Additive Manufacturing Machine Research Articles

Physics-Informed Bayesian learning of electrohydrodynamic polymer jet printing dynamics

Calibration of highly dynamic multi-physics manufacturing processes such as electrohydrodynamics-based additive manufacturing (AM) technologies (E-jet printing) is still performed by labor-intensive trial-and-error practices. Such practices have hindered the broad adoption of these technologies, demanding a new paradigm of self-calibrating E-jet printing machines. Here we develop an end-to-end physics-informed Bayesian learning framework (GPJet) which can learn the jet process dynamics with minimum experimental cost. GPJet consists of three modules: the machine vision module, the physics-based modeling module, and the machine learning (ML) module. GPJet was tested on a virtual E-jet printing machine with in-process jet monitoring capabilities. Our results show that the Machine Vision module can extract high-fidelity jet features in real-time from video data using an automated parallelized computer vision workflow. The Machine Vision module, combined with the Physics-based modeling module, can also act as closed-loop sensory feedback to the Machine Learning module of high- and low-fidelity data. This work extends the application of intelligent AM machines to more complex working conditions while reducing cost and increasing computational efficiency.

Additive manufacturing of silicone composite structures with continuous carbon fiber reinforcement

AbstractAs a relatively new material deployed in additive manufacturing (AM), silicone and its composites have the potential to realize tunable functionality and heterogeneous, architected properties for a number of applications requiring low modulus, elastic materials. Continuous fiber reinforced composites have been developed for AM to achieve various complex structures that are lightweight with high mechanical properties. AM of silicone‐based composites with direct ink writing (DIW) technology has potential application in medical devices, gasket components, flexible soft electronics, and food packaging. However, DIW printed materials have mechanical anisotropy since the extrusion‐based printing process creates small changes in geometry during the material deposition process. In addition, silicone elastomers are relatively low modulus in tension and can be reinforced with woven cloth or fibers. In this work, a continuous fiber AM machine is developed to manufacture silicone composite structures with continuous fiber reinforcing the printed silicone. Tensile tests show that the anisotropic property of the perpendicular printed specimens, relative to the tension direction, has been significantly improved by continuous carbon fiber reinforcements. This continuous fiber silicone reinforcement printing technique can be applied to tune fiber volume ratios and orientations for different silicone composite structures to meet the desired strength and stiffness.

A Literature Review of Additive Manufacturing in the Fabrication of Soft Robots: Main Techniques, Applications, and Related Industrial-Sized Machines

Soft robots have been receiving unprecedented attention in recent years for being able to be used side-by-side with humans, exploring dangerous environments and confined spaces, moving across uneven terrain, and solving problems that rigid robots cannot solve. The wide range of additive manufacturing techniques has also boosted research in the area. This work summarizes the characteristics of the five most relevant techniques – FDM, DIW, SLS, Inkjet, and SLA – for fabricating soft robots together with case studies. A summary contains models of industrial-sized additive manufacturing machines that can compose a facility for fabricating large-scale soft robots.

A Review on Recent Trends and Applications of IoT in Additive Manufacturing

The Internet of Things (IoT) is a new way of communicating that is changing the way things are monitored and controlled from a distance. Gradually, companies want to digitalize their production processes and implement control and monitoring systems on the shop floor. On the basis of the Industry 4.0 concept, internet features and database services have been incorporated into processes in order to reinvent manufacturing. This study proposes a proof-of-concept system for the management of additive manufacturing (AM) machines, where an internet integration of beacon technology in the manufacturing environment enables the rapid and intuitive interchange of production data retrieved from machines with mobile devices in various applications. Even though AM technologies can be used to customize the final product, they cannot be used to make a lot of 3D-printed jobs at once for commercial usage. Therefore, this research-based study aims to understand IoT technologies to improve the understanding and reliability of AM processes and 3D print smart materials in large quantities for manufacturers around the world. This study demonstrates the significance of the successful use of internet-based technologies in AM by examining its practical consequences in various fields. This paper gives an overview of IoT-based remote monitoring and control systems that could solve problems in AM, particularly in digital twin, human augmentation (HA), 3D bioprinters, 3D scanners, input parameters optimization, and electronics fields. IoT in AM makes production processes more efficient, reduces waste, and meets customer needs.

