A Cyber-Physical System (CPS) is a system in which physical components and software components are deeply intertwined, each operating on different spatial and temporal scales, exhibiting multiple and distinct behavioral modalities, and interacting with each other in a myriad of ways that change with context. Such systems are software-intensive systems because software contributes essential influences to the design, construction, deployment, and evolution of the system as a whole. In the Christian Doppler Lab VaSiCS we will focus on the particular domain of Software-intensive Cyber-Physical Production Systems (SiCPPS). SiCPPS, like metallurgical plants or car manufacturing plants, reflect the characteristics of CPS to the production domain, building ubiquitous systems that autonomously interact with their environments and are capable of flexibly manufacturing a variety of products based on customer demands.

SiCPPS are highly variable systems of systems that frequently evolve, particularly they typically involve a large number of heterogeneous components (mechanical, electrical, mechatronic, software) that can be configured and combined in different ways. Variability regards not only hardware and software artifacts but also development processes, domains (from mechanical to electrical to software engineering), and methods and tools. Particularly the hardware is a key driver for the variability reflected in all artifacts, directly followed by market pressure for customization. Industry is thus very interested in mastering variability because it is a prerequisite for successful reuse, which in turn helps to reduce development, certification, and maintenance costs and shortens time to market.

Dealing with variability in industry, however, currently depends too much on tacit domain expert knowledge and custom-built tools focusing on very specific artifacts and software and hardware platforms. Existing research in the area of SiCPPS does not explicitly and systematically deal with variability. Current methods and tools are not flexible enough to adapt to heterogeneous (types of) artifacts. Also, there is poor integration between real systems and abstract (model-based) system representations. Industry thus has for many years and is still suffering from a lack of methods and tools to deal with variability in their systems. Research from the area of software engineering (particularly from software product lines and variability management/modeling) is a good starting point, but methods and tools need to be adapted to the SiCPPS context. Particularly, to properly manage variability, possible dependencies and interactions between variable, heterogeneous SiCPPS components need to be modeled considering the system environment and changing requirements.

Together with our industrial partner Primetals Technologies, opens an external URL in a new window, the Christian Doppler Lab VaSiCS aims to conduct applied basic research focusing on methodological support for mastering variability in SiCPPS. A key focus is on the automatic handling of variability, e.g., analyzing existing SiCPPS artifacts from the design process of SiCPPS to automatically extract and model variability information and generating and configuring target artifacts, especially to better support system evolution and future changes in software and hardware platforms as well as tools.