Mohammed Omar

Review of Microcrack Detection Techniques for Silicon Solar Cells

Microcracks at the device level in bulk solar cells are the current subject of substantial research by the photovoltaic (PV) industry. This review paper addresses nondestructive testing techniques that are used to detect microfacial and subfacial cracks. In this paper, we mainly focused on mono- and polycrystalline silicon PV devices and the root causes of the cracks in solar cells are described. We have categorized these cracks based on size and location in the wafer. The impact of the microcracks on electrical and mechanical performance of silicon solar cells is reviewed. For the first time, we have used the multi-attribute decision-making method to evaluate the different inspection tools that are available on the market. The decision-making tool is based on the analytical hierarchy process and our approach enables the ranking of the inspection tools for PV production stages, which have conflicting objectives and multi-attribute constraints.

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

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.

Robotic automotive paint curing using thermal signature feedback

Purpose – The purpose of this paper is to present a new closed‐loop radiative robotic paint curing process that could replace less efficient and bulky convection‐based paint curing processes in automotive manufacturing.Design/methodology/approach – The proposed robotic paint curing processes uses an Ultraviolet LED panel for a heat source, an infra‐red camera for non‐contact thermal signature feedback of cure level, and a robot control strategy that incorporates the cure‐level information in an inverse dynamics control of the robotic manipulator. To demonstrate the advantage of the closed‐loop process in improving cure uniformity, detailed models and discussions of the irradiation process, the robotics and the control strategy are presented.Findings – A simulation‐based comparison of the closed‐loop robotic curing with the open‐loop robotic curing clearly shows the benefits of using thermal signature feedback in improving cure level uniformity.Originality/value – This is a new approach proposed to exploit...

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

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.

Pedestrian tracking routine for passive automotive night vision systems

Purpose – This paper aims to present a new approach to implement a pedestrian tracking algorithm for a passive automotive night vision application.Design/methodology/approach – First, the basic information of passive and active night vision systems is presented, with implementation methods adopted in previous work. The proposed thermal‐image processing is a combination of seed detection, boundary detection and seed growth computations, based on a temperature thresholding scheme.Findings – The processing routine performance is assessed when implemented to a continuous sequence of thermal acquisitions, from a commercial automotive night vision module. Experimental results show good tracking performance for both pedestrians and passing vehicles.Research limitations/implications – A strategy of multi‐seed growth, directional seed growth and image fusion is proposed to improve the current tracking algorithm.Originality/value – New thermal image processing routines are applied to commercial, automotive night vi...

Sustainable lightweight vehicle design: a case study of eco-material selection for body-in-white

Sustainable product development when applied to an automotive structure requires a balanced approach towards technological, economic and ecological aspects. Current paper investigates the main input parameters and the different measures for the vehicular structures design for sustainability (DFS) in general and its material selection for sustainable lightweight design in particular. This study proposes a set of metrics for material selection that takes all sustainability aspects into consideration. These metrics include: products’ environmental impact, functionality and manufacturability, in addition to the economic and societal factors. The manuscript then proceeds to show the material selection methodology and its limitations.

Organizational learning in automotive manufacturing: a strategic choice

This manuscript surveys the changes that affected the automotive industry in recent years with the evolution of industrial focus on globalization forces. Further, it proposes organizational learning as a viable strategy for the automotive industry, to effectively embrace and be agile to the continually changing environment. First, the manuscript characterizes and surveys the impact of globalization (global markets and competitors) on the current automotive industry in three categories: challenges in new markets, challenges in mature markets, and challenges in customer demands and hence sales trends. Second, the traditional strategies implemented in the automobile industry such as the “Company” and “Plant” specific production systems are presented. Lastly, the manuscript supports its proposal through case examples from Original Equipment Manufacturers the Rover group and Volvo AB.

Pixel-Level Fusion for Infrared and Visible Acquisitions

This article presents a unique combined routine to fuse Long Wave Infrared (7.5–13 micron) with visible (0.38–0.78 micron) acquisitions, and to track pedestrians and road information in night or low light driving scenarios. Three fusion levels are presented and discussed: pixel-level, feature-level and decision-level. A pixel-level fusion is then used, through a novel combination of an adaptive weighting algorithm for un-saturated data points, and a PCA statistics for saturated pixels. The registration is done at the hardware level with Gaussian smoothing, while the smoothed histograms provide initial threshold values. The proposed routine is then applied for different night-time driving scenarios, further compared with the tracking results for non-fused thermal imagery from a commercial night-vision module. The fused imagery coupled with the proposed pre and post-processing provide complete detection of reflective and emitting objects with better shape retrieval and orientation prediction, computed and judged through objects morphology. The result of current work is an enhanced passive display for: passing vehicles with glare, pedestrians and non-emitting road features, with its motion predicted.

Cure-feature based online trajectory generation in a robotic paint curing system

Ultra-violate (UV) radiation-based robotic paint curing systems have great potential in improving energy efficiency and reducing the operating cost of the traditional oven-based units currently used in the automotive industry. This paper presents and compares two strategies for online trajectory generation in the control of such a robotic paint curing system. The system proposed here incorporates thermal vision feedback from an infra-red (IR) camera to ensure cure quality in the face of changing surface geometries and irradiance characteristics. To compare the two proposed strategies a computer simulation of the robotic curing system is developed. The results indicate that both strategies give comparable cure quality in the face of uneven target characteristics.

Eco-material selection assisted with decision-making tools, guided by product’s attributes; functionality and manufacturability

This study proposes an eco-material selection approach assisted with decision-making tools namely; analytical hierarchy process (AHP) and quality function deployment (QFD). The study derives the material selection indices for an automobile’s structural and closure panels based on each panel; manufacturability, functionality requirements (load bearing characteristics). Additionally, two constraints are mainly defined; the cost (economic aspect) and the environmental impact (using embodied energy and recyclability). The decision-making tools prioritise the derived metrics based on current original equipment manufacturers (OEMs) perspective. The developed approach is then applied to rank different lightweight material options for vehicular panels. This study has the potential to present a balanced scheme between technological, economic and ecological aspects of automotive body-in-white (BIW) design, and to be implemented in a life-cycle assessment (LCA) study.