Risk analysis (engineering)
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Risk analysis in engineering is a systematic process for identifying, evaluating, and mitigating potential hazards and failure modes in complex systems before or during their deployment. It encompasses quantitative and qualitative methods—such as fault tree analysis, failure mode and effects analysis (FMEA), and probabilistic risk assessment—to estimate the likelihood and severity of adverse outcomes. In robotics and AI, risk analysis is essential across diverse applications: ensuring safe physical human-robot interaction in industrial and surgical settings, validating autonomous vehicles and unmanned aerial systems, assessing agricultural and inspection robots operating in unstructured environments, and evaluating autonomous weapon systems for meaningful human control. It informs design requirements, safety standards, and operational boundaries by systematically examining how hardware failures, software errors, or unexpected human behaviors could lead to harm. Risk analysis matters because deploying autonomous and semi-autonomous systems in real-world environments introduces consequences that can affect human life, infrastructure, and broader societal systems. Rigorous risk assessment enables engineers to make informed trade-offs between capability and safety, satisfy regulatory requirements, build public trust, and ultimately accelerate the responsible adoption of robotic and AI technologies across industries.
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