Ronny Seiger
49 results
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Item type:Publication, A conceptual model and methodology for sustainability-aware, IoT-enhanced business processes(2026-10); - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Online detection of process activity executions from IoT sensors using generated event processing servicesData streams from Internet of Things (IoT) devices containing sensors and actuators provide new insights into their interactions, context, and process executions in the physical world. These new data sources may open up novel opportunities to apply Business Process Management (BPM) technologies to analyze process and activity executions using established process mining techniques. However, the rather low abstraction level of data emitted from the IoT devices is often not suitable to directly apply process mining, which requires additional steps of event abstraction. Related approaches train expensive supervised machine learning models on historical sensor data to realize this event abstraction enabling only a post-mortem classification of activity executions. In this work we propose a framework to automatically generate activity detection services from IoT data with minimal human involvement to implement the event abstraction. Along with the framework, we present a software architecture focused on a flexible and extensible complex event processing (CEP) platform that achieves high-performance activity detection from IoT data streams at runtime-enabling online process analytics. Evaluations of our proof-of-concept implementation to monitor processes executed in smart manufacturing and smart healthcare show acceptable results when detecting activities that are affected by no to only small variations in the underlying IoT data. We identify several ways to improve the robustness of the activity detections regarding variations in IoT data as starting points for future work.Type:journal articleJournal:Future Generation Computer SystemsVolume:174Scopus© Citations 7 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Digital Twins of Business Processes: A Research Manifesto(Elsevier, 2024)Scopus© Citations 24 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, RBPMN: the value of roles for business process modelingBusiness process modeling is essential for organizations to comprehend, analyze, and enhance their business operations. The business process model and notation (BPMN) is a standard widely adopted for illustrating business processes. However, it falls short when modeling roles, interactions, and responsibilities within complex modern processes that involve digital, human, and non-human entities, typically found in cyber-physical systems (CPS). In this paper, we introduce Role-based BPMN (RBPMN), a standard-compliant extension of BPMN 2.0 that distinctly depicts roles and their interactions within business processes. We underscore the value of RBPMN and a role-based context modeling approach through a modeling example in CPS that facilitates the representation of role-based variations in the process flow, namely a production process in a smart factory. Our findings suggest that RBPMN is a valuable BPMN extension that enhances the expressiveness, variability, and comprehensiveness of business process models, especially in complex and context-sensitive processes.Type:journal articleJournal:Software and Systems ModelingScopus© Citations 14 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, The biggest business process management problems to solve before we die(Elsevier, 2023-01)Scopus© Citations 165 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, An Interactive Method for Detection of Process Activity Executions from IoT Data(2023-02); ; The increasing number of IoT devices equipped with sensors and actuators pervading every domain of everyday life allows for improved automated monitoring and analysis of processes executed in IoT-enabled environments. While sophisticated analysis methods exist to detect specific types of activities from low-level IoT data, a general approach for detecting activity executions that are part of more complex business processes does not exist. Moreover, dedicated information systems to orchestrate or monitor process executions are not available in typical IoT environments. As a consequence, the large corpus of existing process analysis and mining techniques to check and improve process executions cannot be applied. In this work, we develop an interactive method guiding the analysis of low-level IoT data with the goal of detecting higher-level process activity executions. The method is derived following the exploratory data analysis of an IoT data set from a smart factory. We propose analysis steps, sensor-actuator-activity patterns, and the novel concept of activity signatures that are applicable in many IoT domains. The method shows to be valuable for the early stages of IoT data analyses to build a ground truth based on domain knowledge and decisions of the process analyst, which can be used for automated activity detection in later stages.Type:journal articleJournal:Future InternetVolume:15Issue:2Scopus© Citations 40 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Integrating process management and event processing in smart factories: A systems architecture and use casesThe developments of new concepts for an increased digitization of manufacturing industries in the context of Industry 4.0 have brought about novel system architectures and frameworks for smart production systems. These range from generic frameworks for Industry 4.0 to domain-specific architectures for Industrial Internet of Things (IIoT). While most of the approaches include a service-based architecture for selective integration with enterprise systems, a close two-way integration of the production control systems and IIoT sensors and actuators with Process-Aware Information Systems (PAIS) on the management level for automation and mining of production processes is rarely discussed. This fusion of Business Process Management (BPM) with IIoT can be mutually beneficial for both research areas, but is still in its infancy. We propose a systems architecture for IIoT that shows how to integrate the low-level hardware components–sensors and actuators–of a smart factory with BPM systems. We discuss the software components and their interactions to address challenges of device encapsulation, integration of sensor events, and interaction with existing BPM systems. This integration is demonstrated within several use cases regarding process modeling, automation and mining for a smart factory model, showing benefits of using BPM technologies to analyze, control, and adapt discrete production processes in IIoT.Type:journal articleJournal:Journal of Manufacturing SystemsVolume:63Scopus© Citations 69 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, HoloFlows: modelling of processes for the Internet of Things in mixed realityOur everyday lives are increasingly pervaded by digital assistants and smart devices forming the Internet of Things (IoT). While user interfaces to directly monitor and control individual IoT devices are becoming more sophisticated and end-user friendly, applications to connect standalone IoT devices and create more complex IoT processes for automating and assisting users with repetitive tasks still require a high level of technical expertise and programming knowledge. Related approaches for process modelling in IoT mostly suggest extensions to complex modelling languages, require high levels of abstraction and technical knowledge, and rely on unintuitive tools. We present a novel approach for end-user oriented--no-code--IoT process modelling using Mixed Reality (MR) technology: HoloFlows. Users are able to explore the IoT environment and model processes among sensors and actuators as first class citizens by simply "drawing" virtual wires among physical IoT devices. MR technology hereby facilitates the understanding of the physical contexts and relations among the IoT devices and provides a new and more intuitive way of modelling IoT processes. The results of a user study comparing HoloFlows with classical modelling approaches show an increased user experience and decrease of required modelling knowledge and technical expertise to create IoT processes.Type:journal articleJournal:Software and Systems ModelingScopus© Citations 54 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, Immersives verteiltes Robotic Co-workingType:journal articleJournal:Informatik SpektrumVolume:43Issue:6Scopus© Citations 2 - Some of the metrics are blocked by yourconsent settings
Item type:Publication, AI Assistance for Architectural Decision Making: Domain-Driven Context and Prompt EngineeringGenerative Artificial Intelligence (AI) is receiving a lot of focus in research and practice at present; positions vary from euphoria to "just another tool" to skepticism. Software architecture analysis, synthesis, and evaluation offer many opportunities for AI, e.g., support for knowledge-intensive tasks such as making and recording architectural decisions. It is not yet fully understood how architects can be assisted by AI effectively and efficiently: AI services have to be supervised via input specifications and output validation, requiring architecting skills and application domain expertise. In this paper, we identify architecturally significant requirements to drive the design of a future ecosystem of AI-Assisted Decision Assistance tools (AID). We apply Domain-Driven Design (DDD) to establish a logical component architecture for AID that leverages model-driven knowledge management concepts to accelerate context and prompt/skills engineering and to guard response processing.Type:conference paperJournal:Workshop on Intelligent & Data-driven Engineering for Software Architecture (IDEA-ARCH)