• Proceedings of the Korean Institute of Building Construction Conference
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• 2012.05a
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• pp.119-120
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• 2012

The management for materials and inventory is one of the factors which are considered the most for profits of a business in almost all industrial fields. Resource procurement which occupies more than 40% of an overall construction cost has a strong relationship with profits of a business but it is regarded as a work for a manager rather than for a technician. It makes the importance of resource procurement relatively low and slows down the development of workings. As the construction project becomes more larger and complicated, effective management for materials are directly affecting the profits of a business. Therefore, this research works on finding an economical managing method for materials according to a characteristic of construction project based on accurately forecasted BIM data. Finding a reorder point by using BIM data which contains an accurate data for schedule and material enables a better management for materials and provides more accurate data on matters which were used to be determined by an intuition of a manager.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.4
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• pp.69-78
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• 2010

Multi-criteria ABC inventory classification is one of the most widely employed techniques for efficient inventory control, and it considers more than one criterion for categorizing inventory items into groups of different importance. Recently, Ramanathan (2006) proposed a weighted linear optimization (WLO) model for the problem of multi-criteria ABC inventory classification. The WLO model generates a set of criteria weights for each item and assigns a normalized score to each item for ABC analysis. Although the WLO model is considered to have many advantages, it has a limitation that many items can share the same optimal efficiency score. This limitation can hinder a precise classification of inventory items. To overcome this deficiency, we propose a context-dependent DEA based method for multi-criteria ABC inventory classification problems. In the proposed model, items are first stratified into several efficiency levels, and then the relative attractiveness of each item is measured with respect to less efficient ones. Based on this attractiveness measure, items can be further discriminated in terms of their importance. By a comparative study between the proposed model and the WLO model, we argue that the proposed model can provide a more reasonable and accurate classification of inventory items.

• Journal of the Korea Society for Simulation
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• v.24 no.1
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• pp.1-8
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• 2015

This research focuses on the method of inventory management to find out the best way in various SCM. There are several comparable methods of inventory management like Min-Max, regular interval, fixed target inventory that have different lead-time and demand for each product. Also, the inventory performances between the case of three-stages and two-stages in SCM are analyzed. 8 scenarios for the simulation are suggested considering order ways and stages. Input data for the simulation is from the result of the previous studies and actual data in the market. The performance measurements are selected as sales revenue, total number of sales, total delivery cost, total inventory shortages, the number of inventory shortage occurrence, the loss for inventory shortages, average inventory, handling cost, net profit. According to the results of the simulation, fixed target inventory management is better than existing inventory management method by net profit and inventory and so on. Also, it was confirmed that the increase in profit is obtained when SCM stages is reduced from three-stages to two-stages in existing SCM. The result of the research provides significant meaning that newly introduced target inventory management system shows good performance and SCM performance can be improved by reducing the stages.

• Proceedings of the KSRS Conference
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• 2008.10a
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• pp.41-44
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• 2008

In this paper, major species of tree were discriminated in compartment by using LiDAR data and optic imagery. This is an important work in forest field. A current digital stock map has created the aerial photo and collecting survey data. Unlike high resolution imagery, LiDAR data is not influenced by topographic effects since it is an active sensory system. LiDAR system can measure three dimension information of individual tree. And the main methods of this study were to extract reliable the individual tree and analysis techniques to facilitate the used LiDAR data for calculating tree crown 2D parameter. We should estimate the forest inventory for calculating parameter. 2D parameter has need of area, perimeter, diameter, height, crown shape, etc. Eventually, major species of tree were determined the tree parameters, compared a digital stock map.

• Journal of Forest and Environmental Science
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• v.24 no.3
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• pp.127-135
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• 2008

The mission of the Forest Inventory and Analyis (FIA) program of the Forest Service, U.S. Department of Agriculture, is to conduct the national forest inventory of the United States of America for purposes of estimating the area of forest land; the volume, growth, and removal of forest resources; and the health of the forest. Users of FIA data, estimates, and related products include land managers, policy and decision-makers, forest industry, environmental organizations, and university researchers. To accomplish its mission, the FIA program has established a sampling design with an intensity of approximately one permanent plot per 2,400 ha across the entire country. Depending on the region of the country, each plot is remeasured at intervals of five or 10 years. The program releases data annually and reports estimates at the county level for each state every five years. Due to budgetary constraints and natural variability among plot observations, sufficient numbers of plots cannot be measured to satisfy precision guidelines for the estimates of many variables unless the estimation process is enhanced using ancillary data. Classified satellite imagery has been demonstrated to be a source of ancillary data that can be used with stratified estimation techniques to increase the precision of estimates with little corresponding increase in costs. A crucial factor restricting the utility of FIA data is that the exact locations of inventory plots cannot be released to the public. Thus, users are generally not able to obtain estimates for small areas or for their own areas of interest if exact plot locations are required. To compensate, satellite imagery, inventory plot data, and the k-Nearest Neighbors technique are being used to construct Internet-based maps of forest attributes from which estimates for arbitrary user-defined areas of interest may be obtained.

