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[국내논문] 군용차량을 위한 디젤기관의 방산기술 식별기준 정립에 관한 연구
A Study on Establishment of Criteria to Identify the Defense Industrial Technology of Diesel Engine for Military Vehicle 원문보기

한국융합학회논문지 = Journal of the Korea Convergence Society, v.10 no.3, 2019년, pp.177 - 184  

윤흥수 (명지대학교 대학원 보안경영공학과) ,  류연승 (명지대학교 대학원 보안경영공학과)

초록
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방산기술이 복제되거나 방해기술이 발달되어 그 가치와 효용이 낮아지는 것을 방지하고 부적절한 수출을 방지하기 위한 보호가 필요하여 2015년도에 방위산업기술보호법이 제정되었다. 방산기술이란 방위산업과 관련된 국방과학기술 중에서 국가안보를 위하여 보호되어야 하는 기술을 의미한다. 그러나 현재 방산기술 보호체계 중에서 보호대상 기술의 식별 및 관리 체계의 기술식별 기준이 법규화 되어 있지 않다. 이에 본 연구에서는 델파이 설문을 통하여 141개 방산기술 중에서 고효율 내연기관 추진 기술과 관련 있는 디젤기관 요소기술 식별기준을 정립하고 방산기술 보호체계 중 보호대상 기술의 식별 및 관리 체계를 개선하였다. 연구결과로 디젤기관 요소기술 식별기준으로 작전 운용성, 내구성, 안전성, 계열화 및 모듈화 등을 정립하였다.

Abstract ▼ AI-Helper 아이콘AI-Helper

The Defense Technology Security Act was enacted in 2015 to protect the defense industrial technology from being duplicated or interfering technologies being developed, which prevents its value and utility from deterioration and prevents inappropriate export. Defense industrial technology refers to t...

Keyword

#방산기술   #방위산업기술보호법   #군용차량   #디젤기관  

표/그림 (7)

AI 본문요약
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* AI 자동 식별 결과로 적합하지 않은 문장이 있을 수 있으니, 이용에 유의하시기 바랍니다.

제안 방법

  • The results of the survey and the research model were then verified and the reliability was secured through the Content Validity Ratio(CVR) evaluation and the Kendall's W test on the Delphi survey results.
  • In order to evaluate and verify the validity of selected evaluation items selected through literature reviews and expert interviews, standards were established from 2 times of Delphi survey, conducted for 8 experts from June 14 to August 2, 2018. The number of expert groups in the Delphi survey has no established rules[13], and Lynn(1986) suggested that the number of expert groups to verify the validity of the content should be preferably 3 to 10[14].
  • The CVR evaluation was used to verify whether the contents of each item were valid about the Delphi survey results. The CVR value was calculated in the process of assigning the total number of expert groups who responded to the survey and the number of expert groups who responded the CVR survey to be valid into the CVR formula. The result was judged to be valid if the value was more than the CVR minimum value according to the number of experts, If the value is less than the minimum value, it is judged to be invalid and deleted[16].
  • In the second survey, it was concluded that experts agreed on the establishment of the core technology identification criteria, so survey results of Delphi first and second were put together and established as diesel engine core technology identification criteria. However, since there are limitations to obtain various opinions with a relatively small number of Delphi survey subjects, it is necessary to increase the number of survey subjects to conduct research.

대상 데이터

  • The evaluation items were selected through consensus after collecting opinions from 3 experts interview. One doctor of defense acquisition, one automotive engineering professor, and one senior research engineer of the military vehicle development were selected as experts. Interviews were conducted via email, telephone, and direct interviews.
  • The number of expert groups in the Delphi survey has no established rules[13], and Lynn(1986) suggested that the number of expert groups to verify the validity of the content should be preferably 3 to 10[14]. In order to increase the reliability of the survey results, 8 experts except the 3 experts who participated in the interview stage were selected again. 8 experts consisted of 4 automotive engineering professors, and 4 research engineers of the military vehicle development.
  • In order to increase the reliability of the survey results, 8 experts except the 3 experts who participated in the interview stage were selected again. 8 experts consisted of 4 automotive engineering professors, and 4 research engineers of the military vehicle development.
  • As a result of review of the literature, the evaluation items of the core technology identification criteria related to the diesel engine technology were extracted to 11 items. Criteria #1 to #7 were constituted with criteria to be considered when developing the military vehicles, suggested by B.

