Investigation into the Influence of Build Parameters on Failure of 3D Printed Parts

Additive manufacturing, including fused deposition modeling (FDM), is transforming the built world and engineering education. Deep understanding of parts created through FDM technology has lagged behind its adoption in home, work, and academic environments. Properties of parts created from bulk materials through traditional manufacturing are understood well enough to accurately predict their behavior through analytical models. Unfortunately, Additive Manufacturing (AM) process parameters create anisotropy on a scale that fundamentally affects the part properties. Understanding AM process parameters (implemented by program algorithms called slicers) is necessary to predict part behavior. Investigating algorithms controlling print parameters (slicers) revealed stark differences between the generation of part layers. In this work, tensile testing experiments, including a full factorial design, determined that three key factors, width, thickness, infill density, and their interactions, significantly affect the tensile properties of 3D printed test samples.

Assessment of naproxen adsorption on bone char in aqueous solutions using batch and fixed-bed processes

An integrated analysis of naproxen adsorption on bone char in batch and packed-bed column conditions has been performed. Kinetic, thermodynamic and breakthrough parameters have been calculated using adsorption models and artificial neural networks. Results show that naproxen removal using bone char in batch conditions is a feasible and effective process, which could involve electrostatic and non-electrostatic interactions depending mainly on pH conditions. However, the application of packed-bed column for naproxen adsorption on bone char is not effective for the treatment of diluted solutions due to the low degree of adsorbent utilization (below 4%) at tested operating conditions. The proposed mechanism for naproxen removal using bone char could include a complexation process via phosphate and naproxen, hydrogen bonding and the possibility of hydrophobic interactions via π–π electron. This study highlights the relevance of performing an integrated analysis of adsorbent effectiveness in batch and dynamic conditions to establish the best process configuration for the removal of emerging water pollutants such as pharmaceuticals.

Genetic parameters for carcass traits and body weight using a Bayesian approach in the Canchim cattle.

Correlation between genetic parameters and factors such as backfat thickness (BFT), rib eye area (REA), and body weight (BW) were estimated for Canchim beef cattle raised in natural pastures of Brazil. Data from 1648 animals were analyzed using multi-trait (BFT, REA, and BW) animal models by the Bayesian approach. This model included the effects of contemporary group, age, and individual heterozygosity as covariates. In addition, direct additive genetic and random residual effects were also analyzed. Heritability estimated for BFT (0.16), REA (0.50), and BW (0.44) indicated their potential for genetic improvements and response to selection processes. Furthermore, genetic correlations between BW and the remaining traits were high (P > 0.50), suggesting that selection for BW could improve REA and BFT. On the other hand, genetic correlation between BFT and REA was low (P = 0.39 ± 0.17), and included considerable variations, suggesting that these traits can be jointly included as selection criteria without influencing each other. We found that REA and BFT responded to the selection processes, as measured by ultrasound. Therefore, selection for yearling weight results in changes in REA and BFT.

Studio e ottimizzazione del processo di fabbricazione additiva (SLM) per applicazioni in ambito biomedicale: produzione di protesi e strutture reticolari

Il progetto di dottorato che verrà presentato in questa tesi è focalizzato sullo sviluppo di un metodo sperimentale per la produzione di protesi personalizzate utilizzando il processo di fabbricazione additiva di Selective Laser Melting (SLM). L’obiettivo è quello di definire una condizione di processo ottimizzata per applicazioni in ambito chirurgico che possa essere generalizzabile, ovvero che ne garantisca la riproducibilità al variare dell’anatomia del paziente e che rappresenti la base per estendere il metodo ad altre componenti protesiche. Il lavoro si è sviluppato lungo due linee principali, la cui convergenza ha permesso di realizzare prototipi di protesi complete utilizzando un solo processo: da una parte la produzione di componenti a massima densità per il raggiungimento di elevate resistenze meccaniche, buona resistenza ad usura e corrosione e controllo di tensioni residue e deformazione delle parti stampate. Dall’altra si sono studiate strutture reticolari a geometria e porosità controllata per favorire l’osteointegrazione della componente protesica post impianto. In questo studio sono stati messe a confronto le possibili combinazioni tra parametri di processo e sono state individuate le correlazioni con le proprietà finali dei componenti stampati. Partendo da queste relazioni si sono sviluppate le strategie tecnologiche per la progettazione e la produzione dei componenti. I test sperimentali svolti e i risultati ottenuti hanno dimostrato la fattibilità dell’utilizzo del processo SLM per la produzione di protesi personalizzate e sono stati fabbricati i primi prototipi funzionali. La fabbricazione di protesi personalizzate richiede, però, anche la progettazione e la produzione di strumentario chirurgico ad hoc. Per questo motivo, parallelamente allo studio della lega di Cromo Cobalto, sono stati eseguiti i test anche su campioni in INOX 316L. Anche in questo caso è stato possibile individuare una finestra operativa di processo che garantisse proprietà meccaniche comparabili, e in alcuni casi superiori, a quelle ottenute con processi convenzionali.

