Feasibility Analysis of Safety Training in Human-Robot Collaboration Scenario: Virtual Reality Use Case

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Design and modification of human-robot collaboration workspace requires analysis of the safety of systems. Generally, the safety analysis process of a system commences with conducting a risk assessment. There exists a number international standards for design robotics work cells and collaborative shared workspaces. These guidelines expound on principles and measures to identify hazards and reduce risks. Measures of risk reductions include eliminating hazards by design, safeguarding, and providing supplementary protective measures such as user training. This study analyzed the technical feasibility and industrial readiness of Virtual Reality (VR) technology for safety training in manufacturing sector. The test case of a VR-based safety training application is defined in the human-robot collaboration pilot-line of diesel engines. The Analytic Hierarchy Process method was utilized for conducting a quantitative analysis of the survey with ten experts. The participants performed the importance rating with respect to two hierarchy level criteria. Regarding the evaluation of safety training methods in a human-robot collaboration environment, two alternatives of traditional and Virtual Reality -based training are compared. The results indicates that the VR-based training is valued over the traditional method, with a scored proportion of approximately 65 percent over 35 percent.

Original languageEnglish
Title of host publicationFlexible Automation and Intelligent Manufacturing
Subtitle of host publicationThe Human-Data-Technology Nexus - Proceedings of FAIM 2022
EditorsKyoung-Yun Kim, Leslie Monplaisir, Jeremy Rickli
Number of pages11
ISBN (Print)9783031183256
Publication statusPublished - 2023
Publication typeA4 Article in conference proceedings
EventInternational Conference on Flexible Automation and Intelligent Manufacturing - Detroit, Michigan, United States
Duration: 19 Jun 202223 Jun 2022

Publication series

NameLecture Notes in Mechanical Engineering
ISSN (Print)2195-4356
ISSN (Electronic)2195-4364


ConferenceInternational Conference on Flexible Automation and Intelligent Manufacturing
Country/TerritoryUnited States
CityDetroit, Michigan


  • Human-robot collaboration
  • Learning transfer
  • Manufacturing assembly
  • Safety training
  • Virtual reality

Publication forum classification

  • Publication forum level 1

ASJC Scopus subject areas

  • Automotive Engineering
  • Aerospace Engineering
  • Mechanical Engineering
  • Fluid Flow and Transfer Processes


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