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The critical applications of difficult-to-machine Inconel 617 (IN617) compel the process to be accurate enough that the requirement of tight tolerances can be met. Electric discharge machining (EDM) is commonly engaged in its machining. However, the intrinsic issue of over/undercut in EDM complicates the achievement of accurately machined profiles. Therefore, the proficiency of deep cryogenically treated (DCT) copper (Cu) and brass electrodes under modified dielectrics has been thoroughly investigated to address the issue. A complete factorial design was implemented to machine a 300 µm deep impression on IN617. The machining ability of DCT electrodes averagely gave better dimensional accuracy as compared to non-DCT electrodes by 13.5% in various modified dielectric mediums. The performance of DCT brass is 29.7% better overall compared to the average value of overcut (OC) given by DCT electrodes. Among the non-treated (NT) electrodes, the performance of Cu stands out when employing a Kerosene-Span-20 modified dielectric. In comparison to Kerosene-Tween-80, the value of OC is 33.3% less if Kerosene-Span-20 is used as a dielectric against the aforementioned NT electrode. Finally, OC's nonlinear and complex phenomena are effectively modeled by an artificial neural network (ANN) with good prediction accuracy, thereby eliminating the need for experiments.
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[This corrects the article DOI: 10.1007/s40964-022-00373-9.].
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Despite the extensive research, the moisture-based degradation of the 3D-printed polypropylene and polylactic acid blend is not yet reported. This research is a part of study reported on partial biodegradable blends proposed for large-scale additive manufacturing applications. However, the previous work does not provide information about the stability of the proposed blend system against moisture-based degradation. Therefore, this research presents a combination of excessive physical interlocking and minimum chemical grafting in a partial biodegradable blend to achieve stability against in-process thermal and moisture-based degradation. In this regard, a blend of polylactic acid and polypropylene compatibilized with polyethylene graft maleic anhydride is presented for fused filament fabrication. The research implements, for the first time, an ANOVA for combined thermal and moisture-based degradation. The results are explained using thermochemical and microscopic techniques. Scanning electron microscopy is used for analyzing the printed blend. Fourier transform infrared spectroscopy has allowed studying the intermolecular interactions due to the partial blending and degradation mechanism. Differential scanning calorimetry analyzes the blending (physical interlocking or chemical grafting) and thermochemical effects of the degradation mechanism. The thermogravimetric analysis further validates the physical interlocking and chemical grafting. The novel concept of partial blending with excessive interlocking reports high mechanical stability against moisture-based degradation.
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This research presents a partial biodegradable polymeric blend aimed for large-scale fused deposition modeling (FDM). The literature reports partial biodegradable blends with high contents of fossil fuel-based polymers (>20%) that make them unfriendly to the ecosystem. Furthermore, the reported polymer systems neither present good mechanical strength nor have been investigated in vulnerable environments that results in biodegradation. This research, as a continuity of previous work, presents the stability against biodegradability of a partial biodegradable blend prepared with polylactic acid (PLA) and polypropylene (PP). The blend is designed with intended excess physical interlocking and sufficient chemical grafting, which has only been investigated for thermal and hydrolytic degradation before by the same authors. The research presents, for the first time, ANOVA analysis for the statistical evaluation of endurance against biodegradability. The statistical results are complemented with thermochemical and visual analysis. Fourier transform infrared spectroscopy (FTIR) determines the signs of intermolecular interactions that are further confirmed by differential scanning calorimetry (DSC). The thermochemical interactions observed in FTIR and DSC are validated with thermogravimetric analysis (TGA). Scanning electron microscopy (SEM) is also used as a visual technique to affirm the physical interlocking. It is concluded that the blend exhibits high stability against soil biodegradation in terms of high mechanical strength and high mass retention percentage.
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Ti-6Al-4V is considered a challenging material in terms of accurate machining. Therefore, electric discharge machining (EDM) is commonly engaged, but its low cutting rate depreciates its use. This issue is resolved if graphene nanoparticles are mixed in the dielectric. However, the control over the sparking phenomenon reduces because of the dispersion of graphene particles. Subsequently, the machined profile's geometric accuracy is compromised. Furthermore, the presence of nanographene induces different sparks along axial and radial cutting orientations. This aspect has not been comprehensively examined yet and dedicatedly targeted in this study to improve the quality of EDM process for Ti-6Al-4V. A total of 18 experiments were conducted under Taguchi's L18 design considering six parameters namely, electrode type, polarity, flushing time, spark voltage, pulse time ratio, and discharge current. The aluminum electrode proved to be the best choice to reduce the errors in both the cutting orientations. Despite the other parametric settings, negative tool polarity yields lower values of axial (ADE) and radial errors (RDE). The developed optimal settings ensure 4.4- and 6.3-times reduction in RDE and ADE, respectively. In comparison to kerosene, graphene-based dielectric yields 10.2% and 19.4% reduction in RDE and ADE, respectively.