Additive Manufacturing by LPBF and WAAM of metals: correlation between production process, microstructure and mechanical properties

In the most recent years, Additive Manufacturing (AM) has drawn the attention of both academic research and industry, as it might deeply change and improve several industrial sectors. From the material point of view, AM results in a peculiar microstructure that strictly depends on the conditions of the additive process and directly affects mechanical properties. The present PhD research project aimed at investigating the process-microstructure-properties relationship of additively manufactured metal components. Two technologies belonging to the AM family were considered: Laser-based Powder Bed Fusion (LPBF) and Wire-and-Arc Additive Manufacturing (WAAM). The experimental activity was carried out on different metals of industrial interest: a CoCrMo biomedical alloy and an AlSi7Mg0.6 alloy processed by LPBF, an AlMg4.5Mn alloy and an AISI 304L austenitic stainless steel processed by WAAM. In case of LPBF, great attention was paid to the influence that feedstock material and process parameters exert on hardness, morphological and microstructural features of the produced samples. The analyses, targeted at minimizing microstructural defects, lead to process optimization. For heat-treatable LPBF alloys, innovative post-process heat treatments, tailored on the peculiar hierarchical microstructure induced by LPBF, were developed and deeply investigated. Main mechanical properties of as-built and heat-treated alloys were assessed and they were well-correlated to the specific LPBF microstructure. Results showed that, if properly optimized, samples exhibit a good trade-off between strength and ductility yet in the as-built condition. However, tailored heat treatments succeeded in improving the overall performance of the LPBF alloys. Characterization of WAAM alloys, instead, evidenced the microstructural and mechanical anisotropy typical of AM metals. Experiments revealed also an outstanding anisotropy in the elastic modulus of the austenitic stainless-steel that, along with other mechanical properties, was explained on the basis of microstructural analyses.

Design of experiment in drug development: optimal allocations in multi-arm clinical trials and design space for multi-step processes

In this thesis, we deal with the design of experiments in the drug development process, focusing on the design of clinical trials for treatment comparisons (Part I) and the design of preclinical laboratory experiments for proteins development and manufacturing (Part II). In Part I we propose a multi-purpose design methodology for sequential clinical trials. We derived optimal allocations of patients to treatments for testing the efficacy of several experimental groups by also taking into account ethical considerations. We first consider exponential responses for survival trials and we then present a unified framework for heteroscedastic experimental groups that encompasses the general ANOVA set-up. The very good performance of the suggested optimal allocations, in terms of both inferential and ethical characteristics, are illustrated analytically and through several numerical examples, also performing comparisons with other designs proposed in the literature. Part II concerns the planning of experiments for processes composed of multiple steps in the context of preclinical drug development and manufacturing. Following the Quality by Design paradigm, the objective of the multi-step design strategy is the definition of the manufacturing design space of the whole process and, as we consider the interactions among the subsequent steps, our proposal ensures the quality and the safety of the final product, by enabling more flexibility and process robustness in the manufacturing.

