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

Alabi, Micheal Omotayo; Botef, Ionel

doi:10.3844/ajeassp.2018.1114.1124

Cited by 20 publications

(4 citation statements)

References 23 publications

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“…More recently, artificial intelligence, machine learning, and deep learning have become integral components of 3D printing used in various aspects of additive manufacturing, including design optimization, predicting 3D printing parameters and process control, material development, part orientation, support generation, defect detection, quality control, etc. The application and importance of AI methods in 3D printing show promising advancements in eco-friendly applications, spanning from manufacturing to healthcare [81][82][83][84], e.g., in the machining industry [85], diagnosis systems to address anomalies and reducing printing errors [86,87], building reconstruction [83], predicting 3D-printed biomedical microneedle features [88,89], printable biomaterials [4,90,91], and automated and personalized production processes for pharmaceutics [92].…”

Section: History: Bridging Innovation With Environmental Sustainabilitymentioning

confidence: 99%

Let’s Print an Ecology in 3D (and 4D)

Szechyńska-Hebda,

Hebda,

Doğan-Sağlamtimur

et al. 2024

Materials

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The concept of ecology, historically rooted in the economy of nature, currently needs to evolve to encompass the intricate web of interactions among humans and various organisms in the environment, which are influenced by anthropogenic forces. In this review, the definition of ecology has been adapted to address the dynamic interplay of energy, resources, and information shaping both natural and artificial ecosystems. Previously, 3D (and 4D) printing technologies have been presented as potential tools within this ecological framework, promising a new economy for nature. However, despite the considerable scientific discourse surrounding both ecology and 3D printing, there remains a significant gap in research exploring the interplay between these directions. Therefore, a holistic review of incorporating ecological principles into 3D printing practices is presented, emphasizing environmental sustainability, resource efficiency, and innovation. Furthermore, the ‘unecological’ aspects of 3D printing, disadvantages related to legal aspects, intellectual property, and legislation, as well as societal impacts, are underlined. These presented ideas collectively suggest a roadmap for future research and practice. This review calls for a more comprehensive understanding of the multifaceted impacts of 3D printing and the development of responsible practices aligned with ecological goals.

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Section: History: Bridging Innovation With Environmental Sustainabilitymentioning

confidence: 99%

Let’s Print an Ecology in 3D (and 4D)

Szechyńska-Hebda,

Hebda,

Doğan-Sağlamtimur

et al. 2024

Materials

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“…This will assist in preventing the accumulation of excess resources and thereby eliminating or reducing waste. In summary, effective use of big data analytics as a digital lean tool would a make significant contribution to enhancing efficiency and reducing waste in AM production processes [54][55]. International Conference on Sustainable Engineering and Materials Development (ICSEMD)…”

Section: Development Of Digital Lean Manufacturing Systems/tools and ...mentioning

confidence: 99%

Application of Digital Lean Manufacturing System in Additive Manufacturing Industries: A Review

Alabi

2024

Engineering Headway

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Application of lean manufacturing (LM) principles within the manufacturing industry extends back several decades to drive efficiency and reduce waste across complex production lines. The advent of the Fourth Industrial Revolution, known as “Industry 4.0” technology is transforming the LM processes to promote the manufacturing industry. Additive Manufacturing (AM) has been identified as a technology with great potential to create a longstanding impact on the manufacturing world and is a core component of the Fourth Industrial Revolution. Many successful industries have achieved outstanding performance by integrating LM principles at the core of their corporate transformation. Of recent, AM and 3D printing has been identified as a technology that is revolutionizing LM principles in the following ways: easier prototyping, easily customize products, shorter lead times, local on-demand manufacturing, and lower cost production. Despite the exceptional success of LM principles across different industries and sectors, still many companies LM journeys fail due to many obvious reasons. The emergence of Industry 4.0 digital technologies has created an enabling environment for different manufacturing industries currently using LM principles to identify the need to embrace or add digital technologies to their lean manufacturing transformation journey. The intersections between LM and digital technologies are termed as “Digital Lean” or “Lean 4.0”. There are limited studies and literature gaps on lean manufacturing within the context of AM industry. More so, there is no study that examines the application of digital lean manufacturing in an AM industry. The paper presents a review of the concept of lean manufacturing principles and how it is revolutionizing the AM industry. This paper investigates the concept of digital lean manufacturing and its future potential impact in the AM industry. Finally, this paper develops a digital lean manufacturing system or tools considered suitable for the AM industry.

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“…clustering) in a given random dataset [37]. Unsupervised learning is widely used in anomaly detection [38], recommendations systems [39], and market segmentation [40,41].…”

Section: Machine Learningmentioning

confidence: 99%