---
_id: '63397'
abstract:
- lang: eng
text: Decarbonizing industrial process heat is a crucial step in mitigating climate
change. While Process Mining (PM) has gained traction in sustainability research—such
as optimizing production scheduling to reduce energy use or accounting for carbon
footprints—it has largely overlooked the challenges and opportunities related
to thermal energy, accounting for 66% of total energy demand in industrial processes.
At the same time, Heat Integration (HI) is an established engineering discipline
focused on maximizing the efficiency of thermal energy systems. However, HI traditionally
relies on static or incomplete data about energy demands, limiting its effectiveness
and accuracy. In this paper, we propose a novel framework that combines PM and
HI to enable data-driven, process- and product-centric modeling of industrial
energy demands. By integrating event logs and thermal energy data, our approach
allows for a fine-grained analysis of heat demand patterns corresponding to specific
process activities and product variants. We demonstrate the applicability and
advantages of the framework by simulating a pharmaceutical manufacturing process
and evaluating energy demands and heat recovery potentials. Our findings show
that our PM-enabled HI framework provides more accurate and actionable insights
into the temporal and product-specific variation of thermal energy demands. By
capturing the causal relationships between process activities, product characteristics,
and energy consumption, our approach enables improved analysis, planning, and
optimization for heat recovery and process decarbonization. This integration of
PM and HI expands the analytical tools for both disciplines and contributes to
advancing the sustainable transformation of industrial processes.
author:
- first_name: David Ricardo
full_name: Zapata Gonzalez, David Ricardo
id: '105506'
last_name: Zapata Gonzalez
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Kay
full_name: Benkert, Kay
last_name: Benkert
- first_name: Florian
full_name: Schlosser, Florian
id: '88614'
last_name: Schlosser
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Zapata Gonzalez DR, Brennig K, Benkert K, Schlosser F, Müller O. Process Mining
for Robust Heat Integration through Process- and Product-Centric Energy Demand
Modeling. In: ACM SIGEnergy Energy Informatics Review. Vol 5. Association
for Computing Machinery (ACM); 2025:19-31. doi:10.1145/3777518.3777520'
apa: Zapata Gonzalez, D. R., Brennig, K., Benkert, K., Schlosser, F., & Müller,
O. (2025). Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling. ACM SIGEnergy Energy Informatics Review, 5(3),
19–31. https://doi.org/10.1145/3777518.3777520
bibtex: '@inproceedings{Zapata Gonzalez_Brennig_Benkert_Schlosser_Müller_2025, title={Process
Mining for Robust Heat Integration through Process- and Product-Centric Energy
Demand Modeling}, volume={5}, DOI={10.1145/3777518.3777520},
number={3}, booktitle={ACM SIGEnergy Energy Informatics Review}, publisher={Association
for Computing Machinery (ACM)}, author={Zapata Gonzalez, David Ricardo and Brennig,
Katharina and Benkert, Kay and Schlosser, Florian and Müller, Oliver}, year={2025},
pages={19–31} }'
chicago: Zapata Gonzalez, David Ricardo, Katharina Brennig, Kay Benkert, Florian
Schlosser, and Oliver Müller. “Process Mining for Robust Heat Integration through
Process- and Product-Centric Energy Demand Modeling.” In ACM SIGEnergy Energy
Informatics Review, 5:19–31. Association for Computing Machinery (ACM), 2025.
https://doi.org/10.1145/3777518.3777520.
ieee: 'D. R. Zapata Gonzalez, K. Brennig, K. Benkert, F. Schlosser, and O. Müller,
“Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling,” in ACM SIGEnergy Energy Informatics Review, 2025,
vol. 5, no. 3, pp. 19–31, doi: 10.1145/3777518.3777520.'
mla: Zapata Gonzalez, David Ricardo, et al. “Process Mining for Robust Heat Integration
through Process- and Product-Centric Energy Demand Modeling.” ACM SIGEnergy
Energy Informatics Review, vol. 5, no. 3, Association for Computing Machinery
(ACM), 2025, pp. 19–31, doi:10.1145/3777518.3777520.
