• Journal of Korean Institute of Industrial Engineers
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• v.34 no.4
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• pp.386-397
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• 2008

Due to the rapid advancement of technologies, a growing number of innovative products with a short life-cycle have been introduced to the market. As the life-cycles of such products are shorter than those of durable goods, the demand variation during the life-cycle adds to the difficulty of inventory management. Traditional inventory planning models and techniques mostly deal with products that have long life-cycles. The assumptions on the demand pattern and subsequent solution approaches are generally, not suitable for dealing with products with short life-cycles. In this research, inventory replenishment problems based on the logistic demand model are formulated and solved to facilitate the management of products with short life-cycles. An extended Wagner- Whitin approach is used to determine the replenishment cycle, schedules and lot-sizes.

• Journal of The Korean Society of Agricultural Engineers
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• v.53 no.3
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• pp.59-64
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• 2011

The objective of the study is to develop life cycle inventory (LCI) database of dam, a major facility for irrigation water supply. The types of database developed are three out of nine dams according to the size of the wate r storage capacity: two kinds larger than 500,000 $m^3$ depending on gate for discharging (Type 1) and the other dam smaller than 500,000 $m^3$ (Type 2). According to the LCI analysis, type 1 larger than 500,000 $m^3$ storage capacity with gate has the lowest environment impact in the 6 impact categories. The impact of the type 1 accounts for 7~35 % of the type 2 for supplying irrigation water. Comparing with the environment impacts of water for other uses such as drinking and industrial water, the impacts of 1 $m^3$ irrigation water supply is 4~45 % of the one for industrial water supply and 1~16 % of the drinking water's. The three types of LCI DB on the irrigation water by dams will be useful in the application of Life Cycle Assessment in agricultural products and environmental labelling including carbon footprint since it is complied to the guidelines of LCI DB constr uction issued by Ministry of Environment and Ministry of Knowledge Economy.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.1
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• pp.73-77
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• 1993

This paper considers an Economic Order Quantity Model under random life cycle. It is assumed that the life cycle of the product is unknown; a random variable. Three cost parameters are considered; ordering cost, inventory carrying cost and salvage cost. Expected total cost is the optimization criterion. We show that the optimal cycle length is unique and finite, and present a simple line search method to find an optimal cycle length.

• Proceedings of the KSR Conference
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• 2006.11b
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• pp.1123-1125
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• 2006

As Kyoto protocol has been effective in 2005, the reduction of $CO_2$ emission is a global urgent problem. In Korea, the $CO_2$ emission of transportation increases continuously, which can be solved partially by the use of railroad. Therefore, it is necessary to calculate exactly the $CO_2$ emission of railroad through life cycle approach. In this study, the $CO_2$ emission of electric motor unit (EMU) was evaluated with its carboy material using life cycle inventory analysis (LCIA). Among the life cycles of EMU, $CO_2$ emission was the highest in the running phase. As the total weight of EMU was lowered, $CO_2$ emission was reduced. In conclusion, the light-weighting of EMU can reduce $CO_2$ emission efficiently.

• Environmental Engineering Research
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• v.22 no.3
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• pp.266-276
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• 2017

A life cycle impact assessment was applied in an industrial waste incineration plant to evaluate the direct and indirect environmental impacts based on toxicity and non-toxicity categories. The detailed life cycle inventory of material and energy inputs and emission outputs was compiled based on the realistic data collected from a local industrial waste incineration plant, and the Korean life cycle inventory and ecoinvent database. The functional unit was the treatment of 1 tonne of industrial waste by incineration and the system boundary included the incineration plant and landfilling of ash. The result on the variation of the impact by the unit processes showed that the direct impact was decreased by 79.3, 71.6, and 90.1% for the processes in a semi dry reactor, bag filter, and wet scrubber, respectively. Considering the final impact produced from stack, the toxicity categories comprised 91.7% of the total impact. Among the toxicity impact categories, the impact in the eco-toxicity category was most significant. A separate estimation of the impact due to direct and indirect emissions showed that the direct impact was 97.7% of the total impact. The steam recovered from the waste heat of the incineration plant resulted in a negative environmental burden.

