This study studied a system that can redesign the production site layout and respond with dynamic simulation through fabric production process innovation for smart factory promotion and digital-oriented decision making of the production process. We propose to reflect the required throughput and throughput per unit facility of fabric production process as probability distribution, and to construct data-driven metabolism such as data collection, data conversion processing, data rake generation, production site monitoring and simulation utilization. In this study, we demonstrate digital-centric field decision smartization through architectural design for the smartization of fabric production plants and dynamic simulations that reflect it.

The established supply chain format has been radically changing from a three-month production to a shortened lead-time in the fashion industry. The faster pace of fashion trends, changing consumer lifestyle, and consequent demands for newness have been mainly attributed to the rapid development of high-tech information systems and mass communication. In particular, global fast-fashion leaders have become more successful by producing not as was initially planned and forecasted, but with an agility subject to customer responses. Latest customer trends are captured quickly, and production and distribution is steered to meet the response. In order to further maximize benefits and efficiency in a sustainable manner, the fast-fashion industry is seeking a production optimization model under which product attributes are defined in a short period of time, and an optimal quantity of products by style is produced. This paper aims to provide an optimal production quantity which subsequently requires an optimal parts procurement from the perspective of the supplier. This is obtained in order to minimize the cost function by identifying cost factors through an economic analysis technique. In this study, we propose a model for optimal production and its parts procurement to maximize target sales and profits by taking inventory and pricing into account.

오늘날 물류 서비스 산업에서는 수요예측을 통해 불확실성을 줄여나가는 것이 경영상 매우 중요한 이슈로 제기되고 있다. 비교적 시장 점유율이 견고하게 유지되는 제조산업과는 달리 물류 서비스 산업은 매우 빠른 속도로 시장이 성장하고 변화하기 때문에, 시장 환경의 변화를 반영하여 정확한 수요 예측에 기반한 적절한 물류 서비스 공급을 위한 운송 및 인력 공급 계획을 수립하여 운용하여야 한다. 본 연구는 물류 서비스 업계를 위하여 추세 요소, 계절 요소 등 수요에 영향을 미치는 요소를 분석하고, 영향 효과를 산출하여 물류 서비스 산업을 위한 수요예측 시스템에 반영하는 방안을 연구하였다. 특히 지역 특산물, 기상효과, 음력으로 발생하는 명절 효과 등 수요를 크게 변화시키는 중요 영향 요소에 의한 수요 변동을 수요 예측에 활용하는 방안을 도출함으로써, 물류 서비스 산업계의 수요 예측을 위하여 분해법(Decomposition Method)을 제시하였다.

The current environment of technological and competitive changes influences not only the business R&D environment but also government driven national R&D strategies. Open innovation has now become an important paradigm that is replacing the outdated paradigm of closed innovation. Many companies and nations have been increasing R&D investment because R&D has been considered a driving force for national and corporate competitive advantage. The purpose of this paper is to evaluate and compare the performance of R&D focused on open innovation according to scientific and technological outputs which is based on paper publications, patents and etc. Comparisons should not be only based on the quantity but also on the quality of the output. This paper shows that it is possible to develop DEA models that utilize the Analytical Hierarchical Process in order to transform the qualitative index into a quantitative index. Hence, the relative efficiency for R&D organizations is obtained based on both quantity and quality outputs and subsequently provides comprehensive and realistic methods for decision makers to identify levels of project efficiency.

This paper proposes a computation model of the quantity supplied to optimize inventory costs for the fast fashion. The model is based on a forecasting, a store and production capacity, an assortment planning and quick response model for fast fashion retai

수리가능 제품은 가격 비싸고 중요성이 크면서 새 제품을 구매하기 어려운 부품을 의미하며, 항공기 또는 선박의 엔진 등을 들 수 있다. 수리가능 제품에 대하여 고장이 발생할 경우 가용성을 유지하기 위하여 즉지 교체하여야 하고, 교체된 부품은 수리에 들어가야 한다. 이러한 문제에 대한 통제 시스템은 시스템의 효율성을 결정하는 중요한 요소이기 때문에, 다양한 시스템 구성에 대하여 많은 연구가 이루어져 왔다. 본 연구에서는 우선 중앙 수리기지와 여러 지역 수리

The purpose of this paper is to suggest a supplier and buyer’s pricing decision strategy model with discount-policy over a long-term replenishment contract in a supply chain environment by small and medium size manufacturing company. We assume that the bu

This paper reviews a case study of the use of eCRM weblog analysis for understanding of customer information and Customer-specific marketing Strategy by Korea's leading insurance company with the changing situation of the business environment due to the i

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic prog

The traditional portfolio optimization problem is to find an investment plan for securities with reasonable trade-off between the rate of return and the risk. The seminal work in this field is the mean-variance model by Markowitz, which is a quadratic programming problem. Since it is now computationally practical to solve the model, a number of alternative models to overcome this complexity have been proposed. In this paper, among the alternatives, we focus on the Mean Absolute Deviation (MAD) model. More specifically, we developed an algorithm to obtain an optimal portfolio from the MAD model. We showed mathematically that the algorithm can solve the problem to optimality. We tested it using the real data from the Korean Stock Market. The results coincide with our expectation that the method can solve a variety of problems in a reasonable computational time.