# Towards Modern Inclusive Factories: A Methodology for the Development of Smart Adaptive Human-Machine Interfaces

## TL;DR

This paper introduces a methodology for designing adaptive, human-centered HMIs in manufacturing, aiming to reduce cognitive workload and improve customization, productivity, and acceptance of automation.

## Contribution

It proposes a novel approach based on measuring user capabilities, adapting information presentation, and user training for smarter HMIs in industrial settings.

## Key findings

- Enhanced customization and productivity in manufacturing processes
- Reduced cognitive workload for human operators
- Improved acceptance of automation technologies

## Abstract

Modern manufacturing systems typically require high degrees of flexibility, in terms of ability to customize the production lines to the constantly changing market requests. For this purpose, manufacturing systems are required to be able to cope with changes in the types of products, and in the size of the production batches. As a consequence, the human-machine interfaces (HMIs) are typically very complex, and include a wide range of possible operational modes and commands. This generally implies an unsustainable cognitive workload for the human operators, in addition to a non-negligible training effort. To overcome this issue, in this paper we present a methodology for the design of adaptive human-centred HMIs for industrial machines and robots. The proposed approach relies on three pillars: measurement of user's capabilities, adaptation of the information presented in the HMI, and training of the user. The results expected from the application of the proposed methodology are investigated in terms of increased customization and productivity of manufacturing processes, and wider acceptance of automation technologies. The proposed approach has been devised in the framework of the European project INCLUSIVE.