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This work presents a decision-making methodology that allows the merging of quantitative and qualitative decision variables for selecting the optimal metal Additive Manufacturing (AM) technology. The approach is applied on two competing technologies in the field of metal AM industry, i.e., the metal extrusion AM process (metal FFF) and the Laser Powder Bed Fusion process (LPBF) with single and multiple lasers, which represent the benchmark solution currently on the market. A comprehensive techno-economical comparison is presented where the two processes are analysed in terms of process capabilities (quality, easiness of use, setup time, range of possible materials, etc.) and costs, considering two different production scenarios and different parts’ geometries. In the first scenario, the AM system is assumed to be dedicated to one single part production while in this second scenario, the AM system is assumed to be saturated, as devoted to producing a wide mix of part types. For each scenario, two different part types made of 17–4 PH stainless steel are considered as a reference to investigate the effect of shape complexity, part size and production times to select the best technology when metal FFF and LPBF must be considered. The first part type refers to an extrusion die, to represent typical shapes of interest in the tooling industry, while the second part type is an impeller which can be used in many different industrial sectors, ranging from oil and gas to aerospace. In order to include quantitative and qualitative criteria, a decision-making model based on Analytic Hierarchy Process (AHP) is proposed as the enabler tool for decision making. The proposed approach allows to determine the most effective solution depending on the different production configurations and part types and can be used as a guideline and extended to include other technologies in the field of metal AM. On the other side, the critical discussion of the criteria selected, and the results achieved allow to highlight the pros and cons of the competing technologies, thus defining the existing limits to define directions for future research.

Solid ceramic end mills for machining heat resistant super alloys (HRSA) have the potential to generate higher material removal rates, up to one order of magnitude, with respect to standard carbide tools. The machining operations in aerospace industry, where large removals are required to obtain tiny and slender parts like turbine blades, is a cost-intensive task that can benefit of the adoption of ceramic solid end mills. However, these tools show a quite limited tool life, especially when used with interrupted tool engagement strategies. Moreover, they might induce heat-related problems in the workpiece material surface integrity. This paper investigates the cutting and the tool wear during milling Inconel 718 with solid ø12 mm cutting end tool made by SiAlON. The wear mechanisms are studied together with their effects on process signals as cutting forces and power, measured via external and CNC integrated sensors. The carried experimental campaign allowed to find out that tool clogging and edge chipping were the primary cutting phenomena leading the tool wear. Cutting strategy (downmilling or upmilling) produced different results in terms of tool wear sensitivity and process outputs whereas upmilling configuration showed the best results in terms of cutting signals stability and surface integrity. At the same time, cutting speed was found to increase the cutting power more in upmilling than downmilling cutting. The analysis of the forces and power demonstrated that the typical tool wear mechanisms can be traced by signal monitoring due to their high impact on cutting processes. This fact shows the good potential of signal monitoring for a better tool life evaluation.

A checklist of the damselfishes of the world, family Pomacentridae, is presented. A total of 798 nominal species belonging to 423 valid species and 29 genera is included. Most of the species are grouped in five genera: Chromis (109 species), Pomacentrus (82), Chrysiptera (40), Stegastes (39), and Amphiprion (29), but 12 genera contain only one or two species. The following main taxonomic decisions are taken: Chrysiptera personata Fowler, 1946 is a new synonym of Chrysiptera rex (Snyder 1909); Dischistodus notophthalmus (Bleeker, 1853) is the valid name for the species known as Dischistodus melanotus (Bleeker, 1858). Chaetodon rotundus Linnaeus, 1758 and Chaetodon rotundatus Lacepède, 1802 are senior synonyms of Abudefduf bengalensis (Bloch, 1787). Perca japonica Bloch, 1792 is a senior synonym of Chromis notata (Temminck and Schlegel, 1843); Pomacentrus niomatus De Vis, 1884 is a senior synonym of Stegastes fasciolatus (Ogilby, 1889); Glyphisodon sculptus Peters, 1855 is a senior synonym of Abudefduf notatus (Day, 1870). All these senior synonyms are herein regarded as nomina oblita. Neopomacentrus flavicauda is proposed as nomen novum Neopomacentrus xanthurus Allen and Randall, 1980. Stegastes adustus (Troschel, 1865) is the valid name for the species known as Stegastes dorsopunicans (Poey, 1868) and Wangia Fowler, 1954 is an available name not invalidated by Wanga Chen 1943.

