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This study explores the relationship between natural fiber filling density (10%, 15%, 25%) and its impact on the bending properties of polymer compounds reinforced with Diss, Sisal and Luffa fibers. Using advanced techniques like fiber analysis and Fourier transform infrared spectrometry (FTIR), the research reveals that a 25% filling density results in the highest stress values (25.61 MPa, 22.21 MPa and 20.88 MPa) for Diss, Sisal and Luffa compounds, respectively, fostering robust bonds in Diss-reinforced polymers. The Artificial Neural Network (ANN) model demonstrates superior predictive capability with correlation coefficients exceeding 0.99 for stress and displacement, outperforming Response Surface Methodology (RSM). Analysis of Variance (ANOVA) underscores the impact of sample section parameters and fiber rate on stress, establishing the significance of type parameters and fiber rate on displacement. This integration of ANN and RSM represents a paradigm shift in predicting bending mechanical properties, advancing our understanding of composite materials for innovative applications. [ABSTRACT FROM AUTHOR]

Our study focuses on the critical steps of balancing and maintaining the turbine rotor in electricity production companies. We aim to develop a MATLAB program for blade distribution to optimize the turbine's performance. We conducted practical tests using the BLADIS software from a major company in the field and compared it with the test data from our program. We performed three blade distribution experiments using the initial static moment values of each blade, which the MEI Company's (Sonelgaz-M'sila) electronic balance provided. Our main objective is to propose a new algorithm for turbine rotor blade distribution using a MATLAB subroutine that remains applicable during maintenance operations, including punctual blade changes. This proposed algorithm will help improve the turbine rotor's efficiency and performance. Electricity production companies to maintain their turbines and optimize energy output can use our study’s findings and algorithm. By implementing our proposed algorithm, companies can save costs and increase their energy efficiency, making them more competitive in the market. [ABSTRACT FROM AUTHOR]

The field of automation in tool path generation for a 3-axis CNC machine is experiencing significant growth in the computer-aided manufacturing sector. Current research efforts are focused on improving the efficiency and precision of this process. To achieve this, new technologies are being explored to enable a more advanced and automated generation of tool paths. In this article, we will examine the current state of research concerning automated tool path generation on a 3-axis CNC machine using Matlab programming tools. As an example, we will consider a complex butterfly shape derived from a mathematical function that allows drawing the 2D geometric form. At the end of the process, a G-code is automatically generated for future use in the CNC machine. The obtained results are highly encouraging, which provides further motivation for continuing research in this direction. [ABSTRACT FROM AUTHOR]

In the manufacturing industry, Mastercam X5 is a widely used CNC simulation and programming suite that offers high efficiency. It can be easily integrated with the Mastercam model, providing full associativity and seamless single-window integration. The iMachining technology, which uses patented algorithms for specific operations, is a breakthrough in CNC milling tool path technology. It optimizes the tool path, reduces machining time, and minimizes tool wear. The suite enables a wide range of machining operations on various stock objects, making it flexible and versatile. The simulation process allows real-time observation of operations and ensures error-free G-code for physical operation. This paper details the procedures of machining a spur gear from stock material using Mastercam 2D iMachining technology. The simulation process generates automatic Gcodes for practical use in CNC machines. Mastercam simplifies the concept, operation, and importance of using CAM software in modern-day manufacturing industries. It also enables optimization of operational steps and parameter details to save time, cost, and tool lives, improving overall efficiency. [ABSTRACT FROM AUTHOR]