• Journal of the Korean Institute of Intelligent Systems
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• v.11 no.7
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• pp.584-590
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• 2001

An inventory management system of manufacturing industry has a model of different kinds according to the objective and the situation. An inventory management system needs superior system technique in demand forecast, economical efficiency, reliability and application for stable supply of the finished goods, the raw materials and the parts. This paper proposes a demand forecast method based on fuzzy structured neural network, which uses min-operation and trapezoid membership function of fuzzy rules. So we can construct an intelligent inventory management system that make optimized decision-making for forecasting data with expert s opinion in fuzzy environment. The inventory management system uses intelligence agent and it could be adapted to a system environment change in order.

• Journal of the Korean Home Economics Association
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• v.34 no.5
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• pp.1-12
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• 1996

The purpose of this study was to develop the Self-Esteem Inventory for Children in Korea. The 772 subjects were selected from 3rd-6th grades of elementory schools and the first and second grades of middle schools in Pusan. Statistics used for data analysis were Pearson's r, Cramer's V, X2, factor analysis, multi-regression, splithalf reliability, Cronbach's α. The major findings were that 1) eight factors(home self, personality self, academic self, teacher-related self, general self, physical-appearance self, peer-related self, physical-competence self) were extracted by factor analysis, multi-regression analysis conducted to reduce the iength of inventory have drawed 38 items for the Self-Esteem Inventory for Children in Korea. 2) the discriminant coefficients of the items (Cramer's V) ranged from 0.55 to 0.67. 3) the reliability coefficients of this inventory (Cronbach's α) ranged from 0.63 to 0.81. It was concluded that Self-Esteem Inventory for children is acceptable.

• Proceedings of the Korean Geotechical Society Conference
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• 2010.09a
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• pp.722-726
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• 2010

Inventory survey is process collecting data about cut slope. It's different from inspection. It contains not only basic information about cut slope, especially location, GPS positioning, height, length, weathering, joint direction, water conditions but also level of danger and damage. Collected data are being used get at status about cut slope along national roads. And It helps judging about priority of detailed investigation. According to results of analysis, we found better method about maintenance of cut slope. Later on, if inventory research is finished, we will understand characteristics of collapse slopes.

• Journal of Distribution Science
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• v.11 no.7
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• pp.23-30
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• 2013

Purpose - The study attempts to investigate the relationship between inventory management and firm performance using a multi-dimensional aspect of inventory management with respect to lean management practices across countries. Research design, data, and methodology - 1643 manufacturing firms from Japan and the US that SIC ranges from 2000 to 3999 were chosen to conduct the empirical test. This study employs hierarchical OLS regression analysis to examine the impact of control variables, ABI, EBI, and the interaction between ABI and EBI on firm performance. Results - The result indicates that in Japan high level of inventory negatively influences the accounting flows of business, while US manufactures exhibit strong positive impact of ELI on firm performance across accounting and market measures. The results show that the complementarity between the amount and the speed of inventory does exist. Except for Tobin's q, the sign of interaction term coefficient is negative, suggesting that when the amount of inventory increases and it stays longer in a firm, market values, ROS, and ROA suffers. Conclusions - The major finding of this study is that there exist some complementarities between the scope and implication of inventory management for lean strategy across countries, particularly in U.S. and Japanese firms.

• The Journal of Asian Finance, Economics and Business
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• v.9 no.1
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• pp.121-132
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• 2022

The uncertainty regarding inventory may impart dynamic impacts on corporate-level financial decisions. Among others, a decision about capital investment is a crucial decision that requires overall financial stability. Following these theoretical notions, the current study aims to identify possible consequences of inventory volatility relating to corporate capital investment decisions. We employed ten years of data (2010-2019) of non-financial sector firms to achieve the objective. The Driscoll-Kraay model was used to quantify the regression. The statistical results imply that inventory volatility negatively influences capital investment decisions due to information asymmetry about the current financial position. Additionally, more volatility brings discrepancies in managers' investing decisions to fulfill the possible demand options of capital investment that require processing the inventory. However, based upon the statistical findings, it is suggested to corporate managers that they should consider the financial sensitivity of enterprises regarding inventory volatility. Thus, the current study introduces new thoughts regarding inventory volatility and its empirical role in determining capital investment.