• 한국산학기술학회논문지
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• 제17권6호
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• pp.291-299
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• 2016

최근 지식산업센터는 지식산업, 정보통신 관련 첨단업체들이 주로 입주하여 경제적 부가가치를 창출하는 시설로써의 역할을 담당하고 있다. 반면, 지식산업센터 내부에 설치되는 지원시설은 입주기업 지원, 그리고 근로자의 근로환경개선을 위하여 역할을 충실해야 하고, 다양한 활동을 영위할 수 있는 공간을 지원한다. 하지만 정부의 정책 지원이 해당 기업에 한하여 실행되고 있으며, 첨단지식산업센터 내 지원시설에는 어떠한 정책적 지원도 이루어지지 않고 있는 실정이다. 이에 본 연구는 근로자 근로환경 지원을 위한 시설인 지식산업센터 지원시설을 대상으로 다각적 분석을 실시하였으며, 근로자 지원시설의 분석결과, 정리하면 다음과 같다. 첫째, 지식산업센터 지원시설에 대한 적정면적 확보규정 도입이 필요하다. 둘째, 지원시설 중, 설치율이 저조한 시설에 대하여 주변시설과의 공유 방안이 필요하다. 셋째, IPA 분석결과, 상업시설 지원면적이 높은 것으로 나타났으나 문화지원시설에 대한 선호도 및 중요도가 높은 것으로 제시되어, 근로자의 근본적 욕구 및 기대에 부응할 수 있는 이용자 특성을 고려한 지원시설 구성방안이 요구되어진다. 마지막으로 근로환경에 영향을 미치는 시설은 사업초기부터 지구단위계획수법을 통한 계획적 도시관리가 적용된다면 근로자의 생산활동 지원에 많은 기여를 할 것으로 분석된다.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2005년도 추계학술대회 논문집
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• pp.954-957
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• 2005

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence is applied for many industrial product and machine tools are the center of manufacturing devices in intelligent manufacturing system. The purpose of this paper is to present the construction of Rule Base for knowledge structure that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It constructs Rule Base of knowledge used of machine toots. The constructed Rule Base facilitates the effective operation and control of machine tools and will provide a systematic way to integrate the expert's knowledge that will apply Intelligent Machine Tools.

• 벤처창업연구
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• 제9권4호
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• pp.27-39
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• 2014

기술사업화를 위한 연구개발 센터 조직은 크게 세 가지 단계로 구분된다. 첫째는 산업계의 문제를 해결하는 역량을 개발하는 것이며, 둘째는 선진국을 따라잡기 위해 수입된 기술을 창조적 모방을 통해 개발하는 것이다. 셋째 단계는 선진화된 지식창조 역량을 습득하는 것이다. 따라서 센터의 조직은 대학과 정부의 발전전략과 잘 연계되어야 한다. 본 연구는 개발도상국에게 연구센터의 개발을 통해 경제개발과 관련된 관리적 시사점을 제공하고 있다. 사례연구로 든 카자흐스탄의 경우 산업계 문제해결 단계인 첫 번째 단계에서 센터는 기술과 인적자원 측면에서 인프라구조를 구축한다. 두 번째 단계는 지식 역량을 구축하는 것으로 중앙 아시아에서 주요 산업 연구개발 허브로서의 역할을 하는 것이다. 셋째 단계에서는 센터가 선진화된 지식을 구축하여 세계수준의 지식센터를 만드는 것이다. 이같은 점에서 연구개발과 사업화 센터의 진화는 센터의 서비스 형태에 따라 다르게 나타나야 할 것이다.

• 산업경영시스템학회지
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• 제29권1호
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• pp.87-93
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• 2006

In order to implement Artificial Intelligence, various technologies have been widely used. Artificial Intelligence are applied for many industrial products and machine tools are the center of manufacturing devices in intelligent manufacturing devices. The purpose of this paper is to present the design of Decision Support Agent that is applicable to machine tools. This system is that decision whether to act in accordance with machine status is support system. It communicates with other active agents such as sensory and dialogue agent. The proposed design of decision support agent facilitates the effective operation and control of machine tools and provides a systematic way to integrate the expert's knowledge that will implement Intelligent Machine Tools.

