Journal of Manufacturing and Materials Processing

22 pages, 14393 KiB

Open AccessArticle

Pressure and Liquid Distribution under the Blade of a Basket Extruder of Continuous Wet Granulation of Model Material

by Roman Fekete, Peter Peciar, Martin Juriga, Štefan Gužela, Michaela Peciarová, Dušan Horváth and Marian Peciar

J. Manuf. Mater. Process. 2024, 8(3), 127; https://doi.org/10.3390/jmmp8030127 - 18 Jun 2024

Viewed by 931

Abstract

This study explores the influence of blade design on the low-pressure extrusion process, which is relevant to techniques like spheronization. We investigate how blade geometry affects the extruded paste and final product properties. A model paste was extruded through a basket extruder with [...] Read more.

This study explores the influence of blade design on the low-pressure extrusion process, which is relevant to techniques like spheronization. We investigate how blade geometry affects the extruded paste and final product properties. A model paste was extruded through a basket extruder with varying blade lengths to create distinct wedge gaps (20°, 26° and 32° contact angles). The theoretical analysis explored paste behavior within the gap and extrudate. A model material enabled objective comparison across blade shapes. Our findings reveal a significant impact of blade design on the pressure profile, directly influencing liquid distribution in the paste and extrudate. It also affects the required torque relative to extruder output. The findings of this study hold significant implications for continuous granulation, a technique employed in the pharmaceutical industry for producing granules with uniform size and properties. Understanding the influence of blade geometry on the extrusion process can lead to the development of optimized blade designs that enhance granulation efficiency, improve product quality, and reduce energy consumption. By tailoring blade geometry, manufacturers can achieve more consistent granule characteristics, minimize process variability, and ultimately produce pharmaceuticals with enhanced efficacy. Full article

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25 pages, 16854 KiB

Open AccessArticle

Optimizing the Electrical Discharge Machining Process Parameters of the Nimonic C263 Superalloy: A Sustainable Approach

by Renu Kiran Shastri, Chinmaya Prasad Mohanty, Umakant Mishra, Tapano Kumar Hotta, Viraj Vishwas Patil and Konda Gokuldoss Prashanth

J. Manuf. Mater. Process. 2024, 8(3), 126; https://doi.org/10.3390/jmmp8030126 - 15 Jun 2024

Viewed by 1268

Abstract

Engineers continue to be concerned about electrical discharge-machined components’ high energy consumption, machining debris, and poor dimensional precision. The aim of this research is to propose a hybrid neuro-genetic approach to improve the machinability of the electrical discharge machining (EDM) of the Nimonic [...] Read more.

Engineers continue to be concerned about electrical discharge-machined components’ high energy consumption, machining debris, and poor dimensional precision. The aim of this research is to propose a hybrid neuro-genetic approach to improve the machinability of the electrical discharge machining (EDM) of the Nimonic C263 superalloy. This approach focuses on reducing the energy consumption and negative environmental impacts. The material removal rate (MRR), electrode wear ratio (EWR), specific energy consumption (SEC), surface roughness (Ra), machining debris (db), and circularity (C) are examined as a function of machining parameters such as the voltage (V), pulse on time (T_on), current (I), duty factor (τ), and electrode type. By employing the VIKOR method, all the responses are transformed into a distinctive VIKOR index (VI). Neuro-genetic methods (a hybrid VIKOR-based ANN-GA) can further enhance the best possible result from the VIKOR index. During this step, the hybrid technique (VIKOR-based ANN-GA) is used to estimate an overall improvement of 9.87% in the response, and an experiment is conducted to confirm this condition of optimal machining. This work is competent enough to provide aeroengineers with an energy-efficient, satisfying workplace by lowering the machining costs and increasing productivity. Full article

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15 pages, 5556 KiB

Open AccessArticle

The Machining and Surface Modification of H13 Die Steel via the Electrical Discharge Machining Process Using Graphite Mixed Dielectric

by Dharmesh Singh, Parveen Goyal and Shankar Sehgal

J. Manuf. Mater. Process. 2024, 8(3), 125; https://doi.org/10.3390/jmmp8030125 - 14 Jun 2024

Viewed by 1017

Abstract

Surface modification through electrical discharge machining (EDM) results in many advantages, such as improved surface hardness, enhanced wear resistance, and better micro-structuring. During EDM-based surface modification, either the eroding tool electrode or a powder-mixed dielectric can be utilized to add material onto the [...] Read more.

Surface modification through electrical discharge machining (EDM) results in many advantages, such as improved surface hardness, enhanced wear resistance, and better micro-structuring. During EDM-based surface modification, either the eroding tool electrode or a powder-mixed dielectric can be utilized to add material onto the machined surface of the workpiece. The current study looks at the surface modification of H13 die steel using EDM in a dielectric medium mixed with graphite powder. The experiments were carried out using a Taguchi experimental design. In this work, peak current, pulse-on time, and powder concentration are taken into consideration as input factors. Tool wear rate (TWR), material removal rate (MRR), and the microhardness of the surface of the machined specimen are taken as output parameters. The machined surface’s microhardness was found to have improved by 159%. The results of X-ray diffraction (XRD) and energy dispersive X-ray spectroscopy (EDS) analysis and changes in MRR and TWR due to the powder-mixed dielectric are also discussed in detail. Full article

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19 pages, 7997 KiB

Open AccessArticle

Improving Deposited Surface Quality in Additive Manufacturing Using Structured Light Scanning Characterization and Mechanistic Modeling

by Tuhin Mukherjee, Weijun Shen, Yiliang Liao and Beiwen Li

J. Manuf. Mater. Process. 2024, 8(3), 124; https://doi.org/10.3390/jmmp8030124 - 14 Jun 2024

Cited by 1 | Viewed by 1231

Abstract

The surface quality of parts fabricated using laser-directed energy deposition additive manufacturing significantly affects the fatigue life, corrosion resistance, and performance of the components. Surface quality improvements remain a key challenge in laser-directed energy deposition because of the involvement of multiple simultaneously occurring [...] Read more.

