Metallurgical and Materials Engineering (E-Journal)
Not a member yet
915 research outputs found
Sort by
A Review of the Fatigue Behaviour of Laser Powder Bed Fusion Ti6Al4V
Get PDFFatigue in metals has been recognized since the early 1800s, after several cases of fatigue failure were reported. It is described as a material's deterioration brought on by repeated loading that causes progressive, localised structural damage. Fatigue is a problem that affects engineering components that are under the action of cyclic stresses. In these components fatigue failure always occurs at significantly much lower stresses than the yield strength of material. Unlike in the early days of failure, the causes of failure in engineering structures have been studied thoroughly and are nowadays well known. The theory of fatigue allows engineers to design components with the aim of minimizing the possibility of failure. However, it is not possible to guarantee that fatigue failure will not occur, and therefore, the recourse to damage tolerance approach in design for cyclically loaded components. The last few years have seen a pickup of the various additive manufacturing (AM) technologies. This is because AM leads to shorter manufacturing times and is capable of producing parts with complicated geometries and assemblies of interconnected parts. Unlike traditional manufacturing methods, AM does not require post-machining processes thus leading to minimal wastage of material. The microstructures of additively manufactured parts are finer than those of traditional methods, and the strength is higher on the AM parts, but ductility is lower. As in traditionally manufactured metallic components, fatigue failure in parts manufactured by laser powder bed fusion (LPBF) occurs, mainly due to inherent defects such as residual stresses, internal flaws and surface roughness. An insight into the fatigue behaviour of the LPBF Ti6Al4V alloy is presented here
The Impact of Matrix Composition and Microstructure on Nodular Cast Iron Sewage Pump Corrosion Behavior in Alkaline Solutions
No full textThe corrosion resistance of nodular cast iron (NCI) in alkaline sewage environments is critical for ensuring the longevity, efficiency and reliability of sewage pumps. This study systematically investigates the influence of matrix composition, elemental distribution and microstructural features on the corrosion behavior of NCI in alkaline solutions. Using controlled metallurgical processing, samples with varying microstructures—ferritic, pearlitic, and mixed—were prepared and exposed to simulated alkaline sewage environments (pH 10–12). Electrochemical techniques, including potentiodynamic polarization, cyclic voltammetry and electrochemical impedance spectroscopy (EIS), were employed to quantify corrosion rates and protective film characteristics. Results reveal that microstructure significantly influences corrosion resistance. Ferritic NCI exhibited the lowest corrosion rate (0.025 mm/year at pH 12), attributed to its homogeneous phase, refined grain structure and lower galvanic coupling effects. In contrast, pearlitic NCI showed higher corrosion rates (0.065 mm/year at pH 12) due to increased cathodic sites from carbide phases accelerating localized corrosion. Mixed microstructures exhibited intermediate corrosion behavior. Surface analysis via scanning electron microscopy (SEM) and energy-dispersive spectroscopy (EDS) confirmed the formation of passive films with varying compositions, with ferritic structures promoting a more stable and protective oxide layer. This study uniquely quantifies the microstructural impact on NCI corrosion in alkaline sewage environments, offering practical insights for optimizing material selection in pump manufacturing. By tailoring matrix composition, corrosion resistance can be significantly improved, enhancing operational lifespan, mechanical integrity and reducing maintenance costs. These findings provide a scientific basis for engineering more durable sewage pump components, addressing a critical challenge in wastewater infrastructure
The Impact of Facilities and Recognition in Enhancing Employee Satisfaction: A Comparative study of Indian Medium and Large Scale Manufacturing Industries
Get PDFThe comparative study examines the impact on employee satisfaction emanating from facilities and recognition programs between medium and large-scale manufacturing industries. As satisfaction of employees’ is vital to productivity, retention and overall organizational performance, understanding the influences of workplace facilities and formal recognition on them is vital for business that aims at enhancing their work environments. This research, drawing on Herzberg’s two-factor theory of motivation and self-determination theory, explores the potential of facilities and recognition program structures and schemes in affecting job satisfaction industries. The study analyses survey data collected from employees across both industrial sectors and findings suggests that while medium-scale industries leverage informal mechanisms to foster employee satisfaction, larger ones benefit from more formalized programs. Implications for HR practices in tailoring recognition and facilities-related interventions are discussed and paths for further research into the nuances of satisfaction-driven performances in manufacturing sectors are presented
Aesthetic Outcomes of Single-Tooth Implant-Supported Crowns in the Anterior Region: A Retrospective Evaluation Using the Pink and White Esthetic Scores