• 한국산학기술학회논문지
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• 제15권10호
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• pp.6344-6353
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• 2014

지식산업센터는 제조업의 공장 중심에서 산업과 사회의 변화로 지식기반 및 정보통신 등 다양한 용도를 포함하게 되었다. 본 연구는 지식산업센터 관련 제도를 바탕으로 세 시기로 구분하며 선행연구를 통해 배치유형과 외부공간구성요소를 도출하고 사례를 분석하여 배치와 외부공간계획의 기본 방향을 제시하고자 한다. 연구결과, 첫째, 1999년 이전에는 차량중심으로 건물배치가 이루어졌지만 대지의 형태에 따라 중앙배치, 편측배치로 이루어졌다. 둘째, 분산배치는 저층부인 지원시설을 통합하고 고층부 공장동을 분산배치하여 부분통합배치로 건물의 단일화가 이루어졌다. 셋째, 1999년 개정된 건축법에 의해 준공업지역의 공개공지 활성화를 시작으로 외부공간이 넓어지고 건축면적이 줄어들면서 외부공간구성이 오피스나 오피스텔과 같은 업무시설의 계획기법과 유사하게 변화되고 있다.

• 지식경영연구
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• 제20권3호
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• pp.17-38
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• 2019

Rrecently, companies have made great efforts to satisfy various needs and heightened expectations of customers, and the importance of customer center as customer contact department for customer relationship management is increasing. In the knowledge ecosystem, corporate customer centers are emerging as a new alternative to acquiring corporate competitiveness by increasing sales and increasing market share by improving marketing support activities and customer relationship management at customer contact points. As a result, the interest in the customer center has increased rapidly because it provides the opportunity to contact with the customer. In addition, in the era of the fourth industrial revolution, the customer center, which is a collection of information and communication technologies, has a big databased voice recognition technology to elaborate customer service, thereby enhancing customer satisfaction and contributing to marketing through continuous interaction with customers. Of course, we have the opportunity to transform into the frontline business intelligence front for customer knowledge. This study is a comparative case study on how the customer center of K Life Insurance that takes the lead in the customer center industry has successfully renewed and established their key information systems to improve customer services and reinforce marketing support competencies. Based on the above, this study will present factors affecting successful implementation and settlement of the customer service information systems of customer centers by independently analyzing two individual cases.

• 근관절건강학회지
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• 제19권3호
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• pp.340-349
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• 2012

Purpose: This study aimed to identify the influence of knowledge and subjective health status on health promoting behavior about osteoporosis in industrial workers. Methods: The subjects were 292 industrial workers. Data were collected with structured questionnaires in July 10 to August 20, 2012. The collected data were analyzed with t-test, ANOVA, Pearson's correlation coefficients and hierarchical regression analysis by using the SPSS Win 12.0 statistics. Results: The major findings of this study were as follows; 1) The average scores of knowledge about osteoporosis, subjective health status and health promoting behavior about osteoporosis were 9.26 out of 20, 9.64 out of 14 and 39.77 out of 68. 2) There were significantly positive correlations relationship among knowledge, subjective health status and health promoting behavior. 3) The factors influencing health promoting behavior were age(${\beta}$=.069, p=.032), knowledge(${\beta}$=.026, p=.005), subjective health status(${\beta}$=.058, p<.001). Conclusion: This study suggested that we should develop preventive osteoporosis programs for industrial workers considering these results.

• 산업경영시스템학회지
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• 제28권3호
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• pp.109-114
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• 2005

The founding purpose of Business Incubation System is to induce those businessmen who have technology and promising business ideas but are lacking fund, information, and management skill, and to speed up their business establishment and enhance the level of success by providing them with managerial knowledge, production technology, design, and equipment. While some universities made Business Incubation Center to achieve the above purpose, some other universities, especially the local ones, believed that Business Incubation Center, if managed successfully, could be an accelerator picking up the sluggish local economies. This study studied the motivators that let them move in an Incubating Center, their request for support, their level of expert utilization, and the role of head of a Center. This study found a significant level of correlation among the variables such as industrial-educational cooperation, the development of common items, utilization of professors with matching majors, utilization of research professors, and transfer of technology.

• 건축사
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• 통권541호
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• pp.48-53
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• 2014

• 산업공학
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• 제25권1호
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• pp.40-51
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• 2012

Today, many manufacturing companies realize that collaboration is crucial for their survival. Especially, in the perspective of quality, the importance of collaboration is emphasized because economic loss increases exponentially while defective parts go through the process in supply chain. However, the manufacturing companies are facing two main difficulties in implementing collaborative relationships with their suppliers. First, it is difficult for the suppliers to produce reliable products due to their obsolete facilities. The problem gets worse for second- or third-tire vendors. Second, the companies experience the lack of universally understandable set of terminology and effective methodologies for knowledge representation. Ontology is one of the best approaches to expressing and processing a domain knowledge. In this paper, we propose the manufacturing ontology-based quality prediction framework to represent and share the knowledge of industrial environment and to predict product quality in manufacturing processes. In addition, we develop the ontology-based quality prediction system based on the proposed framework. We carried out a series of experiments for an injection molding process at an automotive part supplier. The experimental results demonstrated that the proposed framework and system can be successfully applicable in manufacturing industry.