The surface quality of parts fabricated using laser-directed energy deposition additive manufacturing significantly affects the fatigue life, corrosion resistance, and performance of the components. Surface quality improvements remain a key challenge in laser-directed energy deposition because of the involvement of multiple simultaneously occurring physical phenomena controlling the surface characteristics. Here, a unique combination of structured light scanning characterization and mechanistic modeling was used to identify three key physical factors that affect surface quality. These factors include a geometric factor, an instability factor, and a disintegration factor, which were calculated using a mechanistic model and correlated with the surface characteristics data obtained from the structured light scanning characterization. It was found that these factors can precisely explain the variations in the average surface roughness. In addition, skewness and kurtosis of the surfaces made by laser-directed energy deposition were found to be significantly better than those observed in traditional manufacturing. Based on the experimental and modeling results, a surface quality process map was constructed that can guide engineers in selecting appropriate sets of process variables to improve deposit surface quality in additive manufacturing. Full article

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14 pages, 8100 KiB

Open AccessArticle

Additive Manufacturing of Ti₃AlC₂/TiC and Ti₃AlC₂/SiC Ceramics Using the Fused Granules Fabrication Technique

by Maksim Krinitcyn, Georgy Kopytov and Egor Ryumin

J. Manuf. Mater. Process. 2024, 8(3), 123; https://doi.org/10.3390/jmmp8030123 - 13 Jun 2024

Viewed by 1214

Abstract

In this work, SiC–Ti₃AlC₂ and TiC–Ti₃AlC₂ composites produced by additive manufacturing are investigated. The issue of obtaining ceramic materials using additive manufacturing technologies is currently relevant, since not many modern additive technologies are suitable for working with [...] Read more.

In this work, SiC–Ti₃AlC₂ and TiC–Ti₃AlC₂ composites produced by additive manufacturing are investigated. The issue of obtaining ceramic materials using additive manufacturing technologies is currently relevant, since not many modern additive technologies are suitable for working with ceramic materials. The study is devoted to the optimization of additive manufacturing parameters, as well as the study of the structure and properties of the resulting objects. The fused granules fabrication (FGF) method as one kind of the material extrusion additive manufacturing (MEAM) technology is used to obtain composite samples. The main advantage of the FGF technology is the ability to obtain high-quality samples from ceramic materials by additive manufacturing. Composites with different ratios between components and different powder/polymer ratios are investigated. The technological features of the additive formation of composites are investigated, as well as their structure and properties. The optimal sintering temperature to form the best mechanical properties for both composites is 1300 °C. The composites have a regulatable porosity. Ti₃AlC₂ content, sintering temperature, and polymer content in the feedstock are the main parameters that regulate the porosity of FGF samples. Full article

(This article belongs to the Special Issue Advances in Material Forming: 2nd Edition)

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16 pages, 1316 KiB

Open AccessArticle

Stability of Micro-Milling Tool Considering Tool Breakage

by Yuan-Yuan Ren, Bao-Guo Jia, Min Wan and Hui Tian

J. Manuf. Mater. Process. 2024, 8(3), 122; https://doi.org/10.3390/jmmp8030122 - 11 Jun 2024

Viewed by 1251

Abstract

Micro-milling, widely employed across various fields, faces significant challenges due to the small diameter and limited stiffness of its tools, making the process highly susceptible to cutting chatter and premature tool breakage. Ensuring stable and safe cutting processes necessitates the prediction of chatter [...] Read more.

Micro-milling, widely employed across various fields, faces significant challenges due to the small diameter and limited stiffness of its tools, making the process highly susceptible to cutting chatter and premature tool breakage. Ensuring stable and safe cutting processes necessitates the prediction of chatter by considering the tool breakage. Crucially, the modal parameters of the spindle–holder–tool system are important prerequisites for such stability prediction. In this paper, the frequency response functions (FRFs) of the micro-milling tool are calculated by direct FRFs of the micro-milling cutter and cross FRFs between a point on the shank and one on the tool tip. Additionally, by utilizing a cutting force model specific to micro-milling, the bending stress experienced by the tool is computed, and the tool breakage curve is subsequently determined based on the material’s permissible maximum allowable stress. The FRFs of the micro-milling tool, alongside the tool breakage curve, are then integrated to generate the final stability lobe diagrams (SLDs). The effectiveness and reliability of the proposed methodology are confirmed through a comprehensive series of numerical and experimental validations. Full article

(This article belongs to the Special Issue Dynamics and Machining Stability for Flexible Systems)

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28 pages, 1690 KiB

Open AccessReview

Application of Microwave Energy to Biomass: A Comprehensive Review of Microwave-Assisted Technologies, Optimization Parameters, and the Strengths and Weaknesses

by Alejandra Sophia Lozano Pérez, Juan José Lozada Castro and Carlos Alberto Guerrero Fajardo

J. Manuf. Mater. Process. 2024, 8(3), 121; https://doi.org/10.3390/jmmp8030121 - 7 Jun 2024

Cited by 3 | Viewed by 2543

Abstract

This review article focuses on the application of microwave-assisted techniques in various processes, including microwave-assisted extraction, microwave-assisted pyrolysis, microwave-assisted acid hydrolysis, microwave-assisted organosolv, and microwave-assisted hydrothermal pretreatment. This article discusses the mechanisms behind these techniques and their potential for increasing yield, producing more [...] Read more.

This review article focuses on the application of microwave-assisted techniques in various processes, including microwave-assisted extraction, microwave-assisted pyrolysis, microwave-assisted acid hydrolysis, microwave-assisted organosolv, and microwave-assisted hydrothermal pretreatment. This article discusses the mechanisms behind these techniques and their potential for increasing yield, producing more selectivity, and lowering reaction times while reducing energy usage. It also highlights the advantages and disadvantages of each process and emphasizes the need for further research to scale the processes and optimize conditions for industrial applications. A specific case study is presented on the pretreatment of coffee waste, demonstrating how the choice of microwave-assisted processes can lead to different by-products depending on the initial composition of the biomass. Full article

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

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29 pages, 6590 KiB

Open AccessArticle

Theoretical Assessment of the Environmental Impact of the Preheating Stage in Thermoplastic Composite Processing: A Step toward Sustainable Manufacturing

by Abbas Hosseini

J. Manuf. Mater. Process. 2024, 8(3), 120; https://doi.org/10.3390/jmmp8030120 - 7 Jun 2024

Viewed by 1214

Abstract

Manufacturing processes have always played a pivotal role in the life cycle assessment of products, necessitating focused efforts to minimize their impact on the environment. Thermoplastic composite manufacturing is no exception to this concern. Within thermoplastic composite manufacturing, the preheating process stands out [...] Read more.

