Emmanuel Olorundaisi , Bukola J. Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi Michel Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi
{"title":"Phase formation and mechanical analysis of sintered Ni25Al25Co15Fe15Mn8Ti7Cr5 high entropy alloy","authors":"Emmanuel Olorundaisi , Bukola J. Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi Michel Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi","doi":"10.1016/j.mfglet.2024.09.019","DOIUrl":"10.1016/j.mfglet.2024.09.019","url":null,"abstract":"<div><div>In recent years, the pursuit of cutting-edge materials has intensified, with a focus on affordability, lightweight characteristics, and exceptional performance under high-temperature conditions, to serve as alternatives to Ni-base superalloys and other conventional alloys. Potential materials suitable for high-temperature structural applications with lightweight characteristics are intermetallics such as NiAl, and TiAl, but pose numerous fabrication challenges and poor ductility behaviour at room temperature. In view of this, a novel Ni<sub>25</sub>Al<sub>25</sub>Co<sub>15</sub>Fe<sub>15</sub> Mn<sub>8</sub>Ti<sub>7</sub>Cr<sub>5</sub> high entropy alloy (HEA) was fabricated using spark plasma sintering (SPS). The alloy was developed at a sintering temperature of 850 °C, a heating rate of 90 °C/min, a pressure of 50 MPa, and a dwelling time of 5 min. X-ray diffraction, scanning electron microscopy, and Vickers hardness tester were used to investigate the phase formation, microstructure, and mechanical properties of the HEA, respectively. The microstructure of the sintered HEA shows a homogenous dispersion of the alloying metals. The sintered microstructures showed a mixture of simple and complex phases. The grain size analysis shows that the sintered HEA exhibited a lower grain size of 2.28 µm and a refined crystallite size of 3.159 µm. The microhardness value and relative density of the sintered HEA are 135.8 HV and 99.56 %, respectively.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 153-159"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434349","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Emmanuel Olorundaisi , Bukola J Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi M. Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi
{"title":"Thermo-mechanical and phase prediction of Ni25Al25Co14Fe14Ti9Mn8Cr5 high entropy alloys system using THERMO-CALC","authors":"Emmanuel Olorundaisi , Bukola J Babalola , Ufoma S. Anamu , Moipone L. Teffo , Ngeleshi M. Kibambe , Anthony O. Ogunmefun , Peter Odetola , Peter A. Olubambi","doi":"10.1016/j.mfglet.2024.09.020","DOIUrl":"10.1016/j.mfglet.2024.09.020","url":null,"abstract":"<div><div>This study focuses on predicting phases and thermo-mechanical properties of NiAl-Ti-Mn-Co-Fe-Cr High Entropy Alloys (HEAs) using THERMOCALC software version 2021b with the TCHEA5 HEAs database. The thermodynamic simulation was used to investigate the phase formation and total hardness of the HEAs. The thermodynamic simulation result shows the presence of three major phases at room temperature, namely, BCC, SIGMA, and HEUSLER phases, with the BCC having a higher percentage of volume fraction of 62.4%. The activity of all components at high temperatures was studied, and the study shows Ni and Al to be stable at high temperatures, implying excellent mechanical properties are expected at high temperatures. The predicted total hardness is given as 96.2 HV.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 160-169"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434350","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Characterization of oscillatory magnetic field-assisted finishing of directed energy deposition NASA HR-1 integral channels","authors":"Kateland Hutt , Justin Rietberg , Paul Gradl , Hitomi Yamaguchi","doi":"10.1016/j.mfglet.2024.09.085","DOIUrl":"10.1016/j.mfglet.2024.09.085","url":null,"abstract":"<div><div>Additive manufacturing (AM), such as directed energy deposition (DED), enables fabrication of complex geometries for critical parts at near-net shape, but creates a need for post-processing to achieve desired geometry and performance. In particular, parts made using DED are sometimes printed with a high initial surface roughness, requiring post-processing to meet application-dependent requirements. Magnetic field-assisted finishing (MAF), in which a magnetic polishing tool is manipulated by magnetic force and generates relative motion against a target surface, has been applied to smooth AM parts. An advantage of MAF is that the magnetically manipulated polishing tools can finish both external part surfaces and part interiors. In this paper, an oscillating magnetic polishing tool is proposed to smooth the inner surfaces of rectangular NASA HR-1 alloy channels made using DED. Because effective tool motion allows reduction of surface roughness and waviness, parameters that control polishing-tool motion are of great interest. This paper describes three parameters that control polishing-tool motion: number of polishing tools, magnetic field, and abrasive slurry. The effects of tool motion on the polishing characteristics are demonstrated, showing that the roughness of the interior channel surface can be reduced from several tens of micron to a sub-micron level.