Process-aware digital twin cockpit synthesis from event logs

Bano, Dorina; Michael, Judith; Rumpe, Bernhard; Varga, Simon; Weske, Mathias

doi:10.1016/j.cola.2022.101121

Cited by 24 publications

(17 citation statements)

References 29 publications

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“…Now, we use the Business Process Management (BPM) approach in order to model, define, organize and monitor the healthcare processes, analysing and consequently optimising the clinical activities under study [27]. For the graphical representation of process steps, we have adopted the Business Process Model and Notation (BPMN) [28], [29]. In particular, the process flow modelled with BPMN notation [30] using Signavio tool is visible in the following figure (Figure 9):…”

Section: Process Mining Application and Resultsmentioning

confidence: 99%

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Striani¹,

Colucci²,

Corallo³

et al. 2022

Adv. sci. technol. eng. syst. j.

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Process mining is an innovative technique through which inefficiencies in production systems can be eliminated. This technique has therefore become very important internationally in recent years and is also useful for pursuing the improvement of production systems by extrapolating process knowledge from event logs recorded by information systems. Process mining has easy application in production systems as current business processes are integrated with information systems and this makes data available immediately. This makes the complex nature of industrial operations understandable and, for this reason, process mining could also be used in the healthcare field where cost containment and the quality of service increasing offered to the community has become paramount. The problem is that in this sector, it is much more complex to identify useful data in order to extrapolate the relevant log file. The article aim is to examine the state of the art of the application of process mining in the healthcare sector in order to understand the level of diffusion of these techniques. In the light of this analysis, a case study will then be analysed on the application of process mining techniques in the healthcare sector, and in particular in medical teleconsultation in the field of neuroradiology.

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Section: Process Mining Application and Resultsmentioning

confidence: 99%

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Striani¹,

Colucci²,

Corallo³

et al. 2022

Adv. sci. technol. eng. syst. j.

View full text Add to dashboard Cite

show abstract

“…The developed prototype and the strengths of our approach (see "Discussion: Limitations and Strengths") has provided us with the necessary information to consider an application of this approach in full-size real-world applications, e.g., the MaCoCo project [27]. Additional application areas include assistive services within generated information systems [47], to generate processaware digital twin cockpits [5], or the addition of assistive services for the human-in-the-loop within digital twins [14].…”

Section: Discussionmentioning

confidence: 99%

“…The BPMN generator (4) is responsible to process all necessary model files (1-3): It takes the CD domain model (1) defining the data structure, BPMN models (2) defining the processes and tagging models (3) defining roles as input and produces for each of the given BPMN models (2), one or more CD data models and GUI models (5). The GUI models and CDs are process-specific: For each user task, a GUI model is created, that describes the corresponding task page.…”

Section: Generation Processmentioning

confidence: 99%

“…In a second generation step, the MontiGem generator framework ( 6) is used to generate the PAIS based on the domain model (1), further domain-specific models (7), and the generated models from the first step (5). The PAIS consists of a back-end, front-end, and databases.…”

Section: Generation Processmentioning

confidence: 99%

“…In these cases, already generated forms in the data-centric application will need to be replaced: In Fig. 7, some GUI models (5), which were generated by the BPMN generator (4), will replace some of the hand-written GUI models (7) to generate the new forms. If hand-written additions (8) already exist, they might have to be adapted to extend the newly generated pages and fit to the structure.…”

Section: Adding New Functionalities Vs Replacing Functionalitiesmentioning

confidence: 99%

See 2 more Smart Citations

Model-Driven Engineering of Process-Aware Information Systems

Drave

Michael²,

Müller³

et al. 2022

SN COMPUT. SCI.

Self Cite

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Enterprise information systems created with model-driven software engineering methods need to handle not only data but also business processes in an automated way. This paper shows how to engineer process-aware information systems following the model-driven and generative software engineering paradigms. Existing approaches realize either the generation of automated or manual activities but do not employ model-driven engineering of all system aspects through systematic language composition. A generative approach that additionally uses process modeling languages allows developers to evolve generated data-centric information systems into process-aware information systems. To be usable within our generation process, we have developed a textual BPMN version and a corresponding language tooling to check the soundness of the models. We have included these process models into the generation process of an information system together with other domain-specific modeling languages, e.g., for data structures, and generate an extendable, process-aware information system that is open for continuous regeneration and hand-written additions. This approach allows us to lift a generated data-centric information system to a process-aware information system. Agile development enabled through the opportunity to validate assumptions automatically and adapt changes efficiently, enhances the engineering process as well as the generated systems themselves.

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Model‐based digital twins of medicine dispensers for healthcare IoT applications

Sartaj,

Ali,

Yue

et al. 2024

Softw Pract Exp

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SummaryHealthcare applications with the Internet of Things (IoT) are often safety‐critical, thus, require extensive testing. Such applications are often connected to smart medical devices from various vendors. System‐level testing of such applications requires test infrastructures physically integrating medical devices, which is time and monetary‐wise expensive. Moreover, applications continuously evolve, for example, introducing new devices and users and updating software. Nevertheless, a test infrastructure enabling testing with a few devices is insufficient for testing healthcare IoT systems, hence compromising their dependability. In this paper, we propose a model‐based approach for the creation and operation of digital twins (DTs) of medicine dispensers as a replacement for physical devices to support the automated testing of IoT applications at scale. We evaluate our approach with an industrial IoT system with medicine dispensers in the context of Oslo City and its industrial partners, providing healthcare services to its residents. We study the fidelity of DTs in terms of their functional similarities with their physical counterparts: medicine dispensers. Results show that the DTs behave more than 92% similar to the physical medicine dispensers, providing a faithful replacement for the dispenser.

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Process-aware digital twin cockpit synthesis from event logs

Cited by 24 publications

References 29 publications

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Process Mining in Healthcare: A Systematic Literature Review and A Case Study

Model-Driven Engineering of Process-Aware Information Systems

Model‐based digital twins of medicine dispensers for healthcare IoT applications

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