Hussein A. Abdullah

Influence of aging parameters on the mechanical properties of 6063 aluminium alloy

Abstract The 6063 aluminium alloy were given various heat treatments at under-aged, peak-aged and over-aged temperatures. The effect of precipitation on the tensile strength, yield strength, hardness, ductility and number of cycles required to fail the alloy at constant stress was investigated. The variation in time and temperature have improved the mechanical properties of the Al-alloy, whereas the ductility has decreased. The experimental work has revealed that time and temperature play a very important role in the precipitation hardening process of the Al-alloy. The initial increase in the tensile strength, yield strength, hardness and fatigue is due to vacancies assisted diffusion mechanism and formation of high volume fraction of guinier preston (GP) zones, which disturbs the regularity in the lattices. In over-aging of the alloy, the size of the individual particle increases, but the number of particles decreases. This causes few obstacles to the movement of dislocations, therefore, the mechanical properties decreases. The scanning electron microscope (SEM) study of the under-aged alloy have exhibited facet fatigue fracture surface, whereas the peak-aged and over-aged alloy show a mixed mode of fracture, i.e. facet fracture with striation and also intergranular fracture.

VARI-RO solar-powered desalting technology

Abstract This paper reports on the innovative concepts study conducted for the Middle East Desalination Research Center (MEDRC) to determine the cost-effectiveness of new approaches to solar powered desalting. These approaches include combining of modern solar power conversion technology with newly developed, hydraulic-driven, pumping and energy recovery technology for brackish water and seawater desalting reverse osmosis (BWRO or SWRO) desalting. The study included a literature search of existing methods, preliminary concepting and assessment, technical analysis, and comparisons of water produced per quantity of solar energy insolation for various concepts. The hydraulic driven pumping and energy recovery system is known as the VARI-RO system (patent pending). Four new combinations of solar energy conversion and SWRO desalting systems were evaluated for comparison to existing methods, as follows: System A, solar photovoltaic-electric module with the VARI-RO electric motor drive; System B, solar dish concentrator-Stirling engine electric module with the VARI-RO electric motor drive; System C, solar trough concentrator-thermal energy module with the VARI-RO direct drive engine. System D, solar dish concentrator-thermal energy module with the VARI-RO direct drive engine. It was determined that the VARI-RO technology is uniquely suited for use with solar power because of (1) high efficiency of the pumping and energy recovery system, (2) high efficiency of the direct drive engine system, and (3) the capability to adjust the power consumption to match the solar power variations throughout the day. This study has shown that this solar powered desalination technology can provide substantial environmental benefits in the next century by supplying needed water to remote regions without extensive infrastructure, and also by reducing the environmental emissions (including CO 2 ) for desalting saline water sources.

Results of Clinicians Using a Therapeutic Robotic System in an Inpatient Stroke Rehabilitation Unit

BackgroundPhysical rehabilitation is an area where robotics could contribute significantly to improved motor return for individuals following a stroke. This paper presents the results of a preliminary randomized controlled trial (RCT) of a robot system used in the rehabilitation of the paretic arm following a stroke.MethodsThe studys objectives were to explore the efficacy of this new type of robotic therapy as compared to standard physiotherapy treatment in treating the post-stroke arm; to evaluate client satisfaction with the proposed robotic system; and to provide data for sample size calculations for a proposed larger multicenter RCT. Twenty clients admitted to an inpatient stroke rehabilitation unit were randomly allocated to one of two groups, an experimental (robotic arm therapy) group or a control group (conventional therapy). An occupational therapist blinded to patient allocation administered two reliable measures, the Chedoke Arm and Hand Activity Inventory (CAHAI-7) and the Chedoke McMaster Stroke Assessment of the Arm and Hand (CMSA) at admission and discharge. For both groups, at admission, the CMSA motor impairment stage of the affected arm was between 1 and 3.ResultsData were compared to determine the effectiveness of robot-assisted versus conventional therapy treatments. At the functional level, both groups performed well, with improvement in scores on the CAHAI-7 showing clinical and statistical significance. The CAHAI-7 (range7-49) is a measure of motor performance using functional items. Individuals in the robotic therapy group, on average, improved by 62% (95% CI: 26% to 107%) while those in the conventional therapy group changed by 30% (95% CI: 4% to 61%). Although performance on this measure is influenced by hand recovery, our results showed that both groups had similar stages of motor impairment in the hand. Furthermore, the degree of shoulder pain, as measured by the CMSA pain inventory scale, did not worsen for either group over the course of treatment.ConclusionOur findings indicated that robotic arm therapy alone, without additional physical therapy interventions tailored to the paretic arm, was as effective as standard physiotherapy treatment for all responses and more effective than conventional treatment for the CMSA Arm (p = 0.04) and Hand (p = 0.04). At the functional level, both groups performed equally well.

