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 aim of the present study was to develop theophylline (TP) inhalable sustained delivery system by preparing solid lipid microparticles using glyceryl behenate (GB) and poloxamer 188 (PX) as a lipid carrier and a surfactant respectively. The method involves loading TP nanoparticles into the lipid using high shear homogenization – ultrasonication technique followed by lyophilization. The compositional variations and interactions were evaluated using response surface methodology, a Box – Behnken design of experiment (DOE). The DOE constructed using TP (X1), GB (X2) and PX (X3) levels as independent factors. Responses measured were the entrapment efficiency (% EE) (Y1), mass median
... Show MoreSocial media is known as detectors platform that are used to measure the activities of the users in the real world. However, the huge and unfiltered feed of messages posted on social media trigger social warnings, particularly when these messages contain hate speech towards specific individual or community. The negative effect of these messages on individuals or the society at large is of great concern to governments and non-governmental organizations. Word clouds provide a simple and efficient means of visually transferring the most common words from text documents. This research aims to develop a word cloud model based on hateful words on online social media environment such as Google News. Several steps are involved including data acq
... 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
... Show MoreIn this paper, the memorization capability of a multilayer interpolative neural network is exploited to estimate a mobile position based on three angles of arrival. The neural network is trained with ideal angles-position patterns distributed uniformly throughout the region. This approach is compared with two other analytical methods, the average-position method which relies on finding the average position of the vertices of the uncertainty triangular region and the optimal position method which relies on finding the nearest ideal angles-position pattern to the measured angles. Simulation results based on estimations of the mobile position of particles moving along a nonlinear path show that the interpolative neural network approach outperf
... 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 MoreBeen manufacturing detector Altosalih optical pattern contact metal semiconductor through deposition poles of aluminum metal on the chips of crystal cadmium Tleraad (CdTe) with directional [111] and growing with laboratory and annealed at a temperature 80c for 30 minutes and eat Study of some electrical properties nailed and scoutNmadj ??????? copper with non ??????? models to see effect Alichoab well research deals impact Alichoab and frequency detector resistance
In this work the structural, electrical and optical Properties of CuO semiconductor films had been studied, which prepared at three thickness (100, 200 and 500 nm) by spray pyrolysis method at 573K substrate temperatures on glass substrates from 0.2M CuCl2•2H2O dissolved in alcohol. Structural Properties shows that the films have only a polycrystalline CuO phase with preferential orientation in the (111) direction, the dc conductivity shows that all films have two activation energies, Ea1 (0.45-0.66 eV) and Ea2 (0.055-.0185 eV), CuO films have CBH (Correlated Barrier Hopping) mechanism for ac-conductivity. The energy gap between (1.5-1.85 eV).
Pure Polyaniline salt, and protonation PANI by H2SO4 were synthesized by electro-chemical oxidative polymerization of aniline with acidity of H2SO4. The solution was prepared in reaction temperature equal 291 K and the acidity of aqueous solution was 1 molarities. The prepared polyaniline was characterized by FT-IR, the result indicate that the intensity is increase with increasing of applied voltage. The dc conductivity has been measured for bulk polyaniline pure and doped in the form of compressed pellet with evaporated Ohmic Al electrodes in temperature range (303-423) K. The Eav energy of the thermal rate process of the electrical conductivity was determined. The results indicate that the dc conductivity of doped samples are two or t
... Show MoreThe study effect Graphene on optical and electrical properties of glass prepared on glass substrates using sol–gel dip-coating technique. The deposited film of about (60-100±5%) nm thick. Optical and electrical properties of the films were studied under different preparation conditions, such as graphene concentration of 2, 4, 6 and 8 wt%. The results show that the optical band gap for glass-graphene films decreasing after adding the graphene. Calculated optical constants, such as transmittance, extinction coefficient are changing after adding graphene. The structural morphology and composition of elements for the samples have been demonstrated using SEM and EDX. The electrical properties of films include DC electrical conductivity; we
... Show More