Journal of Manufacturing and Materials Processing

21 pages, 32765 KiB

Open AccessArticle

Sustainable Synthesis of Diamond-like Carbon and Giant Carbon Allotropes from Hyperbaric Methanol–Water Mixtures Through the Critical Point

by Mohamad E. Alabdulkarim, Vibhor Thapliyal and James L. Maxwell

J. Manuf. Mater. Process. 2024, 8(6), 286; https://doi.org/10.3390/jmmp8060286 - 9 Dec 2024

Abstract

Freeform carbon fibres were 3D-printed from CH₃OH:H₂O mixtures using hyperbaric-pressure laser chemical vapour deposition (HP-LCVD). The experiment overlapped a region of known diamond growth, with the objective of depositing diamond-like carbon without the use of plasmas or hot filaments. [...] Read more.

Freeform carbon fibres were 3D-printed from CH₃OH:H₂O mixtures using hyperbaric-pressure laser chemical vapour deposition (HP-LCVD). The experiment overlapped a region of known diamond growth, with the objective of depositing diamond-like carbon without the use of plasmas or hot filaments. A high-pressure regime was investigated for the first time through the precursor’s critical point. Seventy-two C-fibres were grown from 13 different CH₃OH:H₂O mixtures at total pressures between 7.8 and 180 bar. Maximum steady-state axial growth rates of 14 µm/s were observed. Growth near the critical point was suppressed, ostensibly due to thermal diffusion and selective etching. In addition to nanostructured graphite, various carbon allotropes were synthesised at/within the outer surface of the fibres, including diamond-like carbon, graphite polyhedral crystal, and tubular graphite cones. Several allotropes were oversized compared to structures previously reported. Raman spectral pressure–temperature (P-T) maps and a pictorial P-T phase diagram were compiled over a broad range of process conditions. Trends in the Raman I_D/I_G and I_2D/I_G intensity ratios were observed and regions of optimal growth for specific allotropes were identified. It is intended that this work provide a basis for others in optimising the growth of specific carbon allotropes from methanol using HP-LCVD and similar CVD processes. Full article

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15 pages, 4590 KiB

Open AccessArticle

An Integrated Modeling Framework for Automated Product Design, Topology Optimization, and Mechanical Simulation

by Paschalis Charalampous, Athanasios Pelekoudas, Ioannis Kostavelis, Dimosthenis Ioannidis and Dimitrios Tzovaras

J. Manuf. Mater. Process. 2024, 8(6), 285; https://doi.org/10.3390/jmmp8060285 - 7 Dec 2024

Abstract

The present study introduces an integrated software approach that provides an automated product design toolkit for customized products like knives, incorporating topology optimization (TO) and numerical simulations in order to streamline engineering workflows during the product development procedure. The modeling framework combines state-of-the-art [...] Read more.

The present study introduces an integrated software approach that provides an automated product design toolkit for customized products like knives, incorporating topology optimization (TO) and numerical simulations in order to streamline engineering workflows during the product development procedure. The modeling framework combines state-of-the-art technologies into a single platform, enabling the design and the optimization of mechanical structures with minimal human intervention. In particular, the proposed solution leverages artificial intelligence (AI), shape optimization methods, and computational tools in order to iteratively optimize material utilization as well as the design of products based on certain criteria. By embedding simulation within the design optimization loop, the developed software module ensures that performance constraints are respected throughout the design process. The case studies are concentrated in designing knives, demonstrating the platform’s ability to reduce design time, enhance product performance and provide rapid iterations of structurally optimized geometries. Finally, it should be noted that this research showcases the potential of integrated modeling technologies towards the transformation of traditional design paradigms, in this way contributing to faster, more reliable and efficient product development in various engineering industries through the training and deployment of AI models in these scientific fields. Full article

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14 pages, 4203 KiB

Open AccessArticle

Cryo-Rolled AA5052 Alloy: Insights into Mechanical Properties, Formability, and Microstructure

by Arun Achuthankutty, Rohith Saravanan, Hariesh Nagarajan, Vidyanand Pasunuri, Nishanth Hari Gopal, Ajith Ramesh, Sumesh Arangot and Dinu Thomas Thekkuden

J. Manuf. Mater. Process. 2024, 8(6), 284; https://doi.org/10.3390/jmmp8060284 - 7 Dec 2024

Abstract

Industries operating in extreme conditions demand materials with exceptional strength, fatigue resistance, corrosion resistance, and formability. While AA5052 alloy is widely used in such industries due to its high fatigue strength and corrosion resistance, its strength frequently falls short of stringent standards. For [...] Read more.