Towards using a multi-material, pellet-fed additive manufacturing platform to fabricate novel imaging phantoms

The design freedom afforded by additive manufacturing (AM) is now being leveraged across multiple applications, including many in the fields of imaging for personalised medicine. This study utilises a pellet-fed, multi-material AM machine as a route to fabricating new imaging phantoms, used for developing and refining algorithms for the detection of subtle soft tissue anomalies. Traditionally comprising homogeneous materials, higher-resolution scanning now allows for heterogeneous, multi-material phantoms. Polylactic acid (PLA), a thermoplastic urethane (TPU) and a thermoplastic elastomer (TPE) were investigated as potential materials. Manufacturing accuracy and precision were assessed relative to the digital design file, whilst the potential to achieve structural heterogeneity was evaluated by quantifying infill density via micro-computed tomography. Hounsfield units (HU) were also captured via a clinical scanner. The PLA builds were consistently too small, by 0.2 − 0.3%. Conversely, TPE parts were consistently larger than the digital file, though by only 0.1%. The TPU components had negligible differences relative to the specified sizes. The accuracy and precision of material infill were inferior, with PLA exhibiting greater and lower densities relative to the digital file, across the 3 builds. Both TPU and TPE produced infills that were too dense. The PLA material produced repeatable HU values, with poorer precision across TPU and TPE. All HU values tended towards, and some exceeded, the reference value for water (0 HU) with increasing infill density. These data have demonstrated that pellet-fed AM can produce accurate and precise structures, with the potential to include multiple materials providing an opportunity for more realistic and advanced phantom designs. In doing so, this will enable clinical scientists to develop more sensitive applications aimed at detecting ever more subtle variations in tissue, confident that their calibration models reflect their intended designs.

Design and Development of Printable Prosthetic Foot using Acrylonitrile Butadiene Styrene (ABS) for Below Knee Amputation (BKA)

Prosthesis is an artificial replacement for a person's missing limb to help regain mobility and the ability to manage daily activities. The type of prosthetic covered in this project is for people with below-knee amputation (BKA). Muscle fatigue is a major issue for amputees who lose a lower limb after prolonged use of artificial limbs. Available designs of prosthetics for BKA are also expensive. This study aims to design and develop an affordable and comfortable prosthetic foot with an energy-story ability for persons with BKA using an additive manufacturing process to help reduce fatigue. Three conceptual designs based were developed for this purpose. Based on the design selection matrix, the best design was chosen and developed in SolidWorks 2013 environment. Stress and strain analyses were simulated to verify the design's ability to withstand the weight of a sample patient with BKA. A sample of patient details, including weight, amputation side and sole (of the foot) length, were obtained and implemented in the prosthetic foot design. Due to its strength and durability, the design was printed on the Veglar V-821 additive manufacturing machine using Acrylonitrile Butadiene Styrene (ABS) material. A pilot test with a male patient with BKA was conducted under the supervision of a prosthetist under two conditions: standing and walking. The prosthetic prototype did not break during the test, and the patient felt comfortable using it. This finding shows that additive manufacturing can produce an affordable and comfortable prototype of a prosthetic foot using ABS. Hence, more BKA patients can benefit from inexpensive prostheses and finally help them achieve a better quality of life.

Examination of steel compatibility with additive manufacturing and repair via laser directed energy deposition

High strength steels are a vital material for aerospace applications but are also prone to damage from fatigue, corrosion, and wear. Additive manufacturing (AM) processes such as laser directed energy deposition (L-DED) offer a means for repairing both the geometry and structure of damaged steels; however, significant variation in tensile properties have been reported following repair. While previous studies have tried to improve performance through postdeposition heat treatment, such practices may not be possible for commercial parts due to risks of distortion and thermal damage to the substrate. Instead, this investigation analyses the role of the intrinsic heat treatment effect on as-deposited tensile properties through a detailed review of both AM and AM repair literature. By assessing a wide variety of high strength steels, the links between conventional heat treatment parameters and steel performance in AM are established, and the role of steel composition understood. This review is supported by additional AM and L-DED repaired samples, with consistent parameters used between steels to ensure similar thermal histories, and eliminate potential discrepancies seen between AM machines. The results demonstrate the effect of intrinsic heat treatment on martensitic and precipitation hardening steels, the role of residual heat and heat extraction through the substrate, and flag potential issues faced by steels at risk of temper embrittlement. Taken together, these findings provide a clear vision for the advancement of AM repair and the optimization of mechanical performance.

