Data-Driven Pattern-Based Constructs Definition for the Digital Transformation Modelling of Collaborative Networked Manufacturing Enterprises

Abstract

The digital transformation of collaborative networked manufacturing enterprises requires building and applying digital models representing the set of resources and processes knowledge. Modelling such digital copy of the physical system to perform real-time validation and optimization is quite complex and thus needs a big amount of data and some modelling patterns representing the operational semantics of the modelled elements. Generally, the modelling action has a specific application type. For this reason, the core challenge of the digital transformation modelling is to create a modular "digital model", namely a decomposable and re-composable model, towards different applications. The authors propose an approach based on the combination of data-driven and modeldriven approaches, to identify and formalize modelling patterns, that combine for developing a modular executable model of the studied system.

Digital twin paradigm: A systematic literature review

“…The physics-based models are based on a set of different models to represent the structure, the behaviour, and the interactions of a physical system (Tidriri et al, 2016), (Tao et al, 2018c). The most studied models for developing a digital twin (Semeraro et al, 2019a) A geometric model reflects the geometry, the kinematics, the logic, and the interfaces of the real system (Ayani et al, 2018), (Xie et al, 2019). A geometric model defining shapes, sizes, positions and assembling machine components is presented in (Tao et al, 2018c).…”

“…According to the {10 Papers} clustered in C10, the modularity is the ability to integrate, to add, or to replace models (Guo et al, 2018). Two modular approaches have been developed in (Guo et al, 2018), (Semeraro et al, 2019a). The idea behind this approach is to use and especially re-use predefined functional units (Semeraro et al, 2019a), that are systematically developed and logically interlinked for the configuration of a holistic manufacturing system (Stark et al, 2017), (Negri et al, 2019).…”

“…Two modular approaches have been developed in (Guo et al, 2018), (Semeraro et al, 2019a). The idea behind this approach is to use and especially re-use predefined functional units (Semeraro et al, 2019a), that are systematically developed and logically interlinked for the configuration of a holistic manufacturing system (Stark et al, 2017), (Negri et al, 2019). Virtual (VR) or augmented (AR) reality technologies can be integrated in digital twins to create interactive and immersive environments (G. enabling direct interactions between the digital twin and final users.…”

A Novel Collaboration-Oriented Requirement Model Mapping and Classification Method Based on Domain Knowledge for Complex Mechatronic Products

“…In recent years, the complexity of product research and development is increasing. Therefore, digitalized and networked collaborative manufacturing has become an inevitable trend of enterprise transformation and upgrading [1]. However, for complex mechatronic products, the information in some phases of product lifecycle is still stored and distributed in the form of electronic documents, so it is difficult to realize the efficient management of this information.…”

Modelling Cyber‐Physical Systems Using Data‐driven Patterns

“…Fig. 4: SysML Representation (Semeraro et al 2019a) In view of the above, a list of data-driven patterns has been presented in (Semeraro 2020) according to the methodology described in (Semeraro et al 2019a). The detected data-driven patterns are listed as follow: Filling pattern (P1); Re-start machine pattern (P2); Clamping force pattern (P3); Pression control pattern (P4); State pattern (P5).…”