Diffractive microstructured surfaces are nowadays increasingly applied to polymeric parts for aesthetic, security and optical functionalities. However, both the machining of the mould blaze-grating and its replication on plastic are still representing challenging issues, from both the technical and economical points of view. In this work, an innovative process chain based on carbide tools micromilling of mould gratings was developed for mass production of diffractive patterns on injection moulded parts. A micromilling experimental campaign was conducted on a nickel-phosphorus (NiP) thick coating to machine a blaze-grating on the mould surface, evaluating the influence of the cutting parameters on the diffractive surface quality. Subsequently, the microstructures were replicated on ABS, PC and PMMA by injection moulding. The roughness parameters Sk, Spk and Svk were added with the idea that their sum is representative of the polymer replication of regular diffraction grating pattern. Moreover, the effect of the moulded grating surface quality on the optical performance was preliminarily assessed. The obtained results show that the proposed process chain is suitable for low-cost mass production of polymeric parts with diffractive microstructures.

A checklist of the croakers of the world, family Sciaenidae, is presented. A total of 584 nominal species belonging to 289 valid species and 69 genera is included. Four genera, Johnius with 32 species, Cynoscion 25, Stellifer 24, and Umbrina 17 contains 30% of the species, whereas 43% of the genera (31) are monotypic. Eques is a valid genus-name and should be used instead of Equetus. Fourteen nominal species remain unidentifiable and are placed in incertae sedis, whereas 12 nominal species currently described in sciaenid genera lay outside the family. Among this latter group two of them represent senior synonyms of well-established species: Sciaena guttata Bloch and Schneider, 1801 and Sciaena pallida Walbaum, 1792 predate Giuris margaritaceus (Valenciennes, 1837) and Cymolutes praetextatus (Quoy and Gaimard, 1824), respectively, and they are here declared nomina oblita.

Animal populations are increasingly forced to live in small residual natural or semi-natural areas due to habitat loss and fragmentation. Here, the viability of populations is often compromised by intrinsic threat factors typical of small and isolated populations, such as inbreeding depression, genetic drift and environmental and demographic stochasticity. Under these circumstances, organisms may have low fitness due to inadequate physiological responses needed to face environmental challenges. However, few studies have investigated the relationship between habitat fragmentation and stress defences. In this study, we aimed to test whether an increase in the level of individual inbreeding produced an increase in the antioxidant system response. To this purpose, we genotyped 151 individuals of fire salamander Salamandra salamandra (Amphibia: Urodela) within five sampling populations, located in forest landscapes with different degree of fragmentation in northern Italy. For 113 individuals we also measured the glutathione-S-transferase (GST) and catalase (CAT) enzyme activity. Results showed a significant increase in individual GST activity for increasing levels of inbreeding, whereas no relationship was found for CAT. We also measured acetylcholinesterase to test the possible confounding effects of pesticides that might have occurred in fragmented landscapes with forests interspersed with agricultural areas. However, no difference in this enzyme activity was found among sampling populations. We argue that high levels of GST activity may be symptomatic of oxidative stress derived from inbreeding. An increased frequency of homozygous deleterious alleles due to inbreeding may cause homeostatic alterations and trigger the expression of GST for protection against hydrogen peroxide reactive oxygen species. We suggest using GST as a biomarker for environmental stressors with great caution and not to underestimate that the sources of stress deriving from habitat fragmentation could lead to an unbalance in the oxidative status, possibly increasing population susceptibility to infectious diseases and, potentially, spillover events and zoonoses.

Recent developments have showcased that micro-extrusion of feedstock can be used for manufacturing metallic microbi-lumen tubes with very high length-to-diameter aspect ratios, which are not viable by conventional metal extrusion or commonly used feedstock processing technologies like injection molding or hot pressing. The extrusion of high aspect ratio microcomponents faces the challenge of maintaining the geometrical accuracy, surface finish, and structural properties since the micro-extrusion in green state is followed by debinding and sintering operations, which result in shrinkage and variations in surface finish and structure. The stages of the process chain such as solvent/thermal debinding (TD), to remove the polymeric binder, and presintering (PS), to achieve a mild structural rigidity before the sintering, are of critical importance to achieve the surface and structural properties of high aspect ratio microparts and have not been yet studied in case of micro-extrusion of feedstock. In this study, the effect of debinding and PS on surface and structural properties of bi-lumen tubes processed at different extrusion conditions is discussed. Surface roughness of the tubes is analyzed using three-dimensional microscopy, and structural properties are studied using scanning electron microscopy (SEM) and energy dispersive spectroscopy (EDS). The debinding and PS experiments on extruded microbi-lumen tubes retained very good surfaces integrity without any cracks or defects. The study shows that the interactions of extrusion temperature and extrusion velocity influence the surface finish of the extruded tubes the most. The sintered bi-lumen samples showed a good areal surface finish, Sa of 2.21 μm, which is near to the green state value confirming the suitability of the applied debinding and PS parameters.

