International Journal of Lightweight Materials and Manufacture最新文献

{"title":"Electro-discharge machining of microholes on 3d printed Hastelloy using the novel tool-feeding approach","authors":"Akash Korgal ,&nbsp;Arun Kumar Shettigar ,&nbsp;Navin Karanth P ,&nbsp;Nishanth Kumar ,&nbsp;Bindu Madhavi J","doi":"10.1016/j.ijlmm.2024.10.005","DOIUrl":"10.1016/j.ijlmm.2024.10.005","url":null,"abstract":"<div><div>Hastelloy, a nickel-based superalloy renowned for its exceptional resistance to corrosion at high temperatures, is widely used in sectors such as nuclear, aerospace, chemical processing, and pharmaceuticals. Microelectrical discharge machining (μ-EDM) is crucial for generating microholes and channels on Hastelloy. Since it effectively addresses difficulties like work hardening, high strength &amp; wear resistance, and low thermal conductivity in traditional machining. Microholes play a major role in many critical components for precise control of fluids in fuel injectors, managing heat in turbine blades, controlled gas exchange, etc. The current research investigates the drilling of 8:1 aspect ratio microholes machined by 400 μm diameter electrodes. This study investigated the influence of tool material (tungsten carbide, carbide drill bit, and brass) on μ-EDM performance. Compared to tungsten carbide and carbide drill bits, brass exhibited significantly lower electrode wear, leading to more precise microholes with reduced overcut and taper angle. However, brass also required a substantially longer machining time. Carbide drill bits offered a balance between wear resistance, machining time, and overcut/taper angle.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 157-164"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429799","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Advanced machine learning and experimental studies of polypropylene based polyesters tribological composite systems for sustainable recycling automation and digitalization","authors":"Abrar Hussain ,&nbsp;Jakob Kübarsepp ,&nbsp;Fjodor Sergejev ,&nbsp;Dmitri Goljandin ,&nbsp;Irina Hussainova ,&nbsp;Vitali Podgursky ,&nbsp;Kristo Karjust ,&nbsp;Himanshu S. Maurya ,&nbsp;Ramin Rahmani ,&nbsp;Maris Sinka ,&nbsp;Diāna Bajāre ,&nbsp;Anatolijs Borodiņecs","doi":"10.1016/j.ijlmm.2024.11.001","DOIUrl":"10.1016/j.ijlmm.2024.11.001","url":null,"abstract":"<div><div>Digitalization and automation are emerging solutions to the complex problems of recycling. In this research work, the experimental and Python based Archard deep learning wear rate models are introduced regarding recycling automation and composite tribological systems optimization. The optimum polyester fibers (PESF) of length of 3–3.5 mm were used for fabrication of polypropylene (PP)-PESF composite systems. The deformation, high texture, asperities, and micro-cracks were observed during scanning electron microscope and machine-learning studies. The lowest experimental value of abrasive wear of 3.0 × 10⁻⁶ mm³/Nm was observed for PP. Comparatively, higher experimental values of abrasive wear of the PP-PESF composites are found in the range of 4.35 × 10⁻⁶ to 4.7 × 10⁻⁶ mm³/Nm due to presence micro-defects on the surface of composites. The experimental values of Coefficient of friction (COF) of PP and PP-PESF are found in the range of 0.70–0.8 and 1.1–1.3, respectively. The experimental values of abrasive wear and COF are found compatible with literature. Similarly, the simulated values of abrasive wear of PP and PP-PESF composites are predicted in the range of 4.8 × 10⁻⁷ to 3.75 × 10⁻⁷ mm³/Nm, respectively. The predicted values of PP and PP-PESF composite show better resistance towards abrasive wear. The proposed experimental and simulated (in terms of Python coding, machine learning, image processing, artificial intelligence, and deep learning studies) research work can be introduced industrially for automation as well as digitalization of grinding of PES waste, processing, tribological testing, and SEM characterization evaluations.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 252-263"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429715","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Friction stir extrusion: Parametrical optimization for improved Al–Si aluminum tube production","authors":"Mostafa Akbari ,&nbsp;Parviz Asadi ,&nbsp;Fevzi Bedir ,&nbsp;Naghdali Choupani","doi":"10.1016/j.ijlmm.2024.11.003","DOIUrl":"10.1016/j.ijlmm.2024.11.003","url":null,"abstract":"<div><div>Friction Stir Extrusion (FSE) was employed to convert cylindrical LM13 ingots into pipes, utilizing three distinct designs of rotating tool heads. This study examined the influence of process variables, consisting of tool rotational speed and plunging speed, on key properties of the resulting products. The properties investigated encompassed the size of Si precipitates, microhardness, wear resistance, and ultimate compressive strength (UCS). To effectively establish the relationships between the process input variables and the resulting mechanical and microstructural characteristics of the produced pipes, an artificial neural network (ANN) was used. This established correlation was integrated into a hybrid multi-objective optimization framework to identify the optimal process parameters. The investigation determined the ideal configuration: a plunging rate of 31 mm/min, a rotational rate of 653 rpm, and tool design number 3.