Maintenance policies optimization in the Industry 4.0 paradigm

Maintenance management is a relevant issue in modern technical systems due to its financial, safety, and environmental implications. The need to rely on physical assets makes maintenance a necessary evil, which, on the other hand, allows achieving a high quality of end products, or services, and a safety level that is adequate for the regulatory requirements. The advent of the fourth industrial revolution offers meaningful opportunities to improve maintenance management; technologies such as Cyber-Physical Systems, the Internet of Things, and cloud computing enable realizing modern infrastructure to support decisions with advanced analytics. In this thesis, the optimization of maintenance policies is tackled in this renewed technological context. The research methods employed in this thesis include interviewing of subject experts, literature research, and numerical experiments. Mathematical modelling is used to model network effects in complex technical systems, and simulations are used to validate the proposed models and methodologies. The problem of maintenance policies comparison is addressed in one of the publications; using the proposed bi-objective analysis, an effective maintenance policy was identified. Maintenance of complex systems organized in a networked fashion is studied in another project, where maintenance costs and system performances are considered. The proposed model allowed to identify a set of non-dominated (in the Pareto sense) maintenance policies, and an efficient resolution procedure was developed. The possibility to use a digital twin to replicate a Cyber-Physical System for maintenance policies optimization is addressed in another publication. The main hurdles in realizing such a complex infrastructure are analyzed, and managerial implications are presented. Finally, following a qualitative research approach, the opportunities offered by additive manufacturing are identified and presented in a book chapter. The opportunities for both maintenance efficiency gains and new business models are identified and discussed.