Zulkifli Mohd Nopiah

Review of supply chain performance measurement systems

In todays competitive business environment, supply chain performance is one of the most critical issues in various industries. It is argued that supply chain performance measurement is fundamental to efficient supply chain management. Over the past two decades, several frameworks and systems have been developed to meet this need. This study reviews the literature in the field of supply chain performance measurement and assembles an overview of those systems, approaches, techniques and criteria. For this purpose, 83 of 374 related articles from 1998 to 2015 were selected for final review using the Scopus and ISI databases. Findings disclose that performance measurement in supply chain contexts is still a fruitful area of research. The study also provides an overview of the performance measures employed in supply chain systems. These findings present a solid basis for future academic and practitioner work in the field of supply chain performance measurement.

Multi objective optimization of foam-filled circular tubes for quasi-static and dynamic responses

FUEL CONSUMPTION AND SAFETY ARE CURRENTLY KEY ASPECTS IN AUTO-MOBILE DESIGN. THE FOAM-FILLED THIN-WALLED ALUMINIUM TUBE REPRE-SENTS A POTENTIALLY EFFECTIVE MATERIAL FOR USE IN THE AUTOMOTIVE INDUSTRY, DUE TO ITS ENERGY ABSORPTION CAPABILITY AND LIGHT WEIGHT. MULTI-OBJECTIVE CRASHWORTHINESS DESIGN OPTIMIZATION FOR FOAM-FILLED DOUBLE CYLINDRICAL TUBES IS PRESENTED IN THIS PAPER. THE DOUBLE STRUCTURES WERE IMPACTED BY A RIGID WALL SIMULATING QUASI-STATIC AND DYNAMIC LOADINGS. THE OPTIMAL PARAMETERS UNDER CONSIDERATION WERE THE MINIMUM PEAK CRUSHING FORCE AND MAXIMUM SPECIFIC ENERGY ABSORPTION, USING THE NON-DOMINATED SORTING GENETIC ALGORITHM-II (NSGA-II) TECHNIQUE. RADIAL BASIS FUNCTIONS (RBF) AND D-OPTIMAL WERE ADOPTED TO DETERMINE THE MORE COMPLEX CRASHWORTHINESS FUNCTIONAL OBJECTIVES. THE COMPARISON WAS CARRIED OUT BY FINITE ELEMENT ANALYSIS OF THE IMPACT CRASHWORTHINESS CHARACTERISTICS IN TUBES UNDER STATIC AND DYNAMIC LOADS. FINALLY, THE OPTIMUM CRASHWORTHINESS PERFORMANCE OF EMPTY AND FOAM-FILLED DOUBLE TUBES WAS INVESTIGATED AND COMPARED TO THE TRADITIONAL SINGLE FOAM-FILLED TUBE. CONSEQUENTLY, THE RESULTS INDICATE THAT THE FOAM-FILLED DOUBLE ALUMINIUM CIRCULAR TUBE CAN BE RECOMMENDED FOR CRASHWORTHY STRUCTURES.

Multi-Objective optimization of aluminum foam double tube subjected to oblique impact loading for automobile bumper beam

This paper presents the multi-objective optimization of aluminum foam double circular tube under oblique load for various load angle and geometry parameters. Thin-walled metallic tubes are used in vehicle structures to absorb impact energy, such as in bumper beams. In this research, aluminum alloy AA6063 T6 foam filled tube which both end were clamped, at bottom as boundary condition and at the top of tube applied quasi-static force of load angle of 0o to 30o with respect to longitudinal direction of tubes. The finite element analysis using ABAQUS code was validated according to the relevant experimental data, and the deformation modes of the tubes were studied. Multi-objective optimization design of crush parameters such as minimum peak crushing force and maximum specific energy absorption were performed using particle swarm optimization algorithm. Different optimal designs for different angles of loading and geometries of double circular tubes was identified.

Comparative Study on Data Editing Techniques for Fatigue Time Series Signals

This paper presents the comparative study on three types of fatigue data editing technique for summarising long records of fatigue data. Two of techniques were developed based on timefrequency domain (continous wavelet and discrete wavelet) and another one technique was developed based on time domain. These three techniques are used to extract fatigue damaging events in the record that cause the majority of fatigue damage, whilst preserving the load cycle sequence in the data. The objective of this study is to observe the capability of each technique in summarising long records of fatigue data. For the purpose of this study, two set of nonstationary data that exhibits random behaviour was used. This random data was measured in microstrain unit on the SAE1045 material that were used as a lower suspension arm of a car. Experimentally, the data was collected for 60 seconds at sampling rate of 500Hz, which gave 30, 000 discrete data points. The result of the study indicates that all techniques are applicable in detecting and extracts fatigue damaging events that exist in the fatigue data. However, it was found that continous wavelet can extract the data better than the other technique based the shorten signals, retention of damage and statistical parameter.

