Patterns for reuse in production systems engineering

K Meixner, A Lüder, J Herzog, D Winkler… - International Journal of …, 2021 - World Scientific
In Production Systems Engineering (PSE), domain experts aim at reusing partial system
designs implemented as Industry 4.0 assets and software. However, the knowledge on …

Need for UAI–anatomy of the paradigm of usable artificial intelligence for domain-specific AI applicability

H Wiemer, D Schneider, V Lang, F Conrad… - Multimodal …, 2023 - mdpi.com
Data-driven methods based on artificial intelligence (AI) are powerful yet flexible tools for
gathering knowledge and automating complex tasks in many areas of science and practice …

Analysis of quality issues in production with multi-view coordination assets

S Kropatschek, T Steuer, E Kiesling, K Meixner… - IFAC-PapersOnLine, 2022 - Elsevier
The diffusion of the Industry 4.0 paradigm has led to a proliferation of data that is generated
by production assets on the shop floor. This data opens up new opportunities for the …

Designing a digital shadow for efficient, low-delay analysis of production quality risk

S Kropatschek, O Gert, I Ayatollahi… - 2022 IEEE 27th …, 2022 - ieeexplore.ieee.org
Manufacturers in the automotive industry extensively rely on iterative process Failure Mode
and Effects Analysis (FMEA) in their quality management. Process FMEAs model technical …

Risk and engineering knowledge integration in cyber-physical production systems engineering

F Rinker, K Meixner, S Kropatschek… - 2022 48th Euromicro …, 2022 - ieeexplore.ieee.org
In agile Cyber-physical Production System (CPPS) engineering, multi-disciplinary teams
work concurrently and iteratively on various CPPS engineering artifacts, based on …

Engineering Data Treasures, Their Collection and Use

A Lüder, K Meixner, S Biffl - IFAC-PapersOnLine, 2022 - Elsevier
Abstract “Data is the new oil” is a frequently pronounced statement. It is expected that
intelligent utilization of information will change economies. With respect to production …

AutomationML-Based Risk Modeling for Decision Support in Engineering Lifecycles

P Hünecke, C Binder, D Hoffmann… - 2024 IEEE 29th …, 2024 - ieeexplore.ieee.org
This paper discusses the challenges and associated risks that companies face due to the
growing complexity of systems engineering. It highlights the significance of effective and …

[PDF][PDF] Efficient Multi-view Change Management in Agile Production Systems Engineering.

F Rinker, S Kropatschek, T Steuer, K Meixner… - ICEIS (2), 2022 - researchgate.net
Agile Production Systems Engineering (PSE) is a complex, collaborative, and knowledge-
intensive process. PSE requires expert knowledge from various disciplines and the …