Supporting the management of the transition towards human-centricity: characterizations of smart manufacturing systems for efficient performance and dynamic evolution

The integration of smart technologies into manufacturing systems requires adopting transition management strategies that go beyond simple technology implementation. The thesis aims to support the management of smart manufacturing systems in which humans and machines interact, leveraging on the concept of characterization. In this work, characterization is intended as the description and typification of a system, relying on a set of aspects that provide insights about system’s characteristics and properties. Such description could be performed at different levels, i.e., macro- and micro-characterization. First, the potential of the characterization offered by maturity models is explored. Results show that those models provide a partial macro-characterization of manufacturing system. Consequently, the research extends the macro-characterization by considering occupational health and safety issues, relying on Resilience Engineering principles. Finally, a micro-characterization perspective is adopted to explore levels of automation within smart manufacturing systems, focusing on adaptive automation principles. To achieve these results, inductive and deductive methods are alternated to map the state of the art of the concepts investigated, collect direct and indirect knowledge, and translate them into operational implications with respect to specific contexts. The results show how the macro- and micro-characterization provides a comprehensive understanding of smart manufacturing systems, using a more general or more specific level of system detail, depending on the management needs and time horizon under consideration. The macro perspective helps organizations map their digital transformation at a strategic level, while the micro perspective ensures management of the day-to-day complexities and operational challenges that arise. Together, these perspectives provide managers with the understanding they need to navigate the evolving smart manufacturing landscape, fostering the development of more informed and human-centered digital growth strategies.