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Duplex stainless steels are being used on applications that require, especially, high corrosion resistance and overall good mechanical properties, such as the naval and oil-gas exploration industry. The components employed in these industries are usually obtained by machining, however, these alloys have low machinability when compared to conventional stainless steels. In this work, a study of the wear developed when milling duplex stainless-steel, LDX 2101, is going to be presented and evaluated, employing four types of milling tools with different geometries and coatings, while studying the influence of feed rate and cutting length in the wear of these tools. Tools used have been provided with two and four flutes, as well as three different coatings, namely: TiAlN, TiAlSiN and AlCrN. The cutting behavior of these tools was analyzed; data relative to the cutting forces developed during the process were obtained; and roughness measurements of the machined surfaces were executed. The tools were then submitted to scanning electron microscope (SEM) analysis, enabling the identification of the wear mechanisms that tools were subjected to when machining this material, furthermore, the early stages of these mechanisms were also identified. All this work was done with the goal of relating the machining parameters and cutting force values obtained, identifying, and discussing the wear patterns that were observed in the coating and tools after the milling tests, providing further information on the machining of these alloys., The present work was done and funded under the scope of the project ON-SURF (ANI | P2020 | POCI-01-0247-FEDER-024521, co-funded by Portugal 2020 and FEDER, through COMPETE 2020-Operational Programme for Competitiveness and Internationalisation. F.J.G. Silva also thanks INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Indústria, due to its support. The authors would like to thanks to Dr. Rui Rocha from CEMUP (Porto, Portugal), due to his active collaboration in getting the best SEM pictures, helping with his critical analysis of some phenomena. Authors also would like to thank Ing. Ricardo Alexandre due to is extremely important role in providing all the coatings through TEandM company, and also Ing. Nuno André, for providing the substrate material and uncoated tools through the Inovatools company.

Microscale abrasion has been intensively used to study the wear behavior o several hard coatings, enabling the observation of different wear mechanisms. Recently, a study arguing whether the surface texture of the ball could influence the dynamics of abrasive particles throughout the contact was presented. In this work, the influence of the abrasive particles concentration able to change the texture of the ball was studied to understand its influence on the wear modes—rolling or grooving. Thus, tests were carried out using samples with a thin coating of TiN, deposited using the Physical Vapor Deposition (PVD) technique, and AISI 52100 steel balls etched over 60 s to induce a change in their texture and roughness were used. Three abrasive slurries were prepared with black silicon carbide (SiC) particles (average particle size of 4 μm) with different concentrations, 0.25, 0.35, and 0.45 g/cm3. The rotation speed used in the tests was 80 rpm and the normal loads applied in the study were 0.2 N and 0.5 N, and 1 N. After the wear tests, the coated samples and tracks on the surface of the balls were observed by SEM and 3D microscopy to understand the abrasive particle dynamics, evaluating the wear mode transition as well as the function of both applied load and slurry concentration. The tracks in the balls showed particles embedded on their surface. A lower concentration of abrasion was conducted to higher specific wear rate. Moreover, a predominant two-body wear mechanism was induced when the abrasive concentration was increased. There was an increase in the roughness of the scar and the surface of the balls with an increase in the abrasive particles’ concentration.

Abrasive wear is a wear mechanism that results in a loss of material from the interaction of a surface with hard particles. This type of wear is frequently found in the surface of machining tools. Microscale abrasion equipment is often used to characterize the resistance to abrasive wear of a surface. The different parameters able to control micro-abrasion wear tests, such as ball rotation, sliding distance between ball and surface sample, abrasive slurry concentration, normal load acting on the sample, and abrasive flow rate over the sample, have been widely studied. The combination of different variables, including sliding distance, concentration of abrasive particles, their hardness, and size of abrasive particles, promotes the transition between two-body, three-body, or mixed abrasive wear modes. However, the influence of the ball surface on the dragging of abrasive particles, which is reflected in the wear modes, is still poorly studied. One of the variables possible to control and less studied is the influence of the ball surface texture on the dragging of abrasive particles in micro-abrasion wear tests. This work intends to correlate the effect of different testing times (500, 1000, and 1500 cycles) and different concentrations of 3 μm Al2O3 abrasive slurry (25, 35, and 45 g/100 mL) on the micro abrasion resistance of a TiN thin coating film, using balls of AISI 52100 steel whose texture and roughness were prepared by 60 s chemical etching. The rotation speed of each test was 80 rpm, applying a normal load of 2 N. Subsequently, the craters were carefully analyzed using SEM to evaluate the transition of the wear mode as a function of the applied load, the abrasive particle concentration, and the sliding distance. The textured ball tracks were observed via SEM to assess the particle dynamics. The results showed that, contrarily to what is reported in the literature regarding wear modes where rolling is promoted with increasing abrasive concentration, in this work grooving took place instead. This is a result of the rough balls use in the experiments which, due to the embedment of abrasive particles in the ball grooves, promotes the abrasion mechanism. The higher the abrasive concentration, the higher the grooving mechanism, since more particles are available to scratch the surface.

