J. Cent. South Univ. Technol. (2010) 17: 244-256

DOI: 10.1007/s11771-010-0038-y                                                                                                                  

Material selection of polymeric composite automotive bumper beam using analytical hierarchy process

A. HAMBALI¹, S. M. SAPUAN¹, N. ISMAIL¹, Y. NUKMAN²

1. Department of Mechanical and Manufacturing Engineering, Universiti Putra Malaysia,

43400 UPM Serdang, Selangor, Malaysia;

2. Department of Engineering Design and Manufacture, University of Malaya,

50603 Kuala Lumpur, Malaysia

? Central South University Press and Springer-Verlag Berlin Heidelberg 2010

                                                                                                

Abstract: Selection of materials, as an area of design research, has been under considerable interest over the years. Materials selection is one of the most important activities in the product development process. Inappropriate decision of materials can cause the product to be reproduced or remanufactured. To avoid this circumstance, one of the useful tools that can be employed in determining the most appropriate material is analytical hierarchy process (AHP). To illustrate the application of AHP, six different types of composite materials were considered. The most appropriate one for suitability of use in manufacturing automotive bumper beam was determined by considering eight main selection factors and 12 sub-factors. The AHP analysis reveals that the glass fibre epoxy is the most appropriate material because it has the highest value (25.7%, mass fraction) compared with other materials. The final material is obtained by performing six different scenarios of the sensitivity analysis. It is proved that glass fibre epoxy is the most optimum decision.

Key words: composite; polymer matrix; bumper beam; analytical hierarchy process

                                                                                                            

1 Introduction

The importance of materials selection in the product development process has been well recognized. To develop a systematic method for selecting the best material is not an easy task because the best material is determined by a number of factors that influence the selection process. There are two main reasons why materials selection is required:  firstly, to design an existing product for better performance, lower cost, increasing reliability and reduced weight and secondly, to select a material for a new product [1-2]. Materials selection is a main product design consideration because product’s overall performance is mainly affected and determined by materials selection process [3]^.

There are very limited reports on materials selection for the composite automotive bumper beam. However, several papers discussed the selection of a material for automotive bumper beam. For example, SAPUAN et al [4] employed weighted objective method for the selection of materials for the bumper system. HOSSEINZADEH et al [5] studied several composite materials and conventional materials for automotive bumper beam and characterized them based on the cost, production and weight by impact modelling using LS-DYNA ANSYS 5.7. It is shown that sheet moulding compound (SMC) is best material for bumper beam. SUDDIN et al [6] described the development of the knowledge based system (KBS) for materials selection in bumper beam design. The KBS is an expert system approach to selecting the most suitable material by defining constraint values into the system.

However, the above-mentioned methods do not provide easy ways to assist material engineers to determine the most appropriate material. One of the useful tools that provide a sequence way of materials selection process is analytical hierarchy process (AHP). AHP is a basic approach to decision making, which is designed to cope with both the rational and the intuitive to select the best from a number of alternatives evaluated with respect to several criteria [7]. Decision support system (DSS) resource defines AHP as an approach to decision making that involves structuring multiple choice criteria into a hierarchy, assessing the relative importance of these criteria, comparing alternatives for each criterion, and determining an overall ranking of the alternatives [8].

Generally, implementing AHP is based on experience and knowledge of the experts or users to determine the factors affecting the decision process [9-10]. According to Refs.[11-12], AHP is an intuitive method for formulating and analyzing decisions. The advantages of using AHP include achieving higher quality product and shorter product development process. AHP helps to capture both subjective and objective evaluation measures, thus providing a useful mechanism for checking the consistency of the evaluation measures and alternatives suggested by the team, and reducing bias in decision-making. AHP allows organizations to minimize common problems of decision-making process, such as lack of focus, planning, participation or ownership, which ultimately are costly distractions that can prevent teams from making the right choice [8].

AHP has been widely used to solve multi-criteria decision making in both academic research and in industrial practice. It has been implemented in almost all the applications related to decision-making and currently predominantly used in the theme of selection and evaluation especially in the area of engineering, personal and social categories [13]. Although, AHP has been widely used in solving decision making problems, it is still very limited in making right decision in field of materials selection process. HO [9] reviewed international journals related to application of AHP from 1997 to 2006 and found that AHP can be implemented in a wide variety of fields. However, there are a few studies on the application of AHP related to the materials selection for the composite automotive components. Only one paper discussed the use of AHP in material selection process [10].