Dry grinding technology for automotive gears manufacturing: process modeling and optimization

The following thesis focused on the dry grinding process modelling and optimization for automotive gears production. A FEM model was implemented with the aim at predicting process temperatures and preventing grinding thermal defects on the material surface. In particular, the model was conceived to facilitate the choice of the grinding parameters during the design and the execution of the dry-hard finishing process developed and patented by the company Samputensili Machine Tools (EMAG Group) on automotive gears. The proposed model allows to analyse the influence of the technological parameters, comprising the grinding wheel specifications. Automotive gears finished by dry-hard finishing process are supposed to reach the same quality target of the gears finished through the conventional wet grinding process with the advantage of reducing production costs and environmental pollution. But, the grinding process allows very high values of specific pressure and heat absorbed by the material, therefore, removing the lubricant increases the risk of thermal defects occurrence. An incorrect design of the process parameters set could cause grinding burns, which affect the mechanical performance of the ground component inevitably. Therefore, a modelling phase of the process could allow to enhance the mechanical characteristics of the components and avoid waste during production. A hierarchical FEM model was implemented to predict dry grinding temperatures and was represented by the interconnection of a microscopic and a macroscopic approach. A microscopic single grain grinding model was linked to a macroscopic thermal model to predict the dry grinding process temperatures and so to forecast the thermal cycle effect caused by the process parameters and the grinding wheel specification choice. Good agreement between the model and the experiments was achieved making the dry-hard finishing an efficient and reliable technology to implement in the gears automotive industry.

Supported metal nanoparticles for sustainable green catalytic processes

Preformed Au nanoparticles supported on activated carbon and TiO2 were synthesised by sol-immobilisation. Polyethylene glycol, polyvinyl pyrrolidone and polyvinyl alcohol were used as stabilisers for the gold nanoparticles at different polymer/Au wt/wt ratios for each polymer. The effect of polymer/Au wt/wt ratios was investigated on (i) the average nanoparticle size, (ii) catalytic activity for two reactions, 4-nitrophenol reduction and glucose oxidation to glucaric acid. 4-nitrophenol reduction is recognised as a model reaction for nanomaterial catalytic activity tests; glucose oxidation to glucaric acid is a reaction that is traditionally carried out with concentrated nitric acid, for which alternative reaction pathways are looked for in an effort to reduce its environmental impact. The catalysts were characterised from the nanoparticle synthesis by colloidal method by means of UV-vis spectroscopy and DLS analysis, to the immobilisation step by XRD and TEM. The effect of the polymer:Au wt/wt ratio on nanoparticle size depends on the polymer nature, and point out the need to optimise supported nanoparticle synthesis protocols in the future depending on the type of stabiliser. The catalytic tests revealed that the polymers interact with Au nanoparticles through different active sites. Activated carbon (AC) and TiO2 were compared as supports for Au nanoparticles stabilised by PVA at PVA/Au 0,65 wt/wt. AC-supported Au NPs were the most active for glucose oxidation while TiO2-stabilised Au NPs were five times more active in 4-nitrophenol reduction that AC-supported NPs. Hence support and stabiliser are important parameters that should be optimised in order to achieve high catalytic activity for a given reaction.

Metal additive manufacturing of soft magnetic material for electric machines

This research work concerns the application of additive manufacturing (AM) technologies in new electric mobility sectors. The unmatched freedom that AM offers can potentially change the way electric motors are designed and manufactured. The thesis investigates the possibility of creating optimized electric machines that exploit AM technologies, with potential in various industrial sectors, including automotive and aerospace. In particular, we will evaluate how the design of electric motors can be improved by producing the rotor core using Laser Powder Bed Fusion (LPBF) and how the resulting design choices affect component performance. First, the metallurgical and soft magnetic properties of the pure iron and silicon iron alloy parts (Fe-3% wt.Si) produced by LPBF will be defined and discussed, considering the process parameters and the type of heat treatment. This research shows that using LPBF, both pure iron and iron silicon, the parts have mechanical and magnetic properties different from the laminated ones. Hence, FEM-based modeling will be employed to design the rotor core of an SYN RM machine to minimize torque ripple while maintaining structural integrity. Finally, we suggest that further research should extend the field of applicability to other electrical devices.