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The exponential rise of healthcare problems like human aging and road traffic accidents have developed an intrinsic challenge to biomedical sectors concerning the arrangement of patient-specific biomedical products. The additively manufactured implants and scaffolds have captured global attention over the last two decades concerning their printing quality and ease of manufacturing. However, the inherent challenges associated with additive manufacturing (AM) technologies, namely process selection, level of complexity, printing speed, resolution, biomaterial choice, and consumed energy, still pose several limitations on their use. Recently, the whole world has faced severe supply chain disruptions of personal protective equipment and basic medical facilities due to a respiratory disease known as the coronavirus (COVID-19). In this regard, local and global AM manufacturers have printed biomedical products to level the supply-demand equation. The potential of AM technologies for biomedical applications before, during, and post-COVID-19 pandemic alongwith its relation to the industry 4.0 (I4.0) concept is discussed herein. Moreover, additive manufacturing technologies are studied in this work concerning their working principle, classification, materials, processing variables, output responses, merits, challenges, and biomedical applications. Different factors affecting the sustainable performance in AM for biomedical applications are discussed with more focus on the comparative examination of consumed energy to determine which process is more sustainable. The recent advancements in the field like 4D printing and 5D printing are useful for the successful implementation of I4.0 to combat any future pandemic scenario. The potential of hybrid printing, multi-materials printing, and printing with smart materials, has been identified as hot research areas to produce scaffolds and implants in regenerative medicine, tissue engineering, and orthopedic implants.
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Machining operations are very common for the production of auto parts, i.e., connecting rods, crankshafts, etc. In machining, the use of cutting oil is very necessary, but it leads to higher machining costs and environmental problems. About 17% of the cost of any product is associated with cutting fluid, and about 80% of skin diseases are due to mist and fumes generated by cutting oils. Environmental legislation and operators' safety demand the minimal use of cutting fluid and proper disposal of used cutting oil. The disposal cost is huge, about two times higher than the machining cost. To improve occupational health and safety and the reduction of product costs, companies are moving towards sustainable manufacturing. Therefore, this review article emphasizes the sustainable machining aspects of steel by employing techniques that require the minimal use of cutting oils, i.e., minimum quantity lubrication, and other efficient techniques like cryogenic cooling, dry cutting, solid lubricants, air/vapor/gas cooling, and cryogenic treatment. Cryogenic treatment on tools and the use of vegetable oils or biodegradable oils instead of mineral oils are used as primary techniques to enhance the overall part quality, which leads to longer tool life with no negative impacts on the environment. To further help the manufacturing community in progressing towards industry 4.0 and obtaining net-zero emissions, in this paper, we present a comprehensive review of the recent, state of the art sustainable techniques used for machining steel materials/components by which the industry can massively improve their product quality and production.
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The collagen hydrolysate, a proteinic biopeptide, is used for various key functionalities in humans and animals. Numerous reviews explained either individually or a few of following aspects: types, processes, properties, and applications. In the recent developments, various biological, biochemical, and biomedical functionalities are achieved in five aspects: process, type, species, disease, receptors. The receptors are rarely addressed in the past which are an essential stimulus to activate various biomedical and biological activities in the metabolic system of humans and animals. Furthermore, a systematic segregation of the recent developments regarding the five main aspects is not yet reported. This review presents various biological, biochemical, and biomedical functionalities achieved for each of the beforementioned five aspects using a systematic approach. The review proposes a novel three-level hierarchy that aims to associate a specific functionality to a particular aspect and its subcategory. The hierarchy also highlights various key research novelties in a categorical manner that will contribute to future research.
