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Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research
Industry 4.0 is an era of smart manufacturing. Manufacturing is impossible without the use of
machinery. The majority of these machines comprise rotating components and are called …
machinery. The majority of these machines comprise rotating components and are called …
[HTML][HTML] Machine learning in business process management: A systematic literature review
Abstract Machine learning (ML) provides algorithms to create computer programs based on
data without explicitly programming them. In business process management (BPM), ML …
data without explicitly programming them. In business process management (BPM), ML …
The duo of artificial intelligence and big data for industry 4.0: Applications, techniques, challenges, and future research directions
The increasing need for economic, safe, and sustainable smart manufacturing combined
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
with novel technological enablers has paved the way for artificial intelligence (AI) and big …
[PDF][PDF] Predictive process monitoring
Predictive Process Monitoring [29] is a branch of process mining that aims at predicting the
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
future of an ongoing (uncompleted) process execution. Typical examples of predictions of …
Just tell me: Prompt engineering in business process management
GPT-3 and several other language models (LMs) can effectively address various natural
language processing (NLP) tasks, including machine translation and text summarization …
language processing (NLP) tasks, including machine translation and text summarization …
A systematic review of anomaly detection for business process event logs
While a business process is most often executed following a normal path, anomalies may
sometimes arise and can be captured in event logs. Event log anomalies stem, for instance …
sometimes arise and can be captured in event logs. Event log anomalies stem, for instance …
Prescriptive process monitoring based on causal effect estimation
Prescriptive process monitoring methods seek to control the execution of a business process
by triggering interventions, at runtime, to optimise one or more performance measure (s) …
by triggering interventions, at runtime, to optimise one or more performance measure (s) …
An explainable decision support system for predictive process analytics
Abstract Predictive Process Analytics is becoming an essential aid for organizations,
providing online operational support of their processes. However, process stakeholders …
providing online operational support of their processes. However, process stakeholders …
Object-centric process predictive analytics
Object-centric processes (also known as Artifact-centric processes) are implementations of a
paradigm where an instance of one process is not executed in isolation but interacts with …
paradigm where an instance of one process is not executed in isolation but interacts with …
A multi-view deep learning approach for predictive business process monitoring
The predictive business process monitoring is a family of online approaches to predict the
unfolding of running traces based on the knowledge learned from historical event logs. In …
unfolding of running traces based on the knowledge learned from historical event logs. In …