Initial operational capability of future weapon systems and field test method using digital twin

Gakgyu Kim, Kangkyun Jin, Yongjun Cho, Kyoung-Sop Won
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Abstract

The application of artificial-intelligence technology to weapon systems, is difficult to use in military applications for such reasons as killing or wounding problems, ethical problems, and field environment considerations; therefore, more-sophisticated techniques and development are required for testing and evaluation. There is an increasing demand for advanced weapon systems that incorporate new technologies, such as artificial intelligence, and for electrification, and a new paradigm that can confirm and verify the performance required for field operations is required. Therefore, through case studies on digital twins, a plan for field testing and initial operational capability in future weapon systems was developed. Five development directions were identified, including policies and systems, organization, establishment of infrastructure, and utilization plans, to establish a field test and initial operational capability. In addition, studies on economic ripple effects and cost-effectiveness were conducted based on application cases of digital twins in the private sector. An optimal method for users to safely verify performance by utilizing the digital twin method to overcome the difficulties of testing and evaluating weapon systems with new technologies from the time when the weapon system requirements are determined to mass production is proposed.
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未来武器系统的初始作战能力和使用数字孪生的现场测试方法
将人工智能技术应用于武器系统,由于杀伤问题、伦理问题和战场环境考虑等原因,难以在军事应用中使用;因此,测试和评估需要更复杂的技术和开发。对结合人工智能等新技术和电气化的先进武器系统的需求日益增加,需要一种能够确认和验证野战作战所需性能的新范例。因此,通过数字孪生的案例研究,制定了未来武器系统的现场测试和初始作战能力计划。确定了五个发展方向,包括政策和制度、组织、基础设施的建立和利用计划,以建立现场测试和初始操作能力。此外,根据数字孪生在私营部门的应用案例,对经济涟漪效应和成本效益进行了研究。提出了一种利用数字孪生方法克服新技术武器系统从需求确定到批量生产的测试和评估困难,使用户安全验证性能的最佳方法。
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