Manufacturing processes have always played a pivotal role in the life cycle assessment of products, necessitating focused efforts to minimize their impact on the environment. Thermoplastic composite manufacturing is no exception to this concern. Within thermoplastic composite manufacturing, the preheating process stands out as one of the most energy-intensive stages, significantly affecting the environment. In this study, a theoretical analysis is conducted to compare three modes of preheating: conductive, radiative, and convective modes, considering their energy consumption and environmental impact. The analysis reveals the potential for substantial energy savings and emissions reduction through the selection of a proper preheating mode. Since the analysis used in this study is theoretical, it facilitates a parametric study of different modes of preheating to assess how process parameters impact the environment. Moreover, this study includes a comparison between emissions from material production and the preheating process, highlighting the substantial contribution of the preheating process to the overall product life cycle assessment. Full article

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

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13 pages, 4017 KiB

Open AccessEditor’s ChoiceArticle

Effects of Oil Concentration in Flood Cooling on Cutting Force, Tool Wear and Surface Roughness in GTD-111 Nickel-Based Superalloy Slot Milling

by Gábor Kónya and Zsolt F. Kovács

J. Manuf. Mater. Process. 2024, 8(3), 119; https://doi.org/10.3390/jmmp8030119 - 7 Jun 2024

Viewed by 978

Abstract

Cooling–lubricating processes have a big impact on cutting force, tool wear, and the quality of the machined surface, especially for hard-to-machine superalloys, so the choice of the right cooling–lubricating method is of great importance. Nickel-based superalloys are among the most difficult materials to [...] Read more.

Cooling–lubricating processes have a big impact on cutting force, tool wear, and the quality of the machined surface, especially for hard-to-machine superalloys, so the choice of the right cooling–lubricating method is of great importance. Nickel-based superalloys are among the most difficult materials to machine due to their high hot strength, work hardening, and extremely low thermal conductivity. Previous research has shown that flood cooling results in the least tool wear and cutting force among different cooling–lubricating methods. Thus, the effects of the flood oil concentration (3%; 6%; 9%; 12%; and 15%) on the above-mentioned factors were investigated during the slot milling of the GTD-111 nickel-based superalloy. The cutting force was measured during machining with a Kistler three-component dynamometer, and then after cutting the tool wear and the surface roughness on the bottom surface of the milled slots were measured with a confocal microscope and tactile roughness tester. The results show that at a 12% oil concentration, the tool load and tool wear are the lowest; even at an oil concentration of 15%, a slight increase is observed in both factors. Essentially, a higher oil concentration reduces friction between the tool and the workpiece contact surface, resulting in reduced tool wear and cutting force. Furthermore, due to less friction, the heat generation in the cutting zone is also reduced, resulting in a lower heat load on the tool, which increases tool life. It is interesting to note that the 6% oil concentration had the highest cutting force and tool wear, and strong vibration was heard during machining, which is also reflected in the force signal. The change in oil concentration did not effect the surface roughness. Full article

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18 pages, 9340 KiB

Open AccessArticle

Fused Filament Fabrication of WC-10Co Hardmetals: A Study on Binder Formulations and Printing Variables

by Julián David Rubiano Buitrago, Andrés Fernando Gil Plazas, Luis Alejandro Boyacá Mendivelso and Liz Karen Herrera Quintero

J. Manuf. Mater. Process. 2024, 8(3), 118; https://doi.org/10.3390/jmmp8030118 - 31 May 2024

Viewed by 1110

Abstract

This research explores the utilization of powder fused filament fabrication (PFFF) for producing tungsten carbide-cobalt (WC-10Co) hardmetals, focusing on binder formulations and their impact on extrusion force as well as the influence of printing variables on the green and sintered density of samples. [...] Read more.

This research explores the utilization of powder fused filament fabrication (PFFF) for producing tungsten carbide-cobalt (WC-10Co) hardmetals, focusing on binder formulations and their impact on extrusion force as well as the influence of printing variables on the green and sintered density of samples. By examining the interplay between various binder compositions and backbone contents, this study aims to enhance the mechanical properties of the sintered parts while reducing defects inherent in the printing process. Evidence suggests that formulated feedstocks affect the hardness of the sintered hardmetal—not due to microstructural changes but macrostructural responses such as macro defects introduced during printing, debinding, and sintering of samples. The results demonstrate the critical role of polypropylene grafted with maleic anhydride (PP-MA) content in improving part density and sintered hardness, indicating the need for tailored thermal debinding protocols tailored to each feedstock. This study provides insights into feedstock formulation for hardmetal PFFF, proposing a path toward refining manufacturing processes to achieve better quality and performance of 3D printed hardmetal components. Full article

(This article belongs to the Special Issue High-Performance Metal Additive Manufacturing)

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26 pages, 14300 KiB

Open AccessArticle

SolDef_AI: An Open Source PCB Dataset for Mask R-CNN Defect Detection in Soldering Processes of Electronic Components

by Gianmauro Fontana, Maurizio Calabrese, Leonardo Agnusdei, Gabriele Papadia and Antonio Del Prete

J. Manuf. Mater. Process. 2024, 8(3), 117; https://doi.org/10.3390/jmmp8030117 - 31 May 2024

Cited by 1 | Viewed by 1992

Abstract

The soldering process for aerospace applications follows stringent requirements and standards to ensure the reliability and safety of electronic connections in aerospace systems. For this reason, the quality control phase plays an important role to guarantee requirements compliance. This process often requires manual [...] Read more.

The soldering process for aerospace applications follows stringent requirements and standards to ensure the reliability and safety of electronic connections in aerospace systems. For this reason, the quality control phase plays an important role to guarantee requirements compliance. This process often requires manual control since technicians’ knowledge is fundamental to obtain effective quality check results. In this context, the authors have developed a new open source dataset (SolDef_AI) to implement an innovative methodology for printed circuit board (PCB) defect detection exploiting the Mask R-CNN algorithm. The presented open source dataset aims to overcome the challenges associated with the availability of datasets for model training in this specific research and electronics industrial field. The dataset is open source and available online. Full article

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22 pages, 8399 KiB

Open AccessArticle

Process Optimization and Distortion Prediction in Directed Energy Deposition

by Adem Ben Hammouda, Hatem Mrad, Haykel Marouani, Ahmed Frikha and Tikou Belem

J. Manuf. Mater. Process. 2024, 8(3), 116; https://doi.org/10.3390/jmmp8030116 - 30 May 2024

Viewed by 910

Abstract

Directed energy deposition (DED), a form of additive manufacturing (AM), is gaining traction for its ability to produce complex metal parts with precise geometries. However, defects like distortion, residual stresses, and porosity can compromise part quality, leading to rejection. This research addresses this [...] Read more.

