![]() Recently, a structuring and communication concept called service-oriented architecture (SOA) has drawn much attraction, representing a promising compromise between tractable, well-founded design principles and the flexibility and adaptability of the (systems of) systems emerging from SOA design processes.Īs for modellability, the complex and critical nature of systems engineering activities still necessitates a well-founded methodology for the design of complex systems and SoS, from understanding their requirements to deploying and maintaining them according to design-time expectations.Ī go-to methodology for designing and maintaining complex systems, model-based systems engineering (MBSE) offers a comprehensive yet practical foundation for such activities. In addition, not unrelated to the layered, diverse and inter-domain nature of SoS, instantiations of this concept are expected to exhibit a level of autonomy and self-organization not seen before. The present paper proposes an approach to live up to these challenges by identifying an adequate conceptual domain for each of the three goals, and then examining their combination in the light of the state-of-the-art in each of those domains, as well as a current, real-life industrial case study.Īs for complexity of industrial installments, we refer to the more and more prevalent notion of System-of-Systems (SoS) , denoting complex software and hardware (i.e., often, cyber-physical) systems, as well as their large-scale, dynamic compositions. (In particular, (3) appears to be in opposition to the first two.) It is now crucial to achieve a thorough understanding of the interplay of these conceptual points: the success of the ongoing fourth industrial revolution, often called Industry 4.0, depends on finding the right ways to harmonize the aforementioned goals. Notice that the crux of this novel kind of challenges lies within the contradictory nature of those wishes and goals, in short, (1) complexity, (2) autonomy, and (3) modelability. Essentially, these challenges arise as a combination of (1) an increased scale and complexity in industrial engineering and automation processes, as well as in the partaking hardware and software systems and products, (2) an accompanying expectation toward those systems to organize, adapt and optimize themselves autonomously along flexible architectural principles, and, finally, (3) a desire to maintain or even strengthen the use of rigorous design practices and standards while devising these complex systems and processes, thus, retaining a comprehensive overview of the components of the overall industrial scenario, regardless of their individual behavior and their modes of interaction. In the new era of industrial digitalization, engineers are facing a new set of diverse challenges.
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