이론/모형

  • In this study, the 5-point Likert scale was used for the evaluation of each item. Therefore, the number of experts who selected more than 3 points was judged to be the number of experts who answered that the question to be valid.
본문요약 정보가 도움이 되었나요?

참고문헌 (21)

  1. National Law Information Center. (2018). http://www.law.go.kr/LSW/lsRvsRsnListP.do?lsId012437&chrClsCd010102. 

  2. Defense Acquisition Program Administration. (2017). Defense Technology Security Guide 11-1690000-001928-01, 6-7. 

  3. National Law Information Center. (2018). http://www.law.go.kr/법령/방위산업기술보호법. 

  4. Korea Automotive Technology Institute. (2013). A Study on the Optimized of Military Vehicles According to Type of An Army, 8-15. 

  5. B. K. Lee. (2010). A Selection Model of the Development Factors of Military Vehicles Using Analytic Hierarchy Process. Doctors dissertation. Kwangwoon University, 8-10. 

  6. J. B. Lee. (2009). A legal study on the protection of industrial technology in corporate mergers and acquisitions(M&A). Journal of Korean Branch of International Association of Constitutional Law, 297-298. 

  7. B. C. Won. (2017). http://www.boannews.com/media/view.asp?idx55492&kind1. 

  8. Defense Acquisition Program Administration. (2017). Defense Technology Security Act Q&A, 23. 

  9. Defense Agency for Technology and Quality. (2015). A Study of identification of Defense Industrial Technology, 53-55. 

  10. Sungkyunkwan University industry-Academy Collaboration Foundation. (2016). A Defense Development Plans of Defense Industrial Technology, viii-ix. 

  11. A. R. Hur. (2018). A Study on Classification of Defense Industrial Technology Information. Masters dissertation. Myongji University, 1-3. 

  12. H. S. Yoon & Y. S. Ryu. (2018). A Study on Improvement of Test & Evaluation of Vehicle Part in Mixed Equipment and Defense Industrial Technology, Journal of Korea Convergence Society, 9(7), 241-249. 

  13. Rowe, G., & Wright, A. M. (2001). Judgment change during Delphi-like procedures: The role of majority influence, expertise, and confidence. Technological Forecasting and Social Change, 72(4), 377-399. 

  14. M. R. Lynn. (1986). Determination and quantification of content validity. Nursing Research, 35(6), 382-385. 

  15. Y. J. Yoon & J. I. Lee. (1998). An Analysis of the Reliability of Technology Forecasting Outcomes, Journal of Korea Technology Innovation Society, 1(2), 276. 

  16. Lawshe, C. H. (1975). A quantitative approach to content validity. Personnel Psychology, 28(4), 563-575. 

    상세보기 crossref

  17. H. J. Noh. (2015). Nonparametric statistical analysis and correspondence analysis using SPSS. JiPhilmedia, 210. 

  18. H. J. Noh & H. Y. Jung. (2008). Introduction to statistical analysis by SPSS. Hanol publisher, 201. 

  19. Schmidt, R. C. (1997). Managing Delphi surveys using nonparametric statistical techniques. Decision Sciences Journal, 28(3), 763-774. 

    상세보기 crossref

  20. Sidney Chaves, Jose Afonso Mazzon, and Cesar Alexandre de Souza. (2012). Proposition of A Method to Measure Rankings Using the Delphi Technique, Future Journal, 4(2), 52-75. 

  21. B. K. Lee & Y. K. Cho. (2010). Priority Decision based on User's Requirements for the Development of Military Vehicles. Journal of The Korean Society of Automotive Engineers, 18(6), 122-129. 

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