Directed energy deposition (DED), a form of additive manufacturing (AM), is gaining traction for its ability to produce complex metal parts with precise geometries. However, defects like distortion, residual stresses, and porosity can compromise part quality, leading to rejection. This research addresses this challenge by emphasizing the importance of monitoring process parameters (overlayer distance, powder feed rate, and laser path/power/spot size) to achieve desired mechanical properties. To improve DED quality and reliability, a numerical approach is presented and compared with an experimental work. The parametric finite element model and predictive methods are used to quantify and control material behavior, focusing on minimizing residual stresses and distortions. Numerical simulations using the Abaqus software 2022 are validated against experimental results to predict distortion and residual stresses. A coupled thermomechanical analysis model is employed to understand the impact of thermal distribution on the mechanical responses of the parts. Finally, new strategies based on laser scan trajectory and power are proposed to reduce residual stresses and distortions, ultimately enhancing the quality and reliability of DED-manufactured parts. Full article

(This article belongs to the Special Issue Industry 4.0 and Smart Materials Processing for Enhanced Manufacturing)

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26 pages, 8146 KiB

Open AccessEditor’s ChoiceArticle

A Comparative Study of Different Milling Strategies on Productivity, Tool Wear, Surface Roughness, and Vibration

by Francisco J. G. Silva, Rui P. Martinho, Luís L. Magalhães, Filipe Fernandes, Rita C. M. Sales-Contini, Luís M. Durão, Rafaela C. B. Casais and Vitor F. C. Sousa

J. Manuf. Mater. Process. 2024, 8(3), 115; https://doi.org/10.3390/jmmp8030115 - 30 May 2024

Cited by 1 | Viewed by 1310

Abstract

Strategies for obtaining deep slots in soft materials can vary significantly. Conventionally, the tool travels along the slot, removing material mainly with the side cutting edges. However, a “plunge milling” strategy is also possible, performing the cut vertically, taking advantage of the tip [...] Read more.

Strategies for obtaining deep slots in soft materials can vary significantly. Conventionally, the tool travels along the slot, removing material mainly with the side cutting edges. However, a “plunge milling” strategy is also possible, performing the cut vertically, taking advantage of the tip cutting edges that almost reach the center of the tool. Although both strategies are already commonly used, there is a clear gap in the literature in studies that compare tool wear, surface roughness, and productivity in each case. This paper describes an experimental study comparing the milling of deep slots in AA7050-T7451 aluminum alloy, coated with a novel DLCSiO500W3.5O₂ layer to minimize the aluminum adhesion to the tool, using conventional and plunge milling strategies. The main novelty of this paper is to present a broad study regarding different factors involved in machining operations and comparing two distinct strategies using a novel tool coating in the milling of aeronautical aluminum alloy. Tool wear is correlated with the vibrations of the tools in each situation, the cycle time is compared between the cases studied, and the surface roughness of the machined surfaces is analyzed. This study concludes that the cycle time of plunge milling can be about 20% less than that of conventional milling procedures, favoring economic sustainability and modifying the wear observed on the tools. Plunge milling can increase productivity, does not increase tool tip wear, and avoids damaging the side edges of the tool, which can eventually be used for final finishing operations. Therefore, it can be said that the plunge milling strategy improves economic and environmental sustainability as it uses all the cutting edges of the tools in a more balanced way, with less global wear. Full article

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19 pages, 9216 KiB

Open AccessArticle

Monitoring Variability in Melt Pool Spatiotemporal Dynamics (VIMPS): Towards Proactive Humping Detection in Additive Manufacturing

by Mohamed Abubakr Hassan, Mahmoud Hassan, Chi-Guhn Lee and Ahmad Sadek

J. Manuf. Mater. Process. 2024, 8(3), 114; https://doi.org/10.3390/jmmp8030114 - 29 May 2024

Cited by 2 | Viewed by 1173

Abstract

Humping is a common defect in direct energy deposition processes that reduces the geometric integrity of printed products. The available literature on humping detection is deemed reactive, as they focus on detecting late-stage melt pool spatial abnormalities. Therefore, this work introduces a novel, [...] Read more.

Humping is a common defect in direct energy deposition processes that reduces the geometric integrity of printed products. The available literature on humping detection is deemed reactive, as they focus on detecting late-stage melt pool spatial abnormalities. Therefore, this work introduces a novel, proactive indicator designed to detect early-stage spatiotemporal abnormalities. Specifically, the proposed indicator monitors the variability of instantaneous melt pool solidification-front speed (VIMPS). The solidification front dynamics quantify the intensity of cyclic melt pool elongation induced by early-stage humping. VIMPS tracks the solidification front dynamics based on the variance in the melt pool infrared radiations. Qualitative and quantitive analysis of the collected infrared data confirms VIMPS’s utility in reflecting the intricate humping-induced dynamics and defects. Experimental results proved VIMPS’ proactivity. By capturing early spatiotemporal abnormalities, VIMPS predicted humping by up to 10 s before any significant geometric defects. In contrast, current spatial abnormality-based methods failed to detect humping until 20 s after significant geometric defects had occurred. VIMPS’ proactive detection capabilities enable effective direct energy deposition control, boosting the process’s productivity and quality. Full article

(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)

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19 pages, 33144 KiB

Open AccessArticle

Performance Analysis of Helical Milling and Drilling Operations While Machining Carbon Fiber-Reinforced Aluminum Laminates

by Gururaj Bolar, Anoop Aroor Dinesh, Ashwin Polishetty, Raviraj Shetty, Anupama Hiremath and V. L. Neelakantha

J. Manuf. Mater. Process. 2024, 8(3), 113; https://doi.org/10.3390/jmmp8030113 - 29 May 2024

Viewed by 1009

Abstract

Being a difficult-to-cut material, Fiber Metal Laminates (FML) often pose challenges during conventional drilling and require judicious selection of machining parameters to ensure defect-free laminates that can serve reliably during their service lifetime. Helical milling is a promising technique for producing good-quality holes [...] Read more.

Being a difficult-to-cut material, Fiber Metal Laminates (FML) often pose challenges during conventional drilling and require judicious selection of machining parameters to ensure defect-free laminates that can serve reliably during their service lifetime. Helical milling is a promising technique for producing good-quality holes and is preferred over conventional drilling. The paper compares conventional drilling with the helical milling technique for producing holes in carbon fiber-reinforced aluminum laminates. The effect of machining parameters, such as cutting speed and axial feed, on the magnitude of cutting force and the machining temperature during conventional drilling as well as helical milling is studied. It was observed that the thrust force produced during machining reduces considerably during helical milling in comparison to conventional drilling at a constant axial feed rate. The highest machining temperature recorded for helical milling was much lower in comparison to the highest machining temperature measured during conventional drilling. The machining temperatures recorded during helical milling were well below the glass transition temperature of the epoxy used in carbon fiber prepreg, hence protecting the prepreg from thermal degradation during the hole-making process. The surface roughness of the holes produced by both techniques is measured, and the surface morphology of the drilled holes is analyzed using a scanning electron microscope. The surface roughness of the helical-milled holes was lower than that for holes produced by conventional drilling. Scanning electron microscope images provided insights into the interaction of the hole surface with the chips during the chip evacuation stage under different speeds and feed rates. The microhardness of the aluminum layers increased after processing holes using drilling and helical milling operations. The axial feed/axial pitch had minimal influence on the microhardness increase in comparison to the cutting speed. Full article

