현행 강구조내진설계철학의 근거인 역량설계법(capacity design method)에 의할 때 중심가새골조의 에너지 소산요소인 가새가 인장항복하고 압축좌굴 할 때 보와 기둥은 탄성상태를 유지해야 한다. 중심가새골조의 대표적 형식인 역V형 가새골조의 경우 가새가 좌굴하면 인장가새와 압축가새 사이에 수직불균형력이 발생하여 보와 기둥에 추가적인 하중이 가해지므로 이를 반영하여 보 및 기둥 부재를 탄성설계해야 한다. 지진하중 발생시에 모든 가새가 동시에 좌굴하지 않는다는 것은 잘 알려져 있지만, 특정층의 좌굴발생 유무를 정확히 예견하는 방법은 아직 존재하지 않는다. 따라서 현행 설계기준에서는 모든 층에서의 동시 좌굴을 가정하여 보수적으로 설계하거나 시스템초과강도계수로 증폭된 특별지진하중에 대해 기둥부재를 탄성설계하는 경험적이고 우회적인 방법을 제시하고 있다. 이를 개선하기 위한 첫 번째 단계는 우선 지진 내습시에 좌굴발생이 예견되는 층을 정확히 예측하는 것이다. 본 논문에서는 1차모드 푸쉬오버해석, 고차모드 푸쉬오버해석, 선형고유치해석에 의해 좌굴층을 예측한 후 이를 토대로 가새좌굴이 기둥에 가하는 축력을 산정하는 세 가지의 새로운 방법, 즉 FMPM(First Mode Pushover Method), MMPM (Multi-Mode Pushover Method), MSBM(Mode Shape Based Method)을 제안하였다. 이 세 가지 방안의 핵심은 좌굴 포텐셜이 높은 것으로 감지된 층의 수직불균형력은 선형합산하고 그렇지 않은 층의 수직불균형력은 SRSS(square root of sum of squares)법에 의해 조합하여 기둥에 가해지는 축력을 산정하는 것이다. 3층에서 15층에 이르는 5개의 골조모델에 대해 20개 지진가속도기록을 입력으로 한 방대한 비선형동적해석을 수행하여 제시한 방안의 타탕성을 검증하였다. 세 방법에 의한 기둥설계 결과는 모두 현행 설계기준의 방법보다 기둥의 물량을 대폭 줄이면서도 기둥부재가 탄성상태를 유지하여 역량설계법의 철학을 만족시켰다. 특히 MSBM은 간단한 선형 고유치해석결과만을 이용하지만 본 연구에서 가장 정확한 축력산정법인 MMPM과 큰 차이를 보이지 않을 정도로 정확하다. 실무 여건에서도 사용 가능한 방법으로 MSBM을 추천한다.
This study analyzes the effect of Computer Aided Innovation (CAI) to improve R&D Capabilities empirically. Survey was distributed by e-mail and Google Docs, targeting CTO of 235 SMEs. 142 surveys were returned back (rate of return 60.4%) from companies. Survey results from 119 companies (83.8%) which are effective samples except no-response, insincere response, estimated value, etc. were used for statistics analysis. Companies with less than 50billion KRW sales of entire researched companies occupy 76.5% in terms of sample traits. Companies with less than 300 employees occupy 83.2%. In terms of the type of company business Partners (called 'partners with big companies' hereunder) who work with big companies for business occupy 68.1%. SMEs based on their own business (called 'independent small companies') appear to occupy 31.9%. The present status of holding IT system according to traits of company business was classified into partners with big companies versus independent SMEs. The present status of ERP is 18.5% to 34.5%. QMS is 11.8% to 9.2%. And PLM (Product Life-cycle Management) is 6.7% to 2.5%. The holding of 3D CAD is 47.1% to 21%. IT system-holding and its application of independent SMEs seemed very vulnerable, compared with partner companies of big companies. This study is comprised of IT infra and IT Utilization as CAI capacity factors which are independent variables. factors of R&D capabilities which are independent variables are organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability. The highest average value of variables was 4.24 in organization capability 2. The lowest average value was 3.01 in IT infra which makes users access to data and information in other areas and use them with ease when required during new product development. It seems that the inferior environment of IT infra of general SMEs is reflected in CAI itself. In order to review the validity used to measure variables, Factors have been analyzed. 7 factors which have over 1.0 pure value of their dependent and independent variables were extracted. These factors appear to explain 71.167% in total of total variances. From the result of factor analysis about measurable variables in this study, reliability of each item was checked by Cronbach's Alpha coefficient. All measurable factors at least over 0.611 seemed to acquire reliability. Next, correlation has been done to explain certain phenomenon by correlation analysis between variables. As R&D capabilities factors which are arranged as dependent variables, organization capability, process capability, HR capability, technology-accumulating capability, and internal/external collaboration capability turned out that they acquire significant correlation at 99% reliability level in all variables of IT infra and IT Utilization which are independent variables. In addition, correlation coefficient between each factor is less than 0.8, which proves that the validity of this study judgement has been acquired. The pair with the highest coefficient had 0.628 for IT utilization and technology-accumulating capability. Regression