The literature reviews indicate the above researchers have not addressed the use of AHP to determine the most appropriate material for the composite automotive bumper beam. The aim of this work is to assist designers to evaluate and determine the most optimum material by implementing AHP.

2 Selection of materials at conceptual design stage

The proposed framework for the selection materials process during concept selection at the conceptual design stage is shown in Fig.1. The selection method helps the designers to determine the best material in concept selection at the conceptual design stage. A fundamental issue in polymeric composite automotive components particularly related to the selection of materials is a main focus. Thus, this work is only addressed in terms of selecting the best material in the context of concurrent engineering environment. Then, AHP, as a decision support tool, is linked to the framework in order to determine the most appropriate material for the automotive components. After the best material is determined or called material selected, various scenarios of the sensitivity analysis are performed to test the stability of the priority ranking and to increase the confidence in the choice of material in order to carry out the final decision.

3 Selection of materials for polymeric composite bumper beam

The use of composite materials has been rapidly increased in automotive industry. Automotive industry faces greater market pressure to develop high quality products more quickly at lower cost. To determine the right material is a crucial decision in the automotive industry. In recent years, the use of composites has been greatly focused on automotive components such as automotive bumper system. The bumper system is generally recognized as being composed of four basic components of bumper fascia, energy absorber, bumper beam and bumper stay, as depicted in Fig.2. One of the most important components of bumper system is the bumper beam. It plays an important role of absorbing the bulk of energy and provides protection to the rest of the vehicle [14-15]. Therefore, it is important to determine the right material for the automotive bumper beam.

3.1 Various polymeric-based composite automotive bumper beams

Composite bumper beams become more common due to the increased number of low volume vehicles and greater emphasis toward weight reduction. As the function of a bumper beam is to absorb kinetic energy during a collision, the use of composite materials to replace steel or aluminium was reported in the literature. There are many attempts and successful application of polymeric-based composite in automotive bumper beam. MOHAN [17] discussed the use of structural reinforced injection moulding (SRIM) composite in an automobile bumper beam. The material used was glass fibre reinforced polypropylene. The tooling cost was lower than that of metal processes because of the low moulding pressure used. CLARK et al [18] explained their extensive work on bumper beams using glass fibre reinforced plastics to study the stress contour in the component. Three-dimensional models were developed and the analysis was performed using ABAQUS software. The material selected was 40% (mass fraction) glass fibre reinforced polypropylene. CHEON et al [19] developed a composite bumper beam for a passenger car using glass fibre epoxy composite materials with the exception of the elbow section. The elbow section was made of carbon fibre epoxy composite materials. From the static bending test of the prototype composite bumper, it was found that the mass of the composite bumper beam was 30% lighter than that of the steel bumper beam without sacrificing the static bending strength.

Fig.1 Framework of selection process at conceptual stage in concurrent engineering environment

Fig.2 Diagram of bumper systems [16]

KUMAR and JOHNSTON [20] studied and compared the performance of C- and I-section of bumper beam using a variety of compression-moldables, and the material employed was glass-mat thermoplastic (GMT) composite. GILLIARD et al [21] developed the I-section beam with 40% (mass fraction) chopped fibre glass GMT. They found that the I-section bumper design has improved static load and dynamic impact performance by using lower cost mineral filled/chopped fibre glass GMT. According to Ref.[22], front and rear bumper beams of some general motors models are generally made of 60% (mass fraction) glass fibre vinylester SMC, reinforced with a newly developed chopped and continuous strand glass fibre, giving strength in all directions. MOINAR [23] employed a composite material, namely glass fibre embedded with a thermosetting isopolyester resin matrix, to produce the composite bumper beam. KELMAN and NELSON [24] used composite materials consisting of fibre glass perform and two-component urethane based resin polyol and isocyanate to manufacture the composite bumper beam.

HOSSEINZADEH et al [5] investigated and compared various polymeric-based composites such as SMC and GMT, and conventional materials such as steel and aluminium in terms of deflection, stress distribution and kinetic energy transfer when subjected to low- velocity impacts for automotive bumper beam. The results show that SMC composite is the best material for automotive bumper beam due to good impact behaviour, easier production and lower cost. ROBIAH et al [25] investigated the best condition of compounding parameter and mechanical properties of discontinuous carbon fibre reinforced polypropylene for the application of car bumper beam. It was found that, the additional 10% (mass fraction) of chopped carbon fibre gives a significant increase in the tensile strength properties. ANONYMOUS [26] used polyester fiber weave reinforced GMT materials for bumper beams due to its low stiffness and excellent energy absorption properties.