Industries operating in extreme conditions demand materials with exceptional strength, fatigue resistance, corrosion resistance, and formability. While AA5052 alloy is widely used in such industries due to its high fatigue strength and corrosion resistance, its strength frequently falls short of stringent standards. For AA5052 alloy, this study explores the combined use of solutionizing and cryo-rolling, followed by annealing, to improve strength. Although several alloys have been reported to undergo solution treatment before cryo-rolling, this study focuses on how post-processing via annealing can lessen the formability constraints usually connected to conventional cryo-rolling. The study sheds light on the ways that solutionizing, cryo-rolling, and annealing interact to affect the alloy’s mechanical characteristics. Microstructure analysis shows that solutionizing improves the grain structure by reducing dynamic recovery, promoting dislocation density, and facilitating precipitate formation. Sheets subjected to solutionizing + cryo-rolling and partially annealed at 250 °C produce optimal results. Interestingly, formability is decreased when cryo-rolling alone is used instead of cold rolling, whereas formability is successfully increased when solutionizing is used. Comparing solutionized + cryo-rolled sheets that are partially annealed at 250 °C to cold-rolled sheets that are annealed at the same temperature, the former show notable quantitative improvements: a notable 17% increase in ultimate strength, a 10% boost in yield strength, and a noteworthy 13% enhancement in microhardness. Formability has improved with the solutionized + cryo-rolled specimens by annealing. This proposed approach led to noticeable gains in formability, hardness, and strength, which would significantly improve material performance for industrial applications. Full article

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21 pages, 7769 KiB

Open AccessArticle

Enhancing Welding Productivity and Mitigation of Distortion in Dissimilar Welding of Ferritic-Martensitic Steel and Austenitic Stainless Steel Using Robotic A-TIG Welding Process

by Tushar Sonar, Mikhail Ivanov, Igor Shcherbakov, Evgeny Trofimov, Emiliya Khasanova, Muralimohan Cheepu and Kun Liu

J. Manuf. Mater. Process. 2024, 8(6), 283; https://doi.org/10.3390/jmmp8060283 - 5 Dec 2024

Abstract

The P91 martensitic steel and 304L austenitic stainless steels are two mainly used structural steels in power plants. The major problem in conventional multipass tungsten inert gas (TIG) welding of P91/304L steel is high heat input and joint distortion, increased cost and time [...] Read more.

The P91 martensitic steel and 304L austenitic stainless steels are two mainly used structural steels in power plants. The major problem in conventional multipass tungsten inert gas (TIG) welding of P91/304L steel is high heat input and joint distortion, increased cost and time associated with V groove preparation, filler rod requirement, preheating and welding in multiple passes, and labor efforts. Hence, in this study, a novel approach of robotically operated activated flux TIG (A-TIG) welding process and thin AlCoCrFeNi_2.1 eutectic high entropy alloy (EHEA) sheet as the interlayer was used to weld 6.14 mm thick P91 and 304L steel plates with 02 passes in butt joint configuration. The joints were qualified using visual examination, macro-etching, X-ray radiography testing and angular distortion measurement. The angular distortion of the joints was measured using a coordinate measuring machine (CMM) integrated with Samiso 7.5 software. The quality of the A-TIG welded joints was compared to the joints made employing multipass-TIG welding process and Inconel 82 filler rod in 07 passes. The A-TIG welded joints showed significant reduction in angular distortion and higher productivity. It showed a 55% reduction in angular distortion and 80% reduction in welding cost and time compared to the multipass-TIG welded joints. Full article

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30 pages, 6744 KiB

Open AccessReview

Recent Advances and Applications of Carbon Nanotubes (CNTs) in Machining Processes: A Review

by Reza Sallakhniknezhad, Hossein Ahmadian, Tianfeng Zhou, Guo Weijia, Senthil Kumar Anantharajan, Ayman M. Sadoun, Waleed Mohammed Abdelfattah and Adel Fathy

J. Manuf. Mater. Process. 2024, 8(6), 282; https://doi.org/10.3390/jmmp8060282 - 4 Dec 2024

Abstract

Recently, there has been much scholarly research on the applications of CNTs in various fields which can be attributed to their outstanding properties. For that matter, machining processes as the backbone of manufacturing technologies have also benefited greatly from the introduction of CNTs. [...] Read more.