model which can estimate independent variables was used in this study under the hypothesis that there is linear relation between independent variables and dependent variables so as to identify CAI capability's impact factors on R&D. The total explanations of IT infra among CAI capability for independent variables such as organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability are 10.3%, 7%, 11.9%, 30.9%, and 10.5% respectively. IT Utilization exposes comprehensively low explanatory capability with 12.4%, 5.9%, 11.1%, 38.9%, and 13.4% for organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability respectively. However, both factors of independent variables expose very high explanatory capability relatively for technology-accumulating capability among independent variable. Regression formula which is comprised of independent variables and dependent variables are all significant (P<0.005). The suitability of regression model seems high. When the results of test for dependent variables and independent variables are estimated, the hypothesis of 10 different factors appeared all significant in regression analysis model coefficient (P<0.01) which is estimated to affect in the hypothesis. As a result of liner regression analysis between two independent variables drawn by influence factor analysis for R&D capability and R&D capability. IT infra and IT Utilization which are CAI capability factors has positive correlation to organization capability, process capability, human resources capability, technology-accumulating capability, and collaboration capability with inside and outside which are dependent variables, R&D capability factors. It was identified as a significant factor which affects R&D capability. However, considering adjustable variables, a big gap is found, compared to entire company. First of all, in case of partner companies with big companies, in IT infra as CAI capability, organization capability, process capability, human resources capability, and technology capability out of R&D capacities seems to have positive correlation. However, collaboration capability appeared insignificance. IT utilization which is a CAI capability factor seemed to have positive relation to organization capability, process capability, human resources capability, and internal/external collaboration capability just as those of entire companies. Next, by analyzing independent types of SMEs as an adjustable variable, very different results were found from those of entire companies or partner companies with big companies. First of all, all factors in IT infra except technology-accumulating capability were rejected. IT utilization was rejected except technology-accumulating capability and collaboration capability. Comprehending the above adjustable variables, the following results were drawn in this study. First, in case of big companies or partner companies with big companies, IT infra and IT utilization affect improving R&D Capabilities positively. It was because most of big companies encourage innovation by using IT utilization and IT infra building over certain level to their partner companies. Second, in all companies, IT infra and IT utilization as CAI capability affect improving technology-accumulating capability positively at least as R&D capability factor. The most of factor explanation is low at around 10%. However, technology-accumulating capability is rather high around 25.6% to 38.4%. It was found that CAI capability contributes to technology-accumulating capability highly. Companies shouldn't consider IT infra and IT utilization as a simple product developing tool in R&D section. However, they have to consider to use them as a management innovating strategy tool which proceeds entire-company management innovation centered in new product development. Not only the improvement of technology-accumulating capability in department of R&D. Centered in new product development, it has to be used as original management innovative strategy which proceeds entire company management innovation. It suggests that it can be a method to improve technology-accumulating capability in R&D section and Dynamic capability to acquire sustainable competitive advantage.