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Titanium alloys, especially Ti-6Al-4V, which is considered a difficult-to-cut material, bears numerous applications in aerospace and biomedical sectors. The criticality of the accurate formation of the machined cavity for the said applications and properties of Ti-6Al-4V accentuated the use of electric discharge machining (EDM). However, the issues of lower material removal rate (MRR) and tool wear (TWR) discouraged the use of EDM. These inherent issues hold a pivotal role regarding the sustainable machining of Ti-alloy. Therefore, in this research the potentiality of kerosene-based dielectric, having graphene nanoparticles, is comprehensively examined for the sustainable EDM of Ti-6Al-4V, which was not focused upon yet. Experimentation was performed under Taguchi's design (L18) with three types of electrodes, namely Aluminum, Brass and Copper. In total, 36 experiments were conducted, of which 18 were with graphene-mixed dielectric and the remaining were with kerosene. Experimental results reveal that the brass electrode with negative tool polarity yields higher MRR for both types of dielectrics. The maximum MRR (7.602 mm3/min) achieved with graphene mixed dielectric is 64.5% greater as compared to that obtained with kerosene (4.621 mm3/min). Moreover, the minimum TWR obtained for graphene-based dielectric, i.e., 0.17 mg/min is approximately 1.5 times less than that achieved with kerosene.
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Titanium-aluminium-vanadium (Ti 6Al 4V) alloys, nickel alloys (Inconel 718), and duraluminum alloys (AA 2000 series) are widely used materials in numerous engineering applications wherein machined features are required to having good surface finish. In this research, micro-impressions of 12 µm depth are milled on these materials though laser milling. Response surface methodology based design of experiment is followed resulting in 54 experiments per work material. Five laser parameters are considered naming lamp current intensity (I), pulse frequency (f), scanning speed (V), layer thickness (LT), and track displacement (TD). Process performance is evaluated and compared in terms of surface roughness through several statistical and microscopic analysis. The significance, strength, and direction of each of the five laser parametric effects are deeply investigated for the said alloys. Optimized laser parameters are proposed to achieve minimum surface roughness. For the optimized combination of laser parameters to achieve minimum surface roughness (Ra) in the titanium alloy, the said alloy consists of I = 85%, f = 20 kHz, V = 250 mm/s, TD = 11 µm, and LT = 3 µm. Similarly, optimized parameters for nickel alloy are as follows: I = 85%, f = 20 kHz, V = 256 mm/s, TD = 8 µm, and LT = 1 µm. Minimum roughness (Ra) on the surface of aluminum alloys can be achieved under the following optimized parameters: I = 75%, f = 20 kHz, V = 200 mm/s, TD = 12 µm, and LT = 3 µm. Micro-impressions produced under optimized parameters have surface roughness of 0.56 µm, 2.46 µm, and 0.54 µm on titanium alloy, nickel alloy, and duralumin, respectively. Some engineering applications need to have high surface roughness (e.g., in case of biomedical implants) or some desired level of roughness. Therefore, validated statistical models are presented to estimate the desired level of roughness against any laser parametric settings.
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The development of layered/clad composites with a blend of desired characteristics has emerged as a valuable substitute for expensive materials. The inherent heterogeneity offers challenges whenever the cutting of cladded plates/sheets is to be done. The conventional means of cutting such as gas/plasma arc yield a poor cut quality and heat-affected zones. Abrasive waterjet machining (AWJM) is a valuable alternative to mitigate the aforesaid cutting issues. However, the intrinsic attribute of edge damage during AWJM poses a limitation on its use, especially for precision applications. Specifically, it is challenging to control the edge damage in terms of pit depth at both the constituent clad layers and addressing this challenge is the novelty of this work. The said cutting accuracy issues have been thoroughly investigated herein. Four key control parameters of AWJM have been selected for evaluating their impact during machining of stainless-clad steel using L18 Taguchi design. Experimental results have been thoroughly examined using statistical and microscopical evidence. The optimal parametric combination resulting in the minimum magnitude of pit depth at both the clad layers has been developed and experimentally validated. The magnitude of pits depth realized at stainless steel layer (SSL) and mild steel layer (MSL) significantly reduced to 5 µm and 4 µm respectively, at the optimal parametric combination.
