![]() ![]() ![]() The CPS architecture of Jay Lee 5C allows data acquisition, system administration, and control responses for the adoption of different reconfigurations. This metamodel enriches CPS models with high-granularity graph-based skill descriptions, which, in combination with the appropriate manufacturing process descriptions, allow automatic matching for production planning and further simulation and ontimization.read more read lessĪbstract: Cyber-Physical Systems (CPS) are commonly used for the development of Industry, specifically the Industry 4.0 paradigm, allowing the connection of the virtual world with the physical world and the use of information technologies. In this paper, a semantic metamodel for CPS is presented. This description should allow the entirely automatic generation of production cell models through the matching of CPS skills and product requirements. To allow automatic matching from product descriptions to specific CPSs, a new approach to CPS description is necessary. This manual step hinders the automatic production cell model generation based on the product requirements. Instead, production cell components are manually assigned to the manufacturing processes, which are required for the product. Semantic information in the skills description usually is completely absent or present only to the extent, which is not enough to match the corresponding components to the product requirements and necessary production processes. However, existing solutions for CPS description models contain mainly skills and functionalities of the component from a task-oriented perspective to achieve platform-independent code generation for the components control. The model-based systems engineering (MBSE) approach promotes increased reusability of component models and allows an automatic generation of the system of interest model and its validation through simulation, which results in a shorter design phase. Digital representation of those components through the definition of the corresponding description models starts in the early design phase of the engineering process. This paper also shows a way to simplify the evaluation for dynamic system by improving the composability and compositionality of the subsystem.read more read lessĪbstract: Digitalization slowly but steadily transforms the modern production cells by adding an IT layer to their structure, which, subsequently, leads to the use of cyber-physical systems (CPS) as production cell components. The simulation results show that the one-order feedback strategy has high reliability, scalability and stability against the complexity of decision and random failure. Further, two decentralized decision process strategies are proposed based on our framework, and we compare the reliability with the static strategy and the centralized processing strategy. We provide constraints and seven patterns for the composition of reliability and process time requirements. To simplify self-management, a self-similar recursive actor interface is proposed for decision (actor) composition. ![]() Based on the relative time solution, a formal reference framework is introduced for self-managed CPSs, which includes a compositional FSM-based actor model (subsystems of CPS), actor-based advice and runtime decomposable decisions. To guarantee the consistent observation of event orders for causal reasoning, this work first proposes a relative time-based method to improve the composability and compositionality of the timing property of events. In this paper, a formal compositional framework is proposed to systematically improve the dependability of the decision process. Such dynamic adaptation behavior introduces systemic challenges for CPS design, advice evaluation and decision process arrangement. To provide continuous and high quality services, a self-managed CPS should automatically reconstruct itself to adapt to these changes and recover from failures. Abstract: Cyber Physical Systems (CPSs) need to interact with the changeable environment under various interferences. ![]()
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