Evaluation of human performanace in a supervisory inspection task monitoring multiple hybrid inspection systems

The demand for consistent quality has led to 100% inspection using automated systems rather than the traditional sampling with human inspectors. However, these automated systems cannot adapt to novel situations to meet the required performance without human intervention. The need for costeffective and superior inspection performance has resulted in hybrid systems in which the functions are allocated depending on the capabilities of humans and machines. With the increasing availability of computer technology due to decreased costs and size, the role of humans in inspection systems is changing from that of a continuous “online” inspector to that of a supervisor of multiple tasks. This study uses a computer-based visual inspection simulator to investigate the role of the human as a supervisor in inspection systems, with the main focus on the effect of performance of one hybrid inspection system on human decision to intervene in another system to optimize the inspection performance.