Continuous engineering for Industry 4.0 architectures and systems

Abstract

Traditionally, the quality of a software or system architecture has been evaluated in the early stages of the development process using architecture quality evaluation methods. Emergent approaches like Industry 4.0 require continuous monitoring of both run‐time and development‐time quality properties, in contrast to traditional systems where quality is evaluated at specific milestones using techniques such as project reviews. Considering the dynamics and minimum down‐time imposed by the industrial production domain, it must also be ensured that Industry 4.0 system evaluations are continuously performed with high confidence and with as much automation as possible, using simulations, for instance. In this regard, there is a need to develop new methods for continuously monitoring and evaluating the quality properties of software‐based systems for Industry 4.0, which must be supported by automated quality evaluation techniques. In this research we analyze traditional architecture evaluation methods and Industry 4.0 scenarios, and propose an approach based on Digital Twins and simulations to continuously evaluate runtime quality aspects of the architecture and systems of industrial production plants. The evaluation is based on the instantiation of our approach for a concrete demand of an automation plant in the automotive domain.

Survey on open‐source digital twin frameworks–A case study approach

“…If two DTs are composed, will the composition behave as a single DT? If composition is not supported, is hierarchical aggregation of DTs and their sub‐components feasible? Support for Physical Interventions. Continuous engineering and fault‐tolerance is highly relevant in software‐based systems such as DTs 36 . Can the tool still be alive and running if the PE enters in an intervention or failure state?…”

“…Support for Physical Interventions. Continuous engineering and fault‐tolerance is highly relevant in software‐based systems such as DTs 36 . Can the tool still be alive and running if the PE enters in an intervention or failure state?…”

Digital Twins in Software Engineering—A Systematic Literature Review and Vision

“…Al-Najjar et al [190] use virtual infrastructure DTs to help with the complexity of complex workflow ecosystems. In contrast, Oliveira Antonino et al [114] highlight the need for appropriate methods and tools to enable continuous and accurate assessments of the quality of system architectures so that it is not a siloed territory based on the expertise of a few engineers. Also, Asikainen [153] observes that the complexity of software process management grows as the number of related decisions increases, offering a potential framework to tackle this complexity during software processes.…”

“…Antonino et al [114] and Nakagawa et al [115] offer excellent examples of how Industry 4.0 requires continuous engineering monitoring practices for quality properties over a software or system architecture, and the applicability of DTs to simulate the evolving architecture and its evaluation.Likewise, Jones et al [116] apply version control and DTs from conceptual design phases to physical prototypes using DTs to maintain synchronization. These works show how traditional and software industries converge within PLM and ALM, and how DTs can help to extend the capabilities of the value stream in both PLM and ALM.…”