• Journal of Environmental Science International
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• v.23 no.6
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• pp.1067-1074
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• 2014

Life Cycle Assessment(LCA) has been carried out to evaluate the environmental impacts of glass bottle recycle. The LCA consists of four stages such as Goal and Scope Definition, Life Cycle Inventory(LCI) Analysis, Life Cycle Impact Assessment(LCIA), and Interpretation. The LCI analysis showed that the major input materials were water, materials, sand, and crude oil, whereas the major output ones were wastewater, $CO_2$, and non-hazardous wastes. The LCIA was conducted for the six impact categories including 'Abiotic Resource Depletion', 'Acidification', 'Eutrophication', 'Global Warming', 'Ozone Depletion', and 'Photochemical Oxidant Creation'. As for Abiotic Resource Depletion, Acidification, and Photochemical Oxidant Creation, Bunker fuel oil C and LNG were major effects. As for Eutrophication, electricity and Bunker fuel oil C were major effects. As for Global Warming, electricity and LNG were major effects. As for Ozone Depletion, plate glasses were major effects. Among the six categories, the biggest impact potential was found to be Global Warming as 97% of total, but the rest could be negligible.

• KSCE Journal of Civil and Environmental Engineering Research
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• v.37 no.4
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• pp.681-691
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• 2017

In this research, life cycle inventory database (LCI DB) was developed for elastomeric bearing employing life cycle assessment (LCA) methodology additionally the reliability improvement rate in the evaluation of the environmental load of the bridge was analyzed. As are result of impact assessment by 6 major impact categories, production of elastomeric bearing puts on environmental impact in the order of resource depletion, global warming, photochemical oxidant creation. and among a wide variety of input, steel plates contributes in most of the impact categories. As a result of applying the elastomeric bearing LCI database constructed in this study, the environmental loads increased by 0.53% on average, and the cut-off based on the cost of input materials increased by 11.36%. It is anticipated that it will be possible to improve the credibility and to provide data based on current production technology, such as estimating GHG emissions and evaluating environmental load, by constructing elastomeric bearing LCI DB.

• Clean Technology
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• v.21 no.1
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• pp.33-38
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• 2015

In this research, life cycle inventory database (LCI DB) was developed for liquid CO₂ employing life cycle assessment (LCA) methodology. As are result of characterization and normalization process, production of liquid CO₂ puts on environmental impact in the order of resource depletion, global warming, acidification, eutrophication and photochemical oxidation, and among a wide variety of input, electricity contributes in most of the impact categories. Air emission plays a key role in the acidification and eutrophication while ammonia affects most on the ozone depletion. It is anticipated that development of liquid CO₂ LCI DB makes it possible for national environmental strategies to be more activated including environmental labeling scheme.

• Journal of the Korean Society for Precision Engineering
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• v.21 no.12
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• pp.109-118
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• 2004

Life cycle assessment (LCA) usually involves some uncertainty. These uncertainties are generally divided in two categories such lack of data and data inaccuracy in life cycle inventory (LCI). This paper explo.es a methodology on dealing with uncertainty due to lack of data in LCI. In order to treat uncertainty of LCI data, a model for data uncertainty is proposed. The model works with probabilistic curves as inputs and with Monte Carlo Simulation techniques to propagate uncertainty. The probabilistic curves were derived from the results of survey in expert network and Monte Carlo Simulation was performed using the derived probabilistic curves. The results of Monte Carlo Simulation were verified by statistical test. The proposed approach should serve as a guide to improve data quality and deal with uncertainty of LCI data in LCA projects.

• Economic Analysis
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• v.24 no.3
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• pp.1-36
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• 2018

When it comes to explaining the relationship between inventory investment and business fluctuations, the production smoothing theory and the stock-out avoidance theory take contradictory stances. Decision-making related to inventory investments of corporations is thought to be influenced by both motives, but the relative sizes or directions of their respective influences can differ depending upon the phase of the business cycle. Against this backdrop, this paper differs from existing studies in that it theoretically tests the relative significances of the production smoothing and stock-out avoidance motives in the inventory investment dynamics, while placing its analytical focus on determining the existence and patterns of the asymmetric dynamics of inventory investment over the business cycle phases. To this end this paper sets up a non-linear model that is expanded from the existing linear inventory investment model, and checks whether its predictive power is better than that of the existing model. The results of analysis confirm the nature of the asymmetric dynamics of inventory investment over the business cycle phases. A stock-out avoidance motive appears but there is no significant production smoothing motive in boom times. In downturns, in contrast, the stock-out avoidance motive is insignificant, but a quality of asymmetric dynamics in which changes in inventory cause the deepening of recessions, due to the non-convexity of production costs proposed by Ramey (1991), is detected. This paper confirms that a model considering the asymmetric dynamics of inventory investment can have better predictive power than one that does not consider it, through within-sample and out-of-sample predictions and various predictive power tests. These research results are expected to be useful for economic forecasting, through their enhancement of the understandings of the inventory investment dynamics and of the nature of its business cycle destabilization.