Che Rosmani Che Hassan

Factors that Contribute to the Generation of Construction Waste at Sites

Construction industry in Malaysia is growing rapidly with high demand due to vast development and urbanization. Therefore, many commercial and residential buildings are being developed. The increasing number of construction projects in Malaysia will indirectly contribute to the increase of construction waste generation. Thus, waste minimization is an important area of concern in the implementation of the construction waste management in the construction industry of Malaysia. Data collection and observations was conducted at three construction sites which adopt different type of method with different type of building and size of project in Klang Valley. The calculation of the construction waste index generated at these sites is adopted from Poon et al., (2001). Result showed that construction method, size of projects (GFA), type of building, storage method system, human error and technical problem can affect the amount of waste index (debris) and amount of wastage level generated at construction sites. Therefore waste index and wastage level can be used as operational an indicator for waste minimization of the construction activities.

Inclusion of human errors assessment in failure frequency analysis - A case study for the transportation of ammonia by rail in Malaysia

Risk is defined as the probability of a specific adverse event occurring within a specific period, while Quantitative risk assessment (QRA) is the development of a quantitative estimate of risk based on engineering evaluation and mathematical techniques by combining estimate of incident consequences and frequencies. In view of the increase in the use of railways as the mode of transportation for hazardous materials throughout the world, the associated risk analysis should be taken into concern. In this study, the failure frequency of the transportation of ammonia from the Petronas fertilizers Kedah (PFK) plant in Gurun (Northern part of Peninsular Malaysia), to the Chemical Company Malaysia (CCM) fertilizers facilities in Port Klang (South‐western part of Peninsular Malaysia) was evaluated by incorporating the human error assessment. The study highlighted the importance of human error contributions in the failure frequency analysis and its impact on the selected failure scenarios. Besides, it also shows that the application of the human error assessment and reduction technique (HEART), which is a useful human reliability analysis tool, should be used in parallel with the fuzzy arithmetic approach to reduce the uncertainties involved in the estimation of human error probabilities, and hence, to reduce the likelihood of incorrect risks estimates being assessed. The results suggested that the commonly applied approach in quantitative risk assessments, which only consider equipment failures in the failure frequency estimations, are clearly an underestimate of the potential causes of failures leading to hazardous material releases, and hence, the calculated risks based do not reflect the actual risks.

Waste quantification models for estimation of construction and demolition waste generation: a review

Quantification is crucial for construction and demolition waste management. Accurate estimation can be satisfied by developing waste quantification model that is applicable for regional or nation-wide C&D waste generation. This paper presents a review on quantification models for C&D waste from literatures and how they correlate. Most studies combine the empirical waste assessment data or waste generation factor obtained in the field with area of activity level extracted from national statistical database from their respective countries, which provides annual data on sector activities. National or regional estimates provide general figures and forecasts for annual C&D waste generation. Studies found that waste generation factor will differs according to locations. Since volume and characteristic of waste are crucial for waste quantification, quantitative data record from waste audit findings could benefit the authorities for the annual estimates. National C&D waste reduction plan should start from well-established waste minimisation plan at project sites.

Synthetic Batik Wastewater Pretreatment Progress by Using Physical Treatment

One of the most important manufacturing industries in Malaysia is textile and specifically batik making. Many local batik factories discharge their wastewater, which contains wax, resin, silicate and dyes, without treatment, directly to nature. A possible treatment system involving membrane filtration has been tested to remove the dyes. However the presence of wax the wastewater requires a pretreatment stage to remove the undesired wax. In this study the performance of baffle tank pretreatment (own designed and fabricated) was evaluated for 4 different types of synthetic batik wastewater, which contain wax, resin, sodium silicate and 4 different fibers reactive dyes namely, Remazol Turquoise Blue G133 (Blue 21), Remazol Red 194 and Remazol Yellow 14 and Reactive black 5. The removal efficiency (%), pH and COD of each sample were evaluated and recorded. Wax removal efficiency in all samples was more than 88%. The COD and pH of all samples decreased after 60 minutes pretreatment cycle.

Quantification Methods for Construction Waste Generation at Construction Sites: A Review

Estimation of construction and demolition (C&D) waste amount is crucial for implementing waste minimization program. Estimation of C&D waste amount generated is a mean in assessing the potential for waste reduction. Thus, a better understanding of C&D waste generation in terms of causes and sources can be achieved. The aim of this paper is to conduct a review on available construction waste quantification methods from previous studies, which have been utilized in certain countries, while attempting to choose the most suitable and applicable method, and to direct future studies for better quantification methods. This review is applicable only for building construction projects and did not include civil/infrastructure, demolition, renovation, and excavation projects. Six quantification methods and/or waste audit tool available from literatures are discussed, which include their limitation and future direction for this study. It is believed that some combination of these quantification methods could make a good impact in accurate numerical estimation of construction waste amount generated in building construction projects. A strong and accurate database as presented by Soliz-Guzman, combined with effective, vital, and resourceful estimation suggested by Jalali’s Global Index (GI), also with the aid of user-friendly software tool like the SMARTAudit could provide an effective and reliable waste quantification.