short: 'D.R. Zapata Gonzalez, K. Brennig, K. Benkert, F. Schlosser, O. Müller, in:
ACM SIGEnergy Energy Informatics Review, Association for Computing Machinery (ACM),
2025, pp. 19–31.'
date_created: 2025-12-22T13:13:37Z
date_updated: 2025-12-22T13:15:08Z
doi: 10.1145/3777518.3777520
intvolume: ' 5'
issue: '3'
language:
- iso: eng
main_file_link:
- open_access: '1'
url: https://dl.acm.org/doi/abs/10.1145/3777518.3777520
oa: '1'
page: 19-31
publication: ACM SIGEnergy Energy Informatics Review
publication_identifier:
issn:
- 2770-5331
- 2770-5331
publication_status: published
publisher: Association for Computing Machinery (ACM)
status: public
title: Process Mining for Robust Heat Integration through Process- and Product-Centric
Energy Demand Modeling
type: conference
user_id: '105506'
volume: 5
year: '2025'
...
---
_id: '54434'
author:
- first_name: Jonathan
full_name: Brock, Jonathan
last_name: Brock
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Sebastian
full_name: von Enzberg, Sebastian
last_name: von Enzberg
- first_name: Roman
full_name: Dumitrescu, Roman
id: '16190'
last_name: Dumitrescu
citation:
ama: 'Brock J, Brennig K, Löhr B, Bartelheimer C, von Enzberg S, Dumitrescu R. Improving
Process Mining Maturity: From Intentions to Action. Business & Information
Systems Engineering. Published online 2024. doi:10.1007/s12599-024-00882-7'
apa: 'Brock, J., Brennig, K., Löhr, B., Bartelheimer, C., von Enzberg, S., &
Dumitrescu, R. (2024). Improving Process Mining Maturity: From Intentions to Action.
Business & Information Systems Engineering. https://doi.org/10.1007/s12599-024-00882-7'
bibtex: '@article{Brock_Brennig_Löhr_Bartelheimer_von Enzberg_Dumitrescu_2024, title={Improving
Process Mining Maturity: From Intentions to Action}, DOI={10.1007/s12599-024-00882-7},
journal={Business & Information Systems Engineering}, author={Brock, Jonathan
and Brennig, Katharina and Löhr, Bernd and Bartelheimer, Christian and von Enzberg,
Sebastian and Dumitrescu, Roman}, year={2024} }'
chicago: 'Brock, Jonathan, Katharina Brennig, Bernd Löhr, Christian Bartelheimer,
Sebastian von Enzberg, and Roman Dumitrescu. “Improving Process Mining Maturity:
From Intentions to Action.” Business & Information Systems Engineering,
2024. https://doi.org/10.1007/s12599-024-00882-7.'
ieee: 'J. Brock, K. Brennig, B. Löhr, C. Bartelheimer, S. von Enzberg, and R. Dumitrescu,
“Improving Process Mining Maturity: From Intentions to Action,” Business &
Information Systems Engineering, 2024, doi: 10.1007/s12599-024-00882-7.'
mla: 'Brock, Jonathan, et al. “Improving Process Mining Maturity: From Intentions
to Action.” Business & Information Systems Engineering, 2024, doi:10.1007/s12599-024-00882-7.'
short: J. Brock, K. Brennig, B. Löhr, C. Bartelheimer, S. von Enzberg, R. Dumitrescu,
Business & Information Systems Engineering (2024).
date_created: 2024-05-23T10:43:18Z
date_updated: 2024-08-19T09:17:58Z
doi: 10.1007/s12599-024-00882-7
language:
- iso: eng
publication: Business & Information Systems Engineering
publication_status: published
status: public
title: 'Improving Process Mining Maturity: From Intentions to Action'
type: journal_article
user_id: '56760'
year: '2024'
...