Experimental Fatigue Studies of Additively Manufactured Fiber Reinforced Thermoplastic

Additive manufacturing (AM) is a field of study that is gaining importance due to quick manufacturing techniques while providing viable flexibility in design modifications. In comparison with conventional manufacturing methods, AM uses easier processes to manufacture intricate components. AM products maintain consistency as it is constructed by robust universal AM machines. In the present study, a continuous carbon fiber thermoplastics (CFRTP) as a replacement to aluminum alloy (Al6061-T6) material is used for additively manufacturing bicycle crank components. The results from the tensile test and fatigue behavior of the component indicate a strong dependence of percentage concentration of the reinforcement in the CFRTP. A finite element analysis is performed to ascertain the stress distribution for a static load condition as mimicked in the real world situations. To explore the brittle fracture nature of the CFRTP specimen, a SEM image depicting the microstructural nature is provided. It is imperative to note that the comparative studies indicate the light weight CFRTP crank specimen stands out to be a viable replacement to the Al 6061-T6 material.

Workplace Exposure Measurements of Emission from Industrial 3D Printing.

Particle and gaseous contaminants from industrial scale additive manufacturing (AM) machines were studied in three different work environments. Workplaces utilized powder bed fusion, material extrusion, and binder jetting techniques with metal and polymer powders, polymer filaments, and gypsum powder, respectively. The AM processes were studied from operator's point of view to identify exposure events and possible safety risks. Total number of particle concentrations were measured in the range of 10 nm to 300 nm from operator's breathing zone using portable devices and in the range of 2.5 nm to 10 µm from close vicinity of the AM machines using stationary measurement devices. Gas-phase compounds were measured with photoionization, electrochemical sensors, and an active air sampling method which were eventually followed by laboratory analyses. The duration of the measurements varied from 3 to 5 days during which the manufacturing processes were practically continuous. We identified several work phases in which an operator can potentially be exposed by inhalation (pulmonary exposure) to airborne emissions. A skin exposure was also identified as a potential risk factor based on the observations made on work tasks related to the AM process. The results confirmed that nanosized particles were present in the breathing air of the workspace when the ventilation of the AM machine was inadequate. Metal powders were not measured from the workstation air thanks to the closed system and suitable risk control procedures. Still, handling of metal powders and AM materials that can act as skin irritants such as epoxy resins were found to pose a potential risk for workers. This emphasizes the importance of appropriate control measures for ventilation and material handling that should be addressed in AM operations and environment.

Selection of Additive Manufacturing Machines via Ontology-Supported Multi-Attribute Three-Way Decisions

Selection of a suitable additive manufacturing (AM) machine to manufacture a specific product is one of the important tasks in design for AM. So far, many selection approaches based on multi-attribute decision making have been proposed within academia. Each of these approaches works well in its specific context. However, the approaches are not flexible enough and could produce undesirable results as they are all based on multi-attribute two-way decisions. In this paper, a selection approach based on ontology-supported multi-attribute three-way decisions is presented. Firstly, an ontology for AM machine selection is constructed according to vendor documents, benchmark data, expert experience, and the Senvol database. Supported by this ontology, a selection approach based on multi-attribute three-way decisions is then developed. After that, four AM machine selection examples are introduced to illustrate the application of the developed approach. Finally, the effectiveness and advantages of the approach are demonstrated via a set of comparison experiments. The demonstration results suggest that the presented approach is as effective as the existing approaches and more flexible than them when the information for decision making is insufficient or the cost for undesirable decision results is high.