Hybrid processes involving additive and subtractive manufacturing have been showing big potential in producing parts with special engineered properties. Concurrently, the Extrusion Freeform Fabrication (EFF) is growing by showing the capacity to produce complex near-net shape parts made of various metallic and ceramic materials at low production and machine costs. A new Shape Deposition Manufacturing (SDM) is presented, integrating milling technology within a parallel kinematic EFF machine, for producing finished AISI316L parts. With this SDM implementation, the accuracy and the surface quality of the green-state components, as well as the geometrical features generation capacity of standard EFF, is considerably improved.

Optimal design of the machining setup in terms of installed machines, cutting tools and process parameters is of paramount importance for every manufacturing company. In most of the metal cutting companies, all choices related to machine eligibility and cutting parameters selection typically come from heuristic approaches and follow supplier indications or base on the skill of experienced machine operators. More advanced solutions, such as model-based and virtual approaches, are adopted less frequently mainly due to the lack of these techniques in grasping the underlying knowledge successfully. Aim of this work is to introduce a synthetic graphical representation of machining centers and cutting tools capabilities, to provide an accessible way to evaluate the feasibility and close-to-limit conditions of the cutting process. Taking inspiration from previous scientific works from the measurement engineering field, a set of 2D and 3D graphs are presented to map machine, tools and process capabilities, as well as their obtainable manufacturing performances and expectable tool life. This approach synthesizes the nominal data coming from different sources (catalogues, database, tool model geometries etc.) and the real cutting tools parameters used during the production phase. Some examples are provided to show the potential of this graphical evaluation in supporting process planning and decision-making and in formalizing the machining setup knowledge. Further developments are devoted to extend the method to other manufacturing processes, including hybrid processes. At the same time, an in-process data gathering software will be integrated for building a solid database that can be used by an autonomous multi-technological process selector, as well as by a pre-process condition advisor in an Industry 4.0 oriented way.

In this paper, we report the metabolic characterization of two foci, F1 and F3, obtained at the end of Cell Transformation Assay (CTA), performed by treating C3H10T1/2Cl8 mouse embryo fibroblasts with 1 μM CdCl2 for 24 h. The elucidation of the cadmium action mechanism can be useful both to improve the in vitro CTA and to yield insights into carcinogenesis. The metabolism of the two foci was investigated through Seahorse and enzyme activity assays, mitochondria were studied in confocal microscopy and reactive oxygen species were detected by flow cytometry. The results showed that F1 focus has higher glycolytic and TCA fluxes compared to F3 focus, and a more negative mitochondrial membrane potential, so that most ATP synthesis is performed through oxidative phosphorylation. Confocal microscopy showed mitochondria crowded in the perinuclear region. On the other hand, F3 focus showed lower metabolic rates, with ATP mainly produced by glycolysis and damaged mitochondria. Overall, our results showed that cadmium treatment induced lasting metabolic alterations in both foci. Triggered by the loss of the Pasteur effect in F1 focus and by mitochondrial impairment in F3 focus, these alterations lead to a loss of coordination among glycolysis, TCA and oxidative phosphorylation, which leads to malignant transformation.

Biomarkers are widely used in ecotoxicology as indicators of exposure to toxicants. However, their ability to provide ecologically relevant information remains controversial. One of the major problems is understanding if the measured responses are determined by stress factors or lie within the natural variability range. In a previous work, the natural variability of enzymatic levels in invertebrates sampled in pristine rivers was proved to be relevant across both space and time. In this work, the experimental design was improved by considering different life stages of the selected taxa and by measuring more environmental parameters. The experimental design considered: sampling sites in two different rivers; eight sampling dates covering the whole seasonal cycle; four species from three different taxonomic groups (Plecoptera: Perla grandis; Ephemeroptera: Baetis alpinus and Epeorus alpicula; Tricoptera: Hydropsyche pellucidula); different life stages for each species; four enzymes: acetylcholinesterase, glutathione-S-transferase, alkaline phosphatase, and catalase. Biomarkers levels were related to environmental (physico-chemical) parameters to verify any kind of dependence. Data were statistically elaborated using hierarchical multilevel Bayesian models. Natural variability was found to be relevant across both space and time. The results of the present study proved that care should be paid when interpreting biomarker results. Further research is needed to better understand the dependence of the natural variability on environmental parameters. This article is protected by copyright. All rights reserved

Predictive models for machining operations have been significantly improved through numerous methods in recent decades. This study proposed a 3D finite element modeling (3D FEM) approach for the micro end-milling of Al6061-T6. Finite element (FE) simulations were performed under different cutting conditions to obtain realistic numerical predictions of chip flow, burr formation, and cutting forces. FE modeling displayed notable advantages, such as capability to easily handle any type of tool geometry and any side effect on chip formation, including thermal aspect and material property changes. The proposed 3D FE model considers the effects of mill helix angle and cutting edge radius on the chip. The prediction capability of the FE model was validated by comparing numerical model and experimental test results. Burr dimension trends were correlated with force profile shapes. However, the FE predictions overestimated the real force magnitude. This overestimation indicates that the model requires further development.