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 182-193"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429653","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Machine learning in additive manufacturing: A comprehensive insight","authors":"Md Asif Equbal ,&nbsp;Azhar Equbal ,&nbsp;Zahid A. Khan ,&nbsp;Irfan Anjum Badruddin","doi":"10.1016/j.ijlmm.2024.10.002","DOIUrl":"10.1016/j.ijlmm.2024.10.002","url":null,"abstract":"<div><div>Additive manufacturing (AM) is a technological advancement gaining colossal popularity due to its advantages and simplified fabrication. AM facilitates the manufacturing of complex, light, and strong products from digitized designs. With recent advancements, AM can bring digital flexibility and improved efficiency to industrial operations. Despite the various advantages, there is continuous variation in the qualities of AM products, which remains the main challenge in the wide application of AM. The performance of printed parts is directly influenced by processing parameters, and adjusting the parameters in the AM process can be quite challenging. The barrier can be minimized by proper monitoring of the AM process and precise measurement of AM materials and components, which is difficult to achieve through analytical and numerical models. Current research demonstrates machine learning (ML) and its techniques as a novel way to reduce costs. It also helps achieve optimal process design and part quality using the fundamentals of the AM process. ML is a subcategory of artificial intelligence (AI) that enables systems to learn and improve from measured data and past experiences. The present paper is focused on presenting a broad understanding of the current applications of ML in AM and thus provides a solid background for practitioners and researchers to apply ML in AM. Very few earlier reviews were presented before, but their studies mostly focus on artificial neural network technology and other irrelevant papers. In addition, most papers were published in 2021 and 2022 and were not discussed in earlier reviews. This state-of-the-art review is based on the latest database collected from Web of Science (WoS), Publons, Scopus, and Google Scholar using machine learning and additive manufacturing as the keywords. Extensive information collected on the possible applications of ML in AM shows that ML can be effectively applied to improve AM part quality and process reliability.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 264-284"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143510543","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Experimental performance evaluation of a lightweight additively manufactured hydrodynamic thrust bearing","authors":"Collier Fais ,&nbsp;Isaiah Yasko ,&nbsp;Muhammad Ali ,&nbsp;Rick Walker ,&nbsp;Joe Walker","doi":"10.1016/j.ijlmm.2024.10.003","DOIUrl":"10.1016/j.ijlmm.2024.10.003","url":null,"abstract":"<div><div>In this paper, a lightweight additively manufactured (AM) fixed geometry hydrodynamic thrust bearing fabricated via laser powder bed fusion (LPBF) is experimentally compared to a traditionally manufactured cast aluminum alloy thrust bearing of similar design. The purpose of this study is to evaluate how weight-saving design features in the AM bearing affect active critical hydrodynamic performance parameters to better understand in-service viability. Under various static operating conditions, performance parameters such as hydrodynamic pressure distribution, minimum oil film thickness (MOFT), bearing temperature and increase in oil temperature are measured. Compared to the traditionally manufactured bearing, the AM bearing showed an average increase in minimum oil film thickness of 53 %, an average increase in trailing edge hydrodynamic pressure of 116 %, while exhibiting an average decrease in bearing temperature of 1 %. Experimental results are compared to numerical simulation showing reasonably good agreement.