This study focuses on the implementation of interfaces for human machine interaction (HMI) control and monitor automatic production line. The automatic production line can performance feeding, transportation, sorting functions. The objectives of this study are implemented two SCADA/HMI system using two different software. TIA portal software is used to build HMI, alarm, and trends in touch panel which is helped an operator to control and monitor the production line. LabVIEW software is used to build HMI and trends in the computer screen and is linked with Microsoft Excel (ME) to generate information table helped to monitor the performance of the pneumatic equipment. The production line can do performance feeding, transportation, sorting fun

       This work focuses on the implementation of interfaces for human machine interaction (HMI) for control and monitor of automatic production line. The automatic production line which can performance feeding, transportation, sorting functions.      

            The objectives of this work are implemented two SCADA/HMI system using two different software. TIA portal software was used to build HMI, alarm, and trends in touch panel which are helped the operator to control and monitor the production line. LabVIEW software was used to build HMI and trends on the computer screen and was linked with Micros

Abstract

In this study, mucilage was extracted from Malabar spinach and tested for drag-reducing properties in aqueous liquids flowing through pipelines.  Friction produced by liquids flowing in turbulent mode through pipelines increase power consumption. Drag-reducing agents (DRA) such as polymers, suspended solids and surfactants are used to reduce power losses. There is a demand for natural, biodegradable DRA and mucilage is emerging as an attractive alternative to conventional DRAs. Literature review revealed that very little research has been done on the drag-reducing properties of this mucilage and there is an opportunity to explore the potential applications of mucilage from Malabar spinach. An experi

The Artificial Neural Network methodology is a very important & new subjects that build's the models for Analyzing, Data Evaluation, Forecasting & Controlling without depending on an old model or classic statistic method that describe the behavior of statistic phenomenon, the methodology works by simulating the data to reach a robust optimum model that represent the statistic phenomenon & we can use the model in any time & states, we used the Box-Jenkins (ARMAX) approach for comparing, in this paper depends on the received power to build a robust model for forecasting, analyzing & controlling in the sod power, the received power come from

Machine learning models have recently provided great promise in diagnosis of several ophthalmic disorders, including keratoconus (KCN). Keratoconus, a noninflammatory ectatic corneal disorder characterized by progressive cornea thinning, is challenging to detect as signs may be subtle. Several machine learning models have been proposed to detect KCN, however most of the models are supervised and thus require large well-annotated data. This paper proposes a new unsupervised model to detect KCN, based on adapted flower pollination algorithm (FPA) and the k-means algorithm. We will evaluate the proposed models using corneal data collected from 5430 eyes at different stages of KCN severity (1520 healthy, 331 KCN1, 1319 KCN2, 1699 KCN3 a

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This paper studies a novel technique based on the use of two effective methods like modified Laplace- variational method (MLVIM) and a new Variational method (MVIM)to solve PDEs with variable coefficients. The current modification for the (MLVIM) is based on coupling of the Variational method (VIM) and Laplace- method (LT). In our proposal there is no need to calculate Lagrange multiplier. We applied Laplace method to the problem .Furthermore, the nonlinear terms for this problem is solved using homotopy method (HPM). Some examples are taken to compare results between two methods and to verify the reliability of our present methods.

       In the present paper, by making use of the new generalized operator, some results of third order differential subordination and differential superordination consequence for analytic functions are obtained. Also, some sandwich-type theorems are presented.