Distributed C3 Environment for Small to Medium‐sized Enterprises

The adoption of integrated computer‐based manufacturing and management techniques by small, traditional engineering companies often represents an unaffordable and high risk investment strategy in technology that is often not well understood by its recipients. Paradoxically, the opportunity for complete success in a small to medium‐sized enterprise (SME) is greater than in a large company which very often is incapable of full integration due to the divisions and inertia implicit in a large hierarchical organization. To derive full benefits from such an investment the company must possess a meticulous understanding of its market, fiscal environment, operations management, engineering and technological skills, manufacturing facilities and product range. It must adopt an appropriate implementation of CIM that does not debase previous ad hoc investments in what are often termed islands‐of‐automation or information technology. For success a well‐planned stepwise approach is vital. Reports on the approach adopte...

Self-Learning Visual Servoing of Robot Manipulator Using Explanation-Based Fuzzy Neural Networks and Q-Learning

A new self-learning visual servoing system for the robot manipulators is proposed. This system includes two main properties: on-line self training and lifelong learning that are implemented by the Q-Learning algorithm and Explanation-based Fuzzy Neural Networks (EBFNN) respectively. We demonstrate that the number of training samples and the training time for a specific robot positioning accuracy can be reduced using explanation-based fuzzy neural networks and the Q-Learning algorithm. The system uses Q-learning to find the optimal policy in conjunction with the reinforcement learning. This policy is used by a robot to reach an object that has been randomly placed in a static workspace. Background knowledge about the robot and its environment is transferred to the robot agent during the learning process using a set of previously trained neural networks. This system learns the optimal policy in order to select the best action that maximizes the cumulative reward received at each time step. This learning approach does not use either a robot or camera model, or require calibration. Simulation results prove the effectiveness of this methodology to improve the learning process and the performance of the self-learning visual servoing system.

A Slip Detection and Correction Strategy for Precision Robot Grasping

This paper presents a grasp force regulation strategy for precision grasps. The strategy makes no assumptions about object properties and surface characteristics, and can be used with a wide range of grippers. It has two components, a slip signal detector that computes the magnitude of slip and a grasping force set point generator that acts on the detectors output. The force set point generator is designed to ensure that slip is eliminated without using excessive force. This is particularly important in several situations like grasping fragile objects or in-hand manipulation of thin small objects. Several experiments were conducted to simulate various grasping scenarios with different objects. Results show that the strategy was very successful in dealing with uncertainty in object mass, surface characteristics, or rigidity. The strategy is also insensitive to robot motion.

Theoretical and Experimental Investigations of Solar-Thermoelectric Air-Conditioning System for Remote Applications

