Additive manufacturing of zinc-based biomaterials: Fabrication, performance and property evaluation

There is nowadays a lack of knowledge and structured approaches concerning the transition of additive manufacturing systems from rapid prototyping to large scale production. The fundamental advantage of additive manufacturing to produce at virtually no additional cost complex, one-of-a-kind parts suggest addressing their integration in the direction of arranging them into the consolidated Flexible Manufacturing Systems (FMS) paradigm. In this regard, this paper presents a procedure for the simulation-based analysis of FMS hosting additive manufacturing stations, supporting their planning, design as well as performance evaluation. A discrete-event simulation model was developed and applied for the operational evaluation of an industrial case comprising 3D-printing, automated transport, and storage systems. It has been found that simulation experiments can support planning and design decision-making, allowing for a better choice among alternative set-ups. However, the present research explored an application carried out in an academic environment where the simulation model was employed for evaluating the behaviour of new additive manufacturing technologies.

Additive manufacturing of Zn-Mg alloy porous scaffolds with enhanced osseointegration: In vitro and in vivo studies

The use of additive manufacturing for rapid prototyping of near-infrared and terahertz components provides seamless and error-free production. This article discusses the additive manufacturing and post-processing of axicons and their performance evaluation using attenuation and near-field-measurements based fundamental techniques. The axicons are manufactured using the materials cyclic olefin copolymer (TOPAS) and polymethyl methacrylate (PMMA), for their respective use in terahertz and near-infrared applications. The optical and terahertz components manufactured using traditional 3D-printing processes, e.g., fused filament fabrication or stereolithography apparatus exhibit high surface roughness in the range of 15 ± 2.5 µm, resulting in undesired propagation and scattering in the near infrared wavelengths. This research work proposes an economical post-processing technique for additively manufactured terahertz and near-infrared axicons for applications in multispectral characterization, e.g., bio-sensing. The authors used an enhanced method of dip-coating, which involves interval dipping and intermittent hardening to achieve better surface finish. An emphasis is placed on interval dipping and intermittent hardening, which lead to excellent transparency in case of additively-manufactured near-infrared axicons. The dip-coated samples exhibit surface roughness below 10 nm. With the use of heated resin material as the coating layer, due to reduced viscosity, the resin material distributes uniformly over the surface of the 3D-printed terahertz and near-infrared axicons. The authors also observed that the DOF length deviation between unprocessed and enhanced dip-coated axicons remains within the measurement error estimation from analytical calculations. In addition to the improved surface finish and transparency, the coatings are also closely matched in refractive index to the axicon material. Such post-processed axicons pave the way for producing a wide array of systems in the fields of communication, imaging, and bio-sensing.

Many test artefact designs have been proposed for use with additive manufacturing (AM) systems. These test artefacts have primarily been designed for the evaluation of AM form and dimensional performance. A series of surface-specific measurement test artefacts designed for use in the verification of AM manufacturing processes are proposed here. Surface-specific test artefacts can be made more compact because they do not require the large dimensions needed for accurate dimensional and form measurements. The series of three test artefacts are designed to provide comprehensive information pertaining to the manufactured surface. Measurement possibilities include deviation analysis, surface texture parameter data generation, sub-surface analysis, layer step analysis and build resolution comparison. The test artefacts are designed to provide easy access for measurement using conventional surface measurement techniques, for example, focus variation microscopy, stylus profilometry, confocal microscopy and scanning electron microscopy. Additionally, the test artefacts may be simply visually inspected as a comparative tool, giving a fast indication of process variation between builds. The three test artefacts are small enough to be included in every build and include built-in manufacturing traceability information, making them a convenient physical record of the build.

