스포츠 상품 시장에서 각 브랜드가 소비자에게 미치고자 하는 영향력은 여러 가지 형태로 시도 되었으며, 그 효과 또한 증명되어 가고 있다. 각 브랜드들이 자신들이 활용할 가치가 있다고 판단하여 수립한 다양한 마케팅 전략들이 증명되어가고 있는 것이다. 하지만 최근 나타난 새로운 소비 유형이라 할 수 있는 스포츠 상품 수집가를 활용한 마케팅 전략은 지금껏 그 영향력이 실증적으로 검증된 바가 없었다. 기존의 스포츠 상품 시장에서 나타난 수집 행위에 이해도가 매우 낮았기 때문이다. 어느 정도 한계에 봉착했다고 여겨지는 스포츠 상품 시장에 새로운 마케팅 전략이 필요하다고 판단한 도전적 사고에서 본 연구를 시작하였으며 스포츠 상품 수집가를 활용한 마케팅 전략을 수립함에 있어서 그 영향력이 형성되는 경로를 설정하고 증명하는데 그 목적을 두고 있다. 이 연구의 목적을 달성하기 위하여 가상의 스포츠 상품 수집가의 상품 설명에 대한 자극물을 접한 잠재 소비자 231명을 대상으로 SPSS 21.0과 AMOS 20.0을 이용하여 빈도분석, 신뢰도분석, 상관관계분석 및 확인적 요인분석과 구조방정식을 이용하였다. 이 연구에서 도출된 결과를 바탕으로 하여 스포츠 상품 시장에서 스포츠 상품 수집가들이 보유하고 있는 전문성을 바탕으로 하는 새로운 마케팅 전략의 경로를 발견하였다고 할 수 있으며, 이를 바탕으로 침체된 우리나라 스포츠 상품 시장에 새로운 성장 동력의 하나로 작용할 수 있기를 기대하는 바이다.

The purpose of this paper is to examine the effects on reliability of equipment or product which spends a great deal of its time in the dormant condition. Many systems experienced periods of dormancy throughout their life cycle, such as periods of operati

Recently, according to the total quality management environment, the necessity of the systematic administration about the quality information is gradually enlarged as to vehicle related company. Accordingly, related companies require the operation of the information management system matched with the quality administration task level. And through the storage and share of the efficient quality information, they try to solve the customer claim about the quality and prevent the quality problem recurrence of product. This research suggests the standard business process of the auto part supplier for the efficient management of the quality information and the quick correspondence of the quality problem. In addition, by building and managing the quality information management system will be able to expect the more efficient quality management and the product reliability insurance.

Recently, product-reliability and process-reliability in product development processes has been regarded as an important issue in many manufacturers. TRIZ which is theory for inventive solving is required to obtain reliability of each process. To solve the technological problems, TRIZ provides problems can be occurred in product development processes as a contradiction matrix based on 40 creative invention principles with alternatives for physical and technological contradiction. This paper suggests the method for inventive solving to ensure the reliability assurance of product development processes based on TRIZ.

Parametric life-cycle cost(LCC) models have been integrated with traditional design tools, and used in prior work to demonstrate the rapid solution of holistic, analytical tradeoffs between detailed design variations. During early designs stages there may be competing concepts with dramatic differences. Additionally, detailed information is scarce, and decisions must be models. for a diverse range of concepts, and the lack of detailed information make the integration make the integration of traditional LCC models impractical. This paper explores an approximate method for providing preliminary life-cycle cost. Learning algorithms trained using the known characteristics of existing products be approximated quickly during conceptual design without the overhead of defining new models. Artificial neural networks are trained to generalize on product attributes and life cycle cost date from pre-existing LCC studies. The Product attribute data to quickly obtain and LCC for a new and then an application is provided. In additions, the statistical method, called regression analysis, is suggested to predict the LCC. Tests have shown it is possible to predict the life cycle cost, and the comparison results between a learning LCC model and a regression analysis is also shown

In recent years the design of modular products has become the focus of significant research in the area of design theory and methodology. This phenomenon is due to the power of modularity to achieve certain product objectives. Product modularity has many advantages but it can cause reliability problem which relates to simplicity, clarity, and unity of product components. This paper uses fuzzy cluster identification for classifying the functions into several modules and entropy for measuring reliability. We present the relationship between product modularity and reliability according to the number of modules and components.