Application of Pulsed Electric Fields for the Modulation of Chemico-Physical Properties of Different Foods

Pulsed electric field technology is one of the most attractive new non-thermal technology thanks to its lower energy consumption and short treatment times. It consists of an electric treatment of short duration (from several ns to several ms) with electric field strengths from 0.1 to 80 kV/cm that lead to an increase in the permeability of the cell membrane. In this PhD thesis, PEF technology was investigated with the aim of improving mass transfer in plant and animal foods by using it alone or in combination with conventional food processes. Different methods of evaluating electroporation for optimizing PEF processing parameters were investigated. In this respect, the degree of membrane permeabilization in plant and animal food matrices was investigated using electrical impedance spectroscopy, current-voltage measurements and magnetic resonance imaging. The research findings provided useful insights and calls for critical choice of electroporation assessment methods for the selection of adequate PEF treatment conditions. It was outlined that the effect of electroporation is highly dependent on the properties of the food matrix and secondary phenomena occurring in the cell structure undergoing PEF treatment, such as the water re-distribution in the tissue due to the exchange of fluids between intra- and extra-cellular environments. This study also confirmed the great potential of combining PEF technology with conventional food processes, with the main purpose of improving the quality of the food material and accelerating the kinetics of mass transfers, in both plant and animal tissues. Consistent reduction of acrylamide formation in potato crisps was achieved by monitoring key PEF process parameters and subsequent manufacturing steps. Kiwifruit snacks showed a significant reduction in drying kinetics when pre-treated with PEF, while their quality was well maintained. Finally, the research results showed that PEF pre-treatments can shorten the brine process as well as the rehydration kinetics of fish muscles.

Production and characterization of novel thermoplastic (nano)composite materials for additive manufacturing applications

The increasing environmental global regulations have directed scientific research towards more sustainable materials, even in the field of composite materials for additive manufacturing. In this context, the presented research is devoted to the development of thermoplastic composites for FDM application with a low environmental impact, focusing on the possibility to use wastes from different industrial processes as filler for the production of composite filaments for FDM 3D printing. In particular carbon fibers recycled by pyro-gasification process of CFRP scraps were used as reinforcing agent for PLA, a biobased polymeric matrix. Since the high value of CFs, the ability to re-use recycled CFs, replacing virgin ones, seems to be a promising option in terms of sustainability and circular economy. Moreover, wastes from different agricultural industries, i.e. wheat and rice production processes, were valorised and used as biofillers for the production of PLA-biocomposites. The integration of these agricultural wastes into PLA bioplastic allowed to obtain biocomposites with improved eco-sustainability, biodegradability, lightweight, and lower cost. Finally, the study of novel composites for FDM was extended towards elastomeric nanocomposite materials, in particular TPU reinforced with graphene. The research procedure of all projects involves the optimization of production methods of composite filaments with a particular attention on the possible degradation of polymeric matrices. Then, main thermal properties of 3D printed object are evaluated by TGA, DSC characterization. Additionally, specific heat capacity (CP) and Coefficient of Linear Thermal Expansion (CLTE) measurements are useful to estimate the attitude of composites for the prevention of typical FDM issues, i.e. shrinkage and warping. Finally, the mechanical properties of 3D printed composites and their anisotropy are investigated by tensile test using distinct kinds of specimens with different printing angles with respect to the testing direction.

Development and application of a computer-based methodology for design for additive manufacturing of automotive components

The research project aims to improve the Design for Additive Manufacturing of metal components. Firstly, the scenario of Additive Manufacturing is depicted, describing its role in Industry 4.0 and in particular focusing on Metal Additive Manufacturing technologies and the Automotive sector applications. Secondly, the state of the art in Design for Additive Manufacturing is described, contextualizing the methodologies, and classifying guidelines, rules, and approaches. The key phases of product design and process design to achieve lightweight functional designs and reliable processes are deepened together with the Computer-Aided Technologies to support the approaches implementation. Therefore, a general Design for Additive Manufacturing workflow based on product and process optimization has been systematically defined. From the analysis of the state of the art, the use of a holistic approach has been considered fundamental and thus the use of integrated product-process design platforms has been evaluated as a key element for its development. Indeed, a computer-based methodology exploiting integrated tools and numerical simulations to drive the product and process optimization has been proposed. A validation of CAD platform-based approaches has been performed, as well as potentials offered by integrated tools have been evaluated. Concerning product optimization, systematic approaches to integrate topology optimization in the design have been proposed and validated through product optimization of an automotive case study. Concerning process optimization, the use of process simulation techniques to prevent manufacturing flaws related to the high thermal gradients of metal processes is developed, providing case studies to validate results compared to experimental data, and application to process optimization of an automotive case study. Finally, an example of the product and process design through the proposed simulation-driven integrated approach is provided to prove the method's suitability for effective redesigns of Additive Manufacturing based high-performance metal products. The results are then outlined, and further developments are discussed.