The presence of process‐induced internal defects (i.e., pores, microcracks, and lack‐of‐fusions) significantly deteriorates the structural durability of parts fabricated by additive manufacturing. However, traditional defects characterization techniques, such as X‐ray CT and ultrasonic scanning, are costly and time‐consuming. There is a research gap in the nondestructive evaluation of fatigue performance directly from the process signature of laser‐based additive manufacturing processes. Herein, a novel two‐phase modeling methodology is proposed for fatigue life prediction based on in situ monitoring of thermal history. Phase (I) includes a convolutional neural network designed to detect the relative size of the defects (i.e., small gas pores and large lack‐of‐fusions) by leveraging processed thermal images. Subsequently, a fatigue‐life prediction model is trained in Phase (II) by incorporating the defect characteristics extracted from Phase (I) to evaluate the fatigue performance. Estimating defect characteristics from the in situ thermal history facilitates the fatigue predicting process.

Evaluation of defect-related fatigue performance of additive manufacturing GH4169 via small punch test

Test artifacts, resembling real machine parts, allow for quantitative evaluation of system performance and provide insight into individual errors, aiding in improvement and standardization of additive manufacturing. The article provides a comprehensive overview of existing test artifacts, categorized based on geometric features and the material used. Various measurement techniques such as stylus profilometry and computed tomography are employed to assess these artifacts. It is also shown that the selective laser melting (SLM) technology and titanium alloys are prevalent in artifact creation. Specific artifact categories include slits, angular aspects, length parameters, variable surfaces, and others, each accompanied by examples from research literature, highlighting diverse artifact designs and their intended applications. The paper critically discusses the main problems with existing geometries. It underscores the importance of user-friendly and unambiguous artifacts for dimensional control, particularly in surface metrology. Furthermore, it anticipates the continued growth of metrological verification in future manufacturing environments, emphasizing the need for precise and reliable measurement results to support decision-making under production conditions.

Evaluation of evaporative heat transfer performance based on observation of Thermo-Fluid behavior in porous structures fabricated by additive manufacturing

Abstract. Additive Manufacturing can offer different solutions in terms of bespoke implants and deformable structures tailorable by the geometry design. The prototyping phase consists in a preliminary evaluation of the mechanical performances to find a relation with the geometrical parameters. For these reasons, numerical tools that can relate directly the geometrical features, especially for lattice or cellular structures, to the mechanical properties, are often studied to speed up the design and production process. In this study, the predictability of the deformation of a structure composed by honeycomb unit cells was studied performing compression simulations. Successively, the structure was 3D printed using fused filament fabrication and tested using a positioning stage, the relative displacements of 36 specific points of the structure were extracted using contactless measurement techniques and compared with the simulations. The results demonstrated a good predictability of the model in relation to the deformation of the structure with a stable relationship between the geometry selected and the final mechanical properties.

The building energy balance is strongly influenced by the heat transmission losses through the envelope. This justifies the growing effort to search for innovative and high-performance insulating materials. The 3D printing process, also known as additive manufacturing, is already used in various industrial applications thanks to its ability to realize complex structures with high accuracy. It also represents an emerging and still poorly explored field in the world of “building physics”. The aim of this work is to present the design, realization, and analysis phases of a 3D-printed thermal insulating block. The performance analysis of the block was performed via theoretical and experimental approaches. The testing phase was conducted using a Hot Box specially built for this purpose, which allowed to have known, repeatable, and steady thermal conditions. The experimental phase, based on the infrared thermography technique and heat flow meter method, allowed a preliminary evaluation of the 3D-printed block performance. Moreover, to implement the concept of circular economy, the internal cavities of the block were filled with different recovered waste materials: polystyrene and wool. The results obtained have shown, although preliminarily, the potential of additive manufacturing in the field of insulating materials.

In recent years, additive manufacturing (AM) has undergone a rapid growth, therefore several processes based on different working principles (e.g. photopolymerization, sintering, extrusion, material jetting, etc) are now available and allow to manufacture parts using a wide range of materials. Consequently, the so-called benchmark artifacts are necessary to assess the capabilities and limitations of each AM process or to compare the performance of different processes. This paper focuses on the benchmark artifacts for evaluating the geometrical performance of AM processes and proposes an extensive review of the available literature, analyzing the design of such test parts in detail. The investigated test parts are classified according to the process aspect that they are able to evaluate (dimensional/geometrical accuracy, repeatability, minimum feature size) and the combination AM process/materials for which they have been used. In addition, the paper draws a summary of guidelines to design benchmark artifacts for geometrical performance evaluation.