In this paper, we have designed and constructed a low cost solar-thermoelectric (TE) air-conditioning system for people in remote areas where electricity is still in short supply. Such system can be potentially used to condition tents and living areas. The proposed solar-powered TE air-conditioning system is based on the principles of Peltier effect to create a finite temperature difference across the condenser and the evaporator of the TE air-conditioning system. The cold side (or the evaporator) of the TE module is used for air-conditioning application; provides cooling to the living space. The thermal energy from the hot side of the module is dumped to the surrounding environment. Using the existing heat transfer and thermodynamics knowledge, an analytical model is developed to predict the performance of the solar-TE air-conditioning system in terms of the hot and cold reservoir temperatures, heat removal rates from the conditioned space, power input, and coefficient of performance (COP). A second analytical model is proposed to predict the cooling down period of the conditioned space as a function of heat removed by air-conditioning system, heat gained through the wall of the conditioned space, and heat generated inside the conditioned space. A detailed system is constructed to predict the performance of solar-TE air-conditioning system experimentally. A conditioned space was constructed to carry out the experimental work. Multiple air-conditioning systems were installed in the conditioned space. The cooling performance of the designed solar-TE air-conditioning system was experimentally tested and verified with the analytical calculation.

Mathematical modeling of laser based potato cutting and peeling.

A mathematical model is developed and validated to predict the depth of cut in potato tuber slabs as a function of laser power and travel speed. The model considers laser processing parameters such as input power, spot size and exposure time as well as the properties of the material being cut such as specific heat, thermal conductivity, surface reflectance, etc. The model also considers the phase change of water in potato and the ignition temperature of the solid portion. The composition of the potato tuber is assumed to be of water and solid. The model also assumes that the ablation process is accomplished through ejection of liquid water, debris and water vapour, and combustion of solid. A CO(2) laser operating in c.w. mode was chosen for the experimental work because water absorbs laser energy highly at 10.6 microm, and CO(2) laser units with relatively high output power are available. Slabs of potato tuber were chosen to be laser processed since potato contains high moisture and large amounts of relatively homogeneous tissue. The results of the preliminary calculations and experiments concluded that the model is able to predict the depth of cut in potato tuber parenchyma when subjected to a CO(2) laser beam.

Robotic assistants in personal care: A scoping review

The aim of this study is to present an overview of the technological advances in the field of robotics developed for assistance with activities of daily living (ADL), and to present areas where further research is required. Four databases were searched for articles presenting either a novel design of one of these personal care robotic system or trial results relating to these systems. Articles presenting nine different robotic personal care systems were examined, six of which had been developed after 2005. These six also all have publications relating to their trials. In the majority of trials, patient independence was improved with operation of the robotic device for a specific subset of ADL. A map of the current state of the field of personal care robotics is presented in this study. Areas requiring further research include improving feedback and awareness, as well as refining control methods and pre-programmed behaviors. Developing an affordable, easy to use system would help fill the current gap in the commercial market.

Robotic pilot study for analysing spasticity: clinical data versus healthy controls.

BackgroundSpasticity is a motor disorder that causes significant disability and impairs function. There are no definitive parameters that assess spasticity and there is no universally accepted definition. Spasticity evaluation is important in determining stages of recovery. It can determine treatment effectiveness as well as how treatment should proceed. This paper presents a novel cross sectional robotic pilot study for the primary purpose of assessment. The system collects force and position data to quantify spasticity through similar motions of the Modified Ashworth Scale (MAS) assessment in the Sagittal plane. Validity of the system is determined based on its ability to measure velocity dependent resistance.MethodsForty individuals with Acquired Brain Injury (ABI) and 45 healthy individuals participated in a robotic pilot study. A linear regression model was applied to determine the effect an ABI has on force data obtained through the robotic system in an effort to validate it. Parameters from the model were compared for both groups. Two techniques were performed in an attempt to classify between healthy and patients. Dynamic Time Warping (DTW) with k-nearest neighbour (KNN) classification is compared to a time-series algorithm using position and force data in a linear discriminant analysis (LDA).ResultsThe system is capable of detecting a velocity dependent resistance (p<0.05). Differences were found between healthy individuals and those with MAS 0 who are considered to be healthy. DTW with KNN is shown to improve classification between healthy and patients by approximately 20 % compared to that of an LDA.ConclusionsQuantitative methods of spasticity evaluation demonstrate that differences can be observed between healthy individuals and those with MAS of 0 who are often clinically considered to be healthy. Exploiting the time-series nature of the collected data demonstrates that position and force together are an accurate predictor of patient health.