The effect of pesticide mixtures and electromagnetic fields were evaluated on honeybees in three experimental sites located in northern Italy: a control site far from anthropogenic stress sources, a semi-natural site close to a high voltage electric line and an agricultural site with intensive pesticide treatments. From each experimental site, young workers and foraging bees were taken monthly from May to October and analysed for four enzymatic biomarkers: acetylcholinesterase (AChE), catalase (CAT), glutathione S-transferase (GST) and alkaline phosphatase (AP). Results revealed timeand site-specific effects in respect to control site, confirming the role of biomarkers as diagnostic and early-warning tools for multi-stress sources on honeybees. In the electromagnetic-stress site an effect of an over-activation of all analyzed biomarkers was observed at the end of the season. According to other literature findings, this event was related to a behavioral over-activation in a period in which bees should prepare themselves to overwintering. This finding poses potential problems to winter survival. In the pesticide-stress site, different pesticide-induced responses were identified. We demonstrated in the field that pesticide mixtures, currently used in agriculture, were able to greatly affect biochemical parameters of bees (with both enzymatic under- and over-activations).

The manufacturing of metallic micro multi-lumen tubes of high length to diametrical aspect ratio for biomedical and multi-fluidic applications is still a challenge for the current manufacturing methods. The recent research advancements suggested metal particles loaded feedstock extrusion processing as a highly promising method for manufacturing metallic micro multi-lumen tubes where conventional metal extrusion and other feedstock processing technologies are constrained. Feedstock extrusion of micro multi-lumen tubes was inhibited by the absence of understanding on extrusion behavior of feedstocks for attaining high aspect ratio parts. The feedstock micro extrusion processing also experienced difficulties in maintaining the geometrical accuracy and surface finish due to lack of knowledge on influence of extrusion parameters on the properties of the extruded parts and absence of a quality control strategy during extrusion. In this research work, the effect of feedstock extrusion parameters on the dimensional variation as well as surface finish of the extruded multi-lumen tubes are studied by extruding high aspect ratio micro bi-lumen tubes using biocompatible grade 17-4PH stainless steel feedstock. A methodology called ‘product fingerprint’ combined with multi-objective optimization on the basis of ratio analysis (MOORA) method has been studied to assure the quality of the tubes in-line by identifying and monitoring very specific features of the tubes at optimum process conditions. The study showed that extrusion parameters such as extrusion temperature and screw speed have significant influence on diameters, roundness of the tube as well as lumens and the surface roughness. High aspect ratio bi-lumen tubes of optimum dimensional quality with an average green state areal surface roughness value of 1.97 μm were achieved at optimum process parameters levels. This research demonstrated how to manufacture micro bi-lumen tubes made of 17-4PH stainless steel with unrestricted length and even more, control their quality by monitoring couple of identified product fingerprint features of bi-lumen tube, such as external diameter of tube as well as its roundness and varying the process parameters.

Automotive lighting applications require mold micro-features with increasingly better surface finishing, especially for optical lenses and retroreflectors. In this work innovative micromilling experiments were conducted on electroless-plated nickel phosphorous (NiP) surfaces to fabricate a mold for prismatic retroreflectors. Cutting parameters effects on surface topography of mold micro-features were experimentally characterized and optimized, monitoring moreover the cutting forces generated by NiP micromilling. Furthermore, the mold surface topography was replicated on polycarbonate injection molded retroreflectors and its effects on their optical performance was characterized by means of a dedicated spectrophotometric technique. The obtained results show that micromilling of electroless-plated NiP can substitute polishing in the fabrication of high surface finish mold micro-features.

