Communication between Humans and Machines in a Hybrid Inspection System

Recently, 100% inspection using automated systems has seen more frequent application than traditional sampling inspection using human inspectors. Nevertheless, humans still outperform machines in most attribute inspection tasks. Studies have shown that hybrid inspection systems where humans work corporately with machines might achieve superior system performance than either humans or machines alone. In response to this situation, there is a need to study function allocations in hybrid inspection systems, specifically, the communication between humans and machines. This paper introduces three types of communication alternatives in the design of hybrid inspection systems and discusses their impact on dynamically allocating search and decision-making functions to the humans and the machines.