Modeling for Polymer Additive Manufacturing Processes

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

The development of sustainable and functional biocomposites remains a robust research and industrial claim. Herein, the efficiency of using eco-friendly biochar as reinforcement in Additive Manufacturing (AM) was investigated. Two AM technologies were applied, i.e., vat photopolymerization (VPP) and material extrusion (MEX). A standard-grade resin in VPP and the also eco-friendly biodegradable Polylactic Acid (PLA) in the MEX process were selected as polymeric matrices. Biochar was prepared in the study from olive trees. Composites were developed for both 3D printing processes at different biochar loadings. Samples were 3D-printed and mechanically tested after international test standards. Thermogravimetric Analysis and Raman revealed the thermal and structural characteristics of the composites. Morphological and fractographic features were derived, among others, with Scanning Electron Microscopy (SEM) and Atomic Force Microscopy (AFM). Biochar was proven to be sufficient reinforcement agent, especially in the filament MEX process, reaching more than 20% improvement at 4 wt.% loading in tensile strength compared to the pure PLA control samples. In the VPP process, results were not as satisfactory, still, a 5% improvement was achieved in the flexural strength with 0.5 wt.% biochar loading. The findings prove the strong potential of biochar-based composites in AM applications, too.Graphical

Recently, Additive Manufacturing (AM) has been widely used in many applications. For a particular AM component, the choice of available AM processes is critical to the component’s quality, mechanical properties, and other important factors. In that context, this article presents an efficient decision support system for the selection of an appropriate AM process. A novel hybrid Multi-Criteria Decision Making (MCDM) technique has been proposed to select an appropriate AM process from available AM processes. The Best Worst Method (BWM) is used to determine optimal weights of criteria and the Proximity Indexed Value (PIV) method is employed to rank the available AM processes. For benchmarking the abilities of an AM process, a conceptual model of spur gear was fabricated by four available AM processes viz., Vat Photopolymerization (VatPP), Material Extrusion (ME), Powder Bed Fusion (PBF), and Material Jetting (MJ). Additionally, Dimensional accuracy (A), surface roughness (R), tensile strength (S), percentage elongation (%E), heat deflection temperature (HDT), process cost (PC) and build time (BT) has been considered as most significant criteria. Further, sensitivity analysis has been performed to validate the reliability of the results. The results suggested that the Material Jetting (MJ) process produces dimensionally accurate and quality parts among available alternatives AM processes. The ranking obtained using the PIV method is consistent and reliable.

3D printing, a type of additive manufacturing (AM), is a rapidly expanding field. Some adverse health effects have been associated with exposure to printing emissions, which makes occupational exposure studies important. There is a lack of exposure studies, particularly from printing methods other than material extrusion (ME). The presented study aimed to evaluate measurement methods for exposure assessment in AM environments and to measure exposure and emissions from four different printing methods [powder bed fusion (PBF), material extrusion (ME), material jetting (MJ), and vat photopolymerization] in industry. Structured exposure diaries and volatile organic compound (VOC) sensors were used over a 5-day working week. Personal and stationary VOC samples and real-time particle measurements were taken for 1 day per facility. Personal inhalable and respirable dust samples were taken during PBF and MJ AM. The use of structured exposure diaries in combination with measurement data revealed that comparatively little time is spent on actual printing and the main exposure comes from post-processing tasks. VOC and particle instruments that log for a longer period are a useful tool as they facilitate the identification of work tasks with high emissions, highlight the importance of ventilation and give a more gathered view of variations in exposure. No alarming levels of VOCs or dust were detected during print nor post-processing in these facilities as adequate preventive measures were installed. As there are a few studies reporting negative health effects, it is still important to keep the exposure as low as reasonable.

This paper presents the process of manufacturing mechanical joint components using additive manufacturing (AM) techniques such as Material Extrusion (Fused Deposition Modelling (FDM)), Material Jetting (PolyJet), and Vat Photopolymerization (VAT)/Stereolithography (SLA). Using the PolyJet technique and a photopolymer resin, spline and threaded joint components were produced. For comparative analysis, the threaded joint was also fabricated using FDM and SLA techniques. PLA material was used for the FDM technique, while photopolymer resin was utilized for the SLA process. The components produced underwent a surface analysis to evaluate the accuracy of the dimensions in relation to the nominal dimensions. For the spline connection components, the dimensional deviations recorded by a 3D scanner ranged from −0.11 to +0.18 mm for the shaft and up to 0.24 mm for the sleeve. Measurements of screw and nut diameters showed the highest accuracy for screws produced using the PolyJet technique, while the nuts exhibited the best accuracy when fabricated with the SLA method. The profile of the screw threads using a contour gauge revealed the most accurate thread profile on the screw manufactured with the PolyJet technique.