Metal additive manufacturing (AM) is a kind of disruptive manufacturing technology that considers the needs of complex geometry fabrication and high-performance part fabrication. Hence, it has broad applications and extensive development space in aviation, aerospace, transportation, nuclear power, to name a few. However, its large-scale applications suffer from the challenge, including improving manufacturing efficiency and achieving the geometry and mechanical property as desired, which is a cross-cutting problem involving multi-discipline such as mechanics, optics, material science, mechanical engineering, control science. In the viewpoint of mechanics associated with the challenge, this paper critically reviews the recent research progress of AM-oriented structure topology optimization design, numerical simulation of the metal AM process, as-built defects characterization, and mechanical performance evaluation of the fabricated metal materials and components, which are referred to as structure design-process modelling-performance evaluation for metal AM. Finally, research topics that are required to address the fundamental mechanical problems in terms of structure design-process modelling-performance evaluation in AM of metallic components are provided.

Powder bed fusion (PBF) is a popular additive manufacturing (AM) process with wide applications in key industrial sectors, including aerospace, automotive, healthcare, defence. However, a deficiency of PBF is its low quality of surface finish. A number of PBF process variables and other factors (e.g. powders, recoater) can influence the surface quality. It is of significant importance to measure and characterise PBF surfaces for the benefits of process optimisation, product performance evaluation and also product design. A state-of-the-art review is given to summarise the current research work on the characterisation of AM surfaces, particularly PBF surfaces. It is recognised that AM processes are different from conventional manufacturing processes and their produced surface topographies are different as well. In this paper, the surface characterisation framework is updated to reflect the unique characteristics of PBF processes. The surface spatial wavelength components and other process signature features are described and their production mechanisms are elaborated. A bespoke surface characterisation procedure is developed based on the updated framework. The robust Gaussian regression filter and the morphological filters are proposed to be used for the separation of the waviness component due to their robustness. The watershed segmentation is enhanced to extract globules from the residual surface. Two AM components produced by electron beam melting (EBM) and selective laser melting (SLM), are measured and characterised by the proposed methodology. Both of the two filters are qualified for the extraction of melted tracks. The watershed segmentation can enable the extraction of globules. The standard surface texture parameters of different surface wavelength components are compared. A set of bespoke parameters are intentionally developed to offer a quantitative evaluation of the globules.

A reliability engineering program must be implemented from the conceptual phase of the physical asset to define the performance requirements of the components and equipment. Thus, in this work, the aim is to find the most optimal solution to manufacture polymer-based parts for the nuclear power industry using additive manufacturing routes. This case study application has been selected because polymers processed by additive manufacturing (AM) can be well suited for nuclear applications. The methodology includes—firstly—an analysis of the suitability of materials based on high-temperature resistance, thermal aging and irradiation tolerance, considering operation conditions. Secondly, an analysis of materials’ processability considering their associated AM routes is performed based on thermal analysis and evaluation of physical properties of materials. A final assessment integrating the in-service suitability and AM processability is performed using a reliability approach, solving different emerging objective conflicts through defined constraints and selection criteria. According to the integrated in-service performance evaluation: Polypropylene-ethylene polyallomer (PPP), Epoxy (EP), Phenolics (Ph), Polyurethane (PU) and Acrylonitrile butadiene rubber (NBR) are the best options for mild operation conditions and EP, Ph and PU, considering high temperature along with radiation exposure. Considering AM techniques: EP and Ph can be manufactured using VAT photopolymerization-stereolithography (VP-SLA) with a good expected processability being these materials valid for high temperature environments. Consequently, this research work analyzes the viability, processability and in-service behavior of parts.

Masterbatch dosing units