https://ojs.acad-pub.com/index.php/MEA/issue/feed Mechanical Engineering Advances 2024-12-18T08:21:25+00:00 Managing Editor editorial-mea@acad-pub.com Open Journal Systems <p><em>Mechanical Engineering Advances</em> (MEA, ISSN: 3029-1232) is an online double-blind peer reviewed, open access journal dedicated to disseminating cutting-edge research and developments in the field of mechanical engineering.</p> <p></p> <p>&nbsp;</p> <p>The journal welcomes submissions from worldwide researchers, and practitioners in the field of mechanical engineering, which can be original research articles, review articles, letters, commentaries, and so on.</p> <p></p> <p>Please see "<a href="https://ojs.acad-pub.com/index.php/MEA/FocusAndScope">Focus and Scope</a>" for detailed scope.</p> https://ojs.acad-pub.com/index.php/MEA/article/view/1405 Finite element structural analysis of simply supported solid and stiffened plates: A comparative study 2024-12-10T03:13:25+00:00 Shabla K. shabla1999@gmail.com Chitaranjan Pany shabla1999@gmail.com <p>A structure’s form and shape influence how it behaves when loaded. This was achieved by contrasting the stiffened plate’s performance with that of a solid plate made of the same material and volume. The results have demonstrated that bending stress in stiffened plates is decreased when a solid plate of the same material and volume is transformed into a stiffened plate. Because stiffened plates have a higher strength to weight ratio than solid plates, this supports the recommendation of stiffened plates for a variety of technical applications. In order to determine the impact of stiffener orientation on bending stress reduction in stiffened plates, additional investigations were carried out on a number of plates. An investigation was carried out to determine the ideal stiffener angle in a stiffened plate that could offer the least amount of stress. The current work offers insightful information about particular stiffened plate design characteristics that can be used in a variety of engineering contexts.<b></b></p> 2024-11-27T03:17:49+00:00 Copyright (c) 2024 Shabla K., Chitaranjan Pany https://ojs.acad-pub.com/index.php/MEA/article/view/1921 A novel approach for wear assessment of plastic gears using image processing 2024-12-05T06:23:20+00:00 Mahmoud G. Elkasrawi hesham.hegazi@guc.edu.eg Marah A. Elsiedy hesham.hegazi@guc.edu.eg Hesham A. Hegazi hesham.hegazi@guc.edu.eg <p>Plastic gears offer numerous advantages, poised to increasingly supplant metal gears across various applications. Notably, they boast silent operation, resistance to corrosion, and lightweight properties which make them ideal for wind turbine systems. Moreover, the expanding array of plastic materials, including eco-plastics and their natural fibre composites, underscores the imperative for ongoing research into plastic gears and their composites. Addressing existing challenges is pivotal to fully harnessing their potential in sustainable development efforts. The wear of plastic gears is an important factor in plastic gear design and optimization. This paper primarily examines wear assessment in polypropylene (PP) gears by proposing and implementing a novel approach to measure the amount of wear on gear tooth profile using an image processing technique. By subjecting plastic gears to wear experimentation and employing direct image processing methods, the percentage of damage can be accurately evaluated. These percentages were 0.2% and 2.5% for 2 and 5 hours respectively. This underscores the boundless possibilities of integrating image processing techniques into the assessment of plastic gears, paving the way for deeper exploration and optimization of polymer materials for plastic gear manufacturing.</p> 2024-12-05T06:23:01+00:00 Copyright (c) 2024 Mahmoud G. Elkasrawi, Marah A. Elsiedy, Hesham A. Hegazi https://ojs.acad-pub.com/index.php/MEA/article/view/1962 Implementing multi criteria decision making methods for computing complexity involved in industrial investment castings 2024-12-18T08:21:25+00:00 Nikunj Maheta nikunj.maheta@marwadieducation.edu.in Amit Sata amit.sata@marwadieducation.edu.in <p>Investment casting is admired for its ability to produce industrial castings with remarkable precision, exceptional exterior finish and complex designs among diverse industrial application. Traditionally, the complexity of these castings is generally assessed qualitatively while quantitative measurement of this complexity remains largely unexplored. To identify the various parameters that affects the complexity of industrial investment casting, an in-person industrial survey was carried out in one of the major investment casting clusters that accounts for nearly 25% of India’s investment casting foundries. Through this survey it was found that complexity of investment casting is determined by three factors related to geometry, features and manufacturability. These three factors are further driven by 19 elements and 52 attributes. These 52 attributes are further characterised by 212 meta-attributes. This research focuses on applying multi-criteria decision-making methods to quantify the complexity affects in manufacturing industrial investment castings. Numerous methodologies within the domain of Multi-Criteria Decision-Making (MCDM) have been explored to determine the appropriate weightage for the factors, elements, attributes and meta-attributes involved. It was observed that for the specific problem mentioned, the Weighted Criteria Approach (WCA) and Analytical Hierarchy Process (AHP) were identified as suitable choices, aligning well with the required level of accuracy. The result obtained through these methods were used to compute the complexity of industrial castings. The proposed complexity index was validated using various industrial castings and proved to be a valuable tool for designers in adopting investment casting process for producing complex castings.<b></b></p> 2024-12-18T08:21:06+00:00 Copyright (c) 2024 Nikunj Maheta, Amit Sata https://ojs.acad-pub.com/index.php/MEA/article/view/1950 Parametric optimization and determination in machining processes by means of probabilistic multi-objective optimization 2024-12-10T03:02:31+00:00 Maosheng Zheng mszhengok@aliyun.com Jie Yu yujie@nwu.edu.cn <p>In the present article, it attempts to present the determination of optimal parameters of machining processes by means of probabilistic multi-objective optimization (PMOO), in which the optimal objectives (attributes) are fundamentally divided into beneficial type and unbeneficial type, moreover all attributes of both beneficial type and unbeneficial type are evaluated separately with equivalent manner to get their partial preferable probability. Finally, the total preferable probability of each alternative is obtained by the product of all partial preferable probabilities, which is the unique and decisive representative of the alternative to join the competitive optimization, the optimum alternative is with the highest total preferable probability. An example of parametric optimization and determination of aerospace component with Electro Chemical Machining (ECM) is taken to illuminate the procedure. In the case of ECM, the current, voltage, and feed rate are as the optimal parameters to be investigated, while Material Removal Rate (MRR), and Surface Roughness (SR) are the optimal objective responses to be measured. The experimental runs were designed using an L<sub>27 </sub>Taguchi orthogonal array. In the assessment of PMOO for ECM, the objective MRR belongs to the beneficial attribute, and the objective SR is as the unbeneficial attribute. The novelty of this work is to reflect the simultaneity and the irreplacement of optimization of objectives MRR and SR in the optimal system. The evaluated results reveal that the optimized experimental scheme is the alternative 8, which is with the optimal responses of MRR of 280.112 g/min and SR of 0.45 mm, the corresponding optimum experimental parameters are voltage of 12 V, electrolyte flow rate of 12 m/s and tool feed rate of 0.4 mm/min, respectively. The achievement of the present article indicates the validity of the corresponding approach and algorithm.<b></b></p> 2024-11-28T01:00:43+00:00 Copyright (c) 2024 Maosheng Zheng, Jie Yu