Cycle Time Estimation Model for Hybrid Assembly Stations Based on Digital Twin

Abstract

Moving towards factories of the future, Human-Robot Interfaces (HRIs) have come to the foreground. HRIs, offer extended potential in terms of flexibility, time and cost reduction, ergonomics, and the overall company’s sustainability. What is needed, is the provision of digital tools that will accelerate HRI integration to the existing manufacturing plants as well as render their complex behavior, predictable. Following this rationale, this paper presents, the design of a prediction model, for robot moves in hybrid assembly stations, based on the robot’s Digital Twin and a statistical regression model. In addition to that, respect is given to safety standards as well as to robot capabilities. The resulting model is validated against a simulation software, and further implemented in a pilot case derived from the automotive industry.