(This article belongs to the Topic Advanced Composites Manufacturing and Plastics Processing)

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16 pages, 13981 KiB

Open AccessArticle

Electrical Smoothing of the Powder Bed Surface in Laser-Based Powder Bed Fusion of Metals

by Andreas Hofmann, Tim Grotz, Nico Köstler, Alexander Mahr and Frank Döpper

J. Manuf. Mater. Process. 2024, 8(3), 112; https://doi.org/10.3390/jmmp8030112 - 28 May 2024

Cited by 1 | Viewed by 1070

Abstract

Achieving a homogeneous and uniform powder bed surface as well as a defined, uniform layer thickness is crucial for achieving reproducible component properties that meet requirements when powder bed fusion of metals with a laser beam. The existing recoating processes cause wear of [...] Read more.

Achieving a homogeneous and uniform powder bed surface as well as a defined, uniform layer thickness is crucial for achieving reproducible component properties that meet requirements when powder bed fusion of metals with a laser beam. The existing recoating processes cause wear of the recoater blade due to protruded, melted obstacles, which affects the powder bed surface quality locally. Impairments to the powder bed surface quality have a negative effect on the resulting component properties such as surface quality and relative density. This can lead either to scrapped components or to additional work steps such as surface reworking. In this work, an electric smoother is presented with which a wear-free and contactless smoothing of the powder bed can be realized. The achievable powder bed surface quality was analyzed using optical profilometry. It was found that the electric smoother can compensate for impairments in the powder bed surface and achieve a reproducible surface quality of the powder bed regardless of the initial extent of the impairments. Consequently, the electric smoother offers a promising opportunity to reduce the scrap rate in PBF-LB/M and to increase component quality. Full article

(This article belongs to the Special Issue Design, Processes and Materials for Additive Manufacturing)

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12 pages, 1160 KiB

Open AccessArticle

Green Innovation Practices: A Case Study in a Foundry

by Gianluca Fratta, Ivan Stefani, Sara Tapola and Stefano Saetta

J. Manuf. Mater. Process. 2024, 8(3), 111; https://doi.org/10.3390/jmmp8030111 - 26 May 2024

Viewed by 1400

Abstract

The foundry industry is responsible for the production of several potentially polluting and hazardous compounds. One of the major sources of pollution is the use of organic binders for the manufacturing of sand cores and sand moulds. To address this problem, in recent [...] Read more.

The foundry industry is responsible for the production of several potentially polluting and hazardous compounds. One of the major sources of pollution is the use of organic binders for the manufacturing of sand cores and sand moulds. To address this problem, in recent years, the use of low-emission products, known as inorganic binders, has been proposed. Their use in ferrous foundries, otherwise, is limited due to some problematic features that complicate their introduction in the manufacturing process, as often happens when a breakthrough innovation is introduced. In light of this, the aim of this work is to provide a Green Innovation Practice (GIP) to manage the introduction of green breakthrough innovations, as previously described, within an existing productive context. This practice was applied to better manage the experimental phase of the Green Casting Life Project, which aims to evaluate the possibility of using inorganic binders for the production of ferrous castings. After describing the state of the art of GIPs and their application in manufacturing contexts, the paper described the proposed GIP and its application to a real case consisting of testing inorganic binders in a ferrous foundry. Full article

(This article belongs to the Special Issue Industry 4.0 and Smart Materials Processing for Enhanced Manufacturing)

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17 pages, 6785 KiB

Open AccessEditor’s ChoiceArticle

Microstructure and Thermal Mechanical Behavior of Arc-Welded Aluminum Alloy 6061-T6

by Zeli Arhumah and Xuan-Tan Pham

J. Manuf. Mater. Process. 2024, 8(3), 110; https://doi.org/10.3390/jmmp8030110 - 26 May 2024

Cited by 1 | Viewed by 1032

Abstract

In this study, the welding thermal cycle, as well as the microstructural and mechanical properties of welded AA6061-T6 plates, were studied. The plates were prepared and bead-on-plate welded using gas metal arc welding (GMAW). Numerical simulations using SYSWELD^® were performed to obtain [...] Read more.

In this study, the welding thermal cycle, as well as the microstructural and mechanical properties of welded AA6061-T6 plates, were studied. The plates were prepared and bead-on-plate welded using gas metal arc welding (GMAW). Numerical simulations using SYSWELD^® were performed to obtain the thermal distribution in the welded plates. The numerical heat source was calibrated using the temperatures obtained from the experimental work and the geometry of the melting pool. The mechanical properties were obtained through microhardness tests and were correlated with the welding thermal cycle. Moreover, the mechanical behavior and local deformation in the heat-affected zone (HAZ) were investigated using micro-flat tensile (MFT) tests with digital image correlation (DIC). The mechanical properties of the subzones in the HAZ were then correlated with the welding thermal cycle and with the microstructure of the HAZ. It was observed that the welding thermal cycle produced microstructural variations across the HAZ, which significantly affected the mechanical behavior of the HAZ subzones. The results revealed that MFT tests with the DIC technique are an excellent tool for studying the local mechanical behavior change in AA6061-T6 welded parts due to the welding heat. Full article

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15 pages, 8105 KiB

Open AccessArticle

Milling Stability Modeling by Sample Partitioning with Chatter Frequency-Based Test Point Selection

by Tony Schmitz

J. Manuf. Mater. Process. 2024, 8(3), 109; https://doi.org/10.3390/jmmp8030109 - 24 May 2024

Viewed by 1259

Abstract

This paper describes a sample partitioning approach to retain or reject samples from an initial distribution of stability maps using milling test results. The stability maps are calculated using distributions of uncertain modal parameters that represent the tool tip frequency response functions and [...] Read more.

This paper describes a sample partitioning approach to retain or reject samples from an initial distribution of stability maps using milling test results. The stability maps are calculated using distributions of uncertain modal parameters that represent the tool tip frequency response functions and cutting force model coefficients. Test points for sample partitioning are selected using either (1) the combination of spindle speed and mean axial depth from the available samples that provides the high material removal rate, or (2) a spindle speed based on the chatter frequency and mean axial depth at that spindle speed. The latter is selected when an unstable (chatter) result is obtained from a test. Because the stability model input parameters are also partitioned using the test results, their uncertainty is reduced using a limited number of tests and the milling stability model accuracy is increased. A case study is provided to evaluate the algorithm. Full article

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23 pages, 3023 KiB

Open AccessArticle

Tool Wear Monitoring in Micro-Milling Based on Digital Twin Technology with an Extended Kalman Filter

by Christiand, Gandjar Kiswanto, Ario Sunar Baskoro, Zulhendri Hasymi and Tae Jo Ko

J. Manuf. Mater. Process. 2024, 8(3), 108; https://doi.org/10.3390/jmmp8030108 - 23 May 2024

Cited by 1 | Viewed by 1218

Abstract

In order to avoid catastrophic events that degrade the quality of machined products, such as tool breakage, it is vital to have a prognostic system for monitoring tool wear during the micro-milling process. Despite the long history of the tool wear monitoring field, [...] Read more.

