The increasingly intelligent, highly complex, technical systems of tomorrow - for instance autonomous vehicles - result in the necessity for a systematic security- and safety-oriented development process that starts in the early phases of system design. Automotive Systems Engineering (ASE) as one approach is increasingly gaining ground in the automotive industry. However, this approach is still in a prototype stage. The consideration of security and safety within the early stages of systems design leads to so- called ill-defined problems. Such are not covered by ASE, but can be addressed by means of Design Thinking. Therefore we introduce an approach to combine both approaches. Based on this combination, we derive potentials in the context of the consideration of security and safety. Essential advantages are the possibility to think ahead of threat scenarios at an early stage in system design. Due to an incomplete database, this is not supported or only partially supported by conventional approaches. The resulting potentials are derived based upon a practical example.
Due to the managerial, operational and evolutionary independence of constituent systems (CSs) in a System of Systems (SoS) context, top-down and linear requirements engineering (RE) approaches are insufficient. RE techniques for SoS must support iterating, changing, synchronizing, and communicating requirements across different abstraction and hierarchy levels as well as scopes of responsibility. [Question/Problem] We address the challenge of SoS requirements specification, where requirements can describe the SoS behavior, but also the behavior of CSs that are developed independently.[Principal Ideas] To support the requirements specification in an SoS environment, we propose a scenario-based and iterative specification technique. This allows requirements engineers to continuously model and jointly execute and test the system behavior for the SoS and the CS in order to detect contradictions in the requirement specifications at an early stage. [Contribution] In this paper, we describe an extension for the scenario-modeling language for Kotlin (SMLK) to continuously and formally model requirements on SoS and CS level. To support the iterative requirements specification and modeling we combine SMLK with agile development techniques. We demonstrate the applicability of our approach with the help of an example from the field of e-mobility.
Nowadays mechanical engineering products change from mechatronic systems to Cyber-Physical Systems (CPS). CPS are connected, embedded systems which directly record physical data using sensors and affect physical processes using actuators. They evaluate and save recorded data, use globally available services and interact with operators via multimodal human-machine-interfaces. In context of industrial production CPS change production processes radically. Due to the change of technical systems, equipment suppliers, especially companies of the mechanical engineering industry, face the challenges of a rising complexity and a nearly unmanageable amount of new solutions based on information and communication technology. The contribution at hand provides a reference architecture and maturity levels for CPS. The reference architecture serves as an universal blueprint to structure CPS and to visualize all components and relationships. Two sets of CPS maturity levels help companies to assess the status quo, to determine the target state and to define concrete actions for improving their systems
The integration of cognitive functions will enable mechatronic systems to be superiorly embedded into their environment and to follow their system objectives independently. The intention is to develop self-optimizing systems, which can optimize their behavior by themselves to become more flexible, robust and user-friendly. Numerous challenges, however, become apparent on the way to such intelligent technical systems. The development is characterized by an increasing involvement of non-technical disciplines like cognitive science, higher mathematics or neurobiology. Existing design methodologies are focusing technical disciplines on the one hand and non-technical disciplines on the other hand. For instance, there is a lack of a systematic coupling of those disciplines, which are relevant for the exploration of cognitive functions, with the general engineering approach in product development. To rise to these challenges, the integration of cognitive functions has already to be supported with some kind of methodology. Focus of the methodology must be the early stages of the development. Within this design phases the developer have to modify the principle solution in common. Hence, important requirements occur in terms of the intensified interdisciplinarity of the development and the increasing system complexity. Therefore, a design framework for the integration of cognitive functions into self-optimizing systems has been developed which integrates both, existing and newly developed methods in a well-structured procedure. For this purpose, in section two, we will introduce the concept of self-optimizing systems and the operator-controller-module. Afterwards we will describe the need of action in section three and the state of the art: “design framework for cognition” in section four. In section five, we present our developed design framework for the integration of cognitive functions into intelligent technical systems. Therefore, we will explain the procedure model and a specification technique to describe self-optimizing systems. In addition, we will present a uniform type of solution patterns for the reuse of once successfully implemented knowledge and the solution pattern knowledge base for the tool support. To conclude, we will sum up the major points and give a short outlook on our future work
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