---
_id: '54589'
author:
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
orcid: 0000-0001-9581-4602
- first_name: Jonathan
full_name: Brock, Jonathan
last_name: Brock
- first_name: Malte Fabian
full_name: Reineke, Malte Fabian
id: '60641'
last_name: Reineke
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
citation:
ama: 'Brennig K, Löhr B, Brock J, Reineke MF, Bartelheimer C. Maximizing the Impact
of Process Mining Research: Four Strategic Guidelines. In: Americas Conference
on Information Systems (AMCIS). ; 2024.'
apa: 'Brennig, K., Löhr, B., Brock, J., Reineke, M. F., & Bartelheimer, C. (2024).
Maximizing the Impact of Process Mining Research: Four Strategic Guidelines. Americas
Conference on Information Systems (AMCIS). 30th Americas Conference on Information
Systems (AMCIS).'
bibtex: '@inproceedings{Brennig_Löhr_Brock_Reineke_Bartelheimer_2024, title={Maximizing
the Impact of Process Mining Research: Four Strategic Guidelines}, booktitle={Americas
Conference on Information Systems (AMCIS)}, author={Brennig, Katharina and Löhr,
Bernd and Brock, Jonathan and Reineke, Malte Fabian and Bartelheimer, Christian},
year={2024} }'
chicago: 'Brennig, Katharina, Bernd Löhr, Jonathan Brock, Malte Fabian Reineke,
and Christian Bartelheimer. “Maximizing the Impact of Process Mining Research:
Four Strategic Guidelines.” In Americas Conference on Information Systems (AMCIS),
2024.'
ieee: 'K. Brennig, B. Löhr, J. Brock, M. F. Reineke, and C. Bartelheimer, “Maximizing
the Impact of Process Mining Research: Four Strategic Guidelines,” presented at
the 30th Americas Conference on Information Systems (AMCIS), 2024.'
mla: 'Brennig, Katharina, et al. “Maximizing the Impact of Process Mining Research:
Four Strategic Guidelines.” Americas Conference on Information Systems (AMCIS),
2024.'
short: 'K. Brennig, B. Löhr, J. Brock, M.F. Reineke, C. Bartelheimer, in: Americas
Conference on Information Systems (AMCIS), 2024.'
conference:
name: 30th Americas Conference on Information Systems (AMCIS)
date_created: 2024-06-04T12:36:52Z
date_updated: 2025-12-03T14:12:14Z
department:
- _id: '195'
language:
- iso: eng
main_file_link:
- url: https://aisel.aisnet.org/amcis2024/dsa/dsa/14/
publication: Americas Conference on Information Systems (AMCIS)
status: public
title: 'Maximizing the Impact of Process Mining Research: Four Strategic Guidelines'
type: conference
user_id: '56760'
year: '2024'
...
---
_id: '37058'
abstract:
- lang: eng
text: "Digital technologies have made the line of visibility more transparent, enabling
customers to get deeper insights into an organization’s core operations than ever
before. This creates new challenges for organizations trying to consistently deliver
high-quality customer experiences. In this paper we conduct an empirical analysis
of customers’ preferences and their willingness-to-pay for different degrees of
process transparency, using the example of digitally-enabled business-to-customer
delivery services. Applying conjoint analysis, we quantify customers’ preferences
and willingness-to-pay for different service attributes and levels. Our contributions
are two-fold: For research, we provide empirical measurements of customers’ preferences
and their willingness-to-pay for process transparency, suggesting that more is
not always better. Additionally, we provide a blueprint of how conjoint analysis
can be applied to study design decisions regarding changing an organization’s
digital line of visibility. For practice, our findings enable service managers
to make decisions about process transparency and establishing different levels
of service quality.\r\n"
author:
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Brennig K, Müller O. More Isn’t Always Better – Measuring Customers’ Preferences
for Digital Process Transparency. In: Hawaii International Conference on System
Sciences. ; 2023.'
apa: Brennig, K., & Müller, O. (2023). More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency. Hawaii International
Conference on System Sciences. 56th Hawaii International Conference on System
Sciences, Lāhainā.