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 670-678"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434357","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A qualitative validation of an in-situ monitoring system for EHD inkjet printing via laser diffraction","authors":"Xuepeng Jiang, Pengyu Zhang, Hantang Qin","doi":"10.1016/j.mfglet.2024.09.029","DOIUrl":"10.1016/j.mfglet.2024.09.029","url":null,"abstract":"<div><div>Electrohydrodynamic inkjet printing enables high-resolution patterning for nano features. In-flight dynamics of EHD inkjet printing play an essential role in the quality control of printing results. We applied a laser diffraction/scattering in-situ analyzing setup for the EHD inkjet printing system to replace the zoom lens and high-speed camera imaging system. In contrast to conventional imaging systems, the laser diffraction/scattering system is based on analyzing the diffraction pattern and scattering intensity, respectively, which provided higher resolution for micro-scale jetting measurement and enabled sub-micron level jetting correlation between the voltage applied to the electrode and printing results. Furthermore, Taylor cone information from the nozzle head could also be analyzed in real-time to make adjustments to the printing process. In this work, we successfully validated the feasibility of laser diffraction analysis in-situ monitoring for EHD inkjet printing at micron and sub-micron levels.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 248-252"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434277","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Shafahat Ali , Vijayant Mehra , Abdelkrem Eltaggaz , Ibrahim Deiab , Salman Pervaiz
{"title":"Optimization and prediction of additively manufactured PLA-PHA biodegradable polymer blend using TOPSIS and GA-ANN","authors":"Shafahat Ali , Vijayant Mehra , Abdelkrem Eltaggaz , Ibrahim Deiab , Salman Pervaiz","doi":"10.1016/j.mfglet.2024.09.099","DOIUrl":"10.1016/j.mfglet.2024.09.099","url":null,"abstract":"<div><div>Recent years have seen the proliferation of fused deposition modeling (FDM) as a means of manufacturing biodegradable products, for different applications such as rigid packaging, agricultural and biomedical. Blends of Polyhydroxyalkanoates (PHA) and polylactic acid (PLA) have been investigated to ascertain their prospective applications through FDM. This paper includes three parameters that affect the build process: layer height, nozzle temperature, and flow rate. 3D printed PLA/PHA can be characterized mechanically, and process parameters can be optimized to maximize design functionality. The experimental setup utilized a Taguchi L9 design, and TOSPIS was employed to optimize the output results. Using TOPSIS analysis, 0.2 mm layer thickness, 195 °C nozzle temperature, and 100 % flow rate were found to be the most optimal initiation parameters. The Taguchi analysis was used to analyze the output responses, and it was found that layer height had the greatest influence on mechanical properties, followed by flow rate and nozzle temperature. The percentage elongation at break has been improved significantly by adding PHA i.e., 170 % compared to PLA (5–10 %). This paper presents a framework for in-depth mechanical characterization of PLA-PHA 3D-printed parts, along with methods for optimizing process parameters to achieve optimal performance, as well as tools for modeling output responses using GA-ANN with an accuracy of 95 %.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 795-802"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434292","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"Predictive models for 3D inkjet material printer using automated image analysis and machine learning algorithms","authors":"Mutha Nandipati, Michael Ogunsanya, Salil Desai","doi":"10.1016/j.mfglet.2024.09.101","DOIUrl":"10.1016/j.mfglet.2024.09.101","url":null,"abstract":"<div><div>Additive manufacturing (AM) is a smart manufacturing process to fabricate components with high precision, minimal post-processing, and increased component complexity in a variety of materials. This research focuses on developing automated image analysis and predictive models for a widely used 3D material inkjet printing (IJP) process. The interplay of four input process parameters, which include frequency, voltage, temperature, and meniscus vacuum, on the output metrics of the inkjet printer was evaluated using statistical measures (ANOVA). Droplet types were classified as no drop, satellite drop, and normal drop using four machine learning classifiers, including random forest, support vector classifier, k-nearest neighbor, and decision trees. Hyperparameter tuning was performed for each model for over 486 data points. Regression predictive models were developed for both ink droplet velocity and volume with three linear models (linear, lasso, and ridge regression) and four non-linear models (random forest, decision tree, support vector regression, and k-nearest neighbor). Mean squared error and the coefficient of determination, r-squared value, were used to evaluate the performance of the predictive models. For the drop type classification models, k-fold of 5 yielded the highest accuracy for the RF, KNN, and DT models of around 98%. Similarly, for the regression based predictive models RF, DT and KNN accuracy results ranged from 97 to 99%. All the machine learning models were validated with experimental data with high prediction accuracies accuracy. This research serves as a foundation for developing design guidelines for 3D material inkjet printing with applications in biosensors, flexible electronics, and regenerative tissue engineering.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 810-821"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434293","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