The use of disinfection and cleaning chemicals in several municipal facilities, such as swimming pools and drinking water treatment plants, causes the degradation of various types of wood, which leads to failures in equipment and the corresponding need for maintenance. This degradation creates added costs for municipalities, as well as the closure of certain facilities due to curative or preventive maintenance and, in many cases, public health issues, due to the water being contaminated with deteriorating products. Through a thorough study of the degradation effect on the products, more resistant materials can be found which are able to withstand these adversities and increase the lifespan of wood in regular contact with chemical agents. This is achievable by the determination of the cost-effectiveness of the substitute material to replace these components with alternative ones, with properties that better resist the deterioration effects promoted by aggressive environments. No studies have been found so far strictly focused on this matter. The objective of this study is to evaluate the degradation presented by two types of wood, beech and oak, which are exposed to the action of chlorine in municipal facilities. This degradation varies according to the chlorine content and the materials’ time of contact with the chemical agent, allowing the selection of new materials which will provide an extended lifetime of the components, reducing maintenance drastically, as well as costs for the facilities and the risk to public health. The performed experimental tests have shown that the oak wood has the best results regarding chlorine degradation resistance.

Although additive manufacturing is gaining prominence in the market, many applications require very high levels of precision, which are currently not attainable by additive manufacturing [...]

Inconel 718 is a highly valued material in the aerospace and nuclear industries due to the fact of its exceptional properties. However, the processing of this material is quite difficult, especially through machining processes. Machining this material results in rapid tool wear, even when low material removal rates are considered. In this study, instrumented turning experiments were employed to evaluate the machinability of Inconel 718 alloy using PCBN tools while assessing the usage of two distinct binder phases, TiN and TiC, for those cutting tools. It was found that the tool life was highly sensitive to the cutting speeds but also affected by the workpiece mechanical properties. At lower cutting speeds, notch wear significantly impacted the tool integrity, whereas at higher cutting speeds, flank wear was the primary failure mode of the tool. The flank wear of the tools with TiN-based binder outperformed TiC by almost 30%, presenting a more consistent behavior when machining.

Due to Inconel 718’s high mechanical properties, even at higher temperatures, tendency to work-harden, and low thermal conductivity, this alloy is considered hard to machine. The machining of this alloy causes high amounts of tool wear, leading to its premature failure. There seems to be a gap in the literature, particularly regarding milling and finishing operations applied to Inconel 718 parts. In the present study, the wear behavior of multilayered PVD HiPIMS (High-power impulse magnetron sputtering)-coated TiN/TiAlN end-mills used for finishing operations on Inconel 718 is evaluated, aiming to establish/expand the understanding of the wear behavior of coated tools when machining these alloys. Different machining parameters, such as cutting speed, cutting length, and feed per tooth, are tested, evaluating the influence of these parameters’ variations on tool wear. The sustained wear was evaluated using SEM (Scanning electron microscope) analysis, characterizing the tools’ wear and identifying the predominant wear mechanisms. The machined surface was also evaluated after each machining test, establishing a relationship between the tools’ wear and production quality. It was noticed that the feed rate parameter exerted the most influence on the tools’ production quality, while the cutting speed mostly impacted the tools’ wear. The main wear mechanisms identified were abrasion, material adhesion, cratering, and adhesive wear. The findings of this study might prove useful for future research conducted on this topic, either optimization studies or studies on the simulation of the milling of Inconel alloys, such as the one presented here.

Many municipal facilities, such as pools and drinking water treatment facilities, are subject to ongoing maintenance due to the corrosion of their metallic materials caused by chlorine, leading to high costs and a possible risk to public health. A proper study of the employed product’s effect could lead to the use of better materials, which significantly increase the lifetime of metallic equipment more attacked by corrosion, through studies evaluating their cost-effectiveness. This paper was carried out with the objective of studying the degradation of some metallic materials (AISI 316L, AISI 321 and Duplex 14462) used in the referred facilities in order to select the one that possessed a better behavior. It was observed that the introduction of some more adequate materials can drastically reduce maintenance operations, with Duplex 14462 showing the best results, ideal for greater chlorine concentrations, followed by AISI 321, which may be employed for components in less contact with chlorine, since it is more easily affordable.