Recently, there has been much scholarly research on the applications of CNTs in various fields which can be attributed to their outstanding properties. For that matter, machining processes as the backbone of manufacturing technologies have also benefited greatly from the introduction of CNTs. However, there is a lack of papers that provide a holistic overview on potential applications, which impedes focused and robust research in their application. In this work, after providing an outline of the methods used in increasing the productivity of machining processes, we will review the ways in which CNTs, known for their remarkable mechanical, chemical, electrical, and thermal characteristics, enhance the productivity of machining processes. We emphasize fit-for-purpose applications to determine the fate of CNTs use in machining processes. We examine the applications of CNTs in enhancing the mechanical characteristics of cutting tools, which include increased wear resistance, strength, and thermal conductivity, thereby extending tool life and performance. Additionally, this work highlights the application of nanofluids in MQL systems, where CNTs play a crucial role in reducing friction and enhancing thermal management, leading to reduced lubricant usage while maintaining cooling and lubrication effectiveness. Full article

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11 pages, 4307 KiB

Open AccessArticle

Local Remelting in Laser Powder Bed Fusion

by Janno Lehmann, Martin Weise, Markus Köhler, Frank von Lacroix, Vasily Ploshikhin and Klaus Dilger

J. Manuf. Mater. Process. 2024, 8(6), 281; https://doi.org/10.3390/jmmp8060281 - 4 Dec 2024

Abstract

In Laser Powder Bed Fusion, process material defects such as a lack of fusion, powder inclusions and cavities occur repeatedly by chance. These stochastically distributed defects can significantly reduce the mechanical performance of the components during operation. Possible in situ repair solutions such [...] Read more.

In Laser Powder Bed Fusion, process material defects such as a lack of fusion, powder inclusions and cavities occur repeatedly by chance. These stochastically distributed defects can significantly reduce the mechanical performance of the components during operation. Possible in situ repair solutions such as multiple remelting of specific layer areas are promising approaches to avoid these defects in the finished component, thus improving the overall properties. In this context, the present study investigates the remelting of artificially introduced defects using the example of M789 tool steel. In the first step, the process parameter settings and mechanical properties were evaluated using a tensile test, and the density of the local repair was examined using X-ray computer tomography and a metallographic analysis. The results demonstrate that the mechanical properties of the tensile test are comparable with those of the reference samples while successfully increasing the component quality. This indicates that defects that arise during the process can be remelted without the loss of mechanical characteristics. Full article

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13 pages, 9271 KiB

Open AccessArticle

Effect of Powder Preparation of FeNiCoCrMo_0.5Al_1.3 High-Entropy Alloy on the Phase Composition and Properties of High-Velocity Oxy-Fuel-Sprayed Coatings

by Anton Semikolenov, Nikolay Mamaev, Tatiana Larionova, Svetlana Shalnova and Oleg Tolochko

J. Manuf. Mater. Process. 2024, 8(6), 280; https://doi.org/10.3390/jmmp8060280 - 3 Dec 2024

Abstract

In this work, the effect of high-entropy alloy powder preparation on the coatings deposited via high-velocity oxygen fuel sprayings was studied. The powders of FeNiCoCrMo_0.5Al_1.3 composition were prepared by milling and gas atomization. The structures, porosity, phase composition, and microhardness [...] Read more.

In this work, the effect of high-entropy alloy powder preparation on the coatings deposited via high-velocity oxygen fuel sprayings was studied. The powders of FeNiCoCrMo_0.5Al_1.3 composition were prepared by milling and gas atomization. The structures, porosity, phase composition, and microhardness of the coatings produced from mechanically alloyed and gas-atomized powders were compared. The influence of milling parameters on the powder phase composition and morphology was studied. Milling at 600 rpm for 1.5 h allowed the production of mechanically alloyed powder with a homogeneous distribution of Fe, Ni, and Al and thin lamellas enriched with Co, Cr, and Mo. Despite the difference in the feedstock powders’ phase compositions, the phase compositions of the coatings deposited from mechanically alloyed and gas-atomized powders are the same consisting of BCC, FCC solutions, and oxide. The amount of FCC solutions and oxide in the coating depends on the size distribution of the sprayed powder. It was found that the phase composition and the properties of the coatings deposited from the mechanically alloyed and gas-atomized powders of similar sizes are similar. Full article

