Personalized work instruction system for revitalizing human-machine interaction

Abstract

Diversification of the workforce and machinery has become a forefront issue in advanced manufacturing industries. To respond this challenge, it is necessary to create a sophisticated mechanism in which humans and machines can mutually assist and evolve together for sustainable growth. In this paper, for assembly cell production, we developed work instructions as exemplar “machine” that interact with workers, and analyzed the effect of this interaction on work efficiency. Based on the resulting statistical model, a system that provides personalized machine support for operators was prepared. Fundamental experiments are reported from an application to the assembly of simple mechanical products.