bibtex: '@inproceedings{Brennig_Müller_2023, title={More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency}, booktitle={Hawaii International
Conference on System Sciences}, author={Brennig, Katharina and Müller, Oliver},
year={2023} }'
chicago: Brennig, Katharina, and Oliver Müller. “More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency.” In Hawaii International
Conference on System Sciences, 2023.
ieee: K. Brennig and O. Müller, “More Isn’t Always Better – Measuring Customers’
Preferences for Digital Process Transparency,” presented at the 56th Hawaii International
Conference on System Sciences, Lāhainā, 2023.
mla: Brennig, Katharina, and Oliver Müller. “More Isn’t Always Better – Measuring
Customers’ Preferences for Digital Process Transparency.” Hawaii International
Conference on System Sciences, 2023.
short: 'K. Brennig, O. Müller, in: Hawaii International Conference on System Sciences,
2023.'
conference:
end_date: '20230106'
location: Lāhainā
name: ' 56th Hawaii International Conference on System Sciences'
start_date: '20230103'
date_created: 2023-01-17T11:34:56Z
date_updated: 2024-01-11T11:21:28Z
department:
- _id: '196'
has_accepted_license: '1'
keyword:
- Digital Services
- Line of Visibility
- Process Transparency
- Customer Preferences
- Conjoint Analysis
language:
- iso: eng
license: https://creativecommons.org/licenses/by-nc-nd/4.0/
publication: Hawaii International Conference on System Sciences
publication_identifier:
unknown:
- 978-0-9981331-6-4
publication_status: published
status: public
title: More Isn’t Always Better – Measuring Customers’ Preferences for Digital Process
Transparency
type: conference
user_id: '51905'
year: '2023'
...
---
_id: '50450'
author:
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Kay
full_name: Benkert, Kay
last_name: Benkert
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Brennig K, Benkert K, Löhr B, Müller O. Text-Aware Predictive Process Monitoring
of Knowledge-Intensive Processes: Does Control Flow Matter? In: Business Process
Management Workshops. ; 2023. doi:10.1007/978-3-031-50974-2_33'
apa: 'Brennig, K., Benkert, K., Löhr, B., & Müller, O. (2023). Text-Aware Predictive
Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?
In Business Process Management Workshops. https://doi.org/10.1007/978-3-031-50974-2_33'
bibtex: '@inbook{Brennig_Benkert_Löhr_Müller_2023, title={Text-Aware Predictive
Process Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?},
DOI={10.1007/978-3-031-50974-2_33},
booktitle={Business Process Management Workshops}, author={Brennig, Katharina
and Benkert, Kay and Löhr, Bernd and Müller, Oliver}, year={2023} }'
chicago: 'Brennig, Katharina, Kay Benkert, Bernd Löhr, and Oliver Müller. “Text-Aware
Predictive Process Monitoring of Knowledge-Intensive Processes: Does Control Flow
Matter?” In Business Process Management Workshops, 2023. https://doi.org/10.1007/978-3-031-50974-2_33.'
ieee: 'K. Brennig, K. Benkert, B. Löhr, and O. Müller, “Text-Aware Predictive Process
Monitoring of Knowledge-Intensive Processes: Does Control Flow Matter?,” in Business
Process Management Workshops, 2023.'
mla: 'Brennig, Katharina, et al. “Text-Aware Predictive Process Monitoring of Knowledge-Intensive
Processes: Does Control Flow Matter?” Business Process Management Workshops,
2023, doi:10.1007/978-3-031-50974-2_33.'
short: 'K. Brennig, K. Benkert, B. Löhr, O. Müller, in: Business Process Management
Workshops, 2023.'
date_created: 2024-01-11T09:26:05Z
date_updated: 2024-01-11T11:22:35Z
department:
- _id: '196'
doi: 10.1007/978-3-031-50974-2_33
language:
- iso: eng
publication: Business Process Management Workshops
publication_identifier:
isbn:
- '9783031509735'
- '9783031509742'
issn:
- 1865-1348
- 1865-1356
publication_status: published
status: public
title: 'Text-Aware Predictive Process Monitoring of Knowledge-Intensive Processes:
Does Control Flow Matter?'
type: book_chapter
user_id: '51905'
year: '2023'
...
