@article{seiger_process_management_smart_factories_2022,
	title        = {{Integrating process management and event processing in smart factories: A systems architecture and use cases}},
	author       = {Seiger, Ronny and Malburg, Lukas and Weber, Barbara and Bergmann, Ralph},
	year         = 2022,
	journal      = {{Journal of Manufacturing Systems}},
	volume       = 63,
	pages        = {575--592},
	doi          = {10.1016/j.jmsy.2022.05.012},
	url          = {http://www.wi2.uni-trier.de/shared/publications/2022_Seiger_JOMS.pdf},
	abstract     = {The 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.}
}

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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.","bibtex":"@article{seiger_process_management_smart_factories_2022,\n\ttitle = {{Integrating process management and event processing in smart factories: A systems architecture and use cases}},\n\tauthor = {Seiger, Ronny and Malburg, Lukas and Weber, Barbara and Bergmann, Ralph},\n\tyear = 2022,\n\tjournal = {{Journal of Manufacturing Systems}},\n\tvolume = 63,\n\tpages = {575--592},\n\tdoi = {10.1016/j.jmsy.2022.05.012},\n\turl = {http://www.wi2.uni-trier.de/shared/publications/2022_Seiger_JOMS.pdf},\n\tabstract = {The 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.}\n}\n\n","author_short":["Seiger, R.","Malburg, L.","Weber, B.","Bergmann, R."],"key":"seiger_process_management_smart_factories_2022","id":"seiger_process_management_smart_factories_2022","bibbaseid":"seiger-malburg-weber-bergmann-integratingprocessmanagementandeventprocessinginsmartfactoriesasystemsarchitectureandusecases-2022","role":"author","urls":{"Paper":"http://www.wi2.uni-trier.de/shared/publications/2022_Seiger_JOMS.pdf"},"metadata":{"authorlinks":{}},"downloads":21,"html":""},"bibtype":"article","biburl":"https://web.wi2.uni-trier.de/publications/PublicationsMalburg.bib","dataSources":["vtdjwAo6eNiqRLfnG","nZxfXH3fRFhwWejKL","MSp3DzP4ToPojqkFy","Td7BJ334QwxWK4vLW","J3orK6zvpR7d8vDmC"],"keywords":[],"search_terms":["integrating","process","management","event","processing","smart","factories","systems","architecture","use","cases","seiger","malburg","weber","bergmann"],"title":"Integrating process management and event processing in smart factories: A systems architecture and use cases","year":2022,"downloads":21}