Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)

Aalst, Wil M. P. van der; Brockhoff, Tobias; Ghahfarokhi, Anahita Farhang; Pourbafrani, Mahsa; Uysal, Merih Seran; Zelst, Sebastiaan J. van

doi:10.1007/978-3-030-83014-4_1

Cited by 13 publications

(7 citation statements)

References 41 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition, interdisciplinary research approaches allow the evaluation and optimization of process mining methods, aimed at the identification of discrete events, potentially enabling the modeling of dependencies in organ crosstalk. 174…”

Section: Systems Biology Approach To Organ Crosstalkmentioning

confidence: 99%

“…[170][171][172][173] In addition, interdisciplinary research approaches allow the evaluation and optimization of process mining methods, aimed at the identification of discrete events, potentially enabling the modeling of dependencies in organ crosstalk. 174 Emerging data ecosystems like International Data Spaces 175 provide a holistic solution for the generation and sharing of data and knowledge, which are mandatory prerequisites for the advancement of analytical methods. Data quality and transparency are identified as key challenges during the evaluation of alliance-driven data ecosystems, in the context of multisite clinical studies.…”

Section: Future Perspective Of Computational Ecosystems For Multiorga...mentioning

confidence: 99%

See 1 more Smart Citation

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

Lohmöller

Kühl

et al. 2023

Circulation Research

View full text Add to dashboard Cite

The identification of mediators for physiologic processes, correlation of molecular processes, or even pathophysiological processes within a single organ such as the kidney or heart has been extensively studied to answer specific research questions using organ-centered approaches in the past 50 years. However, it has become evident that these approaches do not adequately complement each other and display a distorted single-disease progression, lacking holistic multilevel/multidimensional correlations. Holistic approaches have become increasingly significant in understanding and uncovering high dimensional interactions and molecular overlaps between different organ systems in the pathophysiology of multimorbid and systemic diseases like cardiorenal syndrome because of pathological heart-kidney crosstalk. Holistic approaches to unraveling multimorbid diseases are based on the integration, merging, and correlation of extensive, heterogeneous, and multidimensional data from different data sources, both -omics and nonomics databases. These approaches aimed at generating viable and translatable disease models using mathematical, statistical, and computational tools, thereby creating first computational ecosystems. As part of these computational ecosystems, systems medicine solutions focus on the analysis of -omics data in single-organ diseases. However, the data–scientific requirements to address the complexity of multimodality and multimorbidity reach far beyond what is currently available and require multiphased and cross-sectional approaches. These approaches break down complexity into small and comprehensible challenges. Such holistic computational ecosystems encompass data, methods, processes, and interdisciplinary knowledge to manage the complexity of multiorgan crosstalk. Therefore, this review summarizes the current knowledge of kidney-heart crosstalk, along with methods and opportunities that arise from the novel application of computational ecosystems providing a holistic analysis on the example of kidney-heart crosstalk.

show abstract

Section: Systems Biology Approach To Organ Crosstalkmentioning

confidence: 99%

Section: Future Perspective Of Computational Ecosystems For Multiorga...mentioning

confidence: 99%

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

Lohmöller

Kühl

et al. 2023

Circulation Research

View full text Add to dashboard Cite

show abstract

“…One assembly step may involve different parts, a machine, and an operator. This leads to the well-known convergence and divergence problems (van der Aalst and Berti, 2020;van der Aalst, 2021a). The convergence problem surfaces when a fine-grained case notion is used and the flattening of the event data leads to the unintentional replication of events, e.g., an assembly step is replicated for all the parts involved in it.…”

mentioning

confidence: 99%

“…Classical process mining forces the adoption of a single view of the processes under consideration. Object-centric process mining (OCPM) addresses the limitation by allowing for any number of objects per event (van der Aalst and Berti, 2020;van der Aalst, 2021a). This extension is highly relevant for the IoP and its Digital Shadows.…”

mentioning

confidence: 99%

“…3 agree on the core concepts. Using such object-centric event data, it is possible to discover object-centric process models and check conformance automatically (van der Aalst and Berti, 2020;van der Aalst, 2021a). For example, van der Aalst and Berti (2020) shows that it is possible to automatically learn object-centric Petri nets showing frequencies, delay distributions, and probabilities in an integrated process model describing the interactions between any number of object types.…”

mentioning

confidence: 99%

See 1 more Smart Citation

Digital Shadows: Infrastructuring the Internet of Production

Aalst

Jarke

Koren

et al. 2023

Interdisciplinary Excellence Accelerator Series

Self Cite

View full text Add to dashboard Cite

Digitization in the field of production is fragmented in very different domains, ranging from materials to production technology to process and business models. Each domain comes with specialized knowledge, often incorporated into mathematical models. This heterogeneity makes it hard to naively exploit advances in data-driven machine learning that could facilitate situation adaptation and experience transfer. Innovative combinations of model-driven and data-driven solutions must be invented but also made comparable and interoperable to avoid ending up in information silos. In future World Wide Labs (WWLs), experiences can be shared, aggregated, and used for innovation. WWLs will be complex, evolving socio-technical networks of interconnected devices, software, data stores, and humans as users and contributors of expert knowledge and feedback. Integrating a large number of research labs, engineering, and production sites requires a capable cross-domain Internet of Production (IoP) infrastructure. The IoP project claims Digital Shadows (DSs) to offer a shared conceptual foundation for infrastructuring the IoP. In engineering, DSs were introduced as the data provision link to Digital Twins, whereas in computer science, DSs generalize the well-established concept of database views. In this chapter, we elaborate on the roles of DSs in infrastructuring the IoP from three perspectives: analytic functionality, conceptual organization, and technical networking. As an example where an integrative DS-like approach is already highly successful, we showcase the approach and infrastructure of the process mining field.

show abstract

Concurrency and Objects Matter! Disentangling the Fabric of Real Operational Processes to Create Digital Twins

Aalst

2021

Theoretical Aspects of Computing – ICTAC 2021

View full text Add to dashboard Cite

Removing Operational Friction Using Process Mining: Challenges Provided by the Internet of Production (IoP)

Cited by 13 publications

References 41 publications

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

Use of Computation Ecosystems to Analyze the Kidney-Heart Crosstalk

Digital Shadows: Infrastructuring the Internet of Production

Concurrency and Objects Matter! Disentangling the Fabric of Real Operational Processes to Create Digital Twins

Contact Info

Product

Resources

About