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.
ZnO nanostructures were synthesized in one step reaction at 80℃ without any extra treatments.(Zn (NO₃) ₂. 6H2O) and (NaOH) were used for synthesis. Production of ZnO nanostructures occurred relatively in short time. The obtained ZnO nanostructures were characterized by X-ray diffraction (XRD) and the atomic force microscope AFM. Carboxymethyleted PVA (CPVA) has been prepared and characterized.(CPVA) were composite with different ZnO nanoparticles concentrations. The composites are cast into films. The dielectric constant properties of the films were measured with hp LCR meter.
The paper reports the influence of annealing temperature under vacuum for one hour on the some structural and electrical properties of p-type CdTe thin films were grown at room temperature under high vacuum by using thermal evaporation technique with a mean thickness about 600nm. X-ray diffraction analysis confirms the formation of CdTe cubic phase at all annealing temperature. From investigated the electrical properties of CdTe thin films, the electrical conductivity, the majority carrier concentration, and the Hall mobility were found increase with increasing annealing temperatures.
The aim of this paper, study the effect of carbon nanotubes on the electrical properties of polyvinylchloride. Samples of polyvinylchloride carbon nanotubes composite prepared by using hot press technique. The weight percentages of carbon nanotubes are 0,5,10 and 20wt.%. Results showed that the D.C electrical conductivity increases with increasing of the weight percentages of carbon nanotubes. Also, the D.C electrical conductivity changed with increase temperature for different concentrations of carbon nanotubes. The activation energy of D.C electrical conductivity is decreased with increasing of carbon nanotubes concentration.
In this paper, CdO nanoparticles prepared by pulsed laser deposition techniqueonto a porous silicon (PS) surface prepared by electrochemical etching of p-type silicon wafer with resistivity (1.5-4Ω.cm) in hydrofluoric (HF) acid of 20% concentration. Current density (15 mA/cm2) and etching times (20min). The films were characterized by the measurement of AFM, FTIR spectroscopy and electrical properties.
Atomic Force microscopy confirms the nanometric size.Chemical components during the electrochemical etching show on surface of PSchanges take place in the spectrum of CdO deposited PS when compared to as-anodized PS.
The electrical properties of prepared PS; namely current density-voltage charact
... Show MoreIn this work, As60Cu40-xSex thin films were synthesized, and the pulsed laser deposition method was used to study the effected partial replacement of copper with selenium. The electrical characteristics and optical characteristics, as indicated by the absorbance and transmittance as a function of wavelength were calculated. Additionally, the energy gap was computed. The electrical conductivity of the DC in the various conduction zones was calculated by measuring the current and voltage as a function of temperature. Additionally, the mathematical equations are used to compute the energy constants, electron hopping distance, tail width, pre-exponential factor, and density of the energy states in variation zones (densities of the energ
... Show MoreThe friendly-environment geophysical methods are commonly used in various engineering and near-surface environmental investigations. Electrical Resistivity Imaging technique was used to investigate the subsurface rocks, sediments properties of a proposed industrial site to characterize the lateral and vertical lithological changes. via the electrical resistivity, to give an overview about the karst, weak and robust subsoil zones. Nineteen 2D ERI profiles using Wenner array with 2 m electrode spacing have been applied to investigate the specific industry area. One of these profiles has been conducted with one-meter electrode spacing. The surveyed profiles are divided into a number of blocks, each block consists of several parallel pr
... Show MoreCompanies compete greatly with each other today, so they need to focus on innovation to develop their products and make them competitive. Lean product development is the ideal way to develop product, foster innovation, maximize value, and reduce time. Set-Based Concurrent Engineering (SBCE) is an approved lean product improvement mechanism that builds on the creation of a number of alternative designs at the subsystem level. These designs are simultaneously improved and tested, and the weaker choices are removed gradually until the optimum solution is reached finally. SBCE implementations have been extensively performed in the automotive industry and there are a few case studies in the aerospace industry. This research describe the use o
... Show MoreOptical Mark Recognition (OMR) is the technology of electronically extracting intended data from marked fields, such as squareand bubbles fields, on printed forms. OMR technology is particularly useful for applications in which large numbers of hand-filled forms need to be processed quickly and with a great degree of accuracy. The technique is particularly popular with schools and universities for the reading in of multiple choice exam papers. This paper proposed OMRbased on Modify Multi-Connect Architecture (MMCA) associative memory, its work in two phases: training phase and recognition phase. The proposed method was also able to detect more than one or no selected choice. Among 800 test samples with 8 types of grid answer sheets and tota
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