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17 pages, 17995 KiB

Open AccessArticle

The Wettability and High-Temperature Properties of Porous BN/Si₃N₄ Ceramics Bonded with SiTi22 Filler

by Yanli Zhuang, Hao Cheng, Xiao Wang, Limin Dong, Panpan Lin, Tiesong Lin, Peng He, Dan Li, Xinxin Jin and Jian Li

J. Manuf. Mater. Process. 2024, 8(6), 279; https://doi.org/10.3390/jmmp8060279 - 3 Dec 2024

Abstract

The wettability and high-temperature mechanical properties of porous BN/Si₃N₄ ceramics brazed with SiTi22 (wt. %) filler were studied. It is manifested that SiTi22 filler presents remarkable wetting and spreading capabilities on the porous BN/Si₃N₄ ceramic surface. An [...] Read more.

The wettability and high-temperature mechanical properties of porous BN/Si₃N₄ ceramics brazed with SiTi22 (wt. %) filler were studied. It is manifested that SiTi22 filler presents remarkable wetting and spreading capabilities on the porous BN/Si₃N₄ ceramic surface. An interfacial reaction layer is generated at the interface, and the thickness of the reaction layer initially grows and subsequently remains constant with the escalation of temperature. Carbon coating modification is beneficial to the wettability and high-temperature mechanical properties of porous BN/Si₃N₄ ceramics. The wetting driving force is mainly controlled by the interfacial reaction at the three-phase line of the wetting front. The mechanical properties of the carbon-coated joints are significantly enhanced in comparison with uncoated joints. The joint strength attains a maximum value of roughly 73 MPa in the shear test implemented at 800 °C. The strength of the joint is significantly enhanced mainly due to the TiN_0.7C_0.3 particles that consume energy by changing the crack propagation direction, and the SiC nanowires strengthen the connection by bridging. Full article

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15 pages, 4416 KiB

Open AccessArticle

Investigation of the Fabrication Parameters’ Influence on the Tensile Strength of 3D-Printed Copper-Filled Metal Composite Using Design of Experiments

by Vasileios Kyratsis, Anastasios Tzotzis, Apostolos Korlos and Nikolaos Efkolidis

J. Manuf. Mater. Process. 2024, 8(6), 278; https://doi.org/10.3390/jmmp8060278 - 2 Dec 2024

Abstract

The present study investigates the effects of fabrication parameters such as the nozzle temperature, the flow rate, and the layer thickness on the tensile strength of copper-filled metal-composite specimens. The selected material is a polylactic acid (PLA) filament filled with 65% copper powder. [...] Read more.

The present study investigates the effects of fabrication parameters such as the nozzle temperature, the flow rate, and the layer thickness on the tensile strength of copper-filled metal-composite specimens. The selected material is a polylactic acid (PLA) filament filled with 65% copper powder. Two sets of 27 specimens each were fabricated, and equivalent tensile experiments were carried out using a universal testing machine. The experiments were planned according to the full factorial design, with three printing parameters, as well as three value levels for each parameter. The analysis revealed that the temperature and the flow rate had the greatest impact on the yielded tensile strength, with their contribution percentages being 42.41% and 22.16%, respectively. In addition, a regression model was developed based on the experimental data to predict the tensile strength of the 3D-printed copper-filled metal composite within the investigated range of parameters. The model was evaluated using statistical methods, highlighting its increased accuracy. Finally, an optimization study was carried out according to the principles of the desirability function. The optimal fabrication parameters were determined to maximize the tensile strength of the specimens: temperature equal to 220 °C, flow rate equal to 110%, and layer thickness close to 0.189 mm. Full article

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19 pages, 279 KiB

Open AccessReview

Root Cause Analysis in Industrial Manufacturing: A Scoping Review of Current Research, Challenges and the Promises of AI-Driven Approaches

by Dominik Pietsch, Marvin Matthes, Uwe Wieland, Steffen Ihlenfeldt and Torsten Munkelt

J. Manuf. Mater. Process. 2024, 8(6), 277; https://doi.org/10.3390/jmmp8060277 - 2 Dec 2024

Abstract

The manufacturing industry must maintain high-quality standards while meeting customer demands for customization, reduced carbon footprint, and competitive pricing. To address these challenges, companies are constantly improving their production processes using quality management tools. A crucial aspect of this improvement is the root [...] Read more.

