The rise of Industry 4.0 and smart manufacturing has highlighted the importance of utilizing intelligent manufacturing techniques, tools, and methods, including predictive maintenance. This feature allows for the early identification of potential issues with machinery, preventing them from reaching critical stages. This paper proposes an intelligent predictive maintenance system for industrial equipment monitoring. The system integrates Industrial IoT, MQTT messaging and machine learning algorithms. Vibration, current and temperature sensors collect real-time data from electrical motors which is analyzed using five ML models to detect anomalies and predict failures, enabling proactive maintenance. The MQTT protocol is used for efficient communication between the sensors, gateway devices, and the cloud server. The system was tested on an operational motors dataset, five machine learning algorithms, namely k-nearest neighbor (KNN), supported vector machine (SVM), random forest (RF), linear regression (LR), and naive bayes (NB), are used to analyze and process the collected data to predict motor failures and offer maintenance recommendations. Results demonstrate the random forest model achieves the highest accuracy in failure prediction. The solution minimizes downtime and costs through optimized maintenance schedules and decisions. It represents an Industry 4.0 approach to sustainable smart manufacturing.
The present work aims to validate the experimental results of a new test rig built from scratch to evaluate the thermal behavior of the brake system with the numerical results of the transient thermal problem. The work was divided into two parts; in the first part, a three-dimensional finite-element solution of the transient thermal problem using a new developed 3D model of the brake system for the selected vehicle is SAIPA 131, while in the second part, the experimental test rig was built to achieve the necessary tests to find the temperature distribution during the braking process of the brake system. We obtained high agreement between the results of the new test rig with the numerical results based on the developed model of the brake
... Show MoreThe electrical properties of CdO/porous Si/c-Si heterojunction prepared by deposition of CdO layer on porous silicon synthesized by electrochemical etching were studied. The structural, optical, and electrical properties of CdO (50:50) thin film prepared by rapid thermal oxidation were examined. X-ray diffraction (XRD) results confirmed formation of nanostructured silicon layer the full width half maximum (FWHM) was increased after etching. The dark J-V characteristics of the heterojunction showed strong dependence on etching current density and etching time. The ideality factor and saturation current of the heterojunction were calculated from J-V under forward bias. C-V measurements confirmed that the prepared heterojunctions are abrupt
... Show MorePolyimide/MWCNTs nanocomposites have been fabricated by solution mixing process. In the present study, we have investigated electrical conductivity and dielectric properties of PI/MWCNT nanocomposites in frequency range of 1 kHz to 100 kHz at different MWCNTs concentrations from 0 wt.% to 15 wt.%. It has been observed that the electrical conductivity and dielectric constants are enhanced significantly by several orders of magnitude up to 15 wt.% of MWCNTs content. The electrical conductivity increases as the frequency is increased, which can be attributed to high dislocation density near the interface. The rapid increase in the dielectric constant at a high MWCNTs content can be explained by the form
The synthesis of conducting polyaniline (PANI) nanocomposites containing various concentrations of functionalized single-walled carbon nanotubes (f-SWCNT) were synthesized by in situ polymerization of aniline monomer. The morphological and electrical properties of pure PANI and PANI/SWCNT nanocomposites were examined by using Fourier transform- infrared spectroscopy (FTIR), and Atomic Force Microscopy (AFM) respectively. The FTIR shows the aniline monomers were polymerized on the surface of SWCNTs, depending on the -* electron interaction between aniline monomers and SWCNTs. AFM analysis showed increasing in the roughness with increasing SWCNT content. The AC, DC electrical conductivities of pure PANI and PANI/SWCNT nanocomposite h
... Show MoreThe purpose of this resesrh know (the effectiveness of cooperative lerarning implementation of floral material for calligraphy and ornamentation) To achieve the aim of the research scholar put the two zeros hypotheses: in light of the findings of the present research the researcher concluded a number of conclusions, including: -
1 - Sum strategy helps the learner to be positive in all the information and regulations, monitoring and evaluation during the learning process.
2 - This strategy helps the learner to use information and knowledge and their use in various educational positions, and to achieve better education to increase its ability to develop thinking skills and positive trends towards the article.
In light of this, the
In regression testing, Test case prioritization (TCP) is a technique to arrange all the available test cases. TCP techniques can improve fault detection performance which is measured by the average percentage of fault detection (APFD). History-based TCP is one of the TCP techniques that consider the history of past data to prioritize test cases. The issue of equal priority allocation to test cases is a common problem for most TCP techniques. However, this problem has not been explored in history-based TCP techniques. To solve this problem in regression testing, most of the researchers resort to random sorting of test cases. This study aims to investigate equal priority in history-based TCP techniques. The first objective is to implement
... Show MoreSorting and grading agricultural crops using manual sorting is a cumbersome and arduous process, in addition to the high costs and increased labor, as well as the low quality of sorting and grading compared to automatic sorting. the importance of deep learning, which includes the artificial neural network in prediction, also shows the importance of automated sorting in terms of efficiency, quality, and accuracy of sorting and grading. artificial neural network in predicting values and choosing what is good and suitable for agricultural crops, especially local lemons.
A characteristic study of a passively Q-switched diode pumped solid state laser system is presented in this work. For laser a comparison study for the theoretically calculated results with a simulation results using a software which calculates the Q-switched solid state laser parameters was such as energy, peak power and pulse width were performed. There was a good agreement between our theoretical calculations and the simulation values.