A5079692120- Flexible and Reconfigurable Manufacturing Systems
- Manufacturing Process and Optimization
- Digital Transformation in Industry
- Business Process Modeling and Analysis
- Service-Oriented Architecture and Web Services
- Semantic Web and Ontologies
- Model-Driven Software Engineering Techniques
- Software Engineering Research
- Systems Engineering Methodologies and Applications
- Product Development and Customization
- Technology Assessment and Management
- Advanced Software Engineering Methodologies
- Ethics and Social Impacts of AI
- Artificial Intelligence in Healthcare and Education
- Software Engineering Techniques and Practices
- Industrial Vision Systems and Defect Detection
- Biomedical Text Mining and Ontologies
- Simulation Techniques and Applications
- Optimization and Packing Problems
- Industrial Technology and Control Systems
- Safety Systems Engineering in Autonomy
- Advanced Computational Techniques and Applications
- Digital Innovation in Industries
- BIM and Construction Integration
- Biomedical Ethics and Regulation
Christian Doppler Laboratory for Thermoelectricity
2019-2024
TU Wien
2018-2024
La Trobe University
2021
Intel (United Kingdom)
2021
Mälardalen University
2021
University of Applied Sciences Emden Leer
2021
Otto-von-Guericke University Magdeburg
2019
Cyber-Physical Production Systems (CPPSs) are envisioned as next-generation adaptive production systems combining modern techniques with the latest information technology. A CPPS creates a complex environment between different domains (mechanical, electrical, software engineering), requiring multidisciplinary solutions to tackle growing complexity issues and reduce (maintenance) effort. Software plays an increasingly important role in assuring effective efficient operation of CPPSs. However,...
Advanced production systems, for example in the European automotive or steel industries, incorporate Industry 4.0 defined structures based on components and their asset administration shells. Several development standardization initiatives define structures, behavior patterns, meta models, etc. These assume shell (I4.0AAS) as a digital twin of component to contain all relevant engineering runtime data. However, there is only limited discussion how collect represent these data effectively...
In Cyber-Physical Production System (CPPS) engineering, domain experts design assets like products, production processes, and resources. However, the representation of dependencies between in heterogeneous engineering artifacts, system plans, models, tool data, is insufficient to coordinate activities, changes shared asset properties, as it increases risk unplanned rework project delay. While Industry 4.0 (I4.0) assets, defined RAMI 4.0, allow representing multi-disciplinary views on remains...
DevOps is a set of practices that combines software development and operations to enable continuous product life cycle improve the quality systems. Although considered successful for typical systems, it has not yet been widelyadopted in area - Physlcal Production Systems (CPPSs) integrate physical components with computer-based control communication Related industrial settings, many new challenges arise, like long-term investments, missing flexibility asset-heavy production environments,...
Cyber-Physical Production Systems (CPPSs) are envisioned as next-generation adaptive production systems combining modern techniques with the latest information technology. In CPPS engineering, basic planners define functional relations between Product-Process-Resource (PPR) views to specify valid process and resource designs that fulfill customer requirements. Using Formalised Process Description standard (VDI 3682) allows visually model these PPR but is hard by machines insufficiently...
Data exchange and integration in an engineering network are challenges that each organization has to solve. Most practitioners have realized these require detailed consideration involvement of the disciplines involved. However, usually do not speak same language. Thus, a data logistics is required overseeing complete ensuring proper transformation between disciplines. This requires automated mapping data, following VDI Guideline 3695. In this paper, we introduce methodology set up such...
Production system engineering involves various disciplines and tools within an organization. Digitalization in such organization strongly depends on the quality of data logistics that integrates domain-specific languages applied between disciplines. In this paper, we introduce a meta model method for identifying common concepts, elements involved disciplines, establishing foundation logistics. The Common Concepts Identification elicits concepts pathways through process and, thereby,...
The realization of a cyber-physical production system (CPPS) requires suitable methods and tools for the exchange integration engineering data between collaborating disciplines. Unfortunately, description languages used in CPPS Engineering (CPPSE) organization to describe discipline-specific views are not necessarily well suited high-quality workgroups. In this paper, we identify technical debt risks regarding CPPSE using VDI 3695 guideline as best practice. We report on effects likely...
Technical Debt (TD) has proven to be a suitable communication concept for software-intensive contexts raise awareness regarding longterm negative effects of deviations from standards and guidelines. TD also been introduced systems engineering domain, communicate design shortcomings in long-running, software-assisted systems. We analysed potential the data exchange production system engineering. Similar requirements systems, phase plays an integral part Software Engineering (SE) Production...
Abstract The flexibility of production systems is a key factor for Industry 4.0. Capabilities and skills (C&Ss) aim at improving engineering along the system life-cycle by decoupling processes resources. However, traditional reuse approaches in engineering, such as VDI 3695, do not yet consider C&Ss. This paper proposes Capability Skill Reuse (CSR) framework to define how 3695 activities require adaptation C&S models. analyzes can facilitate identifies open issues research.
Multi-disciplinary data exchange still poses many challenges: Heterogeneous sources, diverging views, and lack of communication lead to defects, late resolving errors, mismatches over the project lifecycle. Semantic approaches such as ontologies are a viable solution derive common concepts between disciplines limit negative effects in their collaboration. However, application these semantic is quite limited due its inherent complexity. The purpose this paper, discuss concept local glossaries...
Similar to advanced software engineering, multi-disciplinary systems such as industrial production engineering (PSE), has integrate partial results from workgroups that design in parallel. Due the heterogeneity of data sources and divergence local models exchanged artefacts between PSE are complex, making automation exchange process difficult prone technical debt (TD). In this paper, we report on a case study at large company analyze TD effects, items, causes PSE, focusing process. We...
Optimization of engineering chains within production systems and control can be reached by improving the lossless information exchange among involved engineers. Within R&D different optimal chain scenarios have been developed independent from current state practice. For migrating existing networks towards these network appropriate migration paths need to identified. this paper one possible path is sketched especially reflecting human doubts processes.
In the engineering of Cyber-Physical Production Systems (CPPSs), coordination and data exchange Product (P), Process (P') Resource (R) assets is success-critical for creating high-quality products. industry, product, process, resources are often addressed individually without explicitly expressing their dependencies. Therefore, isolated can hinder efficient collaboration within CPPS projects that lead to risks in case overseen Thus, we see need PPR an Asset Network (PAN) (a) capable handling...
Data exchange and integration in a heterogeneous engineering network are challenges that an organi-zation has to address. Most practitioners have realized this challenge requires detailed consideration involvement of the related disciplines specify implement appropriate data logistics. In paper, we introduce meta-model method for development data-mapping infrastructure support work engineers responsible The is foundation logistics with automated transformation, integration, by automating...
Efficient and effective engineering data exchange is increasingly considered a key success factor in the life cycle of production systems, leading to intensified development logistic solutions. As small medium-size companies (SMEs) play important roles modern organization structures, SMEs have improve their capabilities take part these logistics Unfortunately, strong human financial resource limitations. In this paper, we introduce modular easy-to-use architecture that aims at enabling...