Continuous engineering for Industry 4.0 architectures and systems

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.