Hierarchical workflow management system for life science applications

In modern laboratories, an increasing number of automated stations and instruments are applied as standalone automated systems such as biological high throughput screening systems, chemical parallel reactors etc. At the same time, the mobile robot transportation solution becomes popular with the development of robotic technologies. In this dissertation, a new superordinate control system, called hierarchical workflow management system (HWMS) is presented to manage and to handle both, automated laboratory systems and logistics systems.In modernen Labors werden immer mehr automatisierte Stationen und Instrumente als eigenständige automatisierte Systeme eingesetzt, wie beispielsweise biologische High-Throughput-Screening-Systeme und chemische Parallelreaktoren. Mit der Entwicklung der Robotertechnologien wird gleichzeitig die mobile Robotertransportlösung populär. In der vorliegenden Arbeit wurde ein hierarchisches Verwaltungssystem für Abeitsablauf, welches auch als HWMS bekannt ist, entwickelt. Das neue übergeordnete Kontrollsystem kann sowohl automatisierte Laborsysteme als auch Logistiksysteme verwalten und behandeln

Adaptive Process Management in Cyber-Physical Domains

The increasing application of process-oriented approaches in new challenging cyber-physical domains beyond business computing (e.g., personalized healthcare, emergency management, factories of the future, home automation, etc.) has led to reconsider the level of flexibility and support required to manage complex processes in such domains. A cyber-physical domain is characterized by the presence of a cyber-physical system coordinating heterogeneous ICT components (PCs, smartphones, sensors, actuators) and involving real world entities (humans, machines, agents, robots, etc.) that perform complex tasks in the “physical” real world to achieve a common goal. The physical world, however, is not entirely predictable, and processes enacted in cyber-physical domains must be robust to unexpected conditions and adaptable to unanticipated exceptions. This demands a more flexible approach in process design and enactment, recognizing that in real-world environments it is not adequate to assume that all possible recovery activities can be predefined for dealing with the exceptions that can ensue. In this chapter, we tackle the above issue and we propose a general approach, a concrete framework and a process management system implementation, called SmartPM, for automatically adapting processes enacted in cyber-physical domains in case of unanticipated exceptions and exogenous events. The adaptation mechanism provided by SmartPM is based on declarative task specifications, execution monitoring for detecting failures and context changes at run-time, and automated planning techniques to self-repair the running process, without requiring to predefine any specific adaptation policy or exception handler at design-time

NLP Powered Intent Based Network Management for Private 5G Networks

Intent driven networking holds the promise of simplifying network operations by allowing operators to use declarative, instead of imperative, interfaces. Adoption of this technology for 5G and beyond networks is however still in its infancy, where the required architectures, platforms, interfaces and algorithms are still being discussed. In this work, we present the design and implementation of a novel intent based platform for private 5G networks powered by a Natural Language Processing (NLP) interface. We demonstrate how our platform simplifies network operations in three relevant private network use cases, including: i) an intent based slice provisioning use case, ii) an intent based positioning use case, and iii) an intent based service deployment use case. Finally, all use cases are benchmarked in terms of intent provisioning time.European Commission’s Horizon 2020 871428, 5G-CLARIT