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Sand-casting is a well established primary process for manufacturing various parts of A356 alloy. However, the quality of the casting is adversely affected by the change in the magnitude of the control variables. For instance, a larger magnitude of pouring velocity induces a drop effect and a lower velocity increases the likelihood of cold-shut and mis-run types of defects. Similarly, a high pouring temperature causes the formation of hot tears, whereas a low temperature is a source of premature solidification. Likewise, a higher moisture content yields microcracks (due to gas shrinkages) in the casting and a lower moisture content results in the poor strength of the mold. Therefore, the appropriate selection of control variables is essential to ensure quality manufactured products. The empirical relations could provide valuable guidance in this regard. Additionally, although the casting process was optimized for A356 alloy, it was mostly done for a single response. Therefore, this paper aimed to formulate empirical relations for the contradictory responses, i.e., hardness, ultimate tensile strength and surface roughness, using the response surface methodology. The experimental results were comprehensively analyzed using statistical and scanning electron microscopic analyses. Optimized parameters were proposed and validated to achieve castings with high hardness (84.5 HB) and strength (153.5 MPa) with minimum roughness (5.8 µm).
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Ti-6Al-4V is a material of high interest in various industrial sectors including biomedical, automotive and aerospace. Conventional means of machining encounter different types of difficulties. Electric discharge machining (EDM) is not a contest of hardness. Circular impressions of micro-depth are produced in Ti-6Al-4V using four different electrode materials including aluminum, brass, graphite and copper, each assigned positive and negative polarity. In order to get precise control over the geometry of micro-impressions dimensional accuracy and tool wear must be controlled. Thus, EDM performance has been evaluated in terms of axial dimensional error (D.E_Axi), radial dimensional error (D.E_Rad), tool length reduction (TLR), and surface roughness (SR). Since the EDM process is stochastic in nature therefore in addition to tool polarity only two factors are considered as variables, i.e. discharge current and pulse-time-ratio (ration of on-time to off-time). The behaviors of each of the four electrode materials are compared together under each of the two polarities and two variables for each of the four response characteristics. The search is carried out to select the most appropriate tool electrode polarity (common for all responses) and a single common electrode capable of minimizing all the four response measures simultaneously. Moreover, microstructures of the machined impressions are discussed. Without any compromise in the minimum values of response measures, no single polarity and a single electrode are found common. However, with a slight compromise over the machining measures negative tool polarity and copper electrode served the purpose of set objectives (minimum of D.E, TLR, and SR). The expanse of compromise is found to be ≤ 50 µm in axial and radial dimensional errors, 0.8 µm in surface roughness and no compromise in tool length reduction if the copper electrode is assigned with negative polarity.
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Stainless steel (SS 304) is commonly employed in industrial applications due to its considerable corrosion resistance, thermal resistance, and ductility. Most of its intended applications require the formation of complex profiles, which justify the use of wire electrical discharge machining (WEDM). However, its high thermal resistance imposes a limitation on acquiring adequate surface topography because of the high surface tension of the melt pool, which leads to the formation of spherical modules; ultimately, this compromises the surface quality. Furthermore, the stochastic nature of the process makes it difficult to optimize its performance, especially if more than one conflicting response is involved, such as high cutting speed with low surface roughness and kerf width. Therefore, this study aimed to comprehensively investigate the interaction of SS 304 and WEDM, with a prior focus on simultaneously optimizing all the conflicting responses using the Taguchi-based grey relational approach. Analysis of variance (ANOVA) revealed that the current was the most significant parameter for cutting speed and kerf, whereas roughness, voltage (45%), drum speed (25.8%), and nozzle offset distance (~21%) were major contributing factors. SEM micrographs showed that optimal settings not only ensured simultaneous optimization of the conflicting responses but also reduced the number and size of spherical modules.
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During laser milling, the objective is not always to maximize the material removal rate (MRR). Milling of new material with targeted MRR is challenging without prior knowledge and established sets of laser parameters. The laser milling performance has been evaluated for three important aerospace alloys, i.e., titanium alloy, nickel alloy and aluminum alloy using the response surface method experimental plan (54 experiments for each alloy). Parametric effects of five important laser parameters, statistical analysis (main effects, interaction effects, strength and direction of effects), mathematical modeling and optimality search is conducted for the said alloys. Under the non-optimized laser parameters, the actual MRR significantly varies from the targeted MRR. Variation in the aluminum alloy is at the top as compared to the other two alloys. Among other significant terms, three terms have the largest effect on MRR in the case of TiA, two terms in the case of NiA, and five terms in the case of AlA. Under the optimized sets of laser parameters, the actual material removal highly close to the desired level (100%) can be achieved with minimum variation in all the three alloys. Mathematical models proposed here have the capability to well predict material removal prior to the actual machining of Ti6Al4V, Inconel 718 and AA 2024.