In the growing Industry 4.0 market, there is strong need to implement automatic inspection methods to support manufacturing processes. Tool wear in turning is one of the biggest concerns that most expert operators are able to indirectly infer through the analysis of the removed chips. Automatising this operation would enable developing more efficient cutting processes that turns in easier process planning management toward the Zero Defect Manufacturing paradigm. This paper presents a deep learning approach, based on image processing applied to turning chips for indirectly identifying tool wear levels. The procedure extracts different indicators from the RGB and HSV image channels and instructs a neural network for classifying the chips, based on tool state conditions. Images were collected with a high-resolution digital camera during an experimental cutting campaign involving tool wear analysis with direct microscope imaging. The sensitivity analysis confirmed that the most sensible image channels are the hue valueHthat were used to teach the network, leading to performances in the range of 95 of proper classification. The feasibility of the deep learning approach for indirectly understanding the tool wear from the chip colour characterisation is confirmed. However, due to the big effects on chip colours of variables as the workpiece material and cutting process parameters, the applicability is limited to stable production flows. An industrial implementation can be foreseen by populating proper large databases and by implementing real-time chip segmentation analysis.

The micro-extrusion of feedstock is a promising and emerging technology for manufacturing very high length to thickness aspect ratio metallic microcomponents which are not feasible for conventional metal processing methodologies or commonly used feedstock processing technologies. Extrusion of high aspect ratio microcomponents using metallic feedstock confronts the challenges of achieving a continuous extrusion without any breakage, the geometrical accuracy, surface finish and structural properties for the component which are required for the micro-application, during micro-extrusion process. The type of metallic powder, powder size, type of binder, and binder properties are very decisive in making the extrusion process feasible for the micro-application. The influence of feedstock properties on micro-extrusion of high aspect ratio microcomponents are still unknown in case of micro-extrusion of feedstock. In this research work, the effect of type of feedstock on micro-extrusion is studied by extruding microbi-lumen tubes using biocompatible steel feedstocks AISI316 L and 17-4PH at two different aging states (no aging and 1.5 years aging). The geometrical features of the extruded bi-lumen tubes, surface roughness and structural properties are analyzed using three-dimensional (3D) focus variation microscopy, differential scanning calorimetry (DSC) and scanning electron microscopy (SEM). The analysis showed that feedstock type affects the feasibility of extrusion and geometrical size to a great extent. An average Sa roughness deviation from 1.73 to 4.57 μm was observed for feedstocks 17-4PH and AISI316 L. The study also confirms that binder properties and aging of the feedstocks also have to be taken into account for maintaining the surface finish and structural properties in case of metallic feedstock extrusion of high aspect ratio bi-lumen tubes.

This work investigates the micro-milling machinability of Ti-6Al-4V alloy produced by a Laser Engineered Net Shaping (LENS) additive manufacturing (AM) process with a specific focus on surface quality, cutting forces and burr formation. The effects of additive deposition parameters are also investigated since the material thermal history during processing can affect porosity and mechanical behavior of the samples, giving different milling performances. The material characterization of samples is done through micrographies, hardness tests and porosity evaluation. The roughness of the machined surfaces shows a statistical distinction between the AM and wrought titanium samples. Similar behavior is seen with the cutting forces, which increase with an increase of hardness of the AM samples. The results also show an increased trend towards burr formation in case of down milling of AM samples compared to wrought titanium samples. The future prospective is to take into account the machinability properties as functional material characteristics to optimize through the deposition process.

Dead metal cap plays an important role in the microcutting process because target material piled up on the tool–chip–workpiece interface can alter the cutting geometry. The target of this study is to model and simulate the micro-orthogonal cutting process in the presence of dead metal cap in order to investigate the effects of this phenomenon on the micromachining process outputs (cutting force, thrust force and chip thickness) and stress distribution, equivalent plastic strain and temperature inside the workpiece shear zones. For this purpose, the finite element method with explicit dynamic solution and adiabatic heating effect along with arbitrary Lagrangian–Eulerian approach is used. It is shown that the finite element models with current state-of-the-art assumptions cannot take into account the dead metal cap by default. For this reason, dead metal cap is artificially introduced on the rounded tool edge in this study for carrying out a proper analysis. Several simulations with different dead metal cap geometries are performed and obtained results show that prediction of cutting force, thrust force and chip thickness are sensitive to the presence of dead metal cap and its geometry. Micro-orthogonal cutting experiments are carried out on tubular AISI 1045 workpieces for validating and interpreting simulated results. The error between predicted and experimental data is calculated, and it is shown that simulation performances can be improved by considering the dead metal cap into the process model. For example, it is possible to reduce the error to less than 5% in case of thrust force prediction. This study points out how the target material’s Von Mises stress, equivalent plastic strain and temperature distribution are sensitive to any alteration of the edge geometry due to the dead metal cap. The best dead metal cap configuration in terms of agreement with experiments is also the one introducing a more homogeneous distribution of these quantities along the shear plane.