Nickel-based superalloys, namely INCONEL® variants, have had an increase in applications throughout various industries like aeronautics, automotive and energy power plants. These superalloys can withstand high-temperature applications without suffering from creep, making them extremely appealing and suitable for manufactured goods such as jet engines or steam turbines. Nevertheless, INCONEL® alloys are considered difficult-to-cut materials, not only due to their superior material properties but also because of their poor thermal conductivity (k) and severe work hardening, which may lead to premature tool wear (TW) and poor final product finishing. In this regard, it is of paramount importance to optimise the machining parameters, to strengthen the process performance outcomes concerning the quality and cost of the product. The present review aims to systematically summarize and analyse the progress taken within the field of INCONEL® machining sensitively over the past five years, with some exceptions, and present the most recent solutions found in the industry, as well as the prospects from researchers. To accomplish this article, ScienceDirect, Springer, Taylor & Francis, Wiley and ASME have been used as sources of information as a result of great fidelity knowledge. Books from Woodhead Publishing Series, CRC Press and Academic Press have been also used. The main keywords used in searching information were: “Nickel-based superalloys”, “INCONEL® 718”, “INCONEL® 625” “INCONEL® Machining processes” and “Tool-wear mechanisms”. The combined use of these keywords was crucial to filter the huge information currently available about the evolution of INCONEL® machining technologies. As a main contribution to this work, three SWOT analyses are provided on information that is dispersed in several articles. It was found that significant progress in the traditional cutting tool technologies has been made, nonetheless, the machining of INCONEL® 718 and 625 is still considered a great challenge due to the intrinsic characteristics of those Ni-based-superalloys, whose machining promotes high-wear to the tools and coatings used.

Additive manufacturing is defined as a process based on the superposition of layers of materials in order to obtain 3D parts; however, the process does not allow achieve the adequate and necessary surface finishing. In addition, with the development of new materials with superior properties, some of them acquire high hardness and strength, consequently decreasing their ability to be machined. To overcome this shortcoming, a new technology assembling additive and subtractive processes, was developed and implemented. In this process, the additive methods are integrated into a single machine with subtractive processes, often called hybrid manufacturing. The additive manufacturing process is used to produce the part with high efficiency and flexibility, whilst machining is then triggered to give a good surface finishing and dimensional accuracy. With this, and without the need to transport the part from one machine to another, the manufacturing time of the part is reduced, as well as the production costs, since the waste of material is minimized, with the additive–subtractive integration. This work aimed to carry out an extensive literature review regarding additive manufacturing methods, such as binder blasting, directed energy deposition, material extrusion, material jetting, powder bed fusion, sheet laminating and vat polymerization, as well as machining processes, studying the additive-subtractive integration, in order to analyze recent developments in this area, the techniques used, and the results obtained. To perform this review, ScienceDirect, Web of Knowledge and Google Scholar were used as the main source of information because they are powerful search engines in science information. Specialized books have been also used, as well as several websites. The main keywords used in searching information were: “CNC machining”, “hybrid machining”, “hybrid manufacturing”, “additive manufacturing”, “high-speed machining” and “post-processing”. The conjunction of these keywords was crucial to filter the huge information currently available about additive manufacturing. The search was mainly focused on publications of the current century. The work intends to provide structured information on the research carried out about each one of the two considered processes (additive manufacturing and machining), and on how these developments can be taken into consideration in studies about hybrid machining, helping researchers to increase their knowledge in this field in a faster way. An outlook about the integration of these processes is also performed. Additionally, a SWOT analysis is also provided for additive manufacturing, machining and hybrid manufacturing processes, observing the aspects inherent to these technologies., The present work was done and funded under the scope of the projects ON-SURF (ANI | P2020 | POCI-01-0247-FEDER-024521 and MCTool21 “Manufacturing of cutting tools for the 21st century: from nano-scale material design to numerical process simulation” (ref.: “POCI-01-0247- FEDER-045940”) co-funded by Portugal 2020 and FEDER, through COMPETE 2020-Operational Programme for Competitiveness and Internationalisation. This work is also sponsored by FEDER National funds FCT under the project CEMMPRE ref. “UIDB/00285/2020”. F.J.G. Silva also thanks INEGI-Instituto de Ciência e Inovação em Engenharia Mecânica e Engenharia Indústria due to its support.

One of the most critical factors in producing plastic injection molds is the cost estimation of machining services, which significantly affects the final mold price. These services’ costs are determined according to the machining time, which is usually a long and expensive operation. If it is considered that the injection mold parts are all different, it can be understood that the correct and quick estimation of machining times is of great importance for a company’s success. This article presents a proposal to apply artificial neural networks in machining time estimation for standard injection mold parts. For this purpose, a large set of parts was considered to shape the artificial intelligence model, and machining times were calculated to collect enough data for training the neural networks. The influences of the network architecture, input data, and the variables used in the network’s training were studied to find the neural network with greatest prediction accuracy. The application of neural networks in this work proved to be a quick and efficient way to predict cutting times with a percent error of 2.52% in the best case. The present work can strongly contribute to the research in this and similar sectors, as recent research does not usually focus on the direct prediction of machining times relating to overall production cost. This tool can be used in a quick and efficient manner to obtain information on the total machining cost of mold parts, with the possibility of being applied to other industry sectors.