Here we propose papers and books related to the industrial applications of AI/ML/DS.
Chalapathy, Raghavendra, and Sanjay Chawla. "Deep learning for anomaly detection: A survey." arXiv preprint arXiv:1901.03407 (2019).
Campos, Guilherme O., et al. "On the evaluation of unsupervised outlier detection: measures, datasets, and an empirical study." Data mining and knowledge discovery 30.4 (2016): 891-927.
Fault detection and diagnosis in engineering systems by Janos Gertler
Unsupervised Process Monitoring and Fault Diagnosis with Machine Learning Methods by Chris Aldrich and Lidia Auret
Condition Monitoring with Vibration Signals by Hosameldin Ahmed and Asoke K. Nandi
Compressive Sampling and Learning Algorithms for Rotating Machines
Introduction to Statistical Quality Control by DOUGLAS C. MONTGOMERY
This book is about the use of modern statistical methods for quality control and improvement.
Fault Detection and Diagnosis in Industrial Systems by L. H. Chiang, E. L. Russell and R. D. Braatz
This textbook presents the theoretical background and practical tech- niques for process monitoring.