Purpose Concrete structures undergo early and fast deterioration, which causes defects such as cracks, water leaks and delamination, resulting from a lack of or inefficient maintenance practices. To improve this behaviour, this paper aims to develop a maintenance strategy benchmarking model for concrete structures. Design/methodology/approach Fuzzy logic toolbox on MATLAB R2018a was used to develop the proposed model and it was applied to two cases. A comprehensive literature search was done to review common concrete defects, their impact on the performance and functionality of the structure, effectiveness of maintenance strategies and previous maintenance benchmarking models. The literature findings were further validated through expert interviews which have been incorporated in the model. Findings Case study results show that preventive maintenance (PM), predictive maintenance (PdM) and corrective maintenance (CM) strategies are required more or less in similar combinations for maintenance of concrete roof structures. The best combination for case 1 is 36.42% PM, 35.40% PdM and 28.18% CM, and for case 2 is 35.93% PM, 35.08% PdM and 28.99% CM. According to suitability, they can be ranked as PM > PdM > CM. Originality/value This model will contribute as a comprehensive decision-making tool for building/facility managers. The findings further carry a strong message to those who practice only CM in their buildings.
Textile industry plays a major role in Sri Lankan economy but it is an energy intensive industry which releases a large amount of CO2 to the atmosphere. Therefore, it is important to take sustainable measures to reduce energy consumption and greenhouse gas emissions in textile manufacturing while making efforts to increase the production. This study was conducted considering three textile manufacturing factories in Biyagama Export Processing Zone which produce knitted fabric, and based on the data availability, the energy consumption data for those factories were collected and analysed for the period 2011-2015. The factories have been identified as A, B and C, considering certain ethical concerns. Average annual energy consumption of the factory A, B and C are 158 TJ, 86 TJ and 717 TJ, respectively. Further, energy requirements of factories have increased by 37%, 23% and 54% within the study period. Factories fulfilled this energy requirement using different energy sources: electricity, diesel, heavy fuel oil (HFO), Liquid petroleum gas (LPG), and Biomass (sawdust and wood). However, both factories A and B were able to increase their ecoefficiency of energy use (i.e. mass of the product per energy consumption) by 6% and 57% respectively within the study period by using energy in a more sustainable manner. Factories A, B and C were able to increase their production in 2015 compared to 2011 by 45%, 71% and 31% respectively within the study period but their CO2 emission decreased by 74%, 40% and 46%. This reduction was mainly influenced by the replacement of HFO by biomass. As a result, eco-efficiency of CO2 emission of factories (i.e. mass of the product per CO2 emission) have increased each year with fluctuations within the last five years. Using biomass as the alternative energy source not only caused positive impact on the environment but also on the profit of the factories. Using biomass as the main fuel for the boilers reduced the cost per unit production of the factories A, B and C by 49%, 40% and 3% respectively. Moreover, all three factories buy biomass from the surrounding villages which generate employment opportunities for the villagers. As intensive use of wood logs as biomass may lead to deforestation, all three factories encourage the use of saw dust and sustainably cultivated rubber in generating energy. As biomass positively affects the environment, economy and society, it can be considered as a sustainable energy source for textile industry.
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