Flow-production systems whose pieces are connected in a row may not have maintenance scheduling procedures fixed because problems occur at different times (electricity plants, cement plants, water desalination plants). Contemporary software and artificial intelligence (AI) technologies are used to fulfill the research objectives by developing a predictive maintenance program. The data of the fifth thermal unit of the power station for the electricity of Al Dora/Baghdad are used in this study. Three stages of research were conducted. First, missing data without temporal sequences were processed. The data were filled using time series hour after hour and the times were filled as system working hours, making the volume of the data relatively high for 2015-2016-2017. 2018 was utilized as a test year to assess the modeling work and validate the experimental results. In the second step, the artificial neural networks approach employs the python program as an AI, and the affinity ratio of real data using the performance measurement of the mean absolute error (MAE) was 0.005. To improve and reduce the value of absolute error, the genetic algorithm uses the python program and the convergence ratio became 0.001. It inferred that the algorithm is efficient in improving results. Thus, the genetic algorithm provided better results with fewer errors than the neural network alone. This concludes that the shown network has superior performance over others and the possibility of its long-term predictions for 2030. A Sing time series helped detect future cases by reading and inferring system data. The development of appropriate work plans will lower internal and external expenses of the systems and help integrate other capabilities by giving correct data sources of raw materials, costs, etc. To facilitate prediction for maintenance workers, an interface has been created that facilitates users to apply them using the python program represented by entering the times, an hour, a day, a month, a year, to predict the type and place of failure.
This paper deals with defining Burr-XII, and how to obtain its p.d.f., and CDF, since this distribution is one of failure distribution which is compound distribution from two failure models which are Gamma model and weibull model. Some equipment may have many important parts and the probability distributions representing which may be of different types, so found that Burr by its different compound formulas is the best model to be studied, and estimated its parameter to compute the mean time to failure rate. Here Burr-XII rather than other models is consider because it is used to model a wide variety of phenomena including crop prices, household income, option market price distributions, risk and travel time. It has two shape-parame
... Show MoreObjective: An efficient solution for stabilization is the mobilization of the joints for the arthrokinematics affected by the positional defect of the CAI (i.e. chronic ankle instability). This study put to comparison the impacts of ankle dorsi flexion range of motion (DFROM) as well as dynamic balance ability (DBA) in the patients who have CAI using PJM (i.e. passive joint mobilization), a technique typically been used in previous works, and active joint mobilization (AJM), a technique which could have a greater impact on cortical excitability with the spontaneous movement. Design: rehabilitation program to treat recurrent ankle. Methods: A total of 10 players from the Iraqi clubs Muay Thai team were registered, 5 from each of
... Show MoreA multivariate multisite hydrological data forecasting model was derived and checked using a case study. The philosophy is to use simultaneously the cross-variable correlations, cross-site correlations and the time lag correlations. The case study is of two variables, three sites, the variables are the monthly rainfall and evaporation; the sites are Sulaimania, Dokan, and Darbandikhan.. The model form is similar to the first order auto regressive model, but in matrices form. A matrix for the different relative correlations mentioned above and another for their relative residuals were derived and used as the model parameters. A mathematical filter was used for both matrices to obtain the elements. The application of this model indicates i
... Show MoreBackground: Nursing interventions tailored to the smoking triggers in patients with non-communicable chronic diseases are essential. However, these interventions are scant due to the nature of factors associated with smoking cessation and the poor understanding of the effect of nurse-led intervention in Iraq.Purpose: This study aimed to determine the dominant smoking triggers and examine the effects of a tailored nursing intervention on smoking behavior in patients with non-communicable chronic diseases.Methods: Convenience samples of 128 patients with non-communicable chronic diseases, male and female patients, who were 18-70 years old, were recruited in this quasi-experimental, randomized comparative trial in the outpatient clinic
... Show MoreIn this investigation, water-soluble N-Acetyl Cysteine Capped-Cadmium Telluride QDs (NAC/CdTe nanocrystals), utilizing N-acetyl cysteine as a stabilizer, were prepared to assess their potential in differentiating between DNA extracted from pathogenic bacteria (e.g. Escherichia coli isolated from urine specimen) and intact DNA (extracted from blood of healthy individuals) for biomedical sensing prospective. Following the optical characterization of the synthesized QDs, the XRD analysis illustrated the construction of NAC-CdTe-QDs with a grain size of 7.1 nm. The prepared NAC-CdTe-QDs exhibited higher PL emission features at of 550 nm and UV-Vis absorption peak at 300 nm. Additionally, the energy gap quantified via PL and UV–Vis were 2.2 eV
... Show MoreCassava, a significant crop in Africa, Asia, and South America, is a staple food for millions. However, classifying cassava species using conventional color, texture, and shape features is inefficient, as cassava leaves exhibit similarities across different types, including toxic and non-toxic varieties. This research aims to overcome the limitations of traditional classification methods by employing deep learning techniques with pre-trained AlexNet as the feature extractor to accurately classify four types of cassava: Gajah, Manggu, Kapok, and Beracun. The dataset was collected from local farms in Lamongan Indonesia. To collect images with agricultural research experts, the dataset consists of 1,400 images, and each type of cassava has
... Show MoreUltra-High Temperature Materials (UHTMs) are at the base of entire aerospace industry; these high stable materials at temperatures exceeding 1600 °C are used to manage the heat shielding to protect vehicles and probes during the hypersonic flight through reentry trajectory against aerodynamic heating and reducing plasma surface interaction. Those materials are also recognized as Thermal Protection System Materials (TPSMs). The structural materials used during the high-temperature oxidizing environment are mainly limited to SiC, oxide ceramics, and composites. In addition to that, silicon-based ceramic has a maximum-use at 1700 °C approximately; as it is an active oxidation process o
In the present work, Response Surface Methodology (RSM) was utilized to optimize process variables and find the best circumstances for indirect electrochemical oxidation of mimicked wastewater to remove phenol contaminants using prepared ternary composite electrode. The electrodeposition process is used for the synthesis of a ternary composite electrode of Mn, Co, and Ni oxides. The selected concentrations of metal salts of these elements were 0.05, 0.1, and 1.5 M, with constant molar ratio, current density, and electrolysis time of 1:1:1, 25 mA/cm2, and 2 h. Interestedly, the gathered Mn-Co-Ni oxides were deposited at both the anode and cathode. X-ray diffraction (XRD) and scanning electron microscopy (SEM) facilitated the qualitative char
... Show MoreSewer systems are used to convey sewage and/or storm water to sewage treatment plants for disposal by a network of buried sewer pipes, gutters, manholes and pits. Unfortunately, the sewer pipe deteriorates with time leading to the collapsing of the pipe with traffic disruption or clogging of the pipe causing flooding and environmental pollution. Thus, the management and maintenance of the buried pipes are important tasks that require information about the changes of the current and future sewer pipes conditions. In this research, the study was carried on in Baghdad, Iraq and two deteriorations model's multinomial logistic regression and neural network deterioration model NNDM are used to predict sewers future conditions. The results of the
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