Universiti Teknologi Malaysia

About: Universiti Teknologi Malaysia is a education organization based out in Johor Bahru, Malaysia. It is known for research contribution in the topics: Membrane & Adsorption. The organization has 21644 authors who have published 39500 publications receiving 520635 citations.

The soft foundation of the critical success factors on TQM implementation in Malaysia

Abstract: The literature review concludes that TQM is a proven systematic approach to the improvements of the organisation’s overall business process, including quality of products and services. Organisational lack of information and data on the critical success factors are an obstacle in implementing TQM effectively and successfully. This study has developed a TQM soft model which is fit for application. It has considered the needs and limitation of Malaysian industries and facilitates TQM activities. The study has examined the relationship between the soft elements of critical success factors on TQM tangible effects, influences by soft elements activities such as culture, trust, teamwork, employment continuity, education and training, top management leadership for quality and continuous improvement, employee involvement and customer satisfaction/ involvement. Three main research methods were adopted in developing the TQM soft model: a postal questionnaire survey, a structured interview and the practical implementation of the model at a manufacturing company. Multiple regression analysis and binomial testing are used to analyse the data.

Prediction of the unconfined compressive strength of soft rocks: a PSO-based ANN approach

Abstract: Many studies have shown that artificial neural networks (ANNs) are useful for predicting the unconfined compressive strength (UCS) of rocks. However, ANNs do have some deficiencies: they can get trapped in local minima and they have a slow learning rate. It is widely accepted that optimization algorithms such as particle swarm optimization (PSO) can improve ANN performance. This study investigated the application of a hybrid PSO-based ANN model to the prediction of rock UCS. To prepare a dataset for the predictive model, extensive laboratory tests (i.e., 160 tests in total) were conducted on 40 soft rock sample sets (mostly shale) presenting various weathering grades that were obtained from different excavation sites in Johor, Malaysia. The laboratory tests included the UCS test and other basic rock index tests (the Brazilian tensile strength test, point load index test, and ultrasonic test). When developing the predictive model of UCS, the results of the basic rock tests as well as the bulk densities of the samples were used as input parameters, while the UCS was set as the output of the predictive model. The value account for (VAF), root mean squared error (RMSE), and adjusted R 2 (coefficient of determination) were utilized to check the performances of the predictive models. The high performance indices of the proposed model highlight the superiority of the PSO-based ANN model for UCS prediction.

An overview of immobilized enzyme technologies for dye and phenolic removal from wastewater

Abstract: Global water pollution caused by dye and phenol contaminants has been reported to have reached an alarming level. These hazardous contaminants pose significant threats to humans and ecosystem, due to their toxicity, carcinogenicity, and mutagenicity. Various technologies have emerged for dyes and phenols removal from wastewater, such as physical adsorption, chemical oxidation, ozonation, extraction, and electrochemical treatments. However, these conventional methods are constrained by low efficiency and stability, high cost, and formation of harmful by-products. In recent years, there has been growing interest towards the development of immobilized enzyme technologies because they are more economical, effective and eco-friendly. Among various enzymes, peroxidases have generated extraordinary interest attributed to their ability to catalyze reactions of a variety of undesirable pollutants, such as dyes and phenol effluents. Immobilization of enzyme can enhance its catalytic efficiency, improve storage and operational stabilities, as well as allow enzyme recovery and reusability. Although numerous existing immobilized enzymatic systems have been established, their practical applications are limited due to mass transfer restriction, lack of feasibility for scaling-up and continuous operations, and difficulty for separation of immobilized enzymes from reaction mixtures. Therefore, much attention has been devoted to the immobilization of enzymes on nano-structured materials. In the current review, effects of process parameters on immobilized enzymes for applications in both dye and phenol treatment are discussed and summarized. Recent advanced technologies as well as challenges and future perspectives for research and development in this field are also highlighted.