인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
DBpia AI
AI 에이전트
AI 아이디어
AI 리더
AI 뷰어
Citeasy
크롬 서지관리 다운로드
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
피인용 0
초록·키워드
Purpose: This study develops a discrete-event simulation system to quantitatively assess the impact of CBM+ on RAM-C metrics—reliability, availability, maintainability, and cost—under realistic constraints, thereby supporting pre-adoption decision-making.
Methods: Software was implemented to integratively model key elements required for CBM+ analysis, including a system’s product breakdown structure (PBS), prognostics-driven maintenance logic based on the P–F interval, and a multi-echelon supply network employing a (q, r) inventory policy. The system supports various failure-time distributions and utilizes Monte Carlo simulation methods.
Results: The outcome is a functional simulation software platform built on a RAM-C framework. This flexible tool integrates reliability data, maintenance schedules, and inventory policies, and it can track and report detailed RAM-C metrics, including operational availability and life-cycle cost.
Conclusion: This practical simulation tool enables quantitative analysis for CBM+ adoption. It supports evidence-based decision-making and maintenance-policy optimization across the defense lifecycle, including acquisition, operations, and performance-based logistics (PBL) contracts.
Methods: Software was implemented to integratively model key elements required for CBM+ analysis, including a system’s product breakdown structure (PBS), prognostics-driven maintenance logic based on the P–F interval, and a multi-echelon supply network employing a (q, r) inventory policy. The system supports various failure-time distributions and utilizes Monte Carlo simulation methods.
Results: The outcome is a functional simulation software platform built on a RAM-C framework. This flexible tool integrates reliability data, maintenance schedules, and inventory policies, and it can track and report detailed RAM-C metrics, including operational availability and life-cycle cost.
Conclusion: This practical simulation tool enables quantitative analysis for CBM+ adoption. It supports evidence-based decision-making and maintenance-policy optimization across the defense lifecycle, including acquisition, operations, and performance-based logistics (PBL) contracts.
본문·목차
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UCI(KEPA) : I410-151-26-02-094593043
