Multi-fault diagnosis of Industrial Rotating Machines using Data-driven approach: A review of two decades of research

S Gawde, S Patil, S Kumar, P Kamat, K Kotecha… - … Applications of Artificial …, 2023 - Elsevier
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 …

[HTML][HTML] Machine learning in business process management: A systematic literature review

S Weinzierl, S Zilker, S Dunzer, M Matzner - Expert Systems with …, 2024 - Elsevier
Abstract Machine learning (ML) provides algorithms to create computer programs based on
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

SK Jagatheesaperumal, M Rahouti… - IEEE Internet of …, 2021 - ieeexplore.ieee.org
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 …

[PDF][PDF] Predictive process monitoring

C Di Francescomarino, C Ghidini - Process mining handbook, 2022 - library.oapen.org
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 …

Just tell me: Prompt engineering in business process management

K Busch, A Rochlitzer, D Sola, H Leopold - International Conference on …, 2023 - Springer
GPT-3 and several other language models (LMs) can effectively address various natural
language processing (NLP) tasks, including machine translation and text summarization …

A systematic review of anomaly detection for business process event logs

J Ko, M Comuzzi - Business & Information Systems Engineering, 2023 - Springer
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 …

Prescriptive process monitoring based on causal effect estimation

ZD Bozorgi, I Teinemaa, M Dumas, M La Rosa… - Information Systems, 2023 - Elsevier
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) …

An explainable decision support system for predictive process analytics

R Galanti, M de Leoni, M Monaro, N Navarin… - … Applications of Artificial …, 2023 - Elsevier
Abstract Predictive Process Analytics is becoming an essential aid for organizations,
providing online operational support of their processes. However, process stakeholders …

Object-centric process predictive analytics

R Galanti, M De Leoni, N Navarin, A Marazzi - Expert Systems with …, 2023 - Elsevier
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 …

A multi-view deep learning approach for predictive business process monitoring

V Pasquadibisceglie, A Appice… - IEEE Transactions …, 2021 - ieeexplore.ieee.org
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 …