CRAN - Campus Sciences
BP 70239 - 54506 VANDOEUVRE Cedex
Tél : +33 (0)3 72 74 52 90
cran-secretariat@univ-lorraine.fr
 
 
Ph. D. Project : Contribution to the formalisation of invariant modelling constructs for optimising the sustainability performances of Cyber-Physical Systems
Dates : 2018/05/03 - 2020/11/30
Student: Concetta SEMERARO
Manager(s) CRAN: Hervé PANETTO , Mario LEZOCHE
Other Manager(s): Prof. Michele Dassisti (michele.dassisti@poliba.it)
Full reference: The Smart Factory paradigm represents the "Fourth Industrial Revolution" in the field of manufacturing industry that can be synthesized in systems networks integrating physical components and software for control (Baheti and Gill, 2011) and the improvement of manufacturing processes (Kagermann et al., 2013). Smart systems typically consist of different components including sensors for signal acquisition, communication units for data transmission between components, control and management units for decision-making, and actuators to perform the appropriate actions. They have impacted applications in many fields such as manufacturing, healthcare, energy, environment, logistic, monitoring, and mobility. As the complexity of such systems continue to grow, the challenge of developing integrated smart and sensing systems has surpassed the design complexity of their individual components. Thus, the main issue of developing smart and sensing systems lies in the complexity to integrate and to manage these different components, technologies, and goals across a wide spectrum. The principle of automation, configurability and autonomous interconnection of the machines is widespread. It is then necessary to formalize shared knowledge for defining a modelling method that helps analysing new form of “intelligent” (smart) and sensing systems from a sustainable perspective. The representation of shared knowledge is a branch of artificial intelligence that studies the way in which human reasoning occurs and defines symbols or languages. This representation allows the formalisation of knowledge for making it comprehensible to machines, aligned to reference models. In recent years, the emergence of Cyber-Physical Systems (CPS) has amplified the capacity of sensing the world through a network of connected devices using the existing network infrastructure. Grouping together smart and sensing systems forming a large-scale distributed cyber-physical system has tremendous potential in bringing smart systems to many application domains. However, they suffer of missing modelling techniques taking into account not only their technological settings but also they strong information and functional inter-correlations.
This PhD proposal aims at identifying and formalising modelling constructs contributing at building informational and functional models for improving the sustainability of manufacturing processes and products based on networked components. The constructs will then allow representing knowledge and its deep relationship with the manufacturing processes. They make the shared knowledge more readily reusable and are at the basis of standardization efforts.
Keywords: Sustainable manufacturing, smart factory, knowledge management, cyber-physical systems
Department(s):
Eco-Technic systems engineering