• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.162-168
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• 2010

Information is known to be a key element for the successful operation of a supply chain, which is required of the efficient ordering strategies and accurate predictions of demands. This study proposes a method to effectively utilize the meteorological forecast information in order to make decisions about ordering and prediction of demands by using the Taguchi experimental design. It is supposed that each echelon in a supply chain determines the order quantity with the prediction of precipitation in the next day based on probability forecast information. The precipitation event is predicted when the probability of the precipitation exceeds a chosen threshold. Accordingly, the choice of the threshold affect the performances of a supply chain. The Taguchi method is adopted to deduce a set of thresholds for echelons which is least sensitive to changes in environmental conditions, such as variability of demand distributions and production periods. A simulation of the beer distribution game was conducted to show that the set of thresholds found by the Taguchi method can reduce the cumulative chain cost, which consists of inventory and backlog costs.

• Journal of the Korea Concrete Institute
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• v.24 no.5
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• pp.597-604
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• 2012

The present study assessed the $CO_2$ emissions of concrete according to the type and replacement ratio of supplementary cementitious materials (SCM) and concrete compressive strength using a comprehensive database including 2464 cement concrete specimens and 776 cement concrete mixes with different SCMs. The system studied in $CO_2$ assessment of concrete based on Korean lifecycle inventory was from cradle to pre-construction, which includes consistent materials, transportation and production phases. As the performance efficiency indicators, binder and $CO_2$ intensities were analyzed, and simple equations to evaluate the amount of $CO_2$ emission of concrete were then formulated as a function of concrete compressive strength and the replacement ratio of each SCM. Hence, the proposed equations are expected to be practical and useful as a guideline to determine the type and replacement ratio of SCM and unit content of binder in concrete mix design that can satisfy the target compressive strength and $CO_2$ reduction percentage relative to cement concrete.

• Journal of The Korean Society of Agricultural Engineers
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• v.63 no.3
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• pp.97-105
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• 2021

Most of the rural development projects for the welfare of residents are mainly new construction and remodeling projects for community buildings such as village halls and senior citizens. However, in the case of the construction industry, it has been studied that 23% of the total carbon dioxide emissions generated in Korea are generated in the building-related sector. (GGIC, 2015) In order to reduce the emission of environmental pollutants resulting from construction of rural community buildings, there is a need to establish a system for rural buildings by predicting the environmental impact. As a result of this study, the emissions of air pollutants from buildings in rural communities were analyzed by dividing into seven stages: material production, construction, operation, maintenance, demolition, recycling, and transportation activities related to disposal. As a result, 12 kg of carbon dioxide (CO), 0.06 kg of carbon monoxide (CO), 0.02 kg of methane (CH), 0.04 kg of nitrogen oxides (NO), 0.02 kg of sulfurous acid gas (SO), and non-methane volatile organics per 1m of buildings in rural communities It was analyzed that 0.02 kg of compound (NMVOC) and 0.00011 kg of nitrous oxide (NO) were released. This study proved that environmentally friendly design is possible with a quantitative methodology for the comparison of operating energy and air pollutant emissions through the design specification change based on the statement of the rural community building. It is considered that it can function as basic data for further research by collecting major structural changes and materials of rural community buildings.

• Korean Chemical Engineering Research
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• v.45 no.3
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• pp.249-257
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• 2007

The periodic square wave (PSW) model was successfully applied to the optimal design of a batch-storage network. The network structure can cover any type of batch production, distribution and inventory system, including recycle streams. Here we extend the coverage of the PSW model to multitasking semi-continuous processes as well as pure continuous and batch processes. In previous solutions obtained using the PSW model, the feedstock composition and product yield were treated as known constants. This constraint is relaxed in the present work, which treats the feedstock composition and product yield as free variables to be optimized. This modification makes it possible to deal with the pooling problem commonly encountered in oil refinery processes. Despite the greater complexity that arises when the feedstock composition and product yield are free variables, the PSW model still gives analytic lot sizing equations. The ability of the proposed method to determine the optimal plant design is demonstrated through the example of a high density polyethylene (HDPE) plant. Based on the analytical optimality results, we propose a practical process optimality measure that can be used for any kind of process. This measure facilitates direct comparison of the performance of multiple processes, and hence is a useful tool for diagnosing the status of process systems. The result that the cost of a process is proportional to the square root of average flow rate is similar to the well-known six-tenths factor rule in plant design.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.163-179
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• 2010

Recentlythe concept of fast fashion is drawing attention as customer needs are diversified and supply lead time is getting shorter in fashion industry. It is emphasized as one of the critical success factors in the fashion industry how quickly and efficiently to satisfy the customer needs as the competition has intensified. Because the fast fashion is inherently susceptible to trend, it is very important for fashion retailers to make quick decisions regarding items to launch, quantity based on demand prediction, and the time to respond. Also the planning decisions must be executed through the business processes of procurement, production, and logistics in real time. In order to adapt to this trend, the fashion industry urgently needs supports from intelligent quick response(QR) system. However, the traditional functions of QR systems have not been able to completely satisfy such demands of the fast fashion industry. This paper proposes an intelligent quick response system for the fast fashion(IQRS-FF). Presented are models for QR process, QR principles and execution, and QR quantity and timing computation. IQRS-FF models support the decision makers by providing useful information with automated and rule-based algorithms. If the predefined conditions of a rule are satisfied, the actions defined in the rule are automatically taken or informed to the decision makers. In IQRS-FF, QRdecisions are made in two stages: pre-season and in-season. In pre-season, firstly master demand prediction is performed based on the macro level analysis such as local and global economy, fashion trends and competitors. The prediction proceeds to the master production and procurement planning. Checking availability and delivery of materials for production, decision makers must make reservations or request procurements. For the outsourcing materials, they must check the availability and capacity of partners. By the master plans, the performance of the QR during the in-season is greatly enhanced and the decision to select the QR items is made fully considering the availability of materials in warehouse as well as partners' capacity. During in-season, the decision makers must find the right time to QR as the actual sales occur in stores. Then they are to decide items to QRbased not only on the qualitative criteria such as opinions from sales persons but also on the quantitative criteria such as sales volume, the recent sales trend, inventory level, the remaining period, the forecast for the remaining period, and competitors' performance. To calculate QR quantity in IQRS-FF, two calculation methods are designed: QR Index based calculation and attribute similarity based calculation using demographic cluster. In the early period of a new season, the attribute similarity based QR amount calculation is better used because there are not enough historical sales data. By analyzing sales trends of the categories or items that have similar attributes, QR quantity can be computed. On the other hand, in case of having enough information to analyze the sales trends or forecasting, the QR Index based calculation method can be used. Having defined the models for decision making for QR, we design KPIs(Key Performance Indicators) to test the reliability of the models in critical decision makings: the difference of sales volumebetween QR items and non-QR items; the accuracy rate of QR the lead-time spent on QR decision-making. To verify the effectiveness and practicality of the proposed models, a case study has been performed for a representative fashion company which recently developed and launched the IQRS-FF. The case study shows that the average sales rateof QR items increased by 15%, the differences in sales rate between QR items and non-QR items increased by 10%, the QR accuracy was 70%, the lead time for QR dramatically decreased from 120 hours to 8 hours.