Eco-friendly materials have been developed recently that have made it possible to significantly reduce the maintenance cost of buildings when they are appropriately used in renovation. Indeed, it became extremely important to consider the eco-friendly energy-saving effects on design alternatives during renovation. The present study proposes a framework for the optimum maintenance decision-making model for considering eco-friendly energy to help people interested in making decisions concerning renovation; it requires that both the environmental friendliness and economic feasibility of the target building be simultaneously considered. Several studies mainly cover the structural aspects for energy improvements based on innovation and technology. However, energy simulation in existing buildings needs some additional consideration regarding the economic analysis of energy savings and the recovery period of construction costs. A case study was conducted as a research method by utilizing the proposed framework, which aims to: (1) make energy simulations with different basic design assumptions; (2) perform the energy simulations through building information modeling (BIM) technology; and (3) analyze the economic feasibility of the alternatives. As a result, an alternative combination that can save the net maximum energy cost during the life cycle period and invest the lowest renovation costs has been recommended. Furthermore, effective guidelines were proposed on which items the building owner values, depending on his economic investment conditions in decision-making regarding the level of design, through a comprehensive review of the energy savings by design variable. It is expected that the research findings will be utilized in the decision-making process and for conducting further relevant research in future.

The introduction of new OSHA cranes and derricks regulations in 2010 has been referenced by organizations involved in crane operations as being a significant milestone in reducing the number of crane accidents. This study investigates the impact of the new regulations on the frequency of crane accidents that result in fatalities and injuries while identifying crane related hazards posing significant safety risk during crane operations. Crane related accidents recorded between 2002 and 2012 were analyzed in detail to compare accident frequencies resulting in fatalities and injuries. Specifically, accidents were sorted by causes of crane accidents and types of crane failures grouped into two categories: accidents between 2002 to 2010 representing old crane regulations and accidents between 2011 and 2012 representing new regulations. The expectation was that crane accidents were significantly reduced after the introduction of new crane regulations. Detailed data analysis including chi-square test and proportional analysis were conducted on these two categories. Although no significant relationship was revealed between the frequency of crane accidents and the change in regulations, the proportional analysis showed decline in the frequency of certain types of accidents while revealing areas with proportional increase that require further attention for risk mitigation.

Building information modeling (BIM) provides facility managers with a large database consisting of 3D geometric data as well as management data. In particular, Industry Foundation Class (IFC) has been applied in many studies as it provides extensive and diverse information regarding building components. With the use of BIM combined with case-based reasoning (CBR), in this study, a model was developed to estimate replacement costs by retrieving cost information from IFC. This study focused on the replacement of windows for office buildings, and the costs associated with that replacement. Two main advantages were identified in the proposed approach. First, the replacement information required for the comparison of different cases is automatically obtained from a BIM file and parsed for predicting a cost estimate using IFC. Next, the accuracy is increased by matching various cost-related data such as contractors and manufacturers in the estimation of replacement costs with the help of CBR.

The sudden breakdowns of the power generation facilities caused a serious concern about the stable operation of the power system. However, since electricity system in South Korea is not connected to neighboring country, it is necessary to devise methods to counteract emergency such as unexpected failure of a power plant or sudden increase of electric power demand. In response, South Korea is operating seven pumped-storage power plants whose capacity is equal to that of about five nuclear power plants, accounts for 5.9% of the total power capacity of South Korea. The pumped turbine is a machine that operates through forward and reverse rotations to store energy and produce electric power. It requires high reliability for rapidly generating electricity on load. The losses caused by the shutdown of the power plants due to turbine failures, and the costs of their recovery, are enormous. Thus, improving the reliability of a pumped-storage power plant will have a significant influence on the national power system. In this regard, this research seeks to increase the reliability of the pumped storage power plant by identifying the problematic factors. This study proposes models of Case Based Reasoning (CBR) for eliminating possible problematic factors in pumped storage power plants before operation phase through predicting and checking failure. The development of the model involves analyzing operational data from 36 pumped-storage power plants; conducting decision tree analysis on 19 problems in order to select significant problems; and developing CBR models which can predict and check possible problems to improve the reliability of the pumped-storage power plant.