This article is based on a survey conducted on the top management’s perceptions and practices of critical success factors (CSFs) with respect to benchmarking implementation in Malaysian automotive components manufacturing companies. The main objective of this paper is to provide empirical evidence on top management’s practices of CSFs for implementing benchmarking among eight different companies categories, comprising of all respondents; quality certified; non-quality certified; Small and Medium Enterprise (SME); large; 100% locally owned; 100% foreign owned; and joint venture companies. To achieve this objective, the authors developed a questionnaire comprising of nine major CSFs and 49 elements, checked for reliability and validity by experts and practitioners. The analyses from 68 respondent companies showed the CSFs for benchmarking implementation were practiced at low to moderate level. On overall, there is a significant difference between the CSFs perceived level of importance and extent of practice by the respondent companies. Pair samples t-test results showed there is a significant difference between the level of importance and practices in all CSFs in quality certified, large, SME, 100% local and joint venture companies. The survey results also showed no significant difference in terms of level of importance and practice of all the CSFs in 100% foreign companies. In non-quality certified companies there is no significant difference in terms of level of importance and practice except for four CSFs. Finally, the paper concludes with some suggestions on the steps on how to improve the CSFs adoption rate and thus enhanced business competitiveness and excellence in Malaysian automotive manufacturing companies.

One of the most crucial challenges in lithography is achieving rapid and accurate alignment under a wide variety of conditions brought about by different processing steps. Processing steps may change the nature of alignment mark. Either the mark is deformed or the mark profile is asymmetric, a change in the nature of alignment mark may affect its generated signal behavior. Hence, the objective of this work is to choose a robust alignment mark so that even though there is an extreme process variation, the alignment process still produced reliable alignment accuracy. Unreliable alignment accuracy increased the rework rate, lowered the yield, and eventually may lead to device failure. In this work, several type of alignment mark was evaluated over a range of process variation. From this set of evaluated alignment marks, B2 is the most robust alignment mark within the specified process variation.

Different methods for modelling nonlinear system are investigated in this paper. Neural network (NN) techniques, multiple linear regression (MLR) and principal component regression (PCR) are applied to two nonlinear systems which are sine function and distillation column. For the sake of studying these three distinctive methods, all the data taken is from simulation which is then be seperated into training, testing and validation. Among those different approaches, the NN approach based on the nonlinear prediction technique gives a very good performance in for both case studies. It is also shown that MLR model suffers from glitches due to the collinearity of the input variables whereas PCR model shows good result in the prediction output. As a conclusion, the NN methods exhibit a consistent result with least sum square error (SSE) on the unseen data compared to the other two technique.

The main objective of this paper is to conceptually design the stack of Proton Electrolyte Membrane (PEM) fuel cell taking into consideration the voltage for a single cell, number of cells required, current density, power density and finally the current flow in the stack. A part from that, effect of important parameters such as temperature, pressure, voltage, current density and distance gas flow channel were presented in this paper. From the result, it was observed that 32 numbers of cells (0.7 V for each single cell) with a current flow of 260A were required for power output of 5 kW after considering the parasitic load of 8% from the total power output. The active area of the single cell was found to be about 250 cm2. The current density and power density were determined as 900 mA/cm2 and 660 mW/cm2, respectively. The cell efficiency is expected about 65%. Finally, the electricity cost in this study was calculated as RM 0.152/ kWh-1.

Hospitals provide the same type of service, but not all hospital provides the same quality. No one knows this better than patients. A case study to evaluate the health service quality was conducted in two clinics in Hospital UKM. To measure patients’ satisfaction with HUKM, the research technique called Fuzzy Logic Controller (FLC) was used. This technique gives measurement not in a crisp value but in an interval value. It uses fairly satisfy, rather satisfy than only satisfy and not satisfy. Each of these linguistic was given degree of membership by FLC to show how far it influences the customer satisfaction. Furthermore, FLC is able to compare expectations with perceptions of service received across six dimensions of service quality, namely tangibles, reliability, responsive, assurance, empathy and accessibility and affordability. This study was aimed to determine the reliability and to measure by using the gap analysis into ratio analysis. The results of the analysis show that the instrument is reliable which may as a valuable input for engineering management especially related to their engineering planning. The study also revealed that all service dimensions were unable to meet expectation of the customers. Therefore quality improvement and enhancement effort are recommended be implemented in HUKM.

