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.
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.
This research studies the development and synthesis of blended nanocomposites filled with Titanium dioxide (TiO2). Blended nanocomposites based on unsaturated polyester resin (UPR) and epoxy resins were synthesized by reactive blending. The optimum quantity from nano partical of titanium dioxide was selected and different weight proportions 1%, 3%, 5%, and 7% ratios of new epoxy are blended with UPR resin. The dielectric breakdown strength and thermal conductivity properties of the blended nanocomposites were compared with those of the basis material (UPR and 3% TiO2).The results show good compatibility epoxy resins with the UPR resin on blending, dielectric breakdown strength values are higher while thermal conductivity values of
... Show MoreIn the present work, nanocomposite of poly (vinyl alcohol) (PVA) incorporated with functionalized graphene oxide (FGO) were fabricated using casting method. PVA was dispersed by varying content of FGO (0.3, 0.5, 0.8, 1 wt %). The PVA- FGO nanocomposite was characterized by FT‐IR, FE-SEM and XRD. Frequency dependence of real permittivity (ε’), imaginary (ε’’) and a.c conductivity of PVA/FGO and PVA/GO nanocomposite were studied in the frequency range 100 Hz- 1 MHz. The experimental results showed that the values of real (ε’) and imaginary permittivity (ε’’) increased dramatically by increasing the FGO content in PVA matrix. PVA/ FGO (1 wt %) nanocomposite revealed higher electrical conductivity of 6.4×10-4 Sm-1 compared to
... Show MoreConducting polyaniline / ZnO nano composites are synthesized
using a simplified cheap method with one step in –situ chemical
polymerization, and AC conductivity (σac) of the prepared samples is
studied in the range of frequency from 50 Hz to 15MHz.). The
presence of polarons in the conjugated polymer chain are responsible
for the ac conductivity is reliance on the frequency in these
composites. The effect of increasing the ZnO nano particle
concentration irradiation and gamma radiation on the electric
conductivity was analyzed. The result showed that the
nanocomposite prepared has the highest conductivity, from pure
polyaniline and the exponential factor S was found increasing with
ZnO content it was 0
The electrical properties of pure NiO and NiO:Au Films which are
deposited on glass substrate with various dopant concentrations
(1wt.%, 2wt%, 3wt.% and 4wt.%) at room temperature 450 Co
annealing temperature will be presented. The results of the hall effect
showed that all the films were p-type. The Hall mobility decreases
while both carrier concentration and conductivity increases with the
increasing of annealing temperatures and doping percentage, Thus,
indicating the behavior of semiconductor, and also the D.C
conductivity from which the activation energy decrease with the
doping concentration increase and transport mechanism of the charge
carriers can be estimated.
In the present research, the electrical properties which included the ac-conductivity (σac), loss tangent of dielectric (tan δ) and real dielectric constant (ε’) are studied for nano polycarbonate in different pressures and frequencies as a function of temperature these properties were studied at selective temperature gradients which are (RT-50-100-150-250)°C. The results of the study showed that the values of dielectric constant and dissipation factor increase with increasing pressure and temperature and decreases by increasing frequency. And the results of electrical conductivity showed that it increases with increasing temperature, pressure and frequency.
Cu X Zn1-XO films with different x content have been prepared by
pulse laser deposition technique at room temperatures (RT) and
different annealing temperatures (373 and 473) K. The effect of x
content of Cu (0, 0.2, 0.4, 0.6, 0.8) wt.% on morphology and
electrical properties of CuXZn1-XO thin films have been studied.
AFM measurements showed that the average grain size values for
CuXZn1-xO thin films at RT and different annealing temperatures
(373, 473) K decreases, while the average Roughness values increase
with increasing x content. The D.C conductivity for all films
increases as the x content increase and decreases with increasing the
annealing temperatures. Hall measurements showed that there are
two