Diesel combustion and solid biomass burning are the major sources of ultrafine particles (UFP) in urbanized areas. Cardiovascular and pulmonary diseases, including lung cancer, are possible outcomes of combustion particles exposure, but differences in particles properties seem to influence their biological effects. Here the physico-chemical properties and biological effects of diesel and biomass particles, produced under controlled laboratory conditions, have been characterized. Diesel UFP were sampled from a Euro 4 light duty vehicle without DPF fuelled by commercial diesel and run over a chassis dyno. Biomass UFP were collected from a modern automatic 25 kW boiler propelled by prime quality spruce pellet. Transmission electron microscopy (TEM) and scanning electron microscopy (SEM) images of both diesel and biomass samples showed aggregates of soot particles, but in biomass samples ash particles were also present. Chemical characterization showed that metals and PAHs total content was higher in diesel samples compared to biomass ones. Human bronchial epithelial (HBEC3) cells were exposed to particles for up to 2 weeks. Changes in the expression of genes involved in xenobiotic metabolism were observed after exposure to both UFP already after 24 h. However, only diesel particles modulated the expression of genes involved in inflammation, oxidative stress and epithelial-to-mesenchymal transition (EMT), increased the release of inflammatory mediators and caused phenotypical alterations, mostly after two weeks of exposure. These results show that diesel UFP affected cellular processes involved in lung and cardiovascular diseases and cancer. Biomass particles exerted low biological activity compared to diesel UFP. This evidence emphasizes that the study of different emission sources contribution to ambient PM toxicity may have a fundamental role in the development of more effective strategies for air quality improvement.

Air pollution mostly originating from car exhaust and industrial emissions is seriously endangering human health. The study of toxic effects of particulate matter (PM) is a subject of very active research that covers a broad field from biology to chemistry and technology. The main issue of these works is the understanding of the oxidative properties of PM. In this paper, we present a quantitative analytical method based on the resonance Raman spectroscopy of cytocrome c that can be used to monitor the oxidative reactions that may take place between biological samples and PM. Copyright © 2016 John Wiley & Sons, Ltd.

A checklist of the sparid fishes of the world is presented. The checklist contains 166 valid species, 260 synonyms, including 26 that are here recognized as new, and 19 unplaced nominal species. Seven nominal species recorded as sparid in the Eschmeyer's Catalog of Fishes are here recognized to belong to different families and among them three nominal species predate well established fish names and are here declared nomina oblita. A list of unavailable names is also included.

In the current industry, fabrication of metallic and ceramic artifacts by means of feedstock extrusion additive manufacturing is receiving attention because of the capacity of this technology to deal with low costs and materials that possess a low Additive Manufacturability Index when treated with high power beam technologies. However, the extrusion additive manufacturing lacks in achievable accuracy and productivity therefore techniques that can improve the overall performances are required to increase the impact that this technology can have on industry. This paper demonstrates how extrusion additive technology of metals and ceramics can be enhanced by integrating green-state milling into the manufacturing cycle. In the hybrid cycle, the additive and subtractive processes act alternatively on the green-state part to shape its near-net form. This work shows how this innovative method, that integrates cutting and micro-cutting operations on the feedstock, allows compensating the lack of accuracy and micro reachability that characterize the extrusion-based additive manufacturing method. In the manuscript, the promising aspects of the hybrid concept are presented and discussed. Some examples of manufactured parts are illustrated showing how complex geometries, with good surface quality can be addressed with higher production flexibility. The developed hybrid machine prototype adopted for that scope is described along with the AISI316L parts that are obtained by depositing, green-state milling, debinding and sintering the feedstock. Another contribution is provided regarding the feedstock machinability that is studied under different cutting conditions. The feasibility of the hybrid implementation is confirmed and future steps to improve the process are discussed.

Automatic visual inspection methods for product quality checking are spreading more and more in the present 4.0 manufacturing industry. This paper addresses the automatic inspection of edge integrity in accurate holes obtained by direct drilling of cemented carbide with innovative diamond coated tools. These revolutionary cutting tools, recently appeared on the market, can process extremely hard carbide in the sintered state, with massive increase of productivity with respect to standard methodologies like electrical discharge machining (EDM). However, due to the brittleness of the materials, the mechanical cutting process becomes critical and sensitive to tool breakage and workpiece defects generation. In particular, chipping of the hole edges represents one of the most important issues to monitor and take under control. A software procedure, that analyses high-resolution images taken from optical microscopes, was then developed for that aim. Image processing algorithms were designed and applied to enable the automatic extraction of the holes profile, thus permitting the identification and quantification of the leading edge damage in the radial direction. The proposed approach is fully automatic and is based on a profile segmentation that exploits an edge detection algorithm followed by a contour extraction method based on the solution of a partial differential equation. Dedicated metrics were specifically developed to evaluate the extracted profiles. The approach was validated with a factorial plane involving 1.6 mm diameter holes generated with different cutting parameters and tools on tungsten-carbide (WC) material. The technique resulted suitable for the aim, enabling the automatic characterisation of the defects generation phenomenon throughout the entire tools life. This moves a step toward the implementation of both in-line hole inspection procedures and advanced drilling process control.