In order to avoid catastrophic events that degrade the quality of machined products, such as tool breakage, it is vital to have a prognostic system for monitoring tool wear during the micro-milling process. Despite the long history of the tool wear monitoring field, creating such a system to track, monitor, and foresee the rapid progression of tool wear still needs to be improved in the application of micro-milling. On the other hand, digital twin technology has recently become widely recognized as significant in manufacturing and, notably, within the Industry 4.0 ecosystem. Digital twin technology is considered a potential breakthrough in developing a prognostic tool wear monitoring system, as it enables the tracking, monitoring, and prediction of the dynamics of a twinned object, e.g., a CNC machine tool. However, few works have explored the digital twin technology for tool wear monitoring, particularly in the micro-milling field. This paper presents a novel tool wear monitoring system for micro-milling machining based on digital twin technology and an extended Kalman filter framework. The proposed system provides wear progression notifications to assist the user in making decisions related to the machining process. In an evaluation using four machining datasets of slot micro-milling, the proposed system achieved a maximum error mean of 0.038 mm from the actual wear value. The proposed system brings a promising opportunity to widen the utilization of digital twin technology with the extended Kalman filter framework for seamless data integration for wear monitoring service. Full article

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14 pages, 997 KiB

Open AccessArticle

A Data-Driven Approach for Cutting Force Prediction in FEM Machining Simulations Using Gradient Boosted Machines

by Tim Reeber, Jan Wolf and Hans-Christian Möhring

J. Manuf. Mater. Process. 2024, 8(3), 107; https://doi.org/10.3390/jmmp8030107 - 23 May 2024

Viewed by 1177

Abstract

Cutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the [...] Read more.

Cutting simulations via the Finite Element Method (FEM) have recently gained more significance due to ever increasing computational performance and thus better resulting accuracy. However, these simulations are still time consuming and therefore cannot be deployed for an in situ evaluation of the machining processes in an industrial environment. This is due to the high non-linear nature of FEM simulations of machining processes, which require considerable computational resources. On the other hand, machine learning methods are known to capture complex non-linear behaviors. One of the most widely applied material models in cutting simulations is the Johnson–Cook material model, which has a great influence on the output of the cutting simulations and contributes to the non-linear behavior of the models, but its influence on cutting forces is sometimes difficult to assess beforehand. Therefore, this research aims to capture the highly non-linear behavior of the material model by using a dataset of multiple short-duration cutting simulations from Abaqus to learn the relationship of the Johnson–Cook material model parameters and the resulting cutting forces for a constant set of cutting conditions. The goal is to shorten the time to simulate cutting forces by encapsulating complex cutting conditions in dependence of material parameters in a single model. A total of five different models are trained and the performance is evaluated. The results show that Gradient Boosted Machines capture the influence of varying material model parameters the best and enable good predictions of cutting forces as well as deliver insights into the relevance of the material parameters for the cutting and thrust forces in orthogonal cutting. Full article

(This article belongs to the Special Issue Advances in Metal Cutting and Cutting Tools)

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30 pages, 17895 KiB

Open AccessArticle

Optimization of the FDM Processing Parameters on the Compressive Properties of ABS Objects for the Production of High-Heeled Shoes

by Suzana Kutnjak-Mravlinčić, Damir Godec, Ana Pilipović and Ana Sutlović

J. Manuf. Mater. Process. 2024, 8(3), 106; https://doi.org/10.3390/jmmp8030106 - 22 May 2024

Cited by 1 | Viewed by 848

Abstract

The influence of 3D printing parameters on compressive properties is an important factor in the application of additive manufacturing processes for products subjected to compressive loads in use. In this study, the compressive strength and compressive modulus of acrylonitrile/butadiene/styrene (ABS) test specimens fabricated [...] Read more.

The influence of 3D printing parameters on compressive properties is an important factor in the application of additive manufacturing processes for products subjected to compressive loads in use. In this study, the compressive strength and compressive modulus of acrylonitrile/butadiene/styrene (ABS) test specimens fabricated using the fused deposition modeling (FDM) process were investigated with the aim of producing products of high-heeled shoes for women. The experimental part of the study includes a central composite experimental design to optimize the main 3D printing parameters (layer thickness, infill density, and extrusion temperature) and the infill geometry (honeycomb and linear at a 45° angle—L45) to achieve maximum printing properties of the 3D-printed products. The results show that the infill density has the greatest influence on the printing properties, followed by the layer thickness and, finally, the extrusion temperature as the least influential factor. The linear infill at a 45° angle resulted in higher compressive strength and lower compressive modulus values compared to the honeycomb infill. By optimizing the results, the maximum compressive strength (that of L45 is 41 N/mm² and that of honeycomb 35 N/mm²) and modulus (that of L45 is 918 N/mm² and that of honeycomb is 868 N/mm²) for both types of infill is obtained at a layer thickness of 0.1 mm and infill density of 40%, while the temperature for L45 can be in the range of 209 °C to 254 °C, but for the honeycomb infill, the processing temperature is 255 °C. Additionally, the study highlights the potential for sustainable manufacturing practices and the integration of advanced 3D printing technologies to enhance the efficiency and eco-friendliness of the production process. Full article

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13 pages, 3787 KiB

Open AccessArticle

Experimental Evidence on Incremental Formed Polymer Sheets Using a Stair Toolpath Strategy

by Antonio Formisano, Luca Boccarusso, Dario De Fazio and Massimo Durante

J. Manuf. Mater. Process. 2024, 8(3), 105; https://doi.org/10.3390/jmmp8030105 - 22 May 2024

Viewed by 950

Abstract

Incremental sheet forming represents a relatively recent technology, similar to the layered manufacturing principle of the rapid prototype approach; it is very suitable for small series production and guarantees cost-effectiveness because it does not require dedicated equipment. Research has initially shown that this [...] Read more.

