Integration of risk analysis methods in aerospace research projects
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صندلی اداریAbstract
Organizations are exposed to several types of risks, such as environmental, legal, operational, financial, and technological; that are subjected to epistemic uncertainty. In this context, a contemporary issue is how to deal with accidents, with greater difficulty in understanding the sociotechnical system, due to its complex and dynamic characteristics, in an attempt to prevent accidents based on components’ behavior. Although, for most complex systems and projects, a record of the exposure to hazards is incomplete or nonexistent, especially when it is highly innovative. This study developed a risk analysis framework for complex aerospace research projects by integrating different methods: problem structuring, safety control action analysis, and prioritization of results. Three methods are proposed: (1) Soft Systems Methodology (SSM) for initial review and understanding of the problem situation, and preliminary identification of hazards and losses; (2) Systems-Theoretic Process Analysis (STPA), to identify Unsafe Control Actions (UCAs) and their causal scenarios; and (3), Preferences Sorting Technique by Similarity to Ideal Solution (TOPSIS Fuzzy) for prioritization of the UCAs and mitigating causal scenarios. This proposal was applied to the Liquid Propulsion Injection Systems Laboratory (CEPROS), and, through the SSM, 7 hazards and 4 losses were found. On the other hand, the STPA method found 15 loops with 48 UCAs and 106 causal scenarios. In the end, it is recommended that the Decision Maker establishes a cut-off criterion, that is, a Hierarchy of Management and Control of the identified UCAs. The proposed methods follow the line of sociotechnical systems, considering the difficulty of the decision-maker for risk analysis in aerospace research projects. Thus, this work presents a structure of different methods covering the entire risk management process, increasing the difficulty in fulfilling the mission due to the level of complexity of the project, and supporting strategies for coordinated decision-making.
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