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On obligations in the development process of resilient systems with algorithmic design methods
(2018)
Advanced computational methods are needed both for the design of large systems and to compute high accuracy solutions. Such methods are efficient in computation, but the validation of results is very complex, and highly skilled auditors are needed to verify them. We investigate legal questions concerning obligations in the development phase, especially for technical systems developed using advanced methods. In particular, we consider methods of resilient and robust optimization. With these techniques, high performance solutions can be found, despite a high variety of input parameters. However, given the novelty of these methods, it is uncertain whether legal obligations are being met. The aim of this paper is to discuss if and how the choice of a specific computational method affects the developer’s product liability. The review of legal obligations in this paper is based on German law and focuses on the requirements that must be met during the design and development process.
Algorithmic design and resilience assessment of energy efficient high-rise water supply systems
(2018)
High-rise water supply systems provide water flow and suitable pressure in all levels of tall buildings. To design such state-of-the-art systems, the consideration of energy efficiency and the anticipation of component failures are mandatory. In this paper, we use Mixed-Integer Nonlinear Programming to compute an optimal placement of pipes and pumps, as well as an optimal control strategy.Moreover, we consider the resilience of the system to pump failures. A resilient system is able to fulfill a predefined minimum functionality even though components fail or are restricted in their normal usage. We present models to measure and optimize the resilience. To demonstrate our approach, we design and analyze an optimal resilient decentralized water supply system inspired by a real-life hotel building.
Digital twins enable the modeling and simulation of real-world entities (objects, processes or systems), resulting in improvements in the associated value chains. The emerging field of quantum computing holds tremendous promise forevolving this virtualization towards Quantum (Digital) Twins (QDT) and ultimately Quantum Twins (QT). The quantum (digital) twin concept is not a contradiction in terms - but instead describes a hybrid approach that can be implemented using the technologies available today by combining classicalcomputing and digital twin concepts with quantum processing. This paperpresents the status quo of research and practice on quantum (digital) twins. It alsodiscuses their potential to create competitive advantage through real-timesimulation of highly complex, interconnected entities that helps companies better
address changes in their environment and differentiate their products andservices.
This paper presents an approach for reducing the cognitive load for humans working in quality control (QC) for production processes that adhere to the 6σ -methodology. While 100% QC requires every part to be inspected, this task can be reduced when a human-in-the-loop QC process gets supported by an anomaly detection system that only presents those parts for manual inspection that have a significant likelihood of being defective. This approach shows good results when applied to image-based QC for metal textile products.
The initial idea of Robotic Process Automation (RPA) is the automation of business processes through the presentation layer of existing application systems. For this simple emulation of user input and output by software robots, no changes of the systems and architecture is required. However, considering strategic aspects of aligning business and technology on an enterprise level as well as the growing capabilities of RPA driven by artificial intelligence, interrelations between RPA and Enterprise Architecture (EA) become visible and pose new questions. In this paper we discuss the relationship between RPA and EA in terms of perspectives and implications. As workin- progress we focus on identifying new questions and research opportunities related to RPA and EA.
In der Diskussion über die Digitalisierung der Forschung spielt die Frage nach der optimalen IT-Unterstützung für Forschende eine wichtige Rolle. Forschende können heute an ihren Hochschulen bzw. Wissenschaftseinrichtungen auf ein breites Angebot interner IT-Dienstleistungen zurückgreifen, das auch kooperative IT-Dienste umfasst, die von mehreren Institutionen in Zusammenarbeit bereitgestellt werden. Außerhalb der eigenen Organisation und des weiteren Verbunds hat sich im Internet zudem ein breites externes Angebot an innovativen, häufig kostenlos nutzbaren Onlinediensten entwickelt. Neben horizontalen Onlinediensten, die sich prinzipiell an jeden Internetnutzer richten (bspw. Dropbox, Twitter, WhatsApp), nimmt auch die Zahl von vertikalen Diensten für wissenschaftliche bzw. Forschungszwecke immer weiter zu (bspw. GoogleScholar, ResearchGate, figshare). Für Forschende eröffnen sich damit vielfältige neue Möglichkeiten, ihren individuellen Forschungsprozess durch digitale Werkzeuge zu verbessern. Aufgrund rechtlicher, technischer und personeller Restriktionen können jedoch interne Dienstleister bei der Identifizierung, Auswahl und Nutzung externer Onlinedienste nur wenig Unterstützung leisten. Aus einer serviceorientierten Perspektive stehen Forschende zunehmend vor dem Problem, wie sich heterogene IT-Dienste interner und externer Anbieter in den eigenen Forschungsprozess integrieren lassen. Als Lösungsansatz skizziert das Kapitel das Konzept eines persönlichen Forschungsinformationssystems
nach Gesichtspunkten eines digitalen Servicesystems.