Injection pressure is one of the most significate factor governing the effectiveness of Molding based manufacturing processes. Being the monitoring of injection pressure easy to implement, the opportunity to address quality control on injection pressure as manufacturing fingerprint opens up to the possibility of implementing online process control solutions for Industry 4.0 approaches; examples are machine learning, deep learning and artificial intelligence. For the purpose, the calibration of process fingerprints with a quality feature of the final part is required. In this study, the injection pressure is assessed in different Injection Molding and Injection Compression Molding process conditions when replicating a polymer microstructured optical part [1]. The study case presents a high clarity polymer Fresnel lens showing a square aperture with varying low aspect ratio features. Grooves step height size ranges from 17.3 μm to 346.6 μm for peak-to-valley (PV) while the pitch has a constant value of 748.1 μm. Absolute dimensions of the grooves, as long as global part mass, are investigated in varying compression gap and holding pressure levels. Defining relationship between the geometrical dimensions of the micro structures, global mass and process fingerprint is the main outcome of this research work.

Injection Moulding (IM) and Injection Compression Moulding (ICM) are the leading process technologies to enable mass manufacturing of Fresnel lenses. Even though ICM requires a more expensive and complex process, it is proven to lead to higher optical performances in comparison with IM. In this study, tolerancing for ICM and IM addresses the geometrical accuracy and precision of the two manufacturing processes when micro structures of Fresnel lens surfaces are taken into account.

Complex shaped stainless steel tubes are often required for special purpose biomedical equipment. Nevertheless, traditional manufacturing technologies, such as extrusion, lack the ability to compete in a market of customized complex components because of associated expenses towards tooling and extrusion presses. To rapid manufacture few of such components with low cost and high precision, a new Extrusion based Additive Manufacturing (EAM) process, is proposed in this paper, and as an example, short stainless steel 316L complex shaped and sectioned tubes were prepared by EAM. Several sample parts were produced using this process; the dimensional stability, surface roughness and chemical composition of sintered samples were investigated to prove process competence. The results indicate that feedstock with a 316L particle content of 92.5 wt. % can be prepared with a sigma blade mixing, whose rheological behavior is fit for EAM. The green samples have sufficient strength to handle them for subsequent treatments. The sintered samples considerably shrunk to designed dimensions and have a homogeneous microstructure to impart mechanical strength. Whereas, maintaining comparable dimensional accuracy and chemical composition which are required for biomedical equipment still need iterations, a kinematic correction and modification in debinding cycle was proposed.

The evaluation of micromilled parts quality requires detailed assessments of both geometry and surface topography. However, in many cases, the reduced accessibility caused by the complex geometry of the part makes it impossible to perform direct measurements. This problem can be solved by adopting the replica molding technology. The method consists of obtaining a replica of the feature that is inaccessible for standard measurement devices and performing its indirect measurement. This paper examines the performance of a commercial replication media applied to the indirect measurement of micromilled components. Two specifically designed micromilled benchmark samples were used to assess the accuracy in replicating both surface texture and geometry. A 3D confocal microscope and a focus variation instrument were employed and the associated uncertainties were evaluated. The replication method proved to be suitable for characterizing micromilled surface texture even though an average overestimation in the nano-metric level of the Sa parameter was observed. On the other hand, the replicated geometry generally underestimated that of the master, often leading to a different measurement output considering the micrometric uncertainty.

Understanding the micro milling phenomena involved in the process is critical and difficult through physical experiments. This study presents a 3D finite element modeling (3D FEM) approach for the micro end-milling process on Al6082-T6. The proposed model employs a Lagrangian explicit finite element formulation to perform coupled thermo-mechanical transient analyses. FE simulations were performed at different cutting conditions to obtain realistic numerical predictions of chip formation, temperature distribution, and cutting forces by considering the effect of tool run-out in the model. The radial run-out is a significant issue in micro milling processes and influences the cutting stability due to chip load and force variations. The Johnson–Cook (JC) material constitutive model was applied and its constants were determined by an inverse method based on the experimental cutting forces acquired during the micro end-milling tests. The FE model prediction capability was validated by comparing the numerical model results with experimental tests. The maximum tool temperature was predicted in a different angular position of the cutter which is difficult or impossible to obtain in experiments. The predicted results of the model, involving the run-out influence, showed a good correlation with experimental chip formation and the signal shape of cutting forces.