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 285-299"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143529322","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Sustainable transformation of waste Aluminium into high-performance composites: A review","authors":"Abdullah Al Mahmood ,&nbsp;Md. Abdul Kader ,&nbsp;M. Bodiul Islam ,&nbsp;Rumana Hossain","doi":"10.1016/j.ijlmm.2024.11.002","DOIUrl":"10.1016/j.ijlmm.2024.11.002","url":null,"abstract":"<div><div>In the modern age, metal matrix composites (MMC) are offering numerous advantages over the pure metal and their enhanced physical and mechanical properties have diversified the range of applications of the MMC. Aluminum is one of the most useful metals in the world and highly requires energy intensive process to produce from the ores. Recycling is the only option to save the resources, and it can be done by the minimum level of energy consumption and emission. However, it is very crucial to follow the proper procedure to eliminate any remaining impurities in the waste metal. Secondary Aluminum can be used for unlimited times in every field of applications where primary Aluminum is suitable. However, for the advanced applications of Aluminum including automobiles, aircrafts, defence, and biomedical instruments that require unique sets of properties, alloying or making composites is inevitable. Particulate reinforcement to the Aluminum matrix is an excellent way of modifying the physical, mechanical, and micro-structural properties of Aluminum. Silicon carbide is a very good reinforcing agent used for manufacturing Aluminum matrix composites (AMC). SiC reinforced AMC can offer strong resistance to fracture and high wear resistivity with excellent surface hardness. Recycling aluminum to manufacture AMC is a sustainable solution to meet the current demand for advanced materials. Synthesizing of reinforcing materials from waste materials can also help to build sustainable, affordable and light weight AMC. The aim of this work is to review the present methods of recycling Aluminum and sustainable transformation of the recycled Aluminum to high-performance particulate reinforced AMC.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 194-204"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429567","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Environmentally friendly chemical–magnetorheological finishing method for Ti–6Al–4V biological material based on Fe3O4@SiO2, oxaloacetate acid and H2O2","authors":"Le Anh Duc,&nbsp;Vu Minh Yen,&nbsp;Nguyen Duy Trinh","doi":"10.1016/j.ijlmm.2024.10.004","DOIUrl":"10.1016/j.ijlmm.2024.10.004","url":null,"abstract":"<div><div>Titanium alloy is extensively utilised in various advanced equipment across multiple industries, especially in biological implantable devices. The surface machining of such devices is required to provide a finished surface with high precision and gloss. This study presents an established ecofriendly slurry for a hybrid polishing process utilising a highly efficient chemical and magnetorheological fluid (C-MRF) to obtain ultraprecise surface quality. This slurry incorporated Fe₃O₄@SiO₂ abrasive particles, oxaloacetate acid (C₄H₆O₅), deionised water and hydrogen peroxide (H₂O₂) as an oxidiser. Ti–6Al–4V workpieces polished with C-MRF based on Fe₃O₄@SiO₂ abrasives and polishing performance were used to investigate the influence of the oxidising agent H₂O₂ and oxaloacetate acid (monitored with a pH indicator) on the surface finish of Ti–6Al–4V biomaterial. In contrast to the traditional mechanical and chemical polishing methods for titanium alloys that often include strong bases and acids along with chemicals that endanger the environment and humans, the proposed polishing process based on the newly developed ecofriendly magnetic composite leveraged the advantages of magnetorheological fluid with chemical reactions to create an ultra smooth surface. Experiments were performed to investigate the influence of different polishing durations and factors on the quality of polished surfaces, thereby optimising technological parameters, reducing time and improving surface quality. Various technological parameters were evaluated through single-factor and orthogonal experiments to assess their distinct effects on surface quality and material removal capability. This work proposed an environmentally friendly C-MRF method for finishing Ti–6Al–4V biomaterial with high efficiency and industrial applicability.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 228-240"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429569","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Data-driven approaches in incremental forming: Unravelling the path to enhanced manufacturing efficiency using data acquisition","authors":"S. Pratheesh Kumar,&nbsp;V. Joseph Stanley,&nbsp;S. Nimesha","doi":"10.1016/j.ijlmm.2024.10.001","DOIUrl":"10.1016/j.ijlmm.2024.10.001","url":null,"abstract":"<div><div>Incremental forming is a versatile and cost-effective sheet metal forming technique widely adopted in low-volume manufacturing and prototyping across various industries. Recent advancements in data-driven approaches, including machine vision, neural networks, and 3D reconstruction methods, have significantly enhanced the precision and efficiency of incremental forming processes. This study explores the integration of advanced data acquisition and processing techniques to improve the accuracy, automation, and defect detection capabilities in incremental forming. Key advancements such as robot-assisted forming, computer-controlled toolpath generation from CAD models, and real-time quality monitoring using machine vision are discussed. The potential of single- and multi-view 3D reconstruction methods for optimizing toolpath strategies and enhancing formability is also examined. The findings highlight opportunities for full automation in incremental forming, demonstrating its potential to revolutionize modern manufacturing by reducing costs, increasing customization, and improving product quality. These advancements could benefit industries such as aerospace, automotive, and medical device manufacturing, where precision and flexibility are critical.