Get PDFBackground: Aesthetic success in anterior dental implants is critical for patient satisfaction and overall clinical outcomes. The Pink Esthetic Score (PES) and White Esthetic Score (WES) provide standardized methods to evaluate the aesthetic integration of implant-supported crowns, assessing peri-implant soft tissues and visible restorations, respectively. Study Aim: This study aimed to evaluate the aesthetic outcomes of single-tooth implant-supported crowns in the anterior region using the PES/WES scores and to identify clinical factors influencing these outcomes. Methodology: This retrospective study included 49 participants who received maxillary and mandibular single anterior implants between 2017 and 2023. Aesthetic outcomes were assessed using the PES and WES, with the combined total esthetic score (TES) calculated for each implant. Associations between aesthetic scores and clinical variables such as implant type, site, size, bone graft type, and abutment type were analyzed using statistical tests, with significance set at p < 0.05. Results: The mean PES was 7.4 ± 2.6. The mean WES was 8.6 ± 1.3. The combined TES was 16.4 ± 2.9. Significant associations were found between PES and implant type (p=0.010), implant site (p=0.000), bone graft type (p=0.027), and abutment type (p=0.002). WES was significantly influenced by implant brand (p=0.018) and abutment type (p=0.002). TES showed significant associations with implant type (p=0.004), implant site (p=0.000), implant size (p=0.06), and bone graft type (p=0.015). Clinical parameters such as the modified bleeding index (MBI) and modified plaque index (MPI) also showed significant correlations with aesthetic scores. Conclusion: The study highlights the critical factors influencing aesthetic outcomes in anterior implant-supported crowns. The PES and WES provide a robust framework for assessing implant aesthetics, with significant influences identified for implant type, site, bone graft material, and abutment type. These findings underscore the importance of meticulous planning and selection of appropriate materials to achieve optimal aesthetic results in dental implantology
Comprehensive Analysis of Trihalomethanes (THMs) and Trihalo Acetic Acids (THAAs) in Drinking Water Supply: A Research Investigation
Get PDFWater is the basic need of life. Chlorination is a well-known disinfection technique for potable water due to its cheap availability. Yet, some aspects are harmful to human health and found carcinogenic. An investigation has been made to quantify the occurrence of two prominent Chlorination Disinfectant byproducts (DBPs), i.e., Trihalomethanes (THMs) and Trihalo acetic acids (THAAs) in the water distribution network of galvanized iron Pipes Medium using GC-Mass Spectrometry equipped with Electron Capture Detector (ECD). Two filtration setups, i.e., Granular Activated Carbon (GAC) and a pack of sand, were evaluated as abatement techniques were introduced for removing these chlorination disinfectants by products according to the water source and pipe medium used. The chromatogram with mass spectrometry hints at the occurrence of these two DBPs and the filtration media's characterization and removal capacity. A combination of granulated activated carbon accompanied with sand media and based on gravel was found to be the more feasible and efficient setup to remove DBPs for the galvanized iron pipes distribution network medium
MMM-DADCL-Net: An Integrated Multi-Model Deep Attention Network based on Machine Learning and Recommendation System
Get PDFThe Gulf of Guinea has been in the center of attention since 2010, when the International Maritime Organization labeled it one of the most dangerous areas due to the persistence of piracy and armed robbery against ships. This study presented a novel way to identifying attacks in the GoG. Initially, the dataset is pre-processed using standard methodologies, and features are retrieved using statistical methods. The retrieved characteristics are used to choose features using a self-adaptive bacterial foraging optimization algorithm. Finally, classification is performed using a novel MMM-DADCL Net approach that classifies ship type, ship state, protection level, and attacks in four phases using the self-attention mechanism and CNN models such as Alex-Net, Google-Net, LeNet, VGG-19, LSTM, and Densely connected FCN. The proposed model achieved an Accuracy of 97.09% when implemented on a Python platform. The results demonstrate the proposed model's superior efficiency on comparisons with the current techniques
Optimizing Battery Charge Prediction Accuracy Utilizing Machine Learning Methods
Get PDFEnergy storage systems are more cost-effective when they correctly manage the capacity for lithium-ion batteries (LiBs), especially when they are used on a big scale. The design saves money, in the long run, to repair or fix LiBs less often. To determine the amount that LiBs were capable of holding, adaptive boosting (AdaBoost), extreme gradient boosting (XGBoost), gradient boosting, light gradient boosting machine (LightGBM), category boosting (CatBoost), as well as ensemble learning models are utilized. Employing the mean absolute error (MAE), and the mean squared error (MSE) along R2 numbers, the researcher compared the accuracy with which each model could predict future outcomes. For example, the LightGBM model had the least MAE (0.102) as well as MSE (0.018) values, as well as the greatest R-squared (0.886) value, which means that its predictions were most closely related to reality. It was about the same in terms of speed among the gradient boosting as well as XGBoost models, which came next to LightGBM. The ensemble model's efficiency suggests that integrating many models might result in an overall increase in performance. In addition, the research uses Shapley additive explanations (SHAP) values to analyze important aspects influencing model predictions within the context of explainable artificial intelligence (XAI). This study found that discharge capacity is strongly influenced by temperature, cycle index, voltage, and power. This study demonstrates that Machine Learning (ML) methods can improve energy storage systems and regulate LiB in XAI