The manufacturing industry must maintain high-quality standards while meeting customer demands for customization, reduced carbon footprint, and competitive pricing. To address these challenges, companies are constantly improving their production processes using quality management tools. A crucial aspect of this improvement is the root cause analysis of manufacturing defects. In recent years, there has been a shift from traditional knowledge-driven approaches to data-driven approaches. However, there is a gap in the literature regarding a systematic overview of both methodological types, their overlaps, and the challenges they pose. To fill this gap, this study conducts a scoping literature review of root cause analysis in manufacturing, focusing on both data-driven and knowledge-driven approaches. For this, articles from IEEE Xplore, Scopus, and Web of Science are examined. This review finds that data-driven approaches have become dominant in recent years, with explainable artificial intelligence emerging as a particularly strong approach. Additionally, hybrid variants of root cause analysis, which combine expert knowledge and data-driven approaches, are also prevalent, leveraging the strengths of both worlds. Major challenges identified include dependence on expert knowledge, data availability, and management issues, as well as methodological difficulties. This article also evaluates the potential of artificial intelligence and hybrid approaches for the future, highlighting their promises in advancing root cause analysis in manufacturing. Full article

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36 pages, 5234 KiB

Open AccessArticle

Evaluating Energy Efficiency and Optimal Positioning of Industrial Robots in Sustainable Manufacturing

by Roman Ruzarovsky, Tibor Horak and Robert Bocak

J. Manuf. Mater. Process. 2024, 8(6), 276; https://doi.org/10.3390/jmmp8060276 - 1 Dec 2024

Abstract

Optimizing the energy efficiency of robotic workstations is a key aspect of industrial automation. This study focuses on the analysis of the relationship between the position of the robot base and its energy consumption and time aspects. A number of 6-axis robots, including [...] Read more.

Optimizing the energy efficiency of robotic workstations is a key aspect of industrial automation. This study focuses on the analysis of the relationship between the position of the robot base and its energy consumption and time aspects. A number of 6-axis robots, including the ABB IRB 120 robot, were investigated in this research by combining measurements and simulations using the energy consumption measurement module in the ABB RobotStudio 2024.1.1 environment. The objective of this study was to develop an energy consumption model that can identify the optimal robot positions to minimize energy costs and time losses. The results suggest that the strategic positioning of the robot has a significant impact on its performance and efficiency. These results demonstrate that the ideal working distance of the robots is approximately 50% of its maximum range, and displacements along the X and Z axes affect the energy and time consumption. These findings suggest the existence of a trade-off between time and energy efficiency, providing a basis for further research into the optimization of robotic systems. Thus, this work offers new perspectives for the design of efficient robotic workstations for cross-sensory applications. Full article

(This article belongs to the Special Issue Sustainable Manufacturing for a Better Future)

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26 pages, 5235 KiB

Open AccessArticle

Flexible Symbiosis for Simulation Optimization in Production Scheduling: A Design Strategy for Adaptive Decision Support in Industry 5.0

by Mohaiad Elbasheer, Francesco Longo, Giovanni Mirabelli and Vittorio Solina

J. Manuf. Mater. Process. 2024, 8(6), 275; https://doi.org/10.3390/jmmp8060275 - 30 Nov 2024

Abstract

In the rapidly evolving landscape of Industry 4.0 and the transition towards Industry 5.0, manufacturing systems face the challenge of adapting to dynamic, hyper-customized demands. Current Simulation Optimization (SO) systems struggle with the flexibility needed for quick reconfiguration, often requiring time-consuming, resource-intensive efforts [...] Read more.

In the rapidly evolving landscape of Industry 4.0 and the transition towards Industry 5.0, manufacturing systems face the challenge of adapting to dynamic, hyper-customized demands. Current Simulation Optimization (SO) systems struggle with the flexibility needed for quick reconfiguration, often requiring time-consuming, resource-intensive efforts to develop custom models. To address this limitation, this study introduces an innovative SO design strategy that integrates three flexible simulation modeling techniques—template-based, structural modeling, and parameterization. The goal of this integrated design strategy is to enable the rapid adaptation of SO systems to diverse production environments without extensive re-engineering. The proposed SO versatility is validated across three manufacturing scenarios (flow shop, job shop, and open shop scheduling) using modified benchmark instances from Taillard’s dataset. The results demonstrate notable effectiveness in optimizing production schedules across these diverse scenarios, enhancing decision-making processes, and reducing SO development efforts. Unlike conventional SO system design, the proposed design framework ensures real-time adaptability, making it highly relevant to the dynamic requirements of Industry 5.0. This strategic integration of flexible modeling techniques supports efficient decision support, minimizes SO development time, and reinforces manufacturing resilience, therefore sustaining competitiveness in modern industrial ecosystems. Full article

