Reliability analysis of the components frequently starts with the data that manufacturer provides. If enough failure data are collected from the field operations, the reliability should be recomputed and updated on the basis of the field failure data. However, when the failure time record for a component contains only a few observations, all statistical methodologies are limited. In this case, where the failure records for multiple number of identical components are available, a valid alternative is combining all the data from each component into one data set with enough sample size and utilizing the useful information in the censored data. The ROK Navy has been operating multiple Patrol Killer Guided missiles (PKGs) for several years. The Korea Multi-Function Control Console (KMFCC) is one of key components in PKG combat system. The maintenance record for the KMFCC contains less than ten failure observations and a censored datum. This paper proposes a Bayesian approach with a Dirichlet mixture model to estimate failure time density for KMFCC. Trends test for each component record indicated that null hypothesis, that failure occurrence is renewal process, is not rejected. Since the KMFCCs have been functioning under different operating environment, the failure time distribution may be a composition of a number of unknown distributions, i.e. a mixture distribution, rather than a single distribution. The Dirichlet mixture model was coded as probabilistic programming in Python using PyMC3. Then Markov Chain Monte Carlo (MCMC) sampling technique employed in PyMC3 probabilistically estimated the parameters’ posterior distribution through the Dirichlet mixture model. The simulation results revealed that the mixture models provide superior fits to the combined data set over single models.

We focus on the weapon target assignment and fire scheduling problem (WTAFSP) with the objective of minimizing the makespan, i.e., the latest completion time of a given set of firing operations. In this study, we assume that there are m available weapons to fire at n targets (> m). The artillery attack operation consists of two steps of sequential procedure : assignment of weapons to the targets; and scheduling firing operations against the targets that are assigned to each weapon. This problem is a combination of weapon target assignment problem (WTAP) and fire scheduling problem (FSP). To solve this problem, we define the problem with a mixed integer programming model. Then, we develop exact algorithms based on a dynamic programming technique. Also, we suggest how to find lower bounds and upper bounds to a given problem. To evaluate the performance of developed exact algorithms, computational experiments are performed on randomly generated problems. From the results, we can see suggested exact algorithm solves problems of a medium size within a reasonable amount of computation time. Also, the results show that the computation time required for suggested exact algorithm can be seen to increase rapidly as the problem size grows. We report the result with analysis and give directions for future research for this study. This study is meaningful in that it suggests an exact algorithm for a more realistic problem than existing researches. Also, this study can provide a basis for developing algorithms that can solve larger size problems.

The Cooperative Engagement Capability (CEC) System produces a synergy between the sensors and shooters that are used on various platforms by integrating them. Even the US Navy has been recently adopting the CEC system that maximizes the effectiveness of the air defense operations by efficiently coordinating the dispersed air defense assets. The Navy of other countries are conducting research studies on the theory and application methods for the CEC system. The ROK Navy has limited air defense capabilities due to its independent weapons systems on battle ships. Therefore, the ROK Navy is currently going through a phase where research on proving the validity of building the CEC system because it will provide a way to overcome the limit of the platform based air defense capability. In this study, our goal is to propose methods that maximize the air defense capability of ROK Navy, identify the available assets for constructing the CEC system, and estimate effects of the CEC system when it is applied to the naval operations. In addition, we will provide a simple model that was developed to estimate these effects and a case study with virtual data to demonstrate the effects of the system when it is applied to the naval operations. The research result of this study will provide a way for building the basis of the Korean CEC system.

본 논문은 기술거래 네트워크와 기술거래 관리의 개념을 제시하고 기술도입자가 도입하고자 하는 기술을 제공하는 최적의 기술제공자를 선택하는 방법론을 제시하는데 목적이 있다. 기술거래 네트워크는 기술제공자, 기술마케터, 기술도입자로 구성되며 기술거래 관리는 기술평가, 기술거래, 기술사업화의 단계로 이루어진다. 기술거래 네트워크에서 기술의 연관도와 기술도입비용의 최적화방법을 통해 기술도입자가 도입하고자 하는 기술을 제공하는 최적의 기술제공자를 선택하는 방법론을 제시하며 이 방법은 기술도입자가 기술을 선택하는데 있어서 유용하게 사용될 것으로 기대된다. 기술제공자 선택 방법론은 기술평가 프로세스와 기술제공자 선택 프로세스로 구성된다. 기술평가 프로세스에서는 기술성에 중점을 둔 새로운 개념의 기술평가방법을 개발하여 기술연관도를 정량적으로 산출하였고 기술제공자 선택 프로세스에서는 기술도입에 따른 제반비용을 정의한 후 기술연관도가 최대가 되고 기술도입비용이 최소가 되는 수리모형을 목표계획법을 이용하여 설계하였다. 기술도입자의 요구조건에 대한 성능을 효과적으로 분석하기 위하여 하위기술 별로 방향성을 부여하여 기술네트워크를 각각 구성하였고 이를 효과적으로 목표계획법에 반영하였다. 사례분석에서는 차기전차 기술제공자 선택 사례를 분석하였다.