Machine learning and deep learning based predictive quality in manufacturing: a systematic review
With the ongoing digitization of the manufacturing industry and the ability to bring together
data from manufacturing processes and quality measurements, there is enormous potential …
data from manufacturing processes and quality measurements, there is enormous potential …
Machine learning and data mining in manufacturing
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 …
Machine learning in predictive maintenance towards sustainable smart manufacturing in industry 4.0
Recently, with the emergence of Industry 4.0 (I4. 0), smart systems, machine learning (ML)
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
within artificial intelligence (AI), predictive maintenance (PdM) approaches have been …
Survey on software defect prediction techniques
Recent advancements in technology have emerged the requirements of hardware and
software applications. Along with this technical growth, software industries also have faced …
software applications. Along with this technical growth, software industries also have faced …
A big data-driven framework for sustainable and smart additive manufacturing
From the last decade, additive manufacturing (AM) has been evolving speedily and has
revealed the great potential for energy-saving and cleaner environmental production due to …
revealed the great potential for energy-saving and cleaner environmental production due to …
Data-driven smart manufacturing
The advances in the internet technology, internet of things, cloud computing, big data, and
artificial intelligence have profoundly impacted manufacturing. The volume of data collected …
artificial intelligence have profoundly impacted manufacturing. The volume of data collected …
Integration of Industry 4.0 technologies into Lean Six Sigma DMAIC: A systematic review
T Pongboonchai-Empl, J Antony… - … Planning & Control, 2024 - Taylor & Francis
This review examines which Industry 4.0 (I4. 0) technologies are suitable for improving Lean
Six Sigma (LSS) tasks and the benefits of integrating these technologies into improvement …
Six Sigma (LSS) tasks and the benefits of integrating these technologies into improvement …
Machine learning based digital twin framework for production optimization in petrochemical industry
Q Min, Y Lu, Z Liu, C Su, B Wang - International Journal of Information …, 2019 - Elsevier
Digital twins, along with the internet of things (IoT), data mining, and machine learning
technologies, offer great potential in the transformation of today's manufacturing paradigm …
technologies, offer great potential in the transformation of today's manufacturing paradigm …
Applications of artificial intelligence in engineering and manufacturing: a systematic review
Engineering and manufacturing processes and systems designs involve many challenges,
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
such as dynamism, chaotic behaviours, and complexity. Of late, the arrival of big data, high …
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 …