On an evolutionary information system for personalized support to plant operators

Abstract

Technological advances are gradually transforming industrial plants into cognitive cyber-physical systems. Such systems include heterogeneous assets which need to be adapted and supported throughout this transformation. However, operator support systems are still dependent on fixed guidance and paper-based instructions describing a standard procedure. This paper presents an evolutionary approach for evaluating operators' feedback towards enriching and personalizing the instructions content on how to execute a certain activity. The feedback is provided through a web application and analyzed by artificial intelligence techniques. The proposed information support system has been applied on a case study about the maintenance of an industrial robot.