Modern manufacturing systems typically require high degrees of flexibility,in terms of ability to customize the production lines to the constantlychanging market requests. For this purpose, manufacturing systems are requiredto be able to cope with changes in the types of products, and in the size ofthe production batches. As a consequence, the human-machine interfaces (HMIs)are typically very complex, and include a wide range of possible operationalmodes and commands. This generally implies an unsustainable cognitive workloadfor the human operators, in addition to a non-negligible training effort. Toovercome this issue, in this paper we present a methodology for the design ofadaptive human-centred HMIs for industrial machines and robots. The proposedapproach 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 areinvestigated in terms of increased customization and productivity ofmanufacturing processes, and wider acceptance of automation technologies. Theproposed approach has been devised in the framework of the European projectINCLUSIVE.
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