Big Data, 3D Printing Technology, and Industry of the Future

Alabi, Micheal Omotayo

doi:10.4018/ijbdah.2017070101

Cited by 5 publications

(2 citation statements)

References 15 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Production industries are creating large volumes of data on the manufacturing line in this 4th industrial revolution epoch, often called as "Industry 4.0," and AM /3D printing industry is no exemption. AM technologies are crucial elements of Industry 4.0 concept (Alabi, 2018;Xing et al, 2020). AM denotes a group of manufacturing technologies in which materials are joined directly to produce components based on 3D modelling data.…”

Section: In Additive Manufacturingmentioning

confidence: 99%

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

et al. 2022

View full text Add to dashboard Cite

For several industries, the traditional manufacturing processes are time-consuming and uneconomical due to the absence of the right tool to produce the products. In a couple of years, machine learning (ML) algorithms have become more prevalent in manufacturing to develop items and products with reduced labor cost, time, and effort. Digitalization with cutting-edge manufacturing methods and massive data availability have further boosted the necessity and interest in integrating ML and optimization techniques to enhance product quality. ML integrated manufacturing methods increase acceptance of new approaches, save time, energy, and resources, and avoid waste. ML integrated assembly processes help creating what is known as smart manufacturing, where technology automatically adjusts any errors in real-time to prevent any spillage. Though manufacturing sectors use different techniques and tools for computing, recent methods such as the ML and data mining techniques are instrumental in solving challenging industrial and research problems. Therefore, this paper discusses the current state of ML technique, focusing on modern manufacturing methods i.e., additive manufacturing. The various categories especially focus on design, processes and production control of additive manufacturing are described in the form of state of the art review.

show abstract

Section: In Additive Manufacturingmentioning

confidence: 99%

Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

et al. 2022

View full text Add to dashboard Cite

show abstract

“…In this era of Fourth Industrial Revolution (FIR), also called "Industry 4.0", the manufacturing sectors are generating huge amount of data on the production line and additive manufacturing/3D printing industry is not left out. Big Data and AM technologies are the significant aspect of the sub-set of industry 4.0 (Alabi, 2017). Recently, different studies are being tailored towards additive manufacturing research which allows the use of ML techniques to tackle simple and complex challenges.…”

Section: Introductionmentioning

confidence: 99%

A Survey on Recent Applications of Machine Learning with Big Data in Additive Manufacturing Industry

Alabi¹,

Botef²

2018

American Journal of Engineering and Applied Sciences

Self Cite

View full text Add to dashboard Cite

Additive Manufacturing (AM) which is also known as 3D printing technology; is recognized as a new paradigm for manufacturing industry. Additive manufacturing is rapidly expanding across different sectors such as healthcare, electronics, automotive, science and engineering, education, dental, etc. Machine Learning and Big Data are both emerging technologies which are becoming popular and gaining more attention from the industries and academic. Machine Learning is a growing field of Artificial Intelligence (AI) that allows systems to learn from data, identify patterns and make decisions with very little human involvement. On the other hand, Big Data is referred to as datasets whose size is more than the capacity of what a conventional database software tools can capture, store, manage and analyze. Lately, Machine Learning techniques and Big Data Analytics are being applied to various applications of additive manufacturing to monitor building process and enhance decisions making using data generated through different sensors or cameras. This paper explores recent applications of Machine Learning with Big Data in the field of additive manufacturing, for instance, application of machine learning in detecting defect or anomaly during build process in additive manufacturing/3D printing machine.

show abstract