Institutional-Repository, University of Moratuwa
Welcome to the University of Moratuwa Digital Repository, which houses postgraduate theses and dissertations, research articles presented at conferences by faculties and departments, university-published journal articles and research publications authored by academic staff. This online repository stores, preserves and distributes the University's scholarly work. This service allows University members to share their research with a larger audience.
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Recent Submissions
item: Thesis-Abstract
Investigation into sound absorption properties of 3D cone knitted structures and their composites
(2026) Madushika, JWA; Lanarolle, WDG; Wijerathna, JK
Noise pollution has become a global issue which adversely affects human health. Therefore, noise should be controlled for the comfort of humans. Textiles are widely recognized as cost effective and environmentally friendly solutions for sound absorption. Among textiles, three-dimensional (3D) knitted cone structures which have higher surface area and fiber content than normal fabric can be ideal for sound absorption. The acoustic behaviour of 3D knitted cone structures was mathematically investigated by developing a mathematical model using basic equations of fluid dynamics. The samples were produced with variations in loop length, cone geometry and structural characteristics to investigate their acoustic properties experimentally using reverberation room method. A reverberation room was developed with a volume of 2.06 m³ and an asymmetric design, overcoming limitations of conventional test methods. The test results demonstrated that shorter stitch lengths enhance sound absorption properties at higher frequencies (f > 1000 Hz) whereas, at low frequencies, the effect of the stitch length on sound absorption was negligible. Furthermore, cone geometry significantly influenced the acoustic behaviour of the knitted samples. Samples with taller and narrower cones led to greater sound absorption at low frequencies (f 1000 Hz) while wider and shorter cones demonstrated better absorption at middle and high frequencies. It was further observed that, through the parametric comparison of samples based on the physical parameters such as density and air flow resistance of cone knitted structures, sound absorption coefficients close to 1 can be obtained above 2500 Hz frequencies. The experimental results closely matched the model predictions with a root mean square error (RMSE) of 0.02982 and a mean absolute error (MAE) of 0.02410, confirming the accuracy of the developed mathematical model. Geometrically stable cone knitted samples without compromising acoustic performance were obtained by applying a thin layer of epoxy resin which are suitable for use as acoustic absorbers. The results confirm that cone knitted structures provide a sustainable solution for sound absorption in building applications
item: Thesis-Abstract
Development of a condition-based maintenance model for grease lubrication : a case study of a paper mill
(2026) Pirathees, P; Gamage, JR; Gopura, R
This research highlights a vital challenge in optimization of grease usage as a lubrication in the industry through a development of condition-based maintenance model for grease lubrication throughout a case study of a paper mill. Even though application of grease is found to be a minor task, grease as a lubrication plays a major role in the machinery’s life span, increases the efficiency and reliability of machine elements and optimize maintenance cost as well. The inappropriate grease lubrication causes lot of interruption to production and factory output as well. Old traditional grease application methods required skilled manpower continuously for inspection, application and maintenance. This model has changed this situation to condition based grease application method with the supervision of measurable physical parameters for effective lubrication management. This research highlights the relationship between the measurable physical parameters such as temperature, vibration and noise level and the condition of grease in the machine elements throughout the case study in a paper manufacturing factory. Data collection is done at twenty different spots in different machine elements. These spots are continuously observed with the condition of grease level. Temperature is measured using infrared thermometers, vibration is measured using smart based vibration application and sound level is measured using sound level meters for acoustic pattern monitoring. These provide reliable data with the usage of grease how the parameters change. This has given a clear basis for model creation. The methodology used in this research is based on the physical condition of the machinery with the lubrication levels. Data analysis done which converts the inputs to understandable outputs which is then Processed using data visualization tool which showed a clear pattern in trend what happens with the condition of grease and refilling of grease. With the pattern the threshold level of all parameters is selected. Then the model is developed accordingly using python language. This leads to the successful completion of model. This condition-based maintenance model is designed based on the data collected by the sensors in different spots which is continuously monitored and analyzed. This changes the fixed schedule grease application method to condition based grease method which alarms and inform the manpower to apply grease which prevent the machineries failures. This research contributes to bridge the problem caused by the application of grease and maintenance work and the health of machines which is increased by the grease application at correct time reducing machinery failures by successfully developing a condition-based maintenance model in pilot stage. This also provides a foundation for future work which can be enhanced and advanced for fully automated systems with machine learning technology and increasing accuracy in data collection and processing as the way to Industry 4.0.
item: Conference-Abstract
ICEWSE 2026- 2nd International Conference on Energy and Water for Sustainable Environment 2026 (Pre-Text)
(2026) Rajapakse, RLHL; Prasath, RA
ICEWSE 2026- 2nd International Conference on Energy and Water for Sustainable Environment 2026
item: Thesis-Abstract
Bio-circular-green-lean supply chain adoption in the Sri Lankan apparel industry to mitigate supply chain disruptions : a case study
(2026) Abhimangala, HPLSC; Ratnayake, V
Supply chains are essential in linking suppliers, manufacturers, distributors, and retailers to deliver products efficiently to end customers. In the apparel industry, effective supply chain management is critical for cost efficiency, demand fulfillment, inventory optimization, and operational continuity. However, increasing global volatility has exposed supply chains to frequent disruptions arising from economic instability, environmental challenges, regulatory pressures, and operational inefficiencies, which can adversely affect organizational performance and brand reputation. As a major contributor to the national economy and a key participant in global supply networks, the Sri Lankan apparel industry has been particularly vulnerable to such disruptions. Conventional linear and efficiency-driven supply chain models have proven inadequate in managing uncertainty and ensuring long-term resilience. In response, firms have begun adopting sustainable and flexible separate approaches such as bio based, circular and lean supply chain models, although these often lack an integrated mechanism for comprehensive disruption management. This study investigates how supply chain disruptions are managed within the Sri Lankan apparel industry and evaluates the effectiveness of existing mitigation strategies. Based on eleven qualitative case studies of apparel organizations with varying levels of sustainability and lean maturity, the research identifies prevailing supply chain models, key disruption sources, and current mitigation practices across supply chain stages. The findings indicate that existing models have heightened vulnerability during economic crises, with limited integration of bio-based sourcing, circular material flows, environmental sustainability, and lean efficiency. To address this gap, the study proposes a Bio-Circular-Green Lean (BCGL) supply chain model that systematically embeds disruption mitigation strategies across the entire supply chain. The proposed framework enhances resilience, supports sustainable transformation, reduces waste, and strengthens long-term competitiveness in the apparel industry
item: Conference-Abstract
ICEWSE 2026- 2nd International Conference on Energy and Water for Sustainable Environment 2026
(2026) Rajapakse, RLHL; Prasath, RA