---
_id: '50459'
abstract:
- lang: eng
text: Organizations employ process mining to discover, check, or enhance process
models based on data from information systems to improve business processes. Even
though process mining is increasingly relevant in academia and organizations,
achieving process mining excellence and generating business value through its
application is elusive. Maturity models can help to manage interdisciplinary teams
in their efforts to plan, implement, and manage process mining in organizations.
However, while numerous maturity models on business process management (BPM) are
available, recent calls for process mining maturity models indicate a gap in the
current knowledge base. We systematically design and develop a comprehensive process
mining maturity model that consists of five factors comprising 23 elements, which
organizations need to develop to apply process mining sustainably and successfully.
We contribute to the knowledge base by the exaptation of existing BPM maturity
models, and validate our model through its application to a real-world scenario.
author:
- first_name: Jonathan
full_name: Brock, Jonathan
last_name: Brock
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
orcid: 0000-0001-9581-4602
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Thilo
full_name: Seger, Thilo
last_name: Seger
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Sebastian
full_name: von Enzberg, Sebastian
last_name: von Enzberg
- first_name: Arno
full_name: Kühn, Arno
last_name: Kühn
- first_name: Roman
full_name: Dumitrescu, Roman
last_name: Dumitrescu
citation:
ama: 'Brock J, Löhr B, Brennig K, et al. A Process Mining Maturity Model: Enabling
Organizations to Assess and Improve their Process Mining Activities. In: European
Conference on Information Systems (ECIS). ; 2023.'
apa: 'Brock, J., Löhr, B., Brennig, K., Seger, T., Bartelheimer, C., von Enzberg,
S., Kühn, A., & Dumitrescu, R. (2023). A Process Mining Maturity Model: Enabling
Organizations to Assess and Improve their Process Mining Activities. European
Conference on Information Systems (ECIS).'
bibtex: '@inproceedings{Brock_Löhr_Brennig_Seger_Bartelheimer_von Enzberg_Kühn_Dumitrescu_2023,
title={A Process Mining Maturity Model: Enabling Organizations to Assess and Improve
their Process Mining Activities}, booktitle={European Conference on Information
Systems (ECIS)}, author={Brock, Jonathan and Löhr, Bernd and Brennig, Katharina
and Seger, Thilo and Bartelheimer, Christian and von Enzberg, Sebastian and Kühn,
Arno and Dumitrescu, Roman}, year={2023} }'
chicago: 'Brock, Jonathan, Bernd Löhr, Katharina Brennig, Thilo Seger, Christian
Bartelheimer, Sebastian von Enzberg, Arno Kühn, and Roman Dumitrescu. “A Process
Mining Maturity Model: Enabling Organizations to Assess and Improve Their Process
Mining Activities.” In European Conference on Information Systems (ECIS),
2023.'
ieee: 'J. Brock et al., “A Process Mining Maturity Model: Enabling Organizations
to Assess and Improve their Process Mining Activities,” 2023.'
mla: 'Brock, Jonathan, et al. “A Process Mining Maturity Model: Enabling Organizations
to Assess and Improve Their Process Mining Activities.” European Conference
on Information Systems (ECIS), 2023.'
short: 'J. Brock, B. Löhr, K. Brennig, T. Seger, C. Bartelheimer, S. von Enzberg,
A. Kühn, R. Dumitrescu, in: European Conference on Information Systems (ECIS),
2023.'
date_created: 2024-01-11T11:32:42Z
date_updated: 2025-05-21T08:42:16Z
department:
- _id: '196'
language:
- iso: eng
main_file_link:
- url: https://aisel.aisnet.org/ecis2023_rp/256/
publication: European Conference on Information Systems (ECIS)
status: public
title: 'A Process Mining Maturity Model: Enabling Organizations to Assess and Improve
their Process Mining Activities'
type: conference
user_id: '56760'
year: '2023'
...