Based on responses to a survey of international migrants and Norway-born residents in three rural municipalities, this article analyses place attachment at various levels of scale. It compares international migrants to Norwegian-born internal migrants and local natives. Three questions are addressed: 1) Are there differences in the three resident categories’ levels of place attachment at different levels of scale?; 2) What are the predictors of place attachment, and is being a migrant a predictor in its own right? and 3) Are the predictors of place attachment the same for international migrants, internal migrants and local natives, and for different levels of scale? After controlling for other factors, the study found that all three categories have similar place attachment levels to the local scales. However, place attachment predictors differ, and predictors of place attachment have different relevance on different scales for the three categories. Institutional trust, usually not addressed in the research tradition, predicts place attachment for all categories.

Additive manufacturing technologies for polymer composites: State-of-the-art and future trends

The utilization of additive manufacturing (AM) has entailed numerous benefits such as shortened time-to-market, high product innovation and individualization. The application of AM has gained in significance within the automotive industry as it is transferring from a prototype technology to series applications. Besides technological barriers, an approach to estimate cost to set up a business case of an application is crucial. Material extrusion (ME) as an additive process category is theoretically capable of meeting high requirements in industry. Despite various processes belonging to ME, Fused Layer Modeling (FLM) is the only one entrenched. The establishment of pellet-based processes could overcome restrictions for ME. Although there are various cost estimations for AM, a transparent methodology to carry out a profitability analysis between ME processes is missing. In this study, a cost model for ME is developed to estimate occurring cost and cost drivers. Existing cost models are compared regarding their suitability for ME. The final cost model for ME is activity-based and measuring occurring unit cost during the process steps pre-, in- and postprocessing. The duration of cost-generating activities is considered.

Chapter 4 - Geographic Space as a Living Structure for Predicting Human Activities Using Big Data

Science is made feasible by the adoption of common systems of units. As research has become more data intensive, especially in the biomedical domain, it requires the adoption of a common system of information models, to make explicit the relationship between one set of data and another, regardless of format. This is being realised through the OBO Foundry to develop a suite of reference ontologies, and NCBO Bioportal to provide services to integrate biomedical resources and functionality to visualise and create mappings between ontology terms. Biomedical experts tend to be focused at one level of spatial scale, be it biochemistry, cell biology, or anatomy. Likewise, the ontologies they use tend to be focused at a particular level of scale. There is increasing interest in a multiscale systems approach, which attempts to integrate between different levels of scale to gain understanding of emergent effects. This is a return to physiological medicine with a computational emphasis, exemplified by the worldwide Physiome initiative, and the European Union funded Network of Excellence in the Virtual Physiological Human. However, little work has been done on how information modelling itself may be tailored to a multiscale systems approach. We demonstrate how this can be done for the complex process of heart morphogenesis, which requires multiscale understanding in both time and spatial domains. Such an effort enables the integration of multiscale metrology.

Chapter 4 - 3D printing composite materials: A comprehensive review

PurposeAdditive manufacturing (AM) is a rapidly evolving manufacturing process, which refers to a set of technologies that add materials layer-by-layer to create functional components. AM technologies have received an enormous attention from both academia and industry, and they are being successfully used in various applications, such as rapid prototyping, tooling, direct manufacturing and repair, among others. AM does not necessarily imply building parts, as it also refers to innovation in materials, system and part designs, novel combination of properties and interplay between systems and materials. The most exciting features of AM are related to the development of radically new systems and materials that can be used in advanced products with the aim of reducing costs, manufacturing difficulties, weight, waste and energy consumption. It is essential to develop an advanced production system that assists the user through the process, from the computer-aided design model to functional components. The challenges faced in the research and development and operational phase of producing those parts include requiring the capacity to simulate and observe the building process and, more importantly, being able to introduce the production changes in a real-time fashion. This paper aims to review the role of robotics in various AM technologies to underline its importance, followed by an introduction of a novel and intelligent system for directed energy deposition (DED) technology.Design/methodology/approachAM presents intrinsic advantages when compared to the conventional processes. Nevertheless, its industrial integration remains as a challenge due to equipment and process complexities. DED technologies are among the most sophisticated concepts that have the potential of transforming the current material processing practices.FindingsThe objective of this paper is identifying the fundamental features of an intelligent DED platform, capable of handling the science and operational aspects of the advanced AM applications. Consequently, we introduce and discuss a novel robotic AM system, designed for processing metals and alloys such as aluminium alloys, high-strength steels, stainless steels, titanium alloys, magnesium alloys, nickel-based superalloys and other metallic alloys for various applications. A few demonstrators are presented and briefly discussed, to present the usefulness of the introduced system and underlying concept. The main design objective of the presented intelligent robotic AM system is to implement a design-and-produce strategy. This means that the system should allow the user to focus on the knowledge-based tasks, e.g. the tasks of designing the part, material selection, simulating the deposition process and anticipating the metallurgical properties of the final part, as the rest would be handled automatically.Research limitations/implicationsThis paper reviews a few AM technologies, where robotics is a central part of the process, such as vat photopolymerization, material jetting, binder jetting, material extrusion, powder bed fusion, DED and sheet lamination. This paper aims to influence the development of robot-based AM systems for industrial applications such as part production, automotive, medical, aerospace and defence sectors.Originality/valueThe presented intelligent system is an original development that is designed and built by the co-authors J. Norberto Pires, Amin S. Azar and Trayana Tankova.