Comparative Assessment of Learning Environments and Skill Diversity: An Examination of Work Life Quality in Medium- and Large-Scale Manufacturing Sectors
Get PDFThis article presents a comparative assessment of Quality of Work Life (QWL) dimensions specifically skill variety and learning environment between medium- and large-scale manufacturing industries. It examines variations in opportunities for employee growth through these dimensions. The attributes of these dimensions, namely learning organization, job rotation, job enrichment, and job enlargement, are analysed using samples from both sectors. Given the heterogeneous nature of the samples, descriptive statistics, Welch’s t-test, and Welch’s ANOVA are employed to test the hypotheses. The hypotheses are formulated based on demographic variables such as age, qualification, experience, and designation. The results indicate significant variations and differences between the two sectors across several attributes in different demographic classifications. Key aspects such as platforms for learning through formal and informal setups, on-the-job training, and increased responsibilities are identified as critical factors that employees seek to enhance their QWL and performance. This study contributes to the growing understanding of QWL’s role in fostering employee satisfaction and improving performance by identifying adoptable strategies across both sectors. The findings offer HR practitioners and policymakers actionable insights for workforce development in the manufacturing sector
Experimental and Numerical Dynamic Analysis of a Water Conservation Nozzle for Sustainable Water Management in Pakistan
Get PDFThe water crisis is a global issue, and the situation in Pakistan is no different. With rapid population growth, improper resource management and climate change effects, Pakistan is approaching a state of water scarcity. Tap water is a major contributor in residential water usage, presenting a significant opportunity for water conservation. The principal aim of this study is to propose a sustainable water management solution by introducing inventive household conservation devices. This research will identify the optimum parameters for the design of faucets at the maximum efficiency point, which will maximize water efficiency and reduce water consumption that can be precisely machined using traditional manufacturing processes. Using ANSYS, we performed Finite Element Analysis on the fluid flow through the prototype to observe pressure-velocity variation, and real-world testing was conducted to compare the performance of the prototype against the normal tap. Our study reveals that the prototype can conserve 70% of water by producing mist without affecting the functionality. It was also observed that the formation of mist is dependent on the distance between the screw and the nozzle. In conclusion, our research demonstrates that the domestic and commercial utilization of this prototype can restrain Pakistan's ongoing water crisis. Further, the prototype can be modified and utilized in the showerhead, to maximize water conservation
Assess Systematic Fall Risk Assessment and Prevention Intervention for Elderly Hospitalized Adults
Get PDFBackground: Falls are a leading cause of injury and mortality among older adults, with nearly 29% of individuals aged 65 years or older experiencing at least one fall annually. A history of falls significantly increases the risk of recurrent falls, while fear of falling perpetuates a cycle of reduced physical activity and heightened fall risk. Evidence supports multifactorial interventions, but systematic fall risk assessments are often underutilized during hospitalization. This study evaluated the feasibility and effectiveness of a quality improvement (QI) process aimed at standardizing fall risk assessment and prevention for older adults in acute care settings.
Methods: The intervention involved integrating a standardized fall risk assessment tool into electronic medical records, guided by three screening questions. Participants included 150 nurses and residents working in general internal medicine wards. A mandatory 15–20 minute e-learning program and monthly quizzes reinforced knowledge. Data collection included an online survey, semi-structured interviews, and participation metrics. Quantitative data were analyzed using descriptive statistics, while qualitative data underwent thematic analysis.
Results: Out of 150 invited participants, 94 (63%) completed the e-learning program. Nurses showed higher participation in quizzes initially, although engagement declined over time. Surveys and interviews revealed that 92% of participants found the e-learning content clear and concise, though 49% desired more challenging material. Participants reported increased awareness of fall risk factors (78%), but only 25% noted improvements in interdisciplinary communication. Quizzes were deemed effective in reinforcing knowledge, though some participants recommended shorter, more frequent sessions. Overall, the initiative highlighted the importance of integrating fall risk assessments into routine care, with positive feedback regarding the intervention’s practicality and relevance.
Conclusion: The QI process demonstrated feasibility and acceptability in hospital settings, emphasizing the importance of standardized fall risk assessments. The intervention effectively increased awareness and knowledge of fall prevention among healthcare professionals, although challenges such as sustaining engagement and improving interdisciplinary communication remain. Future efforts should focus on refining training methods, optimizing workflow integration, and expanding the intervention to broader healthcare settings to further reduce fall risks among hospitalized older adults