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.
Abstract
Public debt has posed a major challenge to both developing and developed countries, which has focused attention on the optimal limits (threshold of debt) and its determinants.
The study examines the effect of the Public bank debt on the foreign reserves and the work of the foreign reserve as a limitation on the process of bank debt (part of the internal debt) for the period (2017-2004), in addition to finding the type and nature of the relationship between them according to the hypotheses of the study, Public bank debt and foreign reserves.
The study was based on data from the Iraqi banking sector, which showed that Iraq has a foreign reserve in line with internat
... Show MoreThe value of time out as a time not count of official time form the game like four periods and extra time also it considered a great interest if used well thru the game , the importance of this problem is not using well the time out and when the coach ask for time out and how to invest this time legally to make good results also there is no observing system as the researcher see gives the reality image that the coach is successful lead the game when he takes time out . The goals of research that knowing on numbers of time out for excellent teams in Iraq (first &second) stages and putting special inventory reverse reality of asking time out (positive &negative) on playing basketball , the hypothesis of research that tell the time out effect
... Show MoreIn this paper, we derived an estimators and parameters of Reliability and Hazard function of new mix distribution ( Rayleigh- Logarithmic) with two parameters and increasing failure rate using Bayes Method with Square Error Loss function and Jeffery and conditional probability random variable of observation. The main objective of this study is to find the efficiency of the derived of Bayesian estimator compared to the to the Maximum Likelihood of this function using Simulation technique by Monte Carlo method under different Rayleigh- Logarithmic parameter and sample sizes. The consequences have shown that Bayes estimator has been more efficient than the maximum likelihood estimator in all sample sizes with application
A total of 20 raw milk samples were used as the fouling agent for evaluating the bacteriological effectiveness of cleaning and sanitizing of domestic milking equipment by using ozonated water at 0.5 ppm comparing to the warm water at 55! for 5 minutes respectively. The mean values of total aerobic bacteria, Coliform and E.coli that present on the plastic and stainless-steel containers after using the raw milk as fouling agent were 3.4×10-6 , 6.7x10-5 and 5.8×10-3 cfu/cm2 respectively , after cleaning the stainless steel containers by the ozonated water the mean values of total aerobic bacterial counts, Coliforms and E.coli bacteria were reduced to 1.2×10-6, 4.7×10-5 and 3.3×10-3 CFU/cm2 respectively. while after cleaning by the warm wa
... Show MoreA theoretical study including the effects of the fusion characteristics parameters on the fundamental fusion rate for the BEC state in D-D fusion reaction is deal with varieties physical parameters such as the fuels density, fuel temperature and the astrophysics S-factor are processed to bring an approximately a comparable results to agree with the others previously studies.
In light of the development in computer science and modern technologies, the impersonation crime rate has increased. Consequently, face recognition technology and biometric systems have been employed for security purposes in a variety of applications including human-computer interaction, surveillance systems, etc. Building an advanced sophisticated model to tackle impersonation-related crimes is essential. This study proposes classification Machine Learning (ML) and Deep Learning (DL) models, utilizing Viola-Jones, Linear Discriminant Analysis (LDA), Mutual Information (MI), and Analysis of Variance (ANOVA) techniques. The two proposed facial classification systems are J48 with LDA feature extraction method as input, and a one-dimen
... Show MoreThe present work is an attempt to develop design data for an Iraqi roof and wall constructions using the latest ASHRAE Radiant Time Series (RTS) cooling load calculation method. The work involves calculation of cooling load theoretically by introducing the design data for Iraq, and verifies the results experimentally by field measurements. Technical specifications of Iraqi construction materials are used to derive the conduction time factors that needed in RTS method calculations. Special software published by Oklahoma state university is used to extract the conduction factors according to the technical specifications of Iraqi construction materials. Good agreement between the average theoretical and measured cooli
... Show MoreThe aim of this paper to find Bayes estimator under new loss function assemble between symmetric and asymmetric loss functions, namely, proposed entropy loss function, where this function that merge between entropy loss function and the squared Log error Loss function, which is quite asymmetric in nature. then comparison a the Bayes estimators of exponential distribution under the proposed function, whoever, loss functions ingredient for the proposed function the using a standard mean square error (MSE) and Bias quantity (Mbias), where the generation of the random data using the simulation for estimate exponential distribution parameters different sample sizes (n=10,50,100) and (N=1000), taking initial
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