Quantitative risk assessment for the transport of ammonia by rail

Risk assessments are considered to be an essential tool in ensuring the safety of engineering projects. The benefits of using risks assessments have prompted its acceptance in the safety legislation for a number of industries. The use of quantitative risk assessment for rail transportation of hazardous materials has gained more attention in recent years, because the amount of the transported hazardous materials is large, and the transportation route often passes through populated areas, such as cities. In this study, the risk for the ammonia transportation by rail in Malaysia was conducted by combining the results from a previous failure frequency analysis and consequence analysis. The assessment results acknowledged the significant effects of train speeds on the overall individual risk. The risk with a tolerable risk limit of 1 × 10−6 per year increased significantly with more train accidents occurring at increasing speeds. Most of the surrounding populations along the transportation route analyzed are exposed to higher risk levels than the tolerable limit. This risk exposure to the public demonstrates the need for proper planning of moving ammonia through populated areas.

Fault diagnosis and classification framework using multi-scale classification based on kernel Fisher discriminant analysis for chemical process system

Abstract Fault detection and diagnosis (FDD) in chemical process systems is an important tool for effective process monitoring to ensure the safety of a process. Multi-scale classification offers various advantages for monitoring chemical processes generally driven by events in different time and frequency domains. However, there are issues when dealing with highly interrelated, complex, and noisy databases with large dimensionality. Therefore, a new method for the FDD framework is proposed based on wavelet analysis, kernel Fisher discriminant analysis (KFDA), and support vector machine (SVM) classifiers. The main objective of this work was to combine the advantages of these tools to enhance the performance of the diagnosis on a chemical process system. Initially, a discrete wavelet transform (DWT) was applied to extract the dynamics of the process at different scales. The wavelet coefficients obtained during the analysis were reconstructed using the inverse discrete wavelet transform (IDWT) method, which were then fed into the KFDA to produce discriminant vectors. Finally, the discriminant vectors were used as inputs for the SVM classification task. The SVM classifiers were utilized to classify the feature sets extracted by the proposed method. The performance of the proposed multi-scale KFDA-SVM method for fault classification and diagnosis was analysed and compared using a simulated Tennessee Eastman process as a benchmark. The results showed the improvements of the proposed multiscale KFDA-SVM framework with an average 96.79% of classification accuracy over the multi-scale KFDA-GMM (84.94%), and the established independent component analysis-SVM method (95.78%) of the faults in the Tennessee Eastman process.

Process Monitoring and Fault Detection in Non-Linear Chemical Process Based On Multi-Scale Kernel Fisher Discriminant Analysis

Abstract This paper presents a multi-scale kernel Fisher discriminant analysis (MSKFDA) algorithm combining Fisher discriminant analysis (FDA) and its nonlinear kernel variation with the wavelet analysis. This approach is proposed for investigating the potential integration of wavelets and multi-scale methods with discriminant analysis in nonlinear chemical process monitoring and fault detection system. In this paper, a discrete wavelet transform (DWT) is applied to extract the dynamics of the process at different scales. The wavelet coefficients obtained during the analysis are used as input for the algorithm. By decomposing the process data into multiple scales, MSKFDA analyse the dynamical data at different scales and then restructure scales that contained important information by inverse discrete wavelet transform (IDWT). A monitoring statistic based on Hoteling’s T 2 statistics is used in process monitoring and fault detection. The Tennessee Eastman benchmark process is used to demonstrate the performance of the proposed approach in comparison with conventional statistical monitoring and fault detection methods. A comparison in terms of false alarm rate, missed alarm rate and detection delay, indicate that the proposed approach outperform the others and enhanced the capabilities of this approach for the diagnosis of industrial applications.

Simulated textile (batik) wastewater pre-treatment through application of a baffle separation tank

AbstractOne of the main cultural heritages associated with South-East Asian people’s way of life and economy is batik. Not only batik is a part of textile industries, playing an important role in industrial development, it also, like other wet textile processes, generates huge amounts of hazardous wastewater. Due to the presence of wax in the batik production process an efficient wastewater pre-treatment is necessary to appropriately prepare related effluent conditions for further conventional wastewater treatment. Accordingly, in this study, the application of a baffle separation tank to treat simulated batik effluent as an innovative wastewater pre-treatment method was investigated. Therefore, two sets of simulated batik wastewaters containing constant amounts of chemical components (wax, dye, and sodium silicate with different reactive dyes) were tested. In the next step, the removal efficiency of the discussed samples’ chemical components was calculated based on pre- and post-process analytical experi...

Optimization of Headspace Sampling Using Solid-Phase Microextraction (SPME) for Volatile Components in Starfruit Juice

Abstract Volatiles are important flavor compounds of fruit juices and beverages. In this study, a headspace Solid-phase microextraction (SPME) gas chromatography-mass spectrometry (GC-MS) was used to analyze the volatile components in starfruit juices. Several experimental parameters (e.g. adsorption temperature, adsorption time, and sample volume) were optimized to improve sampling efficiency in two aspects; maximum adsorption and selective adsorption of volatile components onto SPME fiber. The following conditions were found to be optimal for selectivity and sensitivity: adsorption temperature of 50°C for 30 min, with a 65 μm divinylbenzene /polydimethylsiloxane (DVB/PDMS)-coated fiber with a sample volume of 15 g in a 30-ml vial. The proposed technique could be applied for the analysis of volatile compounds that contribute to starfruit juices flavor in different cultivars, and also their ripening stages.