Fluid Flow-inspired Curvature-aware Print-paths from Hexahedral Meshes for Additive Manufacturing

Thanks to recent improvements, computational methods are able to produce high-quality hexahedral meshes, whose hexahedrons are arranged along the principal curvature directions of the input surfaces. Curvature-aware print-paths following these curvature directions have been recently proposed by Gunpinar and enable reduction in stair-stepping effect in the printed parts. However, crosswise contacts can exist between the print-paths (i.e., print-paths are quasi-perpendicular to each other), which is undesirable as failures may occur particularly at those contact regions. Therefore, the present work aims at generation of curvature-aware print-paths without crosswise contacts between them. To solve this problem, we inspire from fluid flow and imitate (laminar) streamlines for an inlet and an outlet of a duct for designing print-paths. A hexahedral mesh is decomposed into blocks (cuboid-like sub-volumes), each of which is covered with fluid flow-inspired print-paths. A multi-axis (collision-free) additive manufacturing (AM) planning technique is also proposed. As a proof of concept, fluid flow-inspired curvature-aware print-paths are validated using a multi-axis AM simulator and machine.

Unpacking Additive Manufacturing Challenges and Opportunities in Moving towards Sustainability: An Exploratory Study

The global market for Additive Manufacturing (AM) is expected to grow, which may increase the prominence of sustainability aspects in the manufacturing process. A growing number of AM academics and practitioners have started to pay attention to the environmental and societal impacts of AM instead of only focusing on its economic aspect. Yet, AM is still not widely adopted, and the research on AM sustainability is still at the nascent stage. This paper aims to better understand AM’s sustainable adoption and seeks to address three questions: what the sustainability implications of AM are; what challenges may prevent the broad adoption of AM; and what opportunities can enable AM sustainability. The research adopts a multiple case study method to investigate six AM companies that play different roles in the AM ecosystem, including AM design, AM machine, AM material, AM service, AM education, and AM consulting. The results from these studies reveal that AM has the potential to reduce environmental and social impacts; however, it might also cause negative consequences and lead to some rebound effects. We identified 43 categories (synthesized from 199 examples) of key challenges for AM adoption and proposed 55 key solutions in moving AM towards sustainability. It is evident that AM acts as a promising digital technology for manufacturing and has the potential to pave the way for a new era of sustainable manufacturing.

Conformal 3D Material Extrusion Additive Manufacturing for Large Moulds

Industrial engineering applications often require manufacturing large components in composite materials to obtain light structures; however, moulds are expensive, especially when manufacturing a limited batch of parts. On the one hand, when traditional approaches are carried out, moulds are milled from large slabs or laminated with composite materials on a model of the part to produce. In this case, the realisation of a mould leads to adding time-consuming operations to the manufacturing process. On the other hand, if a fully additively manufactured approach is chosen, the manufacturing time increases exponentially and does not match the market’s requirements. This research proposes a methodology to improve the production efficiency of large moulds using a hybrid technology by combining additive manufacturing and milling tools. A block of soft material such as foam is milled, and then the printing head of an additive manufacturing machine deposits several layers of plastic material or modelling clay using conformal three-dimensional paths. Finally, the mill can polish the surface, thus obtaining a mould of large dimensions quickly, with reduced cost and without needing trained personnel and handcraft polishing. A software tool has been developed to modify the G-code read by an additive manufacturing machine to obtain material deposition over the soft mould. The authors forced conventional machining instructions to match those of an AM machine. Thus, additive deposition of new material uses 3D conformal trajectories typical of CNC machines. Consequently, communication between two very different instruments using the same language is possible. At first, the code was tested on a modified Fused Filament Fabrication machine whose firmware has been adapted to manage a milling tool and a printing head. Then, the software was tested on a large machine suitable for producing moulds for the large parts typical of marine and aerospace engineering. The research demonstrates that AM technologies can integrate conventional machinery to support the composite materials industry when large parts are required.

