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.
Numerous research studies have been conducted on why some learners acquire a second language more easily and quickly than others. Most of these studies have demonstrated that acquiring a second language does not depend only on learners’ cognitive ability or professional teaching strategies. The learning language process is more complicated than that. It is affected by crucial factors that are beyond the control of learners and teachers. These factors are known as sociolinguistic factors. These factors include culture, age, motivation, socio-economic status, and gender. This research paper mainly concentrates on the role of motivation in second language acquisition.
The electrical properties of polycrystalline cadmium telluride thin films of different thickness (200,300,400)nm deposited by thermal evaporation onto glass substrates at room temperature and treated at different annealing temperature (373, 423, 473) K are reported. Conductivity measurements have been showed that the conductivity increases from 5.69X10-5 to 0.0011, 0.0001 (?.cm)-1 when the film thickness and annealing temperature increase respectively. This increasing in ?d.c due to increasing the carrier concentration which result from the excess free Te in these films.
In this work, p-n junctions were fabricated from highly-pure nanostructured NiO and TiO2 thin films deposited on glass substrates by dc reactive magnetron sputtering technique. The structural characterization showed that the prepared multilayer NiO/TiO2 thin film structures were highly pure as no traces for other compounds than NiO and TiO2 were observed. It was found that the absorption of NiO-on-TiO2 structure is higher than that of the TiO2-on-NiO. Also, the NiO/TiO2 heterojunctions exhibit typical electrical characteristics, higher ideality factor and better spectral responsivity when compared to those fabricated from the same materials by the same technique and with larger particle size and lower structural purity.
Titanium dioxide nanotube arrays (TiO2 NTAs) were successfully decorated with nanoclusters of cobalt by an electrochemical deposition method. This Co-TiO2 NTAs nanostructure exhibited high compatibility with aluminum chloride\ chloroacetamide (an ionic liquid) and calcium chloride dihydrate\ acetamide (a deep eutectic solvent), leading to significant improvements in the electrochemical properties of the system. Significantly, this led to a discernible augmentation in both potential and current values, concomitant with a decrease in internal resistance. The presence of cobalt facilitated a faster transfer of electric charge, enhancing the overall efficiency of the system. Moreover, the incorporation of cobalt exhibited a ben
... Show MoreOptical properties and surface morphology of pure and doped Polystyrene films with different divalent metals of Zn, Cu and Sn and one concentration percentage have been studied. Measurements of UV-Vis spectrophotometer and AFM spectroscopy were determined. The absorbance, transmittance and reflectance spectrums were used to study different optical parameters such as absorption coefficient, refractive index, extinction coefficient and energy gap in the wavelengths rang 200-800nm. These parameters have increased in the presence of the metals. The change in the calculated values of energy gaps with doping metals content has been investigated in terms of PS matrix structural modification. The value of opt
... Show MoreThe influence of sintering and annealing temperatures on the structural, surface morphology, and optical properties of Ag2Cu2O4 thin films which deposited on glass substrates by pulsed laser deposition method have been studied. Ag2Cu2O4 powders have polycrystalline structure, and the Ag2Cu2O4 phase was appear as low intensity peak at 35.57o which correspond the reflection from (110) plane. Scan electron microscopy images of Ag2Cu2O4 powder has been showed agglomerate of oxide particles with platelets shape. The structure of thin films has been improved with annealing temperature. Atomic Force micrographs of Ag2Cu2O4 films showed uniform, homogenous films and the shape of grains was almost spherical and larger grain size of 97.85 nm has o
... Show MoreTo maintain a sustained competitive position in the contemporary environment of knowledge economy, organizations as an open social systems must have an ability to learn and know how to adapt to rapid changes in a proper fashion so that organizational objectives will be achieved efficiently and effectively. A multilevel approach is adopted proposing that organizational learning suffers from the lack of interest about the strategic competitive performance of the organization. This remains implicit almost in all models of organizational learning and there is little focus on how learning organizations achieve sustainable competitive advantage . A dynamic model that captures t
... Show MoreAn optical video communication system is designed and constructed using pulse frequency modulation (PFM) technique. In this work PFM pulses are generated at the transmitter using voltage control oscillator (VCO) of width 50 ns for each pulse. Double frequency, equal width and narrow pulses are produced in the receiver be for demodulation. The use of the frequency doubling technique in such a system results in a narrow transmission bandwidth (25 ns) and high receiver sensitivity.
Interface evaluation has been the subject of extensive study and research in human-computer interaction (HCI). It is a crucial tool for promoting the idea that user engagement with computers should resemble casual conversations and interactions between individuals, according to specialists in the field. Researchers in the HCI field initially focused on making various computer interfaces more usable, thus improving the user experience. This study's objectives were to evaluate and enhance the user interface of the University of Baghdad's implementation of an online academic management system using the effectiveness, time-based efficiency, and satisfaction rates that comply with the task questionnaire process. We made a variety of interfaces f
... Show MoreThe evolution in the field of Artificial Intelligent (AI) with its training algorithms make AI very important in different aspect of the life. The prediction problem of behavior of dynamical control system is one of the most important issue that the AI can be employed to solve it. In this paper, a Convolutional Multi-Spike Neural Network (CMSNN) is proposed as smart system to predict the response of nonlinear dynamical systems. The proposed structure mixed the advantages of Convolutional Neural Network (CNN) with Multi -Spike Neural Network (MSNN) to generate the smart structure. The CMSNN has the capability of training weights based on a proposed training algorithm. The simulation results demonstrated that the proposed
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