(This article belongs to the Special Issue Smart Manufacturing in the Era of Industry 4.0)

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22 pages, 13474 KiB

Open AccessArticle

Multimodal Human–Robot Interaction Using Gestures and Speech: A Case Study for Printed Circuit Board Manufacturing

by Ángel-Gabriel Salinas-Martínez, Joaquín Cunillé-Rodríguez, Elías Aquino-López and Angel-Iván García-Moreno

J. Manuf. Mater. Process. 2024, 8(6), 274; https://doi.org/10.3390/jmmp8060274 - 30 Nov 2024

Abstract

In recent years, technologies for human–robot interaction (HRI) have undergone substantial advancements, facilitating more intuitive, secure, and efficient collaborations between humans and machines. This paper presents a decentralized HRI platform, specifically designed for printed circuit board manufacturing. The proposal incorporates many input devices, [...] Read more.

In recent years, technologies for human–robot interaction (HRI) have undergone substantial advancements, facilitating more intuitive, secure, and efficient collaborations between humans and machines. This paper presents a decentralized HRI platform, specifically designed for printed circuit board manufacturing. The proposal incorporates many input devices, including gesture recognition via Leap Motion and Tap Strap, and speech recognition. The gesture recognition system achieved an average accuracy of 95.42% and 97.58% for each device, respectively. The speech control system, called Cellya, exhibited a markedly reduced Word Error Rate of 22.22% and a Character Error Rate of 11.90%. Furthermore, a scalable user management framework, the decentralized multimodal control server, employs biometric security to facilitate the efficient handling of multiple users, regulating permissions and control privileges. The platform’s flexibility and real-time responsiveness are achieved through advanced sensor integration and signal processing techniques, which facilitate intelligent decision-making and enable accurate manipulation of manufacturing cells. The results demonstrate the system’s potential to improve operational efficiency and adaptability in smart manufacturing environments. Full article

(This article belongs to the Special Issue Smart Manufacturing in the Era of Industry 4.0)

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28 pages, 15253 KiB

Open AccessArticle

Impact of Uniaxial Pre-Strains on the Forming Limit Curve (FLC) of CuZn 70-30 Brass Sheets for Enhanced Formability in Production Applications Using the Nakajima Test

by Aseel Hamad Abed, Raed R. Shwaish, Asaad Ali Abbas, Baha S. Mahdi and Waleed Ahmed

J. Manuf. Mater. Process. 2024, 8(6), 273; https://doi.org/10.3390/jmmp8060273 - 28 Nov 2024

Abstract

Brass sheets are extensively utilized in the automotive, electrical, and other industries, where an in-depth understanding of their formability is crucial for achieving optimal performance in production applications. This study investigates the influence of uniaxial pre-strains on the Forming Limit Curve (FLC) of [...] Read more.

Brass sheets are extensively utilized in the automotive, electrical, and other industries, where an in-depth understanding of their formability is crucial for achieving optimal performance in production applications. This study investigates the influence of uniaxial pre-strains on the Forming Limit Curve (FLC) of CuZn 70-30 brass sheets, which aims to enhance their formability by identifying and optimizing key forming parameters. Adding a new variable, the impact of uniaxial pre-strain upon FLC, was our aim of this study and, consequently, the CuZn 70-30 brass sheet formability using punch-stretching tests with purpose-built tools, we experimentally obtained FLCs for brass sheets under varying levels of pre-strain (0.04, 0.06, and 0.08) applied through uniaxial tension by using Nakajima tests with purpose-built tools. The objective was to understand how specific factors such as punch parameters, punch corner radius, and strain rate impact the FLC and, consequently, the brass sheets formability. Results indicate a distinct trend of increasing pre-strain levels leading to a significant rise in minor strain capacity along the right portionof the FLC, with a comparatively insignificant effect on the left. This consistent elevation across strain paths suggests improved formability due to pre-straining, highlighting the potential for optimized manufacturing processes and enhanced product quality across industrial applications. Full article

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23 pages, 2332 KiB

Open AccessArticle

Concept for Predictive Quality in Carbon Fibre Manufacturing

by Sebastian Gellrich, Thomas Groetsch, Maxime Maghe, Claudia Creighton, Russell Varley, Anna-Sophia Wilde and Christoph Herrmann

J. Manuf. Mater. Process. 2024, 8(6), 272; https://doi.org/10.3390/jmmp8060272 - 28 Nov 2024

Abstract

Remarkable mechanical properties make carbon fibres attractive for many industrial applications. However, up to today, carbon fibres come with a significant environmental backpack, undermining their advantages in light of a strong demand for absolute sustainability of new industrial products. Consequently, there is considerable [...] Read more.

