Planar Parallel manipulators (PPMs) are widely used these days, as they have many advantages compared to their serial counterparts. However, their inverse and direct kinematics are hard to obtain, due to the complexity of the manipulators' behavior. Therefore, this paper provides a comparative analysis for two methods that were used to obtain the inverse kinematics of a 3-RRR manipulator. Instead of the conventional algebraic and graphical methods used for attaining the mathematical models for such manipulators, an adaptive neuro-fuzzy inference structure (AFNIS) model was alternatively

The aim of this research is to reduce the gap between manufacture expertise and management expertise by using modern technology like Manufacturing Execution System (MES) via Artificial Intelligence (AI) and Machin Learning (ML). A design of MES has been proposed and implemented on El-Araby Plastic Injection Molding (PIM) factory. This work is based on the International Society of Automation Standard (ISA-S95). A fully automated data management system has been designed and implemented to control data follow between shop floor e.g. (machines and operators) and management floor e.g. (production

In the use of automatic control and its optimization methods, this research discusses how Proportional Integral Derivative (PID) controller is used to provide a smooth auto-parking for an electrical autonomous car. Different tuning methods are shown, discussed, and applied to the system looking forward to enhancing its performance. Time domain specifications are used as a criterion of comparison between tuning methods in order to select the best tuning method to the system with a proper cost function. Results show that Particle Swarm Optimization (PSO) method gives the best results according

Uncertainty on the condition of the weather always give a major headache to the agricultural industry as the cultivated plant that is grown on a large scale commercially rely on the condition of the weather. Therefore, to reduce the interdependency on the weather itself, a recommendation to develop a prototypic mobile robot for smart irrigation is submitted. Smart irrigation system is an essential tool from yield point of view and scarcity of the water. This smart irrigation system adopts a soil moisture sensor to measure the moisture content of the soil and automatically provide a signal to

Although there is a massive number of food tech enabled startups all over the world only few of them can succeed globally, determining the main factors which affect success or failure are still a challenge. In this paper, industrial engineering fundamentals are used to develop the startup structure and workplace design in two main areas; layout design to improve the work environment as well as flow of workers and flow of materials, supply chain management to design push-pull hybrid system and demand forecasting using non-stationary exponential smoothing method. © 2021 IEEE.

Surface plasmon resonance (SPR) sensors are increasingly in demand due to their high sensitivity, better accuracy, and improved detection limit. Such performance parameters make these sensors suitable for biological and medical field’s applications. During the last decade, prism coupling-based SPR sensors had been a preferred choice among the designer and developers across the globe. This article summarizes a review of prism coupling-based SPR photonic sensors. Important performance characteristics of such sensors have also been studied with respect to their detection accuracy, sensitivity

Sustainability is an important consideration in product design. The sustainable design should fully consider the environmental, social, and economic factors of the product. However, the three factors are often conflicting with each other. This paper aims to strike a balance between these factors and achieve sustainable product design through multi-objective optimization. The three influencing factors of sustainability, namely, the environmental factor, social factor and economic factor, were respectively defined as environmental impact, labor time and labor cost. Then, the product to be

Monitoring light dose is essential in much clinical procedures like bio-stimulation, neuro-medicine and photodynamic therapy and in many biophotonics applications such as optogenetics and biosensing. However, monitoring the optical power dissipation as light travels in different layers of tissue is essential in determining the required optical dose. Each part in the human body is protected by different thickness of skin layer; therefore, studying the variations of the optical power when light propagates in different thicknesses of the human skin is essential for safe and accurate medical

The spread of epidemics and diseases is known to exhibit chaotic dynamics; a fact confirmed by many developed mathematical models. However, to the best of our knowledge, no attempt to realize any of these chaotic models in analog or digital electronic form has been reported in the literature. In this work, we report on the efficient FPGA implementations of three different virus spreading models and one disease progress model. In particular, the Ebola, Influenza, and COVID-19 virus spreading models in addition to a Cancer disease progress model are first numerically analyzed for parameter

Bio-impedance circuit modeling is a popular and effective non-invasive technique used in medicine and biology to fit the measured spectral impedance data of living or non-living tissues. The variations in impedance magnitude and/or phase at different frequencies reflect implicit biophysical and biochemical changes. Bio-impedance is also used for sensing environmental changes and its use in the agriculture industry is rapidly increasing. In this paper, we review and compare among the fractional-order circuit models that best fit bio-impedance data and the different methods for identifying the