Business process management for Industry 4.0 – Three application cases in the DFKI-Smart-Lego-Factory

@article{Rehse2018BusinessPM,
  title={Business process management for Industry 4.0 – Three application cases in the DFKI-Smart-Lego-Factory},
  author={Jana-Rebecca Rehse and Sharam Dadashnia and P. Fettke},
  journal={it - Information Technology},
  year={2018},
  volume={60},
  pages={133 - 141}
}
Abstract The advent of Industry 4.0 is expected to dramatically change the manufacturing industry as we know it today. Highly standardized, rigid manufacturing processes need to become self-organizing and decentralized. This flexibility leads to new challenges to the management of smart factories in general and production planning and control in particular. In this contribution, we illustrate how established techniques from Business Process Management (BPM) hold great potential to conquer… Expand
Development of a Modeling Architecture Incorporating the Industry 4.0 View for a Company in the Gas Sector
TLDR
A complete architecture which proposed in a company activating in gas industry is presented including the appropriate models for the recording of business processes and how Industry 4.0 principles could be incorporated to them. Expand
Towards Explainable Process Predictions for Industry 4.0 in the DFKI-Smart-Lego-Factory
TLDR
This contribution illustrates the opportunities and challenges of process predictions and XAI for Industry 4.0 with the DFKI-Smart-Lego-Factory, a fully automated factory prototype built out of LEGO that predicts likely process outcomes and uses state-of-the-art XAI techniques to explain them to its workers and visitors. Expand
Using Physical Factory Simulation Models for Business Process Management Research
TLDR
This work introduces the physical Fischertechnik factory models simulating a complex production line and three exemplary use cases of combining BPM and IoT, namely the implementation of a BPM abstraction stack on top of a learning factory, the experiencebased adaptation and optimization of manufacturing processes, and the stream processing-based conformance checking of IoT-enabled processes. Expand
A Conceptual Framework to Support Digital Transformation in Manufacturing Using an Integrated Business Process Management Approach
Digital transformation is no longer a future trend, as it has become a necessity for businesses to grow and remain competitive in the market. The fourth industrial revolution, called Industry 4.0, isExpand
Process modeling for smart factories: using science mapping to understand the strategic themes, main challenges and future trends
PurposeThe purpose of this paper is to identify the relationships between process modeling and Industry 4.0, the strategic themes and the most used process modeling language in smart factories. TheExpand
Reengineering of the New Customer Gas Connection Process Utilizing Industry 4.0 Technologies: The Greek Case of Public Gas Distribution Networks S.A.
TLDR
By using technologies and tools related to Industry 4.0, reorganizing processes and making a sensible investment, long-term savings can be achieved and the total duration of the process may be significantly reduced, the present study concluded. Expand
Leveraging Artificial Intelligence for Business Process Management (Extended Abstract)
TLDR
The thesis investigates the application of AI technologies in three exemplary BPM subtopics at different maturity stages regarding both research and practical adoption: Reference Model Mining (RMM), Predictive Process Monitoring (PPM), and Process Discovery (PD). Expand
Conceptual Modelling and Artificial Intelligence: Overview and research challenges from the perspective of predictive business process management
  • P. Fettke
  • Engineering, Computer Science
  • Modellierung
  • 2020
TLDR
The field of predictive business process management is focused as a particular application case of AI and Modelling, which uses machine learning for predicting the future state of a running process instance. Expand
Process-Mining-unterstützte Ad-hoc-Produktionsplanung - Konzept und prototypische Implementierung
TLDR
Das Konzept sieht vor, dass unter bestimmten Voraussetzungen keine vollständige Produktionsplanung durchgeführt wird, sondern stattdessen geeignete bzw. Expand
Explaining a Random Forest With the Difference of Two ARIMA Models in an Industrial Fault Detection Scenario
TLDR
The results of the experiment show that the approach is able to identify a linear trend in some parts of the data, and therefore locally provide an explanation for the functional form of the underlying failure rate. Expand
...
1
2
...

References

SHOWING 1-10 OF 11 REFERENCES
The Internet-of-Things Meets Business Process Management: Mutual Benefits and Challenges
TLDR
To what extent the Internet of Things and Business Process Management can be combined, and the emerging challenges are discussed. Expand
ARIS - Business Process Modeling
From the Publisher: This book describes in detail how ARIS methods model and realize business processes by means of UML (Unified Modeling Language), leading to an information model that is theExpand
A graph-theoretic method for the inductive development of reference process models
TLDR
A new inductive approach for the development of reference models, based on existing individual models from the respective domain, employs a graph-based paradigm, exploiting the underlying graph structures of process models by identifying frequent common subgraphs of the individual models, analyzing their order relations, and merging them into a new model. Expand
Empirical research in business process management - analysis of an emerging field of research
TLDR
A survey of the development of empirical research in business process management (BPM) and applied methodologies by means of a developed framework in order to identify the status quo and to assess the probable future development of the research field. Expand
Process Mining: Data Science in Action
This is the second edition of Wil van der Aalsts seminal book on process mining, which now discusses the field also in the broader context of data science and big data approaches. It includes severalExpand
Predicting process behaviour using deep learning
TLDR
This paper describes an application of deep learning with recurrent neural networks to the problem of predicting the next event in a business process, and shows results that surpass the state-of-the-art in prediction precision. Expand
Intelligent Systems in Maintenance Planning and Management
  • K. Sirvio
  • Computer Science
  • Intelligent Techniques in Engineering Management
  • 2015
TLDR
Intelligent maintenance planning is important in the transport sector and various models and methods have been applied both in road and vehicle maintenance, but data-driven methods are becoming more practical as computation is increasingly more feasible. Expand
A Deep Learning Approach for Predicting Process Behaviour at Runtime
TLDR
This paper describes an initial application of deep learning with recurrent neural networks to the problem of predicting the next process event, which is both a novel method in process prediction, and also a novel application for deep learning methods. Expand
Sirvio, Intelligent Systems in Maintenance Planning and Management, pp. 221–245
  • 2015
Industry 4.0
...
1
2
...