Formalized Identification Of Key Factors In Safety-Relevant Failure Scenarios

• URL: http://arxiv.org/abs/2402.18194v1
• Date: Wed, 28 Feb 2024 09:28:36 GMT
• Title: Formalized Identification Of Key Factors In Safety-Relevant Failure Scenarios
• Authors: Tim Maurice Julitz, Nadine Schl\"uter, Manuel L\"ower
• Abstract summary: This research article presents a data-based approach to systematically identify key factors in safety-related failure scenarios. The approach involves a derivation of influencing factors based on information from failure databases. The research demonstrates a robust method for identifying key factors in safety-related failure scenarios using information from failure databases.
• Score: 0.0
• License: http://creativecommons.org/licenses/by-nc-nd/4.0/
• Abstract: This research article presents a methodical data-based approach to systematically identify key factors in safety-related failure scenarios, with a focus on complex product-environmental systems in the era of Industry 4.0. The study addresses the uncertainty arising from the growing complexity of modern products. The method uses scenario analysis and focuses on failure analysis within technical product development. The approach involves a derivation of influencing factors based on information from failure databases. The failures described here are documented individually in failure sequence diagrams and then related to each other in a relationship matrix. This creates a network of possible failure scenarios from individual failure cases that can be used in product development. To illustrate the application of the methodology, a case study of 41 Rapex safety alerts for a hair dryer is presented. The failure sequence diagrams and influencing factor relationship matrices show 46 influencing factors that lead to safety-related failures. The predominant harm is burns and electric shocks, which are highlighted by the active and passive sum diagrams. The research demonstrates a robust method for identifying key factors in safety-related failure scenarios using information from failure databases. The methodology provides valuable insights into product development and emphasizes the frequency of influencing factors and their interconnectedness.

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