Development of a Near-Miss Event Analysis Support System for Different Types of Human Error Using AI Technology

Abstract: Preventive measures against various human errors are being taken based on information on near-miss events. However, the process from collecting near-miss events to analyzing them and planning countermeasures is labor-intensive. Focusing only on high-risk near-miss events can reduce labor, but many of the collected near-miss events will not be used. To solve these problems, we believe that a "near-miss event analysis support system" consisting of the following tools will be useful.(1st Tool) A tool to support the analysis of near-miss events, especially factor analysis (automatically extracts factors and identifies human error type. Analysts can add or modify.)(2nd Tool) A tool to support risk assessment of near-miss events (calculates the possibility of human error occurring in the target work on a 5-point scale. Analysts input the 5-point scale based on the expected extent of damage when it occurs. These two values are multiplied, and the risk is evaluated on a 5-point scale [1. Take physical measures immediately, 2. Implement on-site response plan immediately, 3. Horizontally deploy to the site and issue a warning, 4. Share information at the site manager level, 5. No response necessary])(3rd Tool) A tool to present countermeasures for near-miss events that are judged to be high risk (automatically presents appropriate human error countermeasure policies and three specific candidate measures based on human error type. Analysts select countermeasures based on the presented countermeasure policies)(4th Tool) Near-miss event occurrence trend analysis tool (Automatically performs statistical analysis of the causes of near-miss events that occurred during a period set by the analyst. Also performs categorization analysis based on the work site, work time period, and SRK level of the work.)(5th Tool) Near-miss event management tool (Connects the near-miss event input tool with the above four tools, stores all data such as evaluation results in the cloud, and supports horizontal deployment within the company. Based on the evaluation results, the urgency is evaluated in four stages (Level 0: no contact required, Level 1: information sharing, Level 2: detailed warning to the site, Level 3: immediate on-site inspection and improvement), and if it is Level 2 or above, a function is added to automatically contact related departments from the system.)We implemented these five tools based on AI technology and built a near-miss event analysis support system. This system is currently being test-operated by safety personnel from several companies, and although we are still in the process of collecting operational issues, it has been confirmed that it has the expected effects.

Keywords: Human Error, Safety Management, Near-miss event

DOI: 10.54941/ahfe1005794

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