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 efforts embedded in this paper have been devoted to designing, preparing, and testing warm mix asphalt (WMA) mixtures and comparing their behavior against traditional hot mix asphalt mixtures. For WMA preparation, the Sasobit wax additive has been added to a 40/50 asphalt binder with a concentration of 3%. An experimental evaluation has been performed by conducting the Marshall together with volumetric properties, indirect tensile strength, and wheel tracking tests to acquire the tensile strength ratio (TSR), retained stability index (RSI), and rut depth. It was found that the gained benefit of reduction in mixing and compaction temperatures was reversely associated with a noticeable decline in Marshall properties and moisture s
... Show MoreThe problem of Bi-level programming is to reduce or maximize the function of the target by having another target function within the constraints. This problem has received a great deal of attention in the programming community due to the proliferation of applications and the use of evolutionary algorithms in addressing this kind of problem. Two non-linear bi-level programming methods are used in this paper. The goal is to achieve the optimal solution through the simulation method using the Monte Carlo method using different small and large sample sizes. The research reached the Branch Bound algorithm was preferred in solving the problem of non-linear two-level programming this is because the results were better.
The corona virus epidemic outbreak has urged an extreme worldwide effort for re‐purposing obtainable approved medications for its treatment. In this review, we're focusing on the chemicals properties andpharmacologicaleffectiveness of medicationsofsmallmolecule that are presently being evaluated in clinical trials for the management of corona virus (COVID‐19). The current review sheds light on a number of drugs that have been diagnosed to treat COVID‐19 and their biological effects.
One of the important differences between multiwavelets and scalar wavelets is that each channel in the filter bank has a vector-valued input and a vector-valued output. A scalar-valued input signal must somehow be converted into a suitable vector-valued signal. This conversion is called preprocessing. Preprocessing is a mapping process which is done by a prefilter. A postfilter just does the opposite.
The most obvious way to get two input rows from a given signal is to repeat the signal. Two rows go into the multifilter bank. This procedure is called “Repeated Row” which introduces oversampling of the data by a factor of 2.
For data compression, where one is trying to find compact transform representations for a
... Show MoreTheoretical spectroscopic study of Beryllium Oxide has been carried out, Boltzmann distribution of P, Q and R branches in the range of (0<J<13) at temperature 4200K for (0-0) band for electronic transitions B1Σ+-A1Π and B1Σ-X1Σ. The Boltzmann distribution of these branches has a maximum values at equal J approximately while the values of relative population are different. For the B1Σ+- X1Σ+ transition the branch's lines extend towards lower wavenumber. This is because (Bv'-Bv") value is negative, i.e Bv'< Bv" For B1Σ+-A1Π
... Show MoreThe study is aimed at social support to the students of the College of Education for women (The research sample) and measuring the quality of life at students of the College of Education for women (The research sample) And to identify the relationship between social support and quality of life of students of the College Education for Women and research sample consisted of 200 students The adoption of the resolution as a tool for data collection and the most important results of the search results that the students of the College Education for Women have social support. In other words, parents and friends are supporting the students. The students have the quality of life any positive meaning to life and that when a person has a quality of
... Show MoreIn this paper, the proposed phase fitted and amplification fitted of the Runge-Kutta-Fehlberg method were derived on the basis of existing method of 4(5) order to solve ordinary differential equations with oscillatory solutions. The recent method has null phase-lag and zero dissipation properties. The phase-lag or dispersion error is the angle between the real solution and the approximate solution. While the dissipation is the distance of the numerical solution from the basic periodic solution. Many of problems are tested over a long interval, and the numerical results have shown that the present method is more precise than the 4(5) Runge-Kutta-Fehlberg method.
Comparative morphological study has been treated for two species of the genus Chaenorhinum (D.C.) Richb., These species were: 1. Chaenorhinum calycinum 2. Chaenorhinum rubrifolium (Robill. & cast. Ex Lam. & DC.) Fourr. The genus belong to the family Scorphulariaceae. Morphological characters has been studies for: root, stem, leaves, flowers (calyx, corolla, androcium including filaments and anthers, gynocium including ovary, style and stigma), fruits and seeds also has been characterized. Key for there two species presented using some quantitative characters. Other characters like shape of fruits and seeds were used too, and they were of a useful taxonomic value
This study is concerned with the topic of the constant and the variable within the artistic theatrical phenomenon and specifically the accompanying music for the movements, scenes and dramatized idea, which translates the Iraqi environments (the serious ones). The researcher, here, tries to determine those variables and constants as a methodological scientific study to serve the scientific and cultural institutions and contribute in settling them intellectually, and entering them in the academic environments that depend on studying the artistic associations between the theatrical science and musical science. We find that this study which addresses the topic (the constant and the variable in the theatrical show music for the department of
... Show MoreThe process of evaluating data (age and the gender structure) is one of the important factors that help any country to draw plans and programs for the future. Discussed the errors in population data for the census of Iraqi population of 1997. targeted correct and revised to serve the purposes of planning. which will be smoothing the population databy using nonparametric regression estimator (Nadaraya-Watson estimator) This estimator depends on bandwidth (h) which can be calculate it by two ways of using Bayesian method, the first when observations distribution is Lognormal Kernel and the second is when observations distribution is Normal Kernel
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