Machine learning and data mining in manufacturing
A Dogan, D Birant - Expert Systems with Applications, 2021 - Elsevier
Manufacturing organizations need to use different kinds of techniques and tools in order to
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …
fulfill their foundation goals. In this aspect, using machine learning (ML) and data mining …
Review on additive manufacturing and non-destructive testing
Additive manufacturing is based on high-precision material deposition to build a final part or
component by using various techniques. It is being one of the main advances in the fourth …
component by using various techniques. It is being one of the main advances in the fourth …
A systematic review on data of additive manufacturing for machine learning applications: the data quality, type, preprocessing, and management
Additive manufacturing (AM) techniques are maturing and penetrating every aspect of the
industry. With more and more design, process, structure, and property data collected …
industry. With more and more design, process, structure, and property data collected …
A sequential cross-product knowledge accumulation, extraction and transfer framework for machine learning-based production process modelling
Machine learning is a promising method to model production processes and predict product
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
quality. It is challenging to accurately model complex systems due to data scarcity, as mass …
Density prediction in powder bed fusion additive manufacturing: machine learning-based techniques
Machine learning (ML) is one of the artificial intelligence tools which uses past data to learn
the relationship between input and output and helps to predict future trends. Powder bed …
the relationship between input and output and helps to predict future trends. Powder bed …
[HTML][HTML] Step heating thermography supported by machine learning and simulation for internal defect size measurement in additive manufacturing
A methodology based on step-heating thermography for predicting the length dimension of
small defects in additive manufacturing from temperature data measured on thermal images …
small defects in additive manufacturing from temperature data measured on thermal images …
[HTML][HTML] Fostering research and innovation in materials manufacturing for Industry 5.0: The key role of domain intertwining between materials characterization …
Recent advances in materials modelling, characterization and materials informatics suggest
that deep integration of such methods can be a crucial aspect of the Industry 5.0 revolution …
that deep integration of such methods can be a crucial aspect of the Industry 5.0 revolution …
The study of machine learning assisted the design of selected composites properties
S Hrehova, L Knapcikova - Applied Sciences, 2022 - mdpi.com
One of the basic points of Industry 5.0 is to make the industry sustainable. There is a need to
develop circular processes that reuse, repurpose, and recycle natural resources, and thus …
develop circular processes that reuse, repurpose, and recycle natural resources, and thus …
Predicting effluent quality parameters for wastewater treatment plant: A machine learning-based methodology
JVR Fuck, MAP Cechinel, J Neves, RC de Andrade… - Chemosphere, 2024 - Elsevier
Abstract Wastewater Treatment Plants (WWTPs) present complex biochemical processes of
high variability and difficult prediction. This study presents an innovative approach using …
high variability and difficult prediction. This study presents an innovative approach using …
[HTML][HTML] Deep convolutional neural support vector machines for the classification of basal cell carcinoma hyperspectral signatures
Non-melanoma skin cancer, and basal cell carcinoma in particular, is one of the most
common types of cancer. Although this type of malignancy has lower metastatic rates than …
common types of cancer. Although this type of malignancy has lower metastatic rates than …