In micro injection molding the quality of 3D complex parts is influenced by the efficiency of the ejection phase. During demolding, the forces taking place at the component-tool interface, due to adhesion and friction, need to be overcome preserving the integrity of the part. This issue is severe in the case of molds characterized by the presence of several deep cores, which are used to manufacture interconnecting through holes in multi-layer microfluidic devices. In this work, the impact of the micro milling cutting strategy on the demolding forces was investigated, using a critical cavity geometry, specifically designed to this purpose. The relation between mold micro manufacturing and the micro injection molding process was studied with the aim of optimizing the demolding phase. The topographies of micro-milled mold surfaces and the molded parts were characterized and different roughness profile parameters were taken in consideration. The results of in-line force acquisitions indicated that the effects of the micro milling strategy on the demolding force is markedly higher than those of micro injection molding process variables. Moreover, the experimental analysis indicated that a combination of worst surface finishing and low viscosity of the molding polymer can result in higher interface interlocking and thus in critical stresses applied to the part during the demolding phase.

Biomarkers have been widely employed in ecotoxicology as early warning indicators of exposure to toxicants. Very often, they are used to compare reference and polluted sites, or to analyse time trends. However, very few studies focus on the natural variability range of biomarkers in the environment, which is pivotal to understand if the detected differences are actually determined by any adverse effects due to pollution. This work assesses the natural spatio-temporal variability of some enzymatic levels, frequently used as biomarkers, in freshwater benthic invertebrates. The influence of some environmental parameters on the enzymatic levels was also evaluated. Three families of insect larvae (Perlidae, Baetidae, and Heptageniidae) were sampled in three pristine streams and in eight different dates. Four enzymes (acetylcholinesterase, glutathione-S-transferase, alkaline phosphatase, and catalase) were measured. The natural variability of enzymatic levels was often significant in all considered species across both space and time. The observed pattern was poorly explained by the monitored environmental parameters. The results of this work show that great care should be paid when interpreting monitoring data in which biomarker levels are measured and compared among sites or dates. Presuming that measured differences are due to anthropogenic factors can be misleading, when other potentially influencing factors have not been accounted for.

Accuracy of micromilled molds play an important role in complex process chains enabling mass production of polymer micro components, such as lab-on-chips, fabricated by micro injection molding. Surface footprint of micromilling is defined as the technological signature left by machining process on the generated mold surface. This is sensitive to selected tools and machining parameters and, when not controlled properly, can badly affect mold topography and functionality (e.g. part demoldability). In case of complex mold geometry, the impact of micromilling footprint increases, in particular during the demolding phase due to the friction generated by the polymer shrinking around cores. This work studies these effects on molds characterized by sub-millimetric cylindrical cores. A physical and statistical modeling was developed to provide deep insights about the effects of milling strategies and cutting parameters on the generated footprint on the mold cores. These effects are investigated by machining cylindrical pins whose roughness and surface form errors, caused by static deflection of tool and parts, were controlled in the range of Sa = 150–400 μm and ΔRmax = 1–10 μm (profile radial deviation), respectively. Micro injection molding experiments proved that mold topography has a relevant effect on the ejection force. The demolding force generated by a specifically developed polystyrene micro part reached the highest value with the mold machined with the most unfavorable milling conditions. Proper controlling of machine parameters and conditions led to a reduction greater than 60% of the demolding force peak, confirming the feasibility of the conjunct approach to processes optimization. The results of this work move a step forward into the integrated optimization of micro manufacturing process chains.

As equivalent stiffness and damping of the grinding process dominate cutting stability, their identification is essential to predict and avoid detrimental chatter occurrence. The identification of these process constants is not easy in large cylindrical grinding machines, e.g. roll grinders, since there are no practical ways to measure cutting force normal component. This paper presents a novel frequency domain approach for identifying these process parameters, exploiting in-process system response, measured via impact testing. This method adopts a sub-structuring approach to couple the wheel-workpiece relative dynamic compliance with a two-dimensional grinding force model that entails both normal and tangential directions. The grinding specific energy and normal force ratio, that determine grinding stiffness and damping, are identified by fitting the closed loop FRF (Frequency Response Function) measured during specific plunge-grinding tests. The fitting quality supports the predictive capability of the model. Eventually, the soundness of the proposed identification procedure is further assessed by comparing the grinding specific energy identified through standard cutting power measurements.