Incremental sheet forming represents a relatively recent technology, similar to the layered manufacturing principle of the rapid prototype approach; it is very suitable for small series production and guarantees cost-effectiveness because it does not require dedicated equipment. Research has initially shown that this process is effective in metal materials capable of withstanding plastic deformation but, in recent years, the interest in this technique has been increasing for the manufacture of complex polymer sheet components as an alternative to the conventional technologies, based on heating–shaping–cooling manufacturing routes. Conversely, incrementally formed polymer sheets can suffer from some peculiar defects, like, for example, twisting. To reduce the risk of this phenomenon, the occurrence of failures and poor surface quality, a viable way is to choose toolpath strategies that make the tool/sheet contact conditions less severe; this represents one of the main goals of the present research. Polycarbonate sheets were worked using incremental forming; in detail, cone frusta with a fixed-wall angle were manufactured with different toolpaths based on a reference and a stair strategy, in lubricated and dry conditions. The forming forces, the forming time, the twist angle, and the mean roughness were monitored. The analysis of the results highlighted that a stair toolpath involving an alternation of diagonal up and vertical down steps represents a useful strategy to mitigate the occurrence of the twisting phenomenon in incremental formed thermoplastic sheets and a viable way of improving the process towards a green manufacturing process. Full article

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23 pages, 5086 KiB

Open AccessArticle

Real-Size Reconstruction of Porous Media Using the Example of Fused Filament Fabrication 3D-Printed Rock Analogues

by Alexander A. Oskolkov, Alexander A. Kochnev, Sergey N. Krivoshchekov and Yan V. Savitsky

J. Manuf. Mater. Process. 2024, 8(3), 104; https://doi.org/10.3390/jmmp8030104 - 17 May 2024

Viewed by 1560

Abstract

The multi-scale study of rock properties is a necessary step in the planning of oil and gas reservoir developments. The amount of core samples available for research is usually limited, and some of the samples can be distracted. The investigation of core reconstruction [...] Read more.

The multi-scale study of rock properties is a necessary step in the planning of oil and gas reservoir developments. The amount of core samples available for research is usually limited, and some of the samples can be distracted. The investigation of core reconstruction possibilities is an important task. An approach to the real-size reconstruction of porous media with a given (target) porosity and permeability by controlling the parameters of FFF 3D printing using CT images of the original core is proposed. Real-size synthetic core specimens based on CT images were manufactured using FFF 3D printing. The possibility of reconstructing the reservoir properties of a sandstone core sample was proven. The results of gas porometry measurements showed that the porosity of specimens No.32 and No.46 was 13.5% and 12.8%, and the permeability was 442.3 mD and 337.8 mD, respectively. The porosity of the original core was 14% and permeability was 271 mD. It was found that changing the layer height and nozzle diameter, as well as the retract and restart distances, has a direct effect on the porosity and permeability of synthetic specimens. This study shows that porosity and permeability of synthetic specimens depend on the flow of the material and the percentage of overlap between the infill and the outer wall. Full article

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16 pages, 4417 KiB

Open AccessArticle

Revealing the Mechanisms of Smoke during Electron Beam–Powder Bed Fusion by High-Speed Synchrotron Radiography

by Jihui Ye, Nick Semjatov, Pidassa Bidola, Greta Lindwall and Carolin Körner

J. Manuf. Mater. Process. 2024, 8(3), 103; https://doi.org/10.3390/jmmp8030103 - 17 May 2024

Cited by 1 | Viewed by 1589

Abstract

Electron beam–powder bed fusion (PBF-EB) is an additive manufacturing process that utilizes an electron beam as the heat source to enable material fusion. However, the use of a charge-carrying heat source can sometimes result in sudden powder explosions, usually referred to as “Smoke”, [...] Read more.

Electron beam–powder bed fusion (PBF-EB) is an additive manufacturing process that utilizes an electron beam as the heat source to enable material fusion. However, the use of a charge-carrying heat source can sometimes result in sudden powder explosions, usually referred to as “Smoke”, which can lead to process instability or termination. This experimental study investigated the initiation and propagation of Smoke using in situ high-speed synchrotron radiography. The results reveal two key mechanisms for Smoke evolution. In the first step, the beam–powder bed interaction creates electrically isolated particles in the atmosphere. Subsequently, these isolated particles get charged either by direct irradiation by the beam or indirectly by back-scattered electrons. These particles are accelerated by electric repulsion, and new particles in the atmosphere are produced when they impinge on the powder bed. This is the onset of the avalanche process known as Smoke. Based on this understanding, the dependence of Smoke on process parameters such as beam returning time, beam diameter, etc., can be rationalized. Full article

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20 pages, 22048 KiB

Open AccessArticle

Digital Twin Modeling for Smart Injection Molding

by Sara Nasiri, Mohammad Reza Khosravani, Tamara Reinicke and Jivka Ovtcharova

J. Manuf. Mater. Process. 2024, 8(3), 102; https://doi.org/10.3390/jmmp8030102 - 17 May 2024

Cited by 1 | Viewed by 2047

Abstract

In traditional injection molding, each level of the process has its own monitoring and improvement initiatives. But in the upcoming industrial revolution, it is important to establish connections and communication among all stages, as changes in one stage might have an impact on [...] Read more.

In traditional injection molding, each level of the process has its own monitoring and improvement initiatives. But in the upcoming industrial revolution, it is important to establish connections and communication among all stages, as changes in one stage might have an impact on others. To address this issue, digital twins (DTs) are introduced as virtual models that replicate the entire injection molding process. This paper focuses on the data and technology needed to build a DT model for injection molding. Each stage can have its own DT, which are integrated into a comprehensive model of the process. DTs enable the smart automation of production processes and data collection, reducing manual efforts in supervising and controlling production systems. However, implementing DTs is challenging and requires effort for conception and integration with the represented systems. To mitigate this, the current work presents a model for systematic knowledge-based engineering for the DTs of injection molding. This model includes fault detection systems, 3D printing, and system integration to automate development activities. Based on knowledge engineering, data analysis, and data mapping, the proposed DT model allows fault detection, prognostic maintenance, and predictive manufacturing. Full article

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37 pages, 9937 KiB

Open AccessArticle

A Study on Powder Spreading Quality in Powder Bed Fusion Processes Using Discrete Element Method Simulation

by Panagiotis Avrampos and George-Christopher Vosniakos

J. Manuf. Mater. Process. 2024, 8(3), 101; https://doi.org/10.3390/jmmp8030101 - 16 May 2024

Cited by 1 | Viewed by 1125

Abstract

Powder deposition is a very important aspect of PBF-based additive manufacturing processes. Discrete Element Method (DEM) is commonly utilized by researchers to examine the physically complex aspects of powder-spreading methods. This work focuses on vibration-assisted doctor blade powder recoating. The aim of this [...] Read more.

