First steps towards a mereo-operandi theory for a system feature-based architecting of cyber-physical systems

Cyber-physical systems (CPSs) are characterized by a high-level synergy among hardware, software and cyberware constituents. Though there has been intense research in various fields of complex engineering systems, still no advanced and comprehensive system design methodologies are available that would facilitate design and development of CPSs in various contexts and applications. This paper reports on the first steps and results of developing a comprehensive trans-disciplinary theory for conceptualization, modeling and realization of system architectures through a unified epistemological platform. The essence of the proposed theory is the fusion of mereotopological, modus operandi and CPS knowledge. 1 Design challenges of cyber-physical systems As a manifestation of emerging highly complex systems, cyber-physical systems (CPSs) are rapidly proliferating. CPSs tightly integrate hardware, software and knowledgeware, are deeply embedded in the application environment, and typically, they are characterized by: (i) structural heterogeneity and complexity, (ii) operational synergy of components, (iii) nonlinear behavior, (iv) decentralized real-time operation capabilities, and (v) open architecture and ad-hoc functional connections between components. Although these characteristics provide completely new capabilities for CPSs, they also imply that the traditional methods and principles cannot realistically be utilized in design and development of CPSs [PHO14]. Our work concentrates on cyber-physical consumer durables (CPCDs). As a specific sub-category of CPSs, CPCDs are product-service combinations that reflect most of the functional and structural features of cyber-physical systems, while enabling a higher level of interaction with users and the embedding environments. The research reported here focuses on exploring the possibilities of designing customizable CPCDs and enabling this by some sort of methodological and/or computational means. Our previous investigation found that achieving the goals of mass customization (MC) in the case of