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Dive into the research topics where Ala Qattawi is active.

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Featured researches published by Ala Qattawi.


IEEE Journal of Photovoltaics | 2014

Evaluation of On-Board Photovoltaic Modules Options for Electric Vehicles

Mahmoud Abdelhamid; R. Singh; Ala Qattawi; Mohammed A. Omar; Imtiaz Haque

This paper presents an overview of different commercial photovoltaic (PV) module options to power on-board electric vehicles (EVs). We propose the evaluation factors, constraints, and the decision-making criteria necessary to assess the suitability of this PV module for this application. The incorporation of quality function deployment (QFD) and the analytical hierarchy process (AHP) is the decision-making methodology used in this study. Our approach is innovative and robust in that the evaluation depends upon data collected from PV manufactures datasheets. Unlike traditional research, a hybrid AHP and QFD innovative decision-making methodology has been created, and current commercial PV market data for all pairwise comparisons are used to show that methodology. Using both cooled and uncooled PV modules, best, intermediate, and worst-case scenarios were used to estimate the driving ranges of lightweight EVs powered exclusively by bulk silicon PV modules. Results showed that the available daily driving ranges were between 25 and 60 km and that the CO2 emissions were reduced between 3 and 6.5 kg, compared with internal combustion vehicles of a similar type. We found that mono-Si PV modules were most suited to power low-speed, lightweight, and aerodynamically efficient EVs.


International Journal of Computer Integrated Manufacturing | 2013

Incorporating quality function deployment and analytical hierarchy process in a knowledge-based system for automotive production line design

Ala Qattawi; Ahmad Mayyas; Mahmoud Abdelhamid; Mohammed Omar

The authors present an intelligent tool to perform the design of automotive production line, specifically for automotive body-in-white panels. The system adopts quality function deployment principle and analytical hierarchy process methodology to be the main reasoning logic for design decisions, and to explore the effect of enhancing these traditional tools with an artificial intelligent scheme, namely the knowledge-based system. Moreover, all knowledge and expertise of production line design are stored in an interactive knowledge base. Thus, the system is knowledge-base-oriented and exhibits the ability to repetitively deal with design problems as changes occur to design needs or manufacturing process options. Furthermore, this technique offers two knowledge bases: the first holds the production requirements and their correlations to essential process attributes, while the second contains available manufacturing processes and their characteristics to fabricate body-in-white panels. Finally, the work contains a case study to verify the developed systems functionality and merits. The results demonstrate an increase in the design procedure efficiency and reduction in the inconsistency. Similarly, the system provides improved results interpretation using graphical representation, in addition to the possibility of tracking the justification of final selected manufacturing processes down to the customer requirements.


Journal of Intelligent Manufacturing | 2014

Design considerations of flat patterns analysis techniques when applied for folding 3-D sheet metal geometries

Ala Qattawi; Ahmad Mayyas; H. Thiruvengadam; V. Kumar; Shan Dongri; Mohammed Omar

This paper discusses a systematic approach to implement the principles of Flat Pattern Analysis FPA for folding sheet metal products. The paper starts by highlighting the needs for the vehicular structure forming process with respect to the main production line requirements through using Quality Function Deployment QFD matrix. Additionally, the potentials of fold forming for sheet metal parts in achieving the major production needs will then be benchmarked against other forming techniques through a decision making tool namely; the Analytical Hierarchy Process AHP. The study investigates the application of flat pattern tools for sheet metal products derived from analysis for thin or zero thickness sheets (i.e. paper origami). The analysis sets an approach to generate all possible configurations of flat patterns that result in a specific 3-D structure profile. Secondly, a set of optimality selection metrics are developed and applied to these configurations to help determine the most optimized flat pattern. These optimality measures are a metric based on compactness, a metric for nesting efficiency to describe the strip layout planning, and two measures to assess the manufacturing aspect i.e. bending operation in terms of number and orientation of bend lines.


International Journal of Sustainable Engineering | 2014

Knowledge-based system, equipped with cluster analysis for eco-material selection: an automobile structure case study

Ahmad Mayyas; Mohammed Omar; Abdel Raouf Mayyas; Ala Qattawi; Qin Shen

The aim of this study is to develop a material selection framework structured around a knowledge-based system (KBS). Specifically, a hybrid data mining technique is employed to extract knowledge from large datasets using cluster analysis techniques; the mined knowledge then serves as the inference logic within the KBS designed for material selection purposes. Cluster analysis results are used as a basis for the tree-based structure of the KBS where if–then rules are developed based on the general cluster properties; that is, inference logic is structured in a way such that it can predict general sustainability characteristics of the material as well as its exact mechanical, cost and physical properties. To develop the structure of the KBS, the selection structure employs sustainable material indices. Additionally, the proposed material selection model of the KBS is purposefully composed of material sustainability, functionality and cost indices. The constructed knowledge is then demonstrated for selecting automobile structural panels.


International Journal of Computer Integrated Manufacturing | 2014

Knowledge-based systems in sheet metal stamping: a survey

Ala Qattawi; Ahmad Mayyas; Shan Dongri; Mohammed A. Omar

This manuscript surveys and analyses the different implementations of knowledge-based systems (KBS) in sheet metal workings. The scope will cover different stamping phases; specifically the stamped part design, the stamping process planning, the die structure planning and manufacturing with the focus on progressive die designs, and lastly, the strip layout planning. The analysis of the KBS in each of these stamping phases will include the intended function of the system, the KBS construction methodology and the reasoning logic scheme utilised to manipulate the content of the knowledge bases. The survey compares the followed approaches in terms of challenges and merits found for each followed approach. This work serves as a current state-of-the-art analysis for employing KBS in sheet metal stamping (SMS).


Renewable & Sustainable Energy Reviews | 2012

Design for sustainability in automotive industry: A comprehensive review

Ahmad Mayyas; Ala Qattawi; Mohammed Omar; Dongri Shan


Materials & Design | 2011

Using Quality Function Deployment and Analytical Hierarchy Process for material selection of Body-In-White

Abdelraoof Mayyas; Qin Shen; Ahmad Mayyas; Mahmoud Abdelhamid; Dongri Shan; Ala Qattawi; Mohammed Omar


Energy | 2012

Life cycle assessment-based selection for a sustainable lightweight body-in-white design

Ahmad Mayyas; Ala Qattawi; Abdel Raouf Mayyas; Mohammed Omar


Journal of Cleaner Production | 2013

Quantifiable measures of sustainability: a case study of materials selection for eco-lightweight auto-bodies

Ahmad Mayyas; Ala Qattawi; Abdel Raouf Mayyas; Mohammed Omar


Infrared Physics & Technology | 2010

Feature-level and pixel-level fusion routines when coupled to infrared night-vision tracking scheme

Yi Zhou; Abedalroof Mayyas; Ala Qattawi; Mohammed Omar

Collaboration


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Mohammed Omar

Center for Automotive Research

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Ahmad Mayyas

Center for Automotive Research

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Abdel Raouf Mayyas

Center for Automotive Research

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Mahmoud Abdelhamid

Center for Automotive Research

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Dongri Shan

Center for Automotive Research

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Qin Shen

Center for Automotive Research

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Shan Dongri

Center for Automotive Research

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Mohammed A. Omar

Masdar Institute of Science and Technology

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Abdelraoof Mayyas

Center for Automotive Research

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Abedalroof Mayyas

Center for Automotive Research

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