Remarkable mechanical properties make carbon fibres attractive for many industrial applications. However, up to today, carbon fibres come with a significant environmental backpack, undermining their advantages in light of a strong demand for absolute sustainability of new industrial products. Consequently, there is considerable demand for high-quality carbon fibre manufacturing, low waste production, or alternative precursor systems allowing minimization of environmental impacts. Therefore, this paper investigates the capabilities of data analytics with a special emphasis on predictive quality in order to advance the quality management of carbon fibre manufacturing. Although existing research supports the applicability of machine learning in carbon fibre production, there is a notable scarcity of case studies and a lack of a structured repetitive data analytics concept. To address this gap, the study proposes a holistic framework for predictive quality in carbon fibre manufacturing that outlines specific data analytics requirements based on the process properties of carbon fibre production. Additionally, it introduces a systematic method for processing trend data. Finally, a case study of polyacrylonitrile (PAN)-based carbon fibre manufacturing exemplifies the concept, giving indications on feature importance and sensitivity related to the expected fibre properties. Future research can build on the comprehensive overview of predictive quality potentials and its implementation concept by extending the underlying data set and investigating the transfer to alternative precursors. Full article

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12 pages, 21287 KiB

Open AccessArticle

Microstructure, Physical-Mechanical, and Magnetic Characteristics of a Butt-Welded Joint Obtained by Rotary Friction Welding Technology of Bimetallic Pipe

by Evgeniia Putilova, Kristina Kryucheva, Ivan Kamantsev and Elena Priymak

J. Manuf. Mater. Process. 2024, 8(6), 271; https://doi.org/10.3390/jmmp8060271 - 28 Nov 2024

Abstract

The development of technology, including in the oil and gas industry, necessitates the creation of materials with special sets of properties, such as high strength characteristics combined with corrosion resistance. One such material is bimetallic pipe, but we are faced with the problem [...] Read more.

The development of technology, including in the oil and gas industry, necessitates the creation of materials with special sets of properties, such as high strength characteristics combined with corrosion resistance. One such material is bimetallic pipe, but we are faced with the problem of creating extended structures and obtaining high-quality butt-welded joints of such industrial bimetallic pipes. The microstructure in different parts of the thermomechanically influenced zone of a butt-welded joint of a bimetallic pipe obtained by rotary friction welding (RFW) was investigated by optical and electron microscopy methods. It was established that during rotary friction welding of the bimetallic pipe in standard mode, one metal flowed into the zone of another. This could be explained by the different plastic properties of the steels that made up the bimetal, which must be taken into account in future welding. Standard RFW mode did not result in the formation of a high-quality weld; defects and discontinuities were observed in the joint area. The maximum hardness values were observed directly in the weld joint. It is concluded that rotary friction welding can be used as a welding technology for bimetallic pipes, but the most attention should be paid to the welding mode to obtain a high-quality butt-welded joint. Full article

(This article belongs to the Special Issue Advances in Dissimilar Metal Joining and Welding)

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17 pages, 42128 KiB

Open AccessArticle

Adaptation of Conventional Toolpath-Generation Software for Use in Curved-Layer Fused Deposition Modeling

by Samuel Maissen, Severin Zürcher and Michael Wüthrich

J. Manuf. Mater. Process. 2024, 8(6), 270; https://doi.org/10.3390/jmmp8060270 - 28 Nov 2024

Abstract

In 3D printing, the layered structure often results in artifacts. This effect becomes stronger for surfaces with a lower ramp angle. This effect can be mitigated by manufacturing parts with non-planar layers that fit the parts’ surface geometry. Using the open-source slicing software [...] Read more.

