Fast technological progress and the dynamics generated by economic, ecological and societal mega-trends are putting manufacturing companies under strong pressure to radically change the way in which they operate and innovate. Consequently, human work in manufacturing is also visibly changing and the need to up-skill and re-skill workers is rapidly increasing in order to sustain industry competitiveness and innovativeness as well as employability. Life-long training is therefore crucial to achieve the vision of a successful and socially sustainable manufacturing ecosystem in which industry, society and individuals can thrive together. In this paper we present a novel training planner, which provides worker-specific training recommendations based on workers’ knowledge, skills and preferences, job content and allocation statistics, and factory demands. Multiple objectives, related to economic and social performances are taken into account

A Multi-horizon, Multi-objective Training Planner: Building the Skills for Manufacturing

PINZONE, MARTA;FANTINI, PAOLA MARIA;TAISCH, MARCO
2016

Abstract

Fast technological progress and the dynamics generated by economic, ecological and societal mega-trends are putting manufacturing companies under strong pressure to radically change the way in which they operate and innovate. Consequently, human work in manufacturing is also visibly changing and the need to up-skill and re-skill workers is rapidly increasing in order to sustain industry competitiveness and innovativeness as well as employability. Life-long training is therefore crucial to achieve the vision of a successful and socially sustainable manufacturing ecosystem in which industry, society and individuals can thrive together. In this paper we present a novel training planner, which provides worker-specific training recommendations based on workers’ knowledge, skills and preferences, job content and allocation statistics, and factory demands. Multiple objectives, related to economic and social performances are taken into account
Advances in Neural Networks
978-3-319-33746-3
Manufacturing, Mathematical model, MOLP, Multi-horizon, Multi-objective, Quantum evolutionary algorithm, Training, Worker-centric
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1015864
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