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 165-181"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429652","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Design of a test rig for the characterization of friction and wear in hot-metal gas-forming of AA 5083 aluminium sheets","authors":"Federico Simone Gobber ,&nbsp;Alexandru Tancau ,&nbsp;Leonardo Daniele Scintilla ,&nbsp;Marco Fontana ,&nbsp;Marco Actis Grande","doi":"10.1016/j.ijlmm.2024.09.002","DOIUrl":"10.1016/j.ijlmm.2024.09.002","url":null,"abstract":"<div><div>Advanced aluminium sheet-forming processes such as the hot-metal gas-forming represent a challenging solution for producing small lots in the high-end car bodies industry, and the adoption of single cavity moulds made from low-cost, easily machinable materials such as cast iron reduces the overall sheet-forming costs. The tribological properties of the mould-sheet tribopair are of great interest for optimizing the sheet forming obtaining an acceptable esthetic surface finishing. This study presents the design and construction of a lab-scale experimental test rig for the tribological characterization at high temperatures of the mould-sheet tribopair. The proposed test method reproduces the sliding at the mould-sheet interface with contemporary sheet straining up to ε = 0.8 at strain rates in the 1.2∗10⁻³ to 2∗10⁻² s⁻¹ range. A series of experiments were carried out in dry and lubricated conditions for a ductile iron EN-GJS grade sliding against a AA 5083 aluminium alloy while straining. After comparing the experimental results with the literature data from other test rigs, comparable results were obtained as COF regards, ranging between 1.2 and 2.5 in dry sliding and between 0.05 and 0.2 in lubricated sliding. The morphological characterization of the sliding surfaces and cross-sections highlights the strong tendency to galling in dry sliding conditions expecially for low strain rates.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 2","pages":"Pages 241-251"},"PeriodicalIF":0.0,"publicationDate":"2025-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143429570","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Thermo-mechanical and electrical properties of graphene nanoplatelets reinforced recycled polypropylene nanocomposites","authors":"Vimukthi Dananjaya ,&nbsp;Chamil Abeykoon","doi":"10.1016/j.ijlmm.2025.01.003","DOIUrl":"10.1016/j.ijlmm.2025.01.003","url":null,"abstract":"<div><div>This study investigates the thermo-mechanical properties of graphene nanoplatelet (GNP)-filled recycled polypropylene (rPP) nanocomposites to enhance their performance and sustainability. It examines the influence of GNP loading on mechanical, thermal, and electrical behaviour, focusing on tensile strength, Young’s modulus, impact strength, heat deflection temperature, thermal conductivity, and electrical resistivity. The GNP-PP composites are fabricated by functionalizing GNPs through mild acid treatment to enhance compatibility with the rPP matrix, followed by melt mixing in a twin-screw extruder at varying GNP loadings (0–20 Phr). The tensile strength, Young's modulus, and flexural strength of recycled polypropylene increased by 15.6 MPa, 3.7 MPa, and 2.41 MPa, respectively, as the GNP loading increased from 0 to 20 Phr. AddingAdding GNP up to 20 Phr into the rPP matrix also increased the crystallization, melting, onset, and maximum decomposition temperatures by 5, 4.7, 8.36, and 7.02 ˚C, respectively. Additionally, the thermal conductivity shows an increasing trend, with an improvement of 221 mW/mK. However, including fillers reduced electrical resistivity by 105 Ω cm and impact strength by 64.27 Jm⁻¹. The significance of this work lies in providing eco-friendly alternatives to conventional polymers, promoting the adoption of recycled materials, and contributing to sustainable product design. The outcomes offer valuable insights for industries promoting a circular economy with cleaner production while reducing the carbon footprint. Also, the recycling and reuse of synthetic polymers uncover a valuable prospect for tackling the escalating global polymeric waste problem.</div></div>","PeriodicalId":52306,"journal":{"name":"International Journal of Lightweight Materials and Manufacture","volume":"8 3","pages":""},"PeriodicalIF":0.0,"publicationDate":"2025-02-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143800356","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}