• 한국정보시스템학회지:정보시스템연구
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• 제30권1호
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 춘계 학술발표회 초청강연 및 논문집
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• pp.858-862
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• 2008

KICT has been carrying out inventory research on the cut slopes of national roads. Inventory research results are basic data used in cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Cut slope inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper drew the distribution of dangerous cut slopes using inventory data in Chungcheongdo, then verified an efficiency on distribution of dangerous cut slopes by comparing occurrence frequency of real collapsed cut slopes.

• 한국지반공학회:학술대회논문집
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• 한국지반공학회 2008년도 추계 학술발표회
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• pp.980-983
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• 2008

KICT has been carrying out inventory research on the cut slopes of national roads. Inventory research results are basic data used in cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Cut slope inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper will draw dangerous cut slope and more important inventory data in Chungcheongdo via correlation analysis.

• 한국방재학회:학술대회논문집
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• 한국방재학회 2008년도 정기총회 및 학술발표대회
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• pp.585-588
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• 2008

KICT has been carried out inventory research on the cut slopes of national roads. Inventory research results are basic data using cut slope management system. Inventory data are classified by general status, cut slope characteristics and inspector opinion. Inventory data are utilized to figure out dangerous slopes and decide survey ranking of detailed safety diagnostication. This paper drew the distribution area of dangerous cut slopes using inventory data in Chungcheongdo, and verified efficiency on distribution area of dangerous cut slopes by comparing occurrence frequency of real collapsed cut slopes.

• 경영과학
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• 제30권3호
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• pp.17-31
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• 2013

The purpose of this paper is to illustrate the importance of identifying and considering 'purchase dependence' when purchase of an item is dependent on availability of other items demanded in the same order. This paper is the first study to develop an inventory model for purchase-dependent inventory systems. Through simulation experiments, we demonstrate that the developed inventory model incurs less inventory operations cost than other inventory models that ignore purchase dependence. For empirical validation of the developed inventory model, the actual inventory data at the Hyundai Engine Europe Service Center is used. We explain the process of identifying purchase dependencies among items through a data mining technique. The empirical study results in similar results to the simulation experiment, demonstrating that the developed inventory model is applicable to real situations.

• 한국대기환경학회지
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• 제30권1호
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• pp.26-36
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• 2014

The uncertainty assessment is important to improve the reliability of emission inventory data. The DARS (Data Attribute Rating System) have recommended as the uncertainty assessment technic of emission inventory by U.S. EPA (Environmental Protection Agency) EIIP (Emission Inventory Improvement Program). The DARS score is based on the perceived quality of the emission factor and activity data. Scores are assigned to four attributes; measurement/method, source specificity, spatial congruity and temporal congruity. The resulting emission factor and activity rate scores are combined to arrive at an overall confidence rating for the inventory. So DARS is believed to be a useful tool and may provide more information about inventories than the usual qualitative grading procedures (e.g. A through E). In this study, the uncertainty assessment for 2009 CAPSS (Clean Air Policy Support System) emission inventory is conducted by DARS. According to the result of this uncertainty assessment, the uncertainty for fugitive dust emission data is higher than other sources, the uncertainty of emission factor for surface coating is the highest value, and the uncertainty of activity data for motor cycle is the highest value. Also it is analysed that the improvement of uncertainty for activity data is as much important as the improvement for emission factor to upgrade the reliability of CAPSS emission inventory.

• Journal of the Korean Data and Information Science Society
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• 제19권4호
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• pp.1345-1352
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• 2008

An inventory with constant demand is studied. We adopt a renewal argument to obtain the transient and stationary distribution of the level of the inventory. We show that the stationary distribution can be also derived by making use of either the level crossing technique or the renewal reward theorem. After assigning several managing costs to the inventory, we calculate the long-run average cost per unit time. A numerical example is illustrated to show how we optimize the inventory.

• 한국인터넷방송통신학회논문지
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• 제18권5호
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• pp.237-244
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• 2018

중소기업 제조공장의 스마트팩토리 수준이 현재에는 기초 수준으로 창고를 관리하기 위해 재고 입출입에 따른 정확한 재고량을 파악하는 시스템이 부족하다. 또한 근로자 수작업과 경험에 의한 생산방식으로 데이터 손실로 정확한 자재를 관리하기 어려운 상황이다. 이를 해결하기 위해 근로자의 재고 파악을 위한 수작업을 최소화하며 자동화를 향상시키기 위해 재고량 자동 수집을 진행한다. 본 논문에서는 IoT기반의 자율이동모듈을 이용한 스마트 창고관리 시스템으로 자율이동모듈이 창고를 이동하면서 재고 보관함의 데이터를 수집한다. 이는 해당 보관함의 자재들 파악하기 위해 카메라 모듈이 비전처리 방식 통해 재고보관함의 네임텍을 인지한다. 인지한 문자화 처리 결과가 일치할 때 센서에 의해 측정된 데이터가 서버로 전달되고 데이터를 처리하여 데이터베이스에 저장한다. 저장된 데이터는 관리자용 웹 기반 모니터링 환경에서 실시간 재고량을 파악할 수 있다. 이를 통해 수작업을 줄이고 자동화된 재고관리시스템의 효과를 기대한다.

• 산업경영시스템학회지
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• 제43권3호
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.

• 한국지반공학회논문집
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• 제25권12호
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• pp.27-35
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• 2009

한국건설기술연구원(KICT)과 한국시설안전공단(KISTEC)에서는 전국 국도변에 분포하고 있는 절토사면에 대한 현황조사를 2006년부터 수행하고 있다. 절토사면 현황조사는 절토사면 정밀안전진단과는 달리, 현장에서 기본적인 육안조사를 통해 얻을 수 있는 여러가지 절토사면 특성에 대한 간단한 조사로 절토사면 유지관리의 기본이 되는 자료를 수집하는 것이다. 현황조사는 조사 대상 절토사면의 일반현황, 절토사면 특성, 조사자 소견으로 구성된다. 조사된 자료는 전국에 분포하고 있는 위험절토사면을 파악하고 정밀 안전진단의 조사순위를 결정하는데 활용된다. 본 논문에서는 SPSS (Statistical Package for the Social Sciences) 통계처리 프로그램을 이용하여 2006년부터 2008년까지 강원도와 충청도 지역에서 수집된 10,461개의 국도변 절토사면 현황조사 자료에 대하여 상관분석을 하였다. 현황조사 항목으로 부터 산출한 절토사면의 위험도 점수와 현황조사 항목간의 상관성을 분석하여 상관계수를 산출하였고 이를 통해 절토사면 위험도 점수에 보다 많은 영향을 미치는 현황조사 항목을 평가해보았다. 상관분석결과, 뜬돌 및 낙석 분포, 불연속면의 방향성 및 상부자연사면의 경사가 절토사면 위험도 점수에 영향을 크게 미치는 항목임을 알 수 있었다. 또한, 위험도 점수에 영향을 미치는 항목은 지역별로 약간의 차이가 나타남을 알 수 있었다. 추후, 절토사면 현황조사가 완료되면 우리나라에 분포하고 있는 절토사면의 지역별 특성을 파악할 수 있을 것으로 생각된다.