Powder deposition is a very important aspect of PBF-based additive manufacturing processes. Discrete Element Method (DEM) is commonly utilized by researchers to examine the physically complex aspects of powder-spreading methods. This work focuses on vibration-assisted doctor blade powder recoating. The aim of this work is to use experiment-verified DEM simulations in combination with Taguchi Design of Experiments (DoE) to identify optimum spreading parameters based on robust layer quality criteria. The verification of the used powder model is performed via angle of repose and angle of avalanche simulation–experiment cross-checking. Then, four criteria, namely layer thickness deviation, surface coverage ratio, surface root-mean-square roughness and true packing density, are defined. It has been proven that the doctor blade’s translational speed plays the most important role in defining the quality of the deposited layer. The true packing density was found to be unaffected by the spreading parameters. The vertical vibration of the doctor blade recoater was found to have a beneficial effect on the quality of the deposited layer. Ultimately, a weighted mean quality criteria analysis is mapped out. Skewness and kurtosis were proven to function as effective indicators of layer quality, showing a linear relation to the weighted means of the defined quality criteria. The specific weights that optimize this linearity were identified. Full article

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20 pages, 807 KiB

Open AccessEditor’s ChoiceArticle

Faster Evaluation of Dimensional Machine Performance in Additive Manufacturing by Using COMPAQT Parts

by Laurent Spitaels, Endika Nieto Fuentes, Valentin Dambly, Edouard Rivière-Lorphèvre, Pedro-José Arrazola and François Ducobu

J. Manuf. Mater. Process. 2024, 8(3), 100; https://doi.org/10.3390/jmmp8030100 - 16 May 2024

Viewed by 895

Abstract

Knowing the tolerance interval capabilities (TICs) of a manufacturing process is of prime interest, especially if specifications link the manufacturer to a customer. These TICs can be determined using the machine performance concept of ISO 22514. However, few works have applied this to [...] Read more.

Knowing the tolerance interval capabilities (TICs) of a manufacturing process is of prime interest, especially if specifications link the manufacturer to a customer. These TICs can be determined using the machine performance concept of ISO 22514. However, few works have applied this to Additive Manufacturing printers, while testing most of the printing area as recommended takes a very long time (nearly 1 month is common). This paper, by proposing a novel part design called COMPAQT (Component for Machine Performances Assessment in Quick Time), aims at giving the same level of printing area coverage, while keeping the manufacturing time below 24 h. The method was successfully tested on a material extrusion printer. It allowed the determination of potential and real machine tolerance interval capabilities. Independently of the feature size, those aligned with the X axis achieved lower TICs than those aligned with the Y axis, while the Z axis exhibited the best performance. The measurements specific to one part exhibited a systematic error centered around 0 mm ± 0.050 mm, while those involving two parts reached up to 0.314 mm of deviation. COMPAQT can be used in two applications: evaluating printer tolerance interval capabilities and tracking its long-term performance by incorporating it into batches of other parts. Full article

(This article belongs to the Special Issue Design, Processes and Materials for Additive Manufacturing)

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14 pages, 4717 KiB

Open AccessEditor’s ChoiceArticle

Exploring Multi-Armed Bandit (MAB) as an AI Tool for Optimising GMA-WAAM Path Planning

by Rafael Pereira Ferreira, Emil Schubert and Américo Scotti

J. Manuf. Mater. Process. 2024, 8(3), 99; https://doi.org/10.3390/jmmp8030099 - 15 May 2024

Viewed by 1263

Abstract

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess [...] Read more.

Conventional path-planning strategies for GMA-WAAM may encounter challenges related to geometrical features when printing complex-shaped builds. One alternative to mitigate geometry-related flaws is to use algorithms that optimise trajectory choices—for instance, using heuristics to find the most efficient trajectory. The algorithm can assess several trajectory strategies, such as contour, zigzag, raster, and even space-filling, to search for the best strategy according to the case. However, handling complex geometries by this means poses computational efficiency concerns. This research aimed to explore the potential of machine learning techniques as a solution to increase the computational efficiency of such algorithms. First, reinforcement learning (RL) concepts are introduced and compared with supervised machining learning concepts. The Multi-Armed Bandit (MAB) problem is explained and justified as a choice within the RL techniques. As a case study, a space-filling strategy was chosen to have this machining learning optimisation artifice in its algorithm for GMA-AM printing. Computational and experimental validations were conducted, demonstrating that adding MAB in the algorithm helped to achieve shorter trajectories, using fewer iterations than the original algorithm, potentially reducing printing time. These findings position the RL techniques, particularly MAB, as a promising machining learning solution to address setbacks in the space-filling strategy applied. Full article

(This article belongs to the Special Issue Advances in Directed Energy Deposition Additive Manufacturing)

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21 pages, 6440 KiB

Open AccessArticle

Transfer Learning-Based Artificial Neural Network for Predicting Weld Line Occurrence through Process Simulations and Molding Trials

by Giacomo Baruffa, Andrea Pieressa, Marco Sorgato and Giovanni Lucchetta

J. Manuf. Mater. Process. 2024, 8(3), 98; https://doi.org/10.3390/jmmp8030098 - 9 May 2024

Viewed by 1478

Abstract

Optimizing process parameters to minimize defects remains an important challenge in injection molding (IM). Machine learning (ML) techniques offer promise in this regard, but their application often requires extensive datasets. Transfer learning (TL) emerges as a solution to this problem, leveraging knowledge from [...] Read more.

Optimizing process parameters to minimize defects remains an important challenge in injection molding (IM). Machine learning (ML) techniques offer promise in this regard, but their application often requires extensive datasets. Transfer learning (TL) emerges as a solution to this problem, leveraging knowledge from related tasks to enhance model training and performance. This study explores TL’s viability in predicting weld line visibility in injection-molded components using artificial neural networks (ANNs). TL techniques are employed to transfer knowledge between datasets related to different components. Furthermore, both source datasets obtained from simulations and experimental tests are used during the study. In order to use process simulations to obtain data regarding the presence of surface defects, it was necessary to correlate an output variable of the simulations with the experimental observations. The results demonstrate TL’s efficacy in reducing the data required for training predictive models, with simulations proving to be a cost-effective alternative to experimental data. TL from simulations achieves comparable predictive metric values to those of the non-pre-trained network, but with an 83% reduction in the required data for the target dataset. Overall, transfer learning shows promise in streamlining injection molding optimization and reducing manufacturing costs. Full article

(This article belongs to the Special Issue Advances in Injection Molding: Process, Materials and Applications)

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J. Manuf. Mater. Process., Volume 8, Issue 3 (June 2024) – 43 articles

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