3.2 Factors consideration in materials selection for polymeric composite automotive bumper beam

The selection of the best material for the polymeric composite automotive bumper beam depends upon the following factors.

3.2.1 Energy absorption (EA)

The most important consideration in selecting the most appropriate material for polymeric composite automotive bumper beam is the ability of the material to absorb enough kinetic energy. Bumper beam is a main structure for absorbing the energy of collisions. The property of material that shows the ability of the material to absorb energy is impact toughness (ITH) [27]. ITH is defined as a measure of the ability of material to absorb energy during impact.

3.2.2 Performance (PR)

Performance is defined as the ability of a bumper beam to stay intact or rigid at high-speed impact and prevent damage to the bodywork in minor impacts. Two factors of material properties should be considered, namely, flexural strength (FS) and flexural modulus (FM). FS is defined as the ability of materials to withstand failure due to bending. FM is also known as stiffness. It is defined as the capability of materials to resist against bending or deflection.

3.2.3 Cost (CS)

Cost plays a very significant role in determining the best material at the early stage of product development process. In this work, raw material cost (RMC) is considered as a main factor for determining the most appropriate material. RMC is defined as the cost of raw material that will be used in fabricating the product.

3.2.4 Weight (W)

One of the primary reasons for material engineers to investigate composite materials for a specific vehicle application is weight reduction. Thus, selecting a material that enables to reduce the weight of vehicle is very important. The density of a material (DS) is defined as its mass per unit volume. Low density of material can contribute to weight reduction.

3.2.5 Service condition (SC)

As bumper beam is exposed to weather, the candidate materials under consideration are expected to satisfy the resistance to weather conditions. Thus, service conditions during use are also important and should also be taken into account in materials selection. Two material properties that need to be considered are resistance to corrosion (RC) and water absorption (WA). RC is defined as the ability of a material to resist corrosion, and WA is defined as the amount of water absorbed by a material.

3.2.6 Manufacturing process (MP)

MP is also needed to be considered when determining the best material at the early stage of the product development process. Shape (SH) is defined as the ability of a material to be shaped into the finished product. As the bumper beam is in a very complex shape, whether the materials to be formed or shaped according to design requirements need to be considered.

3.2.7 Environment consideration (EC)

Due to increasing environmental demands, especially on dealing with products end of life phase, it is important to select the materials easily to be recycled and treated for a better environment. Recycling (RY) is defined as the ability of a material to be recycled at the end of life phase. Disposal (DP) is defined as the ability of a material to be disposed of in an environmental way such as landfill and incineration.

3.2.8 Availability of material (AVM)

AVM can be categorized into two factors, namely availability of raw material (AM) and availability of materials information (AI). The availability of AM means an existence of the raw material in the place of manufacturing; and the availability of AI is defined as the material information readily available to designers during the design process.

3.3 AHP steps at concept selection stage

The AHP developed by SAATY [28] is a powerful and flexible weighted scoring decision making process that helps people to set priorities and make the best decision when both qualitative and quantitative aspects of a decision need to be considered. Generally, AHP is based on the following three principles: decomposition, comparative judgment, and synthesis of priorities [28-30]. These principles can be elaborated by structuring them in a more encompassing nine-step process, as shown in Fig.3.

Fig.3 AHP principle and its steps

Step 1: Define problem. The first step in using AHP is to identify the problem and determine its goal. The problem should be clearly stated and decision makers have to identify factors or criteria affecting the selection process. According to Ref.[31], the most creative and crucial part of the method is the determination of factors influencing the selection process.

Step 2: Develop hierarchical structure. The most influential part of decision making is to construct the decision as a hierarchy. Thus, after determining the problem, goal, criteria, sub-criteria and decision options, it is required for decision makers to form a complicated problem in a hierarchical structure or a model viewing the relationships among the overall goal, criteria, sub-criteria and alternatives, as shown in Fig.4.

Fig.4 Four-level of hierarchy model

Generally, the structure of the hierarchy comprises four basic levels as follows.

(1) Level 1: Goal. The objective or the overall goal of the decision is presented at the top level of the hierarchy (level 1). The goal represents the problem to be solved, for instance, to select the best material for the composite automotive bumper beam.