Hydrogen-rich reformate produced by reforming primary fuels in the fuel processor system, contains significant amount of CO, which is the main culprit for the performance reduction in Proton Electrolyte Membrane Fuel Cell (PEMFC) performance by CO poisoning on the Platinum catalyst at anode. Thus the reformate from the fuel processor system must be purified by removing CO before being used in the PEMFC stack. The objective of the present study is to design conceptually a CO removal system consisting of a mesoporous tubular ceramic membrane (TCM) and a pressure swing adsorber (PSA) in series. The first section of the present study describes the design of the TCM and the second section describes the design of the PSA. The designs for both units are based on new shortcut design methods developed by the authors. The effect of some important parameters such as the temperature, pressure and membrane area on the degree of separation is investigated. It is found that theoretically, the TCM-PSA system capable of reducing the CO concentration from 2000 ppm to less than 10 ppm.

Iris recognition, a relatively new biometric technology, possesses great advantages, such as variability, stability and security, making it to be the most promising method for high security environments. A novel hardware-based iris recognition system is proposed in this paper, which consists of two main parts: image processing and recognition. Image processing involves histogram stress, thresholding, cropping, transformation and normalizing that is performed by using Matlab. Multilayer perceptron architecture with backpropagation algorithm is employed to recognize iris pattern. The entire architecture was modeled using VHDL, a hardware description language. The approach obtained a recognition accuracy of 98.5%. The design was successfully implemented, tested and validated on Altera Mercury EP1M120F484C5 FPGA utilizing 4157 logic cells and achieved a maximum frequency of 121.87 MHz. This novel and efficient method in hardware, based on FPGA technology showed improved performance over existing approaches for iris recognition.

This paper describes the development of logging and transferring data system using a single frequency GPS receiver. GPS is a constellation of 24 satellites launced by the United States to broadcast navigation information such speed, time and location of a receiver. A software has been developed to collect dan save data using a filing format and to transfer files automatically to a local area via a modem communication in which it is also tested using a RS232 serial communication link. The software can receive and save files with error correction method. It also has a capability to transmit the navigation information in every three minutes from a GPS receiver which is located in a far or remote area to a local area. So that the informations can be used for geodesy and geoinformation purposes, and also for scientific research such as radio propagation and, ionospheric total electron content measurement and others. The existence of this datalogging system which can also be displayed on a website, helps users to easily obtain the latest informations with high reliability.

Computer-based instructional materials offer great potential to enhance learning effectiveness including engineering discipline. Using readily available development software, sophisticated graphics, animations and videos can be created to present engineering topics in ways that are not possible within the confines of the traditional textbook and lecture format. This article presents an instructional media (package) which is developed to assist in teaching of processing of plastics course. This example includes lecture supplements, colorful and animated pictures, interactive example problems, videos and interactive computer applications. Using animations, videos, graphics and interactivity, the instructional media is designed to engage and stimulate students, to effectively explain and illustrate course topics and to increase student involvement in the class.

Vehicle license plat recognition has been a much studied research area in many countries. Due to the different types of license plates being used, the requirement of an automatic license plate recognition system is rather different for each country. In this paper, an automatic license plate recognition system is proposed for Malaysian vehicles with standard license plates based on image processing, feature extraction and neural networks. The image processing library is developed in-house which we referred to as Vision System Development Platform (VSDP). The Kirsch Edge feature extraction technique is used to extract features from the license plates characters which are then used as inputs to the neural networks classifier. The neutral network model is the standard multi-layered perception trained using the back propagation algorithm. The prototyped system has an accuracy of about 91%, however, suggestions to further improve the system are discussed in this paper based on the analysis of the error.

The energy absorption capability of a composite material is critical to developing improved human safety in automotive compartment during vehicular collisions. Experimental investigation was conducted to study the crushing effect of conical coir fibre reinforced composites under quasi-static loading. Three semi-vertex angles and fibre loadings were selected in fabricating the conical composites. Load/displacement curves and deformation histories of cones under compressive loadings were presented and discussed. The results showed that both semi-vertex angles and fibre loadings played an important role in determining the energy absorption capability and controlling factor in changing the failure modes. It is important collapse resulted higher energy absorption performance.