Additive Manufacturing of a High Temperature, Ni-Based Superalloy Compact Heat Exchanger: A Study on the Role of Select Key Printing Parameters

Abstract Compared to state-of-the-art heat exchangers, manifold-microchannel heat exchangers have shown superior heat removal density (kW/kg) at moderate pressure drops. However, manifold-microchannel heat exchangers made of Ni-based superalloys or other tough-to-machine materials can be a challenge to fabricate using conventional fabrication methods. This is mainly because of the inherently complex manifold microchannel geometry, as well as the required small feature sizes (e.g., fin thickness) that should be comparable, or smaller than state-of-the-art high-performance metallic-based heat exchangers (∼150 μm or smaller). In this study, a direct metal laser sintering (DMLS) additive manufacturing technique was used to fabricate the compact high-temperature manifold-microchannel heat exchanger reported here. The additively manufactured manifold-microchannel heat exchanger was fabricated as a single object, which significantly simplifies the fabrication process. In this work, three different additive manufacturing machines were used to study the effect of laser power, powder size, and layer thickness on the fin and channel sizes of the fabricated microchannel heat exchangers. To evaluate the minimum wall thickness for holding the required design pressures, pressure containment tests were performed. As a result, a wall thickness of 0.3 mm was shown to withstand 340 kPa and be leakage-free. A detailed analysis of different printing orientations and their effect on the manifold-microchannel heat exchanger's design was also performed. Finally, a 76 × 76 × 76 mm3 manifold microchannel heat exchanger was successfully fabricated with a fin thickness of 0.13 mm out of maraging steel. A second unit with dimensions of 94 × 87.6 × 94.4 mm3 was successfully fabricated with a fin thickness of 0.22 mm out of Inconel 718. Details of the fabrication process and key take-away results are discussed in this paper.

Additive Manufacturing Service Provider Selection Using a Neutrosophic Best Worst Method

Additive manufacturing (AM) is poised to disrupt the manufacturing industry due to its distinctive (layer-by-layer) approach to part production, as AM comprises a range of fabrication techniques that facilitate the production of customized and highly complex parts. For a particular part selecting the most suitable AM machine and material is an indispensable decision due to several AM machines, their process and material constraints like size, accuracy, mechanical properties etc. This paper demonstrates the multi-criteria framework using Delphi and neutrosophic best-worst method to determine the best suitable AM machine and feasible material from the spool of databases. The Delphi method is employed to determine and validate essential criteria for a selected part, which results in shortlisting the 9 most relevant criteria. Further, the neutrosophic best-worst method is utilized to compute the criteria weights. A rating and normalization approach is deployed to calculate each AM machine and compatible material aggregate score to determine the optimal AM machine, material and ultimately, the AM service provider.

Implementing digital twinning in an additive manufacturing process chain

Additive manufacturing (AM) is defined as the process of joining materials layer by layer to produce a part. The Centre for Rapid Prototyping and Manufacturing (CRPM) of the Central University of Technology, Free State has successfully established an AM process chain to produce qualified medical implants. The process chain complies with the international standards ISO 13485:2016 and ISO 14971:2012, which certify the repeatability and reliability of processes. Despite the significant achievements CRPM has obtained in medical applications, efficiency in some areas can be improved through digital twinning approaches. The digital twin has comprehensive capabilities and allows real-time monitoring that can be used to improve different phases of AM processes. In this study, areas that need further improvement in the process chain, such as management information that flows between different users and processes for design and setting up AM machines, will be discussed. The study will further indicate how these areas can benefit from available advanced technologies such as augmented reality (AR) technology and digital twin data management. Further implementation of this approach is expected to confirm the potential of easy self-learning approaches and managing data more effectively for improving the AM process chain.

Increasing the industrial uptake of additive manufacturing processes: A training framework

