Challenges in deploying machine learning: a survey of case studies
In recent years, machine learning has transitioned from a field of academic research interest
to a field capable of solving real-world business problems. However, the deployment of …
to a field capable of solving real-world business problems. However, the deployment of …
Machine learning in manufacturing: advantages, challenges, and applications
The nature of manufacturing systems faces ever more complex, dynamic and at times even
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
chaotic behaviors. In order to being able to satisfy the demand for high-quality products in an …
Applications of machine learning in process monitoring and controls of L-PBF additive manufacturing: A review
One of the main issues hindering the adoption of parts produced using laser powder bed
fusion (L-PBF) in safety-critical applications is the inconsistencies in quality levels …
fusion (L-PBF) in safety-critical applications is the inconsistencies in quality levels …
Transfer-learning: Bridging the gap between real and simulation data for machine learning in injection molding
In the field of manufacturing process planning and initial operation of machines, machine
parameters are often provided from few either expensive and time-consuming experiments …
parameters are often provided from few either expensive and time-consuming experiments …
Towards industry 4.0 utilizing data-mining techniques: a case study on quality improvement
H Oliff, Y Liu - Procedia Cirp, 2017 - Elsevier
The use of data-mining as an analytical tool has been increasing in recent years; and the
emergence of new manufacturing paradigms such as the Industry 4.0 initiative have led …
emergence of new manufacturing paradigms such as the Industry 4.0 initiative have led …
[图书][B] Industrial applications of machine learning
Industrial Applications of Machine Learning shows how machine learning can be applied to
address real-world problems in the fourth industrial revolution, and provides the required …
address real-world problems in the fourth industrial revolution, and provides the required …
Toward improved machine learning-based intrusion detection for Internet of Things traffic
S Alkadi, S Al-Ahmadi, MM Ben Ismail - Computers, 2023 - mdpi.com
The rapid development of Internet of Things (IoT) networks has revealed multiple security
issues. On the other hand, machine learning (ML) has proven its efficiency in building …
issues. On the other hand, machine learning (ML) has proven its efficiency in building …
[HTML][HTML] Monitoring machine learning models: a categorization of challenges and methods
T Schröder, M Schulz - Data Science and Management, 2022 - Elsevier
The importance of software based on machine learning is growing rapidly, but the potential
of prototypes may not be realized in operation. This study identified six categories of …
of prototypes may not be realized in operation. This study identified six categories of …
[PDF][PDF] Machine learning techniques for smart manufacturing: Applications and challenges in industry 4.0
The Industry 4.0 is now underway, changing traditional manufacturing into smart
manufacturing and creating new opportunities, where machines learn to understand those …
manufacturing and creating new opportunities, where machines learn to understand those …
Learning with supervised data for anomaly detection in smart manufacturing
The emergence of the Internet of Things (IoT), cloud computing, cyber-physical systems,
system integration, big data, and data analytics for Industry 4.0 have transformed the world …
system integration, big data, and data analytics for Industry 4.0 have transformed the world …