Semi-solid metal processing, also known as thixoforming is a forming process that shapes metal components in their semisolid state. For this to be possible, it is preferable for an alloy to have as appreciable melting range and before forming the microstructure must consist of solid metal spheroids in a liquid matrix. There is strong interest in thixoforming high temperature materials such as tool steels. The established solid state processing approach to obtaining a non-dendritic microstructure is through recrystalliSation process of RAR (Recrystallisation and Partial Melting) and SIMA (Strain, Induced Melt Activated). The first involves cold or warm working below the recrystallisation temperature followed by heating above the solidus of the materials, while the latter involves hot working between recrystallisation and solidus temperature, followed by cold working so as to produce a critical level of strain, before the material is reheated above the solidus. Here, a commercially produced M2 toll steel alloy, i.e. being hot worked, tempered and annealed, was subjected to a direct partial remelting experiment in a protective atmosphere from a room temperature with no prior additional cold working/ The microstructure revealed equiaxed solid grains (in liquid matrix) of average sizes between 29 and 31 µm when reheated to above the solidus of 1320-1360^oC. Subsequent thixoforming of the material in the form of a slug of 36 mm diameter and 46 mm height into a simple finger of 66 mm long, 43 mm wide and 7 mm thick at 1360^oC showed that the slurry flowed thixotropically under very flow load of typically less than about 2 Kn.

Augmented two level structure without information exchange between local control unit is expended from three level structure with input-output information feedback proven to be real optimum. The advantage of this control structure is no real process output derivatives by perturbation needed. Thus control problems with undifferentiable inequally constraint G (c,y) with respect to output, y, can be easily solved. This research paper widens the usage of the control algorithms by using augmented Lagrangian function. This control structure is having two optomization loops which are external optimization loop and internal optimization loop. The external optimization loop determines optimum value of Lagrange multiplier, λ using Powell conjugate method without any derivation. The internal optimization loop determines optimum control set point, c for certain given value of λ using augmented Lagrangian method. Simulation results show that appropriate combination of the squire term multipliers, ρ and update multiplier, ԑ range from 0.9 to 1.2 is suitable for the structures. However big value of ρ is needed to solve non-cconvex problem.

Augmented two level technique is an extension of the previous two level method which could widen the application of the algorithm to non-convex problems while at the same time improving the convergent of certain convex problems. From the view point of algorithm’s structure, the augmented two level technique may be considered as an equivalent version of the modified two step method, except the difference in calculating the Lagrange multipliers, λ, without using any derivation on process output with respect to the set point. Even though the off-line computer calculation cost may increase, the advantage of this method is the Lagrange multipliers, λ, are determined by supremal level using Powell Conjugate Direction method without disturbing the process. Thus the augmented two level technique can be applied onto systems contaminated by noise and control problems with undifferentiable inequality constraints G (c,y) respect to y. Whereas modified two step method will encounter difficulties due to the need of GY (c,y) to determine the Lagrange multipliers, λ. Simulation results show that appropriate combination value between Lagrange multipliers for square terms, ρ, and update coefficient ԑ, can solve non-convex problem and reduce optimal set points changes significantly for certain convex problems. Update coefficient, ԑ between 0.9 and 1.5 is appropriate for most studied cases.

The augmented three level technique is developed with the aim to extend the application of the three level structures without information exchange between local control units to a non-linear problem. The algorithm is a hierarchical in structure and the solution obtained is the control set-point to satisfy the Kuhn-Tucker necessary condition via integration of the model based optimization with model parameter estimation. The algorithm structure such a manner that it utilizes efficiently the available process mathematical and real process measurement information. The advantages it has over the same class of hierarchical control algorithms are that it does not require real process derivative information and there is no information exchange between local control units. These control algorithms are solved in two stages which are internal and external. Internal optimization consists of two levels which are Price coordinator level and constrained optimization level while Powell conjugate direction method is used in the external optimization to calculate Lagrange coefficient, λ. This control structures have been tested using four simulation problems. Simulation results show that the augmented technique converges faster thus reduce the set point changes than normal technique method at chosen values of Lagrange multiplier, ρ and update coefficient, ԑ for convex problems. ԑ range from 1.0 to 1.2 is suitable for the structures. However augmented Lagrangian function can only solve non-convex problem by using of ρ. Generally, control structure with input-output feedback has less control set points changes and converge faster compared with control structure with output feedback only.