(2) Level 2: Criteria. The second level (level 2) represents the main criteria or major factors that affect the selection process. The criteria identified by decision makers rely on the type of problems that contribute to the objective.

(3) Levels 3: Sub-criteria. The sub-criteria are placed at the third level (level 3) of the hierarchy, which allows more detailed in the AHP model. By adding sub-criteria or more specific criteria of the problem, the process of selection can be performed more accurately for determining the best option.

(4) Level 4: Decision alternatives. Finally, the decision alternatives or options are presented at the lowest level (level 4) of the hierarchy.

Step 3: Construct pairwise comparison matrix. One of the major strengths of AHP is the use of pairwise comparison to derive accurate ratio scale priorities. Pairwise comparisons are fundamental to the AHP methodology [32]. Then, a pairwise comparison matrix (size n×n) is constructed for the lower levels with one matrix in the level immediately above. The pairwise comparisons generate a matrix of relative rankings for each level of the hierarchy. The number of matrices depends on the number of elements at each level. The order of the matrix at each level depends on the number of elements at the lower level that it links to.

Step 4: Perform judgement of pairwise comparison. Pairwise comparison begins with comparing the relative importance of two selected items. There are n×(n-1) judgments required to develop the set of matrices in step 3. The decision makers have to compare or judge each element by using the relative scale pairwise comparison as shown in Table 1. The judgements are decided based on the decision makers’ or users’ experience and knowledge. The scale used for comparisons in AHP enables the decision maker to incorporate experience and knowledge intuitively.

Table 1 Scale for pairwise comparisons [33]

To do pairwise comparison, for instance (Table 2), if C-1 is strongly more important than C-3, then a=5. Reciprocals are automatically assigned to each pairwise comparison.

Step 5: Synthesize pairwise comparison. Hierarchical synthesis is used to weight the eigenvector entries by the weights of the criteria and the sum is taken as overall weighted eigenvector entries corresponding to those in the next lower level of the hierarchy. There are a number of methods that can be used to calculate eigenvector or vectors of priorities, and one of them is the average of normalized column (ANC) method [34]. ANC is to divide the elements or scale points of each column by the sum of the columns, to add the element in each resulting row and divide this sum by the number of elements in the row (n). This is a process of averaging over the normalized columns. In mathematical form, the eigenvector or vector of priorities can be calculated as

 i, j=1, 2, …, n                             (1)

where  W is the eigenvector (priority vector); a_ij is the relative scale, i.e., 1, 3, 5, …; and n is the number of criteria.

Table 2 Performing judgement of pairwise comparison of criteria with respect to goal

Step 6: Perform consistency analysis. As the comparisons are carried out through personal or subjective judgments, some degree of inconsistency may occur. To guar­antee that the judgments are consistent, a process called consistency verification, which is regarded as one of the most advantages of the AHP, is incorporated in order to measure the degree of consistency among the pairwise comparisons by computing the consistency ratio [15]. The consistency is determined by the consistency ratio (CR), the ratio of consistency index (CI) to random index (RI) for the same order matrices. To calculate CR, three steps have to be implemented as follows.

(1) Calculate eigenvalue l_max

                         (2)

(2) Calculate CI

CI=(l_max-n)/(n-1)                                (3)

where n is the matrix size or criterion.

(3) Calculate CR

CR can be calculated using the formula

CR=CI/RI                                            (4)

where RI is the random index of the same order matrix (Table 3).

Table 3 Random index (RI) of analytic hierarchy process (AHP) [33]

CR is acceptable if it does not exceed 0.10. If it is more, the judgment matrix is inconsistent. To obtain a consistent matrix, judgments should be reviewed and improved by repeating step 4 through step 6.

Step 7: Repeat steps 3-6. Steps 3-6 are performed for all levels in the hierarchy.

Step 8: Develop overall priority ranking. The purpose of developing overall priority is to determine the best alternative arrangement. After the consistency calculation for all levels is completed, further calculation of the overall priority vector to select the best design concept must be performed.

Step 9: Select the best decision. Select the best decision option according to the results carried out in step 8.

3.4 Determination of the best material during concept selection

In order to determine the most suitable material, AHP steps have to be employed by utilizing expert choice software. The software developed by FORMAN et al [35] is a multi-attribute decision support software tool based on the AHP methodology, and is also easy to use and understand, thus providing visual representations of overall ranking on a computer screen. The steps of using AHP through utilizing expert choice 11 software are as follows.

