMD) were highlighted by the experts as the most appropriate for aerospace applications. The main outcome of this study is the development of a comparison framework that helps companies select their AM technology depending on their main business or specific application.

Purpose Because of the significant differences in the features and requirements of specific products and the capabilities of various additive manufacturing (AM) solutions, selecting the most appropriate AM technology can be challenging. This study aims to propose a method to solve the complex process selection in 3D printing applications, especially by creating a new multicriteria decision-making tool that takes the direct certainty of each comparison to reflect the decision-maker’s desire effectively. Design/methodology/approach The methodology proposed includes five steps: defining the AM technology selection decision criteria and constraints, extracting available AM parameters from the database, evaluating the selected AM technology parameters based on the proposed decision-making methodology, improving the accuracy of the decision by adopting newly proposed weighting scheme and selecting optimal AM technologies by integrating information gathered from the whole decision-making process. Findings To demonstrate the feasibility and reliability of the proposed methodology, this case study describes a detailed industrial application in rapid investment casting that applies the weightings to a tailored AM technologies and materials database to determine the most suitable AM process. The results showed that the proposed methodology could solve complicated AM process selection problems at both the design and manufacturing stages. Originality/value This research proposes a unique multicriteria decision-making solution, which employs an exclusive weightings calculation algorithm that converts the decision-maker's subjective priority of the involved criteria into comparable values. The proposed framework can reduce decision-maker's comparison duty and potentially reduce errors in the pairwise comparisons used in other decision-making methodologies.

The cyclic manufacturing processes of Additive Manufacturing (AM) create three-dimensional objects layer by layer, offer a large freedom in design, and suffer from very different restrictions compared to conventional manufacturing processes. Nowadays, AM is a mature manufacturing technology capable of being applied in industrial series production. However, the AM technology enters the industrial series production only slowly. A main reason is the fact that engineers in industry have little to no experience in Design for Additive Manufacturing (DfAM) and an integrated experience transfer in engineering education is not yet widespread. To implement the AM technology, a course for graduate students was developed and established, mainly in the master studies and in the field of mechanical engineering. The goal of the course is that the students gain experience in the possibilities and the restrictions of DfAM. The course is based on the Experience Transfer Model (ETM) and is divided in two parts, a lecture and a team project. In the lecture, the students gain explicit knowledge for DfAM. In the practical team project, the students develop and produce AM prototypes based on a variety of AM processes and gain implicit knowledge. The concept of the team project is based on Problem-Based Learning (PBL). The whole team project follows a product development process, including presentations of milestone. The physical outcomes showed that the students are able to design AM optimized parts without falling back into old design patterns. In a survey at the end of the lecture series, the students gave the authors feedback. The large majority of the feedback was positive.

Manufacturing industries across the globe are now adopting additive manufacturing (AM) practices over the traditional manufacturing process due to less waste generation and other economic and emissions benefits. Additive manufacturing can also be considered a key enabling technology for the high technology plan. However, the practices related to additive manufacturing in developing and developed economies are limited due to knowledge and technological advancements. Environmental impact assessment is an emerging research area highlighted in the last few years. At this point, research and industry attention is focused on determining where AM can replace or create new manufacturing systems. This study compares the environmental impact assessment of traditional and additive manufacturing processes by considering a case of pattern making. This paper also investigates how additive manufacturing technologies contribute to creating a sustainable environment in the manufacturing industry. A real-time case study is performed in SMEs of India, showing that additive manufacturing processes help lower the environmental impacts. The present study also highlighted the opportunities for additive manufacturing in sustainability. The gate-to-gate analysis is performed, and impact assessment is done by GABI software version 9 on Windows 10 operating system. In this report, a case study has been done to compare the traditional IC and AM processes using Aluminum alloy (Al-Si-Cu) in terms of environmental Sustainability. Results show that 28.77% reduction in GWP, 74.04% reduction in emission to Air, 36.30% reduction in AP and 45.62% reduction in HTP by using AM process. Overall, AM process is an environmentally sustainable process. This study would help researchers and the manufacturing industry determine the emissions associated with pattern making using the conventional IC process under Indian climatic conditions. It assists manufacturing industries in choosing the best available IC alternative regarding reduced environmental emissions.

Additive manufacturing (AM) processes fabricate parts by adding material in a layer-by-layer fashion. In order to enable closed-loop process control—a major hurdle in the adoption of most AM processes—compact models suitable for control design and for describing the layer-by-layer material addition process are needed. This paper proposes a two-dimensional modeling framework whereby the deposition of the current layer is affected by both in-layer and layer-to-layer dynamics, both of which are driven by the state of the previous layer. The proposed framework can be used to describe phenomena observed in AM processes such as layer rippling and large defects in laser metal deposition (LMD) processes. Further, the proposed framework can be used to create two-dimensional dynamic models for the analysis of layer-to-layer stability and as a foundation for the design of layer-to-layer controllers for AM processes. In the application to LMD, a two-dimensional linear–nonlinear–linear (LNL) repetitive process model is proposed that contains a linear dynamic component, which describes the dynamic evolution of the process from layer to layer, cascaded with a static nonlinear component cascaded with another linear dynamic component, which describes the dynamic evolution of the process within a given layer. A methodology, which leverages the two-dimensional LNL structure, for identifying the model process parameters is presented and validated with quantitative and qualitative experimental results.

Sinter-based metal additive manufacturing (AM) processes that decouple the geometric shaping and consolidation of AM have several advantages over melt-based AM technologies (one-step consolidation and shaping). The sinter-based AM technologies, led by binder jetting, has the potential to significantly increase the productivity and attain more isotropic microstructures in the final product. Sinter-based AM includes the ability to cover a wide spectrum of productivity, including prototyping, low volume serial production, and high-volume mass production. Recently, several non-traditional sinter-based metal AM processes (relatively less common) have emerged. This paper will review some of these emerging and lesser-known sinter-based metal AM technologies along with a few processes based on modifications of binder jet and material extrusion techniques that have gained traction.

The design methodologies and part shape algorithms for additive manufacturing (AM) are rapidly growing fields, proven to be of critical importance for the uptake of additive manufacturing of parts with enhanced performance in all major industrial sectors. The current trend for part design is a computationally driven approach where the parts are algorithmically morphed to meet the functional requirements with optimized performance in terms of material distribution. However, the manufacturability restrictions of AM processes are not considered at the primary design phases but at a later post-morphed stage of the part’s design. This paper proposes an AM design method to ensure: (1) optimized material distribution based on the load case and (2) the part’s manufacturability. The buildability restrictions from the direct energy deposition (DED) AM technology were used as input to the AM shaping algorithm to grant high AM manufacturability. The first step of this work was to define the term of AM manufacturability, its effect on AM production, and to propose a framework to estimate the quantified value of AM manufacturability for the given part design. Moreover, an AM design method is proposed, based on the developed internal stresses of the build volume for the load case. Stress tensors are used for the determination of the build orientation and as input for the part morphing. A top-down mesoscale geometric optimization is used to realize the AM part design. The DED Design for Additive Manufacturing (DfAM) rules are used to delimitate the morphing of the part, representing at the same time the freeform mindset of the AM technology. The morphed shape of the part is optimized in terms of topology and AM manufacturability. The topology optimization and AM manufacturability indicator (TMI) is introduced to screen the percentage of design elements that serve topology optimization and the ones that serve AM manufacturability. In the end, a case study for proof of concept is realized.

Advancements in understanding the microstructure and properties of additive manufacturing Ti-6Al-4V alloy: A comprehensive review

Chapter 6 - Polymer and composites additive manufacturing: material extrusion processes