Landfill area estimation based on integrated waste disposal options and solid waste forecasting using modified ANFIS model

Solid waste prediction is crucial for sustainable solid waste management. The collection of accurate waste data records is challenging in developing countries. Solid waste generation is usually correlated with economic, demographic and social factors. However, these factors are not constant due to population and economic growth. The objective of this research is to minimize the land requirements for solid waste disposal for implementation of the Malaysian vision of waste disposal options. This goal has been previously achieved by integrating the solid waste forecasting model, waste composition and the Malaysian vision. The modified adaptive neural fuzzy inference system (MANFIS) was employed to develop a solid waste prediction model and search for the optimum input factors. The performance of the model was evaluated using the root mean square error (RMSE) and the coefficient of determination (R(2)). The model validation results are as follows: RMSE for training=0.2678, RMSE for testing=3.9860 and R(2)=0.99. Implementation of the Malaysian vision for waste disposal options can minimize the land requirements for waste disposal by up to 43%.

K-means clustering and neural network for evaluating sound level vibration in vehicle cabin

One of the characteristics that may influence customers in vehicle purchasing is the level of comfort of the vehicle’s sound vibration in the vehicle cabin. The basic principle suggests that the sound vibration discomfort level is affected by a few factors which are mainly based on magnitudes, frequencies, directions and also the exposed periods. Normally, the phenomenon of sound vibration disrupts the performance of the driver by affecting the driver’s vision and also inducing a certain degree of stress due to the sound and vibration to which the driver and his or her passengers are exposed. The sound vibration is generally contributed by a few sources originated from the transmission of the vehicle’s engine, tire interactions with the road surface and also the exposure of vehicle’s body vibration during the movement. The objective of this study is to propose an approach that clusters the level of sound and vibration into a few categories and classifies them into those categories without implementing the subjective test that normally involves human assessment. The study has observed the changes of the sound quality and the level of vibration at particular points in the vehicle cabin over the changes of engine speeds. In reference to the results, the study has successfully provided a technical procedure in order to cluster, and also to classify, the level of sound vibration by taking into account the correlation between experienced noise and exposed vibration in the vehicle cabin.

Effects of Load Sequence on Fatigue Crack Growth in Pressure Vessels

Low alloy steels such as ASTM A508 and A533 and their equivalent materials have been extensively applied in fabricating pressure vessels due to their relatively excellent mechanical properties and moderately good weldability. The integrity of such materials governs the safety of the power plants. These vessels mainly are subjected to random loading in service and the load cycle interactions can have a significant effect in fatigue crack growth. Studying of fatigue crack growth rate and fatigue life calculation under spectrum loading is important for the reliable life prediction of vessels. Many models have been proposed, but as yet no universal model exists. In this paper, a fatigue life predicted under various load spectra, using three different fatigue crack growth models namely the Austen, modified Forman and NASGRO models. These models are validated with fatigue crack growth test data under various variable amplitude loadings. This application is performed with aids of three-point bend specimens. The results show clearly the load sequences effect and the predicted results agree with some discrepancies between the different models as well as with the test data. Neglecting, the cycle interaction effects in fatigue calculation under variable amplitude loading lead to invalid life prediction.

A Weighted Genetic Algorithm Based Method for Clustering of Heteroscaled Datasets

This paper introduces a weighted genetic algorithm (GA) based clustering method for datasets with differently scaled dimensions. Several types of synthetic two dimensional scatter data were clustered using the typical k-means clustering method. The weighted GA-based clustering method was developed to address the problem of clustering data with differently scaled (heteroscaled) dimensions. Cluster analysis results obtained from using this method was compared to the results produced from the application of the traditional k-means clustering. By introducing weights in the fitness evaluation component of the meta-heuristic search method, a more efficient clustering of heteroscaled data was produced. In real applications, this method can be used in cluster analyses of scatter data with significantly different scales in dimensions, such as kurtosis versus fatigue damage relationship scatter data.

Noise Annoyance Fuzzy Index in Passenger Car Cabin

Vehicle acoustical comfort and vibration in passenger car cabin are the factors which attract buyers to a vehicle, in order to have a comfortable driving environment. The comfort of the driving will affect the driver by influencing their driving performance. Vehicle acoustical comfort index (VACI) has been introduced to represent the level of annoyance in passenger car cabin. This index has been used in the computation related to the acoustics aspect in the car cabin. Noise annoyance is categorised into five states: most annoying, medium annoying, marginal, medium pleasant and most pleasant. In order to improve the VACI index, this study carries out an approach to classify and categorise the aforementioned five states using the fuzzy set theory approach. At the end of several studies, the noise annoyance fuzzy index (NAFI) has been introduced. By using NAFI, automotive researchers will be able to classify and make judgement about the state of annoyance from the exposed noise in the car cabin numerically, where the use of this index is regarded to be more precise and has practically been used in engineering fields especially where the fuzzy logic system is concerned.

Establishment of Remanufacturing Index for Locally Manufactured Automotive Components

Remanufacturing is aimed at restoring used automotive components to their new condition with the same function. In order to facilitate remanufacturing, it is important for the industry to ascertain remanufacturability of potential automotive components in the form of quantitative metrics or index. This knowledge is essential for decision making and planning for recovery activities of the end-of-life components. Knowledge on remanufacturability at the design and development stages is also vital so that products can be designed with a high remanufacturability index. This paper reports a study that focuses on the assessment of remanufacturability of locally manufactured automotive components from the aspects of design and process attributes, criteria and their relative weights. The proposed remanufacturing index is expected to assist manufacturers in designing for remanufacturing and implementation of their recovery strategy.