Step 1: Define problem. A case study used in this work is concerned with the problem to determine the best material for the automotive bumper beam. After implementing several design steps in product develop- ment process, six materials are considered (Table 4).

Table 4 Materials used in automotive bumper beam design

Step 2: Develop hierarchy model for material selection. In this step, a hierarchy model for structuring material decisions is developed. The factors that influence the selection process are translated to the hierarchy structure, as shown in Fig.5. A four-level hierarchy decision process (see Fig.5) is described as follows.

Fig.5 Hierarchical structure of decision problem in selecting the best material for polymeric composite automotive bumper beam

 (1) Level 1. Initially, the objective or the overall goal of the decision is presented at the top level of hierarchy. Specifically, the overall goal of this case study is to select the best material for the polymeric composite automotive bumper beam.

(2) Level 2. The second level represents the main criteria that can be classified into eight aspects: EA, PR, CS, WE, SC, MP, environment consideration (EC) and availability (AV).

(3) Level 3. The sub-criteria are represented at the third level of hierarchy. Impact toughness (ITH) is a sub-criterion that affects the energy absorption. There are two sub-criteria that affect the performance criterion: FS and FMF. RMC, low density (LD), RC and WA, SH, recycle (RY) and disposal (DP), and AM and AI, are sub-criteria that affect the cost, weight, service condition, manufacturing process, environment considerations and availability, respectively.

(4) Level 4. Finally, at the lowest level of the hierarchy, the alternative materials of the automotive bumper beam are identified, which are decision options.

Step 3: Perform judgements of pairwise comparison matrix. Pairwise comparison begins with comparing the relative importance of the two selected items by using pairwise numerical comparisons provided by expert choice 11 software or relative scale pairwise comparison, as shown in Table 1. Table 5 shows the data used to do pairwise comparison, which are taken from various sources [36-42]. The judgements or assigned values (see Fig.6) are based on the authors’ experience and knowledge.

Table 5 Data used for determining the most appropriate material for polymeric based automotive bumper beam

.

Fig.6 Pairwise comparisons of main criteria with respect to goal

Step 4: Synthesize pairwise comparison. After pairwise comparison process is finished, the priority vectors and the consistency ratio must be analyzed. The results of priority vectors and consistency test for the main criteria with respect to the goal are shown in Fig.7. EA contributes the highest to the goal with a priority vector of 0.363 while the availability (AV) contributes the lowest with a priority vector of 0.022 only. As the value of consistency ratio (CR=0.05) is less than 0.1, the judgements are acceptable. If CR＞0.1, the judgment matrix is inconsistent. To obtain a consistent matrix, judgements should be reviewed and improved.

Fig.7 Priority vectors and consistency test for main criteria with respect to goal (CR=0.05 with 0 missing judgment)

Step 5: Perform steps 3-4 for all levels in the hierarchy for all pairwise comparisons. The results shown in Fig.8 represent the priority vectors for criteria and sub-criteria. The judgements for all levels are acceptable due to the fact that CR is less than 0.1.

Fig.8 All priority vectors for criteria and sub-criteria

Step 6: Select the best material. AHP reveals that the glass fibre epoxy (M-1) will be the most appropriate material for the polymeric composite automotive bumper beam if all criteria and sub-criteria are considered. Fig.9 shows the glass fibre epoxy (M-1) with a weight of 0.257 as the first choice, the second choice is the carbon fibre epoxy (M-2) with a weight of 0.184, and the last choice is the glass fibre reinforced polyester (M-5) with a weight of only 0.112.

Fig.9 Results of selection with overall CR of 0.06

4 Verification of decisions through sensitivity analysis

The power of using AHP through utilizing expert choice is a sensitivity analysis. The purpose of performing the sensitivity analysis is to study the effect of different factors on deciding the best decision option. The final selection of the design concept is highly dependent on the priority vectors attached to the main criteria. Small changes in the priority vectors can therefore cause major changes of the final ranking [43]. Since these priority vectors are usually based on highly subjective judgements, the stability of the ranking under varying criteria weights has to be tested. The sensitivity analysis can be performed by increasing or decreasing the priority vector of individual criteria. Then the resulting changes of the priorities and the ranking of the alternatives can be observed. Sensitivity analysis therefore provides information on the stability of the ranking [31]. Fig.10 shows the sensitivity graph of the main criteria with respect to the goal. It not only demonstrates that the glass fibre epoxy (M-1) is the best choice, but also shows how sensitive the decision is. For this purpose, the priority vectors of the main criteria are separately altered, simulating priority vectors between 0% and 100% (note that the priority vectors of the other criteria change accordingly, reflecting the relative nature of the priority vectors).

