Presentation
92. Leveraging AI to Improve Task-Specific Biomechanical Safety in Work Instruction
SessionPoster Session 1
DescriptionThe integration of large language models (LLMs) into operational environments presents a novel avenue for enhancing both efficiency and safety, including to reduce the risk of injury in sectors where manual handling tasks are prevalent. The present project aimed to explore and validate the efficacy of generative AI in improving work instruction authoring with a focus on biomechanical safety. These tasks often involve substantial manual handling, such as lifting, pushing, or pulling, which are common in environments like airport baggage handling facilities and manufacturing logistics departments. The project utilized commonly available generative AI services capable of parsing and understanding operational procedures and safety requirements. The generative AI was provided with task requirements for 5 different tasks and prompted to create work instructions with biomechanical safety procedures in place. Expert evaluation was used to assess the quality of generative AI created work instruction for biomechanical safety risk reduction.
Event Type
Poster
TimeWednesday, September 11th5:30pm - 6:30pm MST
LocationMcArthur Ballroom
Aerospace Systems
Cognitive Engineering & Decision Making
Computer Systems
Forensics Professional
Health Care
Human Performance Modeling
Individual Differences in Performance
Perception and Performance
Product Design
Safety
Training
Usability and System Evaluation
Extended Reality