In 3D printing, the layered structure often results in artifacts. This effect becomes stronger for surfaces with a lower ramp angle. This effect can be mitigated by manufacturing parts with non-planar layers that fit the parts’ surface geometry. Using the open-source slicing software PrusaSlicer. an algorithm was developed to modify the slicer’s input and output data in a way that fits parts with low ramp angle surfaces. To achieve consistent part quality, all layers were modified to be printed in a non-planar way. The test results indicate that the proposed methods can significantly reduce surface roughness. Although the algorithm works well for parts with a flat base and vertical walls, it would need to be highly adapted to work for different part geometries. Additionally, compared to other algorithms used in Curved-Layer Fused Deposition Modeling (CLFDM), the changed layer structure introduces a changed visual appearance of parts. Full article

(This article belongs to the Special Issue Advances in Additive Manufacturing and Material Characterization Techniques)

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12 pages, 1782 KiB

Open AccessReview

Combining Neural Networks and Genetic Algorithms to Understand Composition–Microstructure–Property Relationships in Additively Manufactured Metals

by Sooraj Patel, Anvesh Nathani, Amin Poozesh, Shuozhi Xu, Pejman Kazempoor and Iman Ghamarian

J. Manuf. Mater. Process. 2024, 8(6), 269; https://doi.org/10.3390/jmmp8060269 - 28 Nov 2024

Abstract

Additive manufacturing (AM) has revolutionized the production of complex metallic components by enabling the direct fabrication of intricate geometries from 3D model data. Despite its advantages in reducing material waste and customization of mechanical properties, AM faces challenges related to microstructural heterogeneity and [...] Read more.

Additive manufacturing (AM) has revolutionized the production of complex metallic components by enabling the direct fabrication of intricate geometries from 3D model data. Despite its advantages in reducing material waste and customization of mechanical properties, AM faces challenges related to microstructural heterogeneity and mechanical property variability. This review highlights the structure–property relationships in additively manufactured metals, emphasizing how heterogeneous microstructure influences yield strength and fracture toughness. Phenomenological equations are provided based on the integration of neural networks and genetic algorithm-based models to predict mechanical properties from composition and microstructural features. We also outline key considerations such as acquiring high-fidelity datasets and understanding mathematical correlations within the data needed to formulate phenomenological equations. Full article

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16 pages, 8683 KiB

Open AccessArticle

Thermal and Mechanical Properties of Nano-TiC-Reinforced 18Ni300 Maraging Steel Fabricated by Selective Laser Melting

by Francisco F. Leite, Indrani Coondoo, João S. Vieira, José M. Oliveira and Georgina Miranda

J. Manuf. Mater. Process. 2024, 8(6), 268; https://doi.org/10.3390/jmmp8060268 - 28 Nov 2024

Abstract

Additive manufacturing (AM) has brought new possibilities to the moulding industry, particularly regarding the use of high-performance materials as maraging steels. This work explores 18Ni300 maraging steel reinforced with 4.5 vol.% TiC nanoparticles, fabricated by Selective Laser Melting (SLM), addressing the effect of [...] Read more.

Additive manufacturing (AM) has brought new possibilities to the moulding industry, particularly regarding the use of high-performance materials as maraging steels. This work explores 18Ni300 maraging steel reinforced with 4.5 vol.% TiC nanoparticles, fabricated by Selective Laser Melting (SLM), addressing the effect of post-fabrication aging treatment on both thermal and mechanical properties. Design of Experiments (DoE) was used to generate twenty-five experimental groups, in which laser power, scanning speed, and hatch distance were varied across five levels, with the aim of generating conclusions on optimal fabrication conditions. A comprehensive analysis was performed, starting with the nanocomposite feedstock and then involving the microstructural, mechanical, and thermal characterisation of SLM-fabricated nanocomposites. Nanocomposite relative density varied between 92.84% and 99.73%, and the presence of martensite, austenite, and TiC was confirmed in the as-built and heat-treated conditions. Results demonstrated a hardness of 411 HV for the as-built 18Ni300-TiC nanocomposite, higher than that of the non-reinforced steel, and this was further increased by performing aging treatment, achieving a hardness of 673 HV. Thermal conductivity results showed an improvement from ~12 W/m·K to ~19 W/m·K for nano-TiC-reinforced 18Ni300 when comparing values before and after heat treatment, respectively. Results showed that the addition of TiC nanoparticles to 18Ni300 maraging steel led to a combined thermal and mechanical performance suited for applications in which heat extraction is required, as in injection moulding. Full article

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Journal of Manufacturing and Materials Processing

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