Quasi-optics are essential components of terahertz (THz) systems, used to direct and manipulate THz radiation. High-resolution additive manufacturing (AM) techniques, such as vat photopolymerization (VP), enable the low-cost production of complex quasi-optical components with optically smooth surfaces and fine geometric features with dimensions comparable to wavelengths in the THz region. However, VP-produced quasi-optics are often inefficient owing to significant absorption losses, with commercially available photopolymers exhibiting absorption coefficients ranging between 19 – 27 cm –1 at 1 THz. Polytetrafluoroethylene (PTFE) is highly transparent in the THz region, making it a promising filler material to reduce the absorption of photopolymers. However, no previous studies have reported the development of a PTFE composite suitable for processing via VP. In this study, PTFE powder-filled composites were formulated containing PTFE-to-photocurable-resin ratios ranging from 1:10–4:10, corresponding to approximately 9.0 % and 28.5 % by weight, respectively. Samples were manufactured via VP and characterised from 0.5 to 2.0 THz using a THz time-domain spectroscopy system. The results demonstrated a correlation between higher PTFE ratios and a reduction in the absorption coefficient of the samples from 0.5 to 2.0 THz, with the 4:10 sample having an absorption coefficient of 15.3 ± 0.3 cm –1 at 1 THz, 27.8 % lower than that of the neat resin (21.2 ± 0.4 cm –1 ). Additionally, experimental results were shown to agree well with a Maxwell Garnett effective medium approximation-based calculation of the THz optical properties of AM composites. These findings highlight the potential of non-polar polymer fillers to enhance the transparency of photopolymers to THz radiation, potentially supporting the future development of more efficient VP-produced quasi-optical components. • PTFE-filled photopolymer composites were developed for stereolithography systems. • The ∼30 wt% PTFE composite had 27.8 % less absorption at 1 THz than the base resin. • The Maxwell Garnett model matched experimental results with high accuracy. • Non-polar fillers can enhance the THz transparency of photopolymers. • Improves the efficiency of THz optics made via stereolithography.

The aim of this study was to measure the concentrations of gaseous and particulate contaminants originated from additive manufacturing operations and post-processes in an occupational setting when plastics were used as feedstock materials. Secondary aims were to evaluate the concentration levels based on proposed exposure limits and target values and to propose means to reduce exposure to contaminants released in additive manufacturing processes. Volatile organic compounds were sampled with Tenax TA adsorption tubes and analyzed with a thermo desorption gas chromatography-mass spectrometry instrument. Carbonyl compounds were sampled with DNPH-Silica cartridges and analyzed with a high-performance liquid chromatography device. Particles were measured with P-Trak instrument and indoor air quality was sampled with IAQ-Calc instrument. Dust mass concentrations were measured simultaneously with a DustTrak DRX instrument and IOM-samplers. Particle concentrations were highest (2070-81 890 #/cm3 mean) during manufacturing with methods where plastics were thermally processed. Total volatile organic compounds concentrations, in contrast, were low (113–317 µg/m3 mean) during manufacturing with such methods, and vat photopolymerization. However, total volatile organic compounds concentrations of material jetting and multi jet fusion methods were higher (1,114–2,496 µg/m3 mean), perhaps because of material and binder spraying, where part of the spray can become aerosolized. Chemical treatment of manufactured objects was found to be a severe volatile organic compounds source as well. Formaldehyde was detected in low concentrations (3–40 µg/m3) in all methods except for material jetting method, in addition to several other carbonyl compounds. Notable dust concentrations (1.4–9.1 mg/m3) were detected only during post-processing of powder bed fusion and multi jet fusion manufactured objects. Indoor air quality parameters were not found to be notably impacted by manufacturing operations. Only low concentrations (below 2 ppm) of CO were detected during several manufacturing processes. All studied additive manufacturing operations emitted potentially harmful contaminants into their environments, which should be considered in occupational additive manufacturing and workplace design. According to the measured contaminant levels it is possible that adverse additive manufacturing related health effects may occur among exposed workers.

Particle-resin systems for additive manufacturing of rigid and elastic magnetic polymeric composites