IDeS methodology applied to automotive component re-engineering focused on lightweight and high-strength by additive manufacturing

The project aims to gather an understanding of additive manufacturing and other manufacturing 4.0 techniques with an eyesight for industrialization. First the internal material anisotropy of elements created with the most economically feasible FEM technique was established. An understanding of the main drivers for variability for AM was portrayed, with the focus on achieving material internal isotropy. Subsequently, a technique for deposition parameter optimization was presented, further procedure testing was performed following other polymeric materials and composites. A replicability assessment by means of the use of technology 4.0 was proposed, and subsequent industry findings gathered the ultimate need of developing a process that demonstrate how to re-engineer designs in order to show the best results with AM processing. The latest study aims to apply the Industrial Design and Structure Method (IDES) and applying all the knowledge previously stacked into fully reengineer a product with focus of applying tools from 4.0 era, from product feasibility studies, until CAE – FEM analysis and CAM – DfAM. These results would help in making AM and FDM processes a viable option to be combined with composites technologies to achieve a reliable, cost-effective manufacturing method that could also be used for mass market, industry applications.

Investigating stellar mixing processes through the study of the Red-Giant Branch bump

Extra mixing at the borders of convective zones in stellar interiors takes on an important role in the chemical evolution of stars and galaxies through the transport of chemical elements towards the stellar surface: knowing the overshooting mechanism can therefore lead to a better understanding of the observed chemical abundances in stellar photospheres. The comprehension of this phenomenon is quite uncertain and currently object of many studies. In particular, concerning low mass stars, in the past decades several works highlighted a discrepancy between the observed luminosity of the Red-Giant Branch bump and its prediction from simulations, which can be fixed including overshooting at the base of the convective envelope. This work, studying the Red-Giant Branch bump and using it as a diagnostic for extra mixing processes, tries to classify two different types of overshooting, instantaneous and diffusive, using both simulations from stellar models and Globular Clusters’ data. The aim is to understand which one of the two mixing processes is the most suitable in reproducing the observed stellar behaviour and, in case both of them provide reliable results, what are the conditions under which they produce the same effects on the Red-Giant Branch bump luminosity function and are consequently indistinguishable. Finally, possible dependences of overshooting efficiency on stellar parameters, such as chemical composition, are analysed.

Geochemistry Of Acid Mine Drainage From A Coal Mining Area And Processes Controlling Metal Attenuation In Stream Waters, Southern Brazil.

Acid drainage influence on the water and sediment quality was investigated in a coal mining area (southern Brazil). Mine drainage showed pH between 3.2 and 4.6 and elevated concentrations of sulfate, As and metals, of which, Fe, Mn and Zn exceeded the limits for the emission of effluents stated in the Brazilian legislation. Arsenic also exceeded the limit, but only slightly. Groundwater monitoring wells from active mines and tailings piles showed pH interval and chemical concentrations similar to those of mine drainage. However, the river and ground water samples of municipal public water supplies revealed a pH range from 7.2 to 7.5 and low chemical concentrations, although Cd concentration slightly exceeded the limit adopted by Brazilian legislation for groundwater. In general, surface waters showed large pH range (6 to 10.8), and changes caused by acid drainage in the chemical composition of these waters were not very significant. Locally, acid drainage seemed to have dissolved carbonate rocks present in the local stratigraphic sequence, attenuating the dispersion of metals and As. Stream sediments presented anomalies of these elements, which were strongly dependent on the proximity of tailings piles and abandoned mines. We found that precipitation processes in sediments and the dilution of dissolved phases were responsible for the attenuation of the concentrations of the metals and As in the acid drainage and river water mixing zone. In general, a larger influence of mining activities on the chemical composition of the surface waters and sediments was observed when enrichment factors in relation to regional background levels were used.