  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.