Additive Manufacturing (AM) is one of the key technologies of Industry 4.0, offering unique advantages and capabilities. The interest in AM has been steadily increasing, leading to its rapid recent growth and improvement in all its aspects. However, its wider adoption is hindered by various barriers, the most important of which are the relatively high initial investment cost, part quality issues, limited material choices, and lack of expertise. The research community, AM machine developers, and larger enterprises are continuously contributing to the improvement of the first three factors. Nonetheless, the same cannot be stated for the barrier of limited expertise, leading the industrial sector to a perpetual lack of knowledge and, therefore, reluctance for a potential AM uptake. This study is addressing the need of the industrial sector for structured and organized expertise training for the fruitful exploitation of AM, paving the road for its wider application. The guidelines for an industrial-oriented AM training curriculum are set through the development of an AM training framework. The different AM thematic areas are classified into educational modules, which are separately analyzed, considering the participants’ active role and hands-on practice. The proposed step-by-step approach builds up from introductory to more advanced concepts, ensuring flexibility and simultaneously encompassing the needs of all industrial stakeholders (engineers, designers, managers, operators). Additionally, strategies corroborating the accessibility of the proposed framework are discussed, as well as dissemination policies and tools to facilitate its industrial endorsement.

Experimental Data Collection of Surface Quality Analysis of CuCrZr Specimens Manufactured with SLM Technology: Analysis of the Effects of Process Parameters

Selective laser melting (SLM) is the most widely used laser powder-bed fusion (L-PBF) technology for the additive manufacturing (AM) of parts from metallic powders. The surface quality of the SLM parts is highly dependent on many factors and process parameters. These factors include the powder grain size, the layer thickness, and the building angle. This paper conducted an experimental analysis of the effects of SLM process parameters on the surface quality of CuCrZr cubic specimens. Thanks to its excellent thermal and mechanical properties, CrCrZr has become one of the most widely used materials in SLM technology. The specimens have been produced with different combinations of layer thickness, laser patterns, building angles, and scanning speed, keeping the energy density constant. The results show how different combinations of parameters affect the surface quality macroscopically (i.e., layer thickness, building angle, and scanning speed); in contrast, other parameters (i.e., laser pattern) do not seem to have any contributions. By varying these parameters within typical ranges of the AM machine used, variations in surface quality can be achieved from 10.4 µm up to 40.8 µm. These results represent an important basis for developing research activities that will further focus on implementing a mathematical/experimental model to help designers optimize the surface quality during the AM pre-processing phase.

A branch-and-price algorithm to perform single-machine scheduling for additive manufacturing

Additive manufacturing (AM) has attracted significant attention in recent years based on its wide range of applications and growing demand. AM offers the advantages of production flexibility and design freedom. In this study, we considered a practical variant of the batch-processing-machine (BPM) scheduling problem that arises in AM industries, where an AM machine can process multiple parts simultaneously, as long as the two-dimensional rectangular packing constraint is not violated. Based on the set-partitioning formulation of our mixed-integer programming (MIP) model, a branch-and-price (B&P) algorithm was developed by embedding a column-generation technique into a branch-and-bound framework. Additionally, a novel labelling algorithm was developed to accelerate the column-generation process. Ours is the first study to provide a B&P algorithm to solve the BPM scheduling problem in the AM industry. We tested the performance of our algorithm using a modern MIP solver (Gurobi) and real data from a 3D printing factory. The results demonstrate that for most instances tested, our algorithm produces results similar or identical to those of Gurobi with reasonable computation time and outperforms Gurobi in terms of solution quality and running time on some large instances.

Extrusion Additive Manufacturing of PEI Pellets

The simplest, most cost-efficient, and most widespread Additive Manufacturing (AM) technology is Extrusion Additive Manufacturing (EAM). Usually, EAM is performed with filament feedstock, but using pellets instead of filaments yields many benefits, including significantly lower cost and a wider choice of materials. High-performance polymers offer high strength even when produced with AM technique, allowing to produce near-net-shape functional parts. The production of these materials in filament form is still limited and expensive; therefore, in this paper, the possibility of producing AM components with engineering polymers from pellets will be thoroughly investigated. In this work, the effectiveness of a specially designed AM machine for printing high-performance materials in pellet form was tested. The material chosen for the investigation is PEI 1000 which offers outstanding mechanical and thermal properties, giving the possibility to produce with EAM functional components. Sensitivity analyses have been carried out to define a process window in terms of thermal process parameters by observing different response variables. Using the process parameters in the specified range, the additive manufactured material has been mechanically tested, and its microstructure has been investigated, both in dried and undried conditions. Finally, a rapid tool for sheet metal forming has been produced.