Fig.10 Sensitivity graph of main criteria with respect to goal

For instance, if the priority vector of CS is increased by 25% (from 12.2% to 37.2%), consequently, the ranking of the priorities is changed. The glass fibre reinforced polypropylene (M-4) with a weight of 0.224 is the first choice, the second choice is the glass fibre epoxy (M-1) with a weight of 0.209, and the last choice is the carbon fibre reinforced polypropylene (M-3) with a weight of only 0.103, as shown in Fig.11.

Fig.11 Sensitivity graph of main criteria with respect to goal when cost (CS) is increased by 25% (from 12.2% to 37.2%)

The final decision was verified by simulating various scenarios and increasing or decreasing the values of the priorities vector of the main criteria (EA, PR, WE and CS). These include the following results.

(1) Priority vector of EA is increased and reduced by 20% (Figs.12(a) and (b)).

Fig.12 Sensitivity graph of main criteria with respect to goal when priority vector of EA is increased (a) and reduced (b) by 20%

(2) Priority vector of PR is increased and reduced by 20% (Figs.13(a) and (b)).

Fig.13 Sensitivity graph of main criteria with respect to goal when priority vector of PR is increased (a) and reduced (b) by 20%

(3) Priority vector of WE is increased by 25% (Fig.14).

Fig.14 Sensitivity graph of main criteria with respect to goal when priority vector of WE is increased by 25%

(4) Priority vector of CS is increased by 25% (Fig.15).

Fig.15 Sensitivity graph of main criteria with respect to goal when priority vector of CS is increased by 25%

The ranking of the early decisions (Fig.9) was compared with that obtained after performing six simulated scenarios, as depicted in Table 6.

Table 6 Rank of priorities obtained by simulating six scenarios of sensitivity analysis

If the priority vector of EA is increased and reduced by 20%, priority vector of PR is increased and reduced by 20% and priority vector of WE is increased by 25%, the results show that glass fibre epoxy (M-1) is the most appropriate material. But if the priority vector of CS is increased by 25%, as a result, the ranking of the priorities will change, and the glass fibre reinforced polypropylene (M-4) is the first choice. It can be concluded from the sensitivity analysis that the final result of the proposed AHP model is mainly based on increasing or decreasing the values of the priorities vector of the main criteria. In this work, the final decision of the most appropriate material is glass fibre epoxy after various scenarios of sensitivity analysis are conducted.

5 Conclusions

 (1) Determining the right selection of material during concept selection at the conceptual design stage is very important. The selection of a material for the automotive composite bumper is investigated. The proposed selection framework provides a systematic step to material engineers to perform material selection process in concept selection stage.

(2) The use of AHP in solving material selection at early stage of product development process is explored. The AHP methodology for determining the most appropriate material for the automotive bumper beam is also described. Several sensitivity analysis scenarios are conducted to verify the final decision. The AHP and sensitivity analysis reveals that the glass fibre epoxy is the most suitable material for automotive bumper beam as it has the highest value (25.7%) compared with other materials.

(3) Sensitivity analysis of various scenarios is conducted to verify the selection process. It is proved that glass fibre epoxy is the most appropriate composite material to be used in manufacturing automotive bumper beam. It is indicated that the AHP approach through utilizing expert choice software is a useful method to solve decision problem in selection of material in concept selection stage.

Acknowledgements

The authors would like to thank Universiti Teknikal Malaysia Melaka (UTeM) for the scholarship award to the principal author to carry out his PhD studies at Universiti Putra Malaysia. Special thank will give Universiti Putra Malaysia (UPM) for the financial support through Research University Grant Scheme 2007 (RUG 2007) with vote number 91045.

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Received date: 2009-03-27; Accepted date: 2009-09-04

Corresponding author: A. HAMBALI, Doctoral candidate; Tel: +60-3-89466318; Fax: +60-3-86567122; E-mail: hambali@utem.edu.my

(Edited by CHEN Wei-ping)