Smart operators in industry 4.0: A human-centered approach to enhance operators' capabilities and competencies within the new smart factory context

TL;DR

This paper introduces Sophos-MS, a human-centered augmented reality and intelligent tutoring system designed to support operators in Industry 4.0, enhancing their skills and adaptability in complex, dynamic manufacturing environments.

Contribution

It presents a reference framework and a modular, multi-layered solution integrating AR and digital assistants, specifically tailored for Industry 4.0 operators' needs.

Findings

Improves operators' learning curves in field experiments.

Statistically significant positive impact on operator training.

Demonstrates practical deployment in smart factory settings.

Abstract

As the Industry 4.0 takes shape, human operators experience an increased complexity of their daily tasks: they are required to be highly flexible and to demonstrate adaptive capabilities in a very dynamic working environment. It calls for tools and approaches that could be easily embedded into everyday practices and able to combine complex methodologies with high usability requirements. In this perspective, the proposed research work is focused on the design and development of a practical solution, called Sophos-MS, able to integrate augmented reality contents and intelligent tutoring systems with cutting-edge fruition technologies for operators' support in complex man-machine interactions. After establishing a reference methodological framework for the smart operator concept within the Industry 4.0 paradigm, the proposed solution is presented, along with its functional and non-function requirements. Such requirements are fulfilled through a structured design strategy whose main outcomes include a multi-layered modular solution, Sophos-MS, that relies on Augmented Reality contents and on an intelligent personal digital assistant with vocal interaction capabilities. The proposed approach has been deployed and its training potentials have been investigated with field experiments. The experimental campaign results have been firstly checked to ensure their statistical relevance and then analytically assessed in order to show that the proposed solution has a real impact on operators' learning curves and can make the difference between who uses it and who does not.