---
_id: '36912'
abstract:
- lang: eng
text: Existing process mining methods are primarily designed for processes that
have reached a high degree of digitalization and standardization. In contrast,
the literature has only begun to discuss how process mining can be applied to
knowledge-intensive processes—such as product innovation processes—that involve
creative activities, require organizational flexibility, depend on single actors’
decision autonomy, and target process-external goals such as customer satisfaction.
Due to these differences, existing Process Mining methods cannot be applied out-of-the-box
to analyze knowledge-intensive processes. In this paper, we employ Action Design
Research (ADR) to design and evaluate a process mining approach for knowledge-intensive
processes. More specifically, we draw on the two processes of product innovation
and engineer-to-order in manufacturing contexts. We collected data from 27 interviews
and conducted 49 workshops to evaluate our IT artifact at different stages in
the ADR process. From a theoretical perspective, we contribute five design principles
and a conceptual artifact that prescribe how process mining ought to be designed
for knowledge-intensive processes in manufacturing. From a managerial perspective,
we demonstrate how enacting these principles enables their application in practice.
author:
- first_name: Bernd
full_name: Löhr, Bernd
id: '56760'
last_name: Löhr
- first_name: Katharina
full_name: Brennig, Katharina
id: '51905'
last_name: Brennig
- first_name: Christian
full_name: Bartelheimer, Christian
id: '49160'
last_name: Bartelheimer
- first_name: Daniel
full_name: Beverungen, Daniel
id: '59677'
last_name: Beverungen
- first_name: Oliver
full_name: Müller, Oliver
id: '72849'
last_name: Müller
citation:
ama: 'Löhr B, Brennig K, Bartelheimer C, Beverungen D, Müller O. Process Mining
of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing.
In: International Conference on Business Process Management. ; 2022. doi:10.1007/978-3-031-16103-2_18'
apa: 'Löhr, B., Brennig, K., Bartelheimer, C., Beverungen, D., & Müller, O.
(2022). Process Mining of Knowledge-Intensive Processes: An Action Design Research
Study in Manufacturing. International Conference on Business Process Management.
https://doi.org/10.1007/978-3-031-16103-2_18'
bibtex: '@inproceedings{Löhr_Brennig_Bartelheimer_Beverungen_Müller_2022, title={Process
Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing},
DOI={10.1007/978-3-031-16103-2_18},
booktitle={International Conference on Business Process Management}, author={Löhr,
Bernd and Brennig, Katharina and Bartelheimer, Christian and Beverungen, Daniel
and Müller, Oliver}, year={2022} }'
chicago: 'Löhr, Bernd, Katharina Brennig, Christian Bartelheimer, Daniel Beverungen,
and Oliver Müller. “Process Mining of Knowledge-Intensive Processes: An Action
Design Research Study in Manufacturing.” In International Conference on Business
Process Management, 2022. https://doi.org/10.1007/978-3-031-16103-2_18.'
ieee: 'B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, and O. Müller, “Process
Mining of Knowledge-Intensive Processes: An Action Design Research Study in Manufacturing,”
2022, doi: 10.1007/978-3-031-16103-2_18.'
mla: 'Löhr, Bernd, et al. “Process Mining of Knowledge-Intensive Processes: An Action
Design Research Study in Manufacturing.” International Conference on Business
Process Management, 2022, doi:10.1007/978-3-031-16103-2_18.'
short: 'B. Löhr, K. Brennig, C. Bartelheimer, D. Beverungen, O. Müller, in: International
Conference on Business Process Management, 2022.'
date_created: 2023-01-16T11:04:54Z
date_updated: 2024-01-11T11:35:54Z
department:
- _id: '196'
doi: 10.1007/978-3-031-16103-2_18
language:
- iso: eng
publication: International Conference on Business Process Management
publication_identifier:
isbn:
- 978-3-031-16103-2
status: public
title: 'Process Mining of Knowledge-Intensive Processes: An Action Design Research
Study in Manufacturing'
type: conference
user_id: '51905'
year: '2022'
...