{"title":"A study on the gas film formation in electrochemical discharging processes by molecular dynamics simulation","authors":"Yu-Jen Chen, Murali Sundaram","doi":"10.1016/j.mfglet.2024.09.042","DOIUrl":"10.1016/j.mfglet.2024.09.042","url":null,"abstract":"<div><div>Molecular Dynamics (MD) simulations have emerged as a potent analytical tool for dissecting the intricate processes involved in nano gas film bubble generation. This study employs MD simulations to identify critical voltage that marks the transition from bubble saturation to gas film formation, while employing a mimic electrolysis model to expedite simulations through accelerated molecular insert rates. The simulations provide insights into underlying mechanisms, revealing the reforming and condensing dynamics of gas structures preceding gas film genesis. Experimental validation corroborates the accuracy of critical voltage predictions derived from MD simulations, with the close alignment between simulated critical points and experimental outcomes underscoring the robust predictive capability of MD simulations in elucidating electrochemical discharging (ECD) processes.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 351-356"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434245","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Nathan Wilson , Robert Patterson , Elijah Charles , Malachi Landis , Joshua Kincaid , Ryan Garcia , Gregory Corson , Tony Schmitz
{"title":"Hybrid manufacturing cost models: Additive friction stir deposition, measurement, and CNC machining","authors":"Nathan Wilson , Robert Patterson , Elijah Charles , Malachi Landis , Joshua Kincaid , Ryan Garcia , Gregory Corson , Tony Schmitz","doi":"10.1016/j.mfglet.2024.09.038","DOIUrl":"10.1016/j.mfglet.2024.09.038","url":null,"abstract":"<div><div>Based on its potential to reduce lead times, hybrid manufacturing, which often includes both additive manufacturing and machining processes, is receiving more attention from manufacturers as they seek to increase their supply chain resilience and efficiency. A new solid-state additive manufacturing, referred to as additive friction stir deposition (AFSD), has shown the potential to become an important process for hybrid manufacturing. To justify the selection of a hybrid manufacturing approach, the cost needs to be estimated for comparison to conventional approaches. Historically, hybrid manufacturing costs have been difficult to estimate due to the complexity and diversity of the manufacturing processes. This paper proposes cost models that include additive friction stir deposition, structured light scanning, milling, and turning, which can be combined in hybrid manufacturing process planning. These cost models are demonstrated in a case study and cost estimates are compared for hybrid and conventional (machining-only) manufacturing approaches. For the selected case, the hybrid manufacturing process cost was $1007.58, while the conventional milling process cost was $833.60. The results of the case study show that both labor and material costs must be considered to make an informed decision between hybrid and conventional manufacturing approaches.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 320-331"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434241","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Iqbal Shareef , Durga Kumar Raja Potluri , Gerry Horton
{"title":"Effect of materials and process parameters on machinability of stainless steels","authors":"Iqbal Shareef , Durga Kumar Raja Potluri , Gerry Horton","doi":"10.1016/j.mfglet.2024.09.088","DOIUrl":"10.1016/j.mfglet.2024.09.088","url":null,"abstract":"<div><div>Stainless steels, recognized for their corrosion resistance attributed to a minimum of 11 % Chromium, encompass a variety of alloys with distinctive microstructures and properties. Machinability significantly varies among these alloys. Austenitic steels such as SS303 and 304 present challenges, demonstrating poor surface finish and high power consumption. This study, employing a central composite design, investigates the machinability of AISI 303, 304, 316, AISI 416, and AISI A36. Turning tests with PVD TiAlN-coated inserts revealed optimal parameters for cutting speeds (90.5256–244.411 m/min), feed (0.0635–0.4826 mm/rev), and depth (0.00016–0.00187 m.). Surface finish analysis identified AISI 316 as the best, closely followed by AISI 303. From a power consumption standpoint, AISI 303 performed the best, and concerning fragmented chip morphology, AISI 303 also excelled. The superior performance of AISI 303 is attributed to 2 % Manganese and 0.15 % Sulfur, proving to be the most effective combination compared to the other four steels, resulting in a higher percentage of MnS<sub>2</sub>, optimal for improving machinability. The depth of cut emerges as the most influential factor affecting dimensional accuracy. These findings hold practical significance in the selection of stainless steels and corresponding process parameters across various industries, including the manufacturing of heavy earthmoving equipment. By shedding light on the optimal composition and machining conditions, this study contributes valuable insights for enhancing performance and efficiency in stainless steel applications.</div></div>","PeriodicalId":38186,"journal":{"name":"Manufacturing Letters","volume":"41 ","pages":"Pages 696-707"},"PeriodicalIF":1.9,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142434297","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}