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Trends, opportunities, and challenges in the integration of the additive manufacturing with Industry 4.0

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Abstract

The current study skims the trends, opportunities, and challenges in integrating additive manufacturing with Industry 4.0. The critical points of the existing review studies have also been discussed. The search query related to AM and Industry 4.0 was used for obtaining the information from two databases: Web of Science and Scopus. The papers were screened for duplicity and irrelevancy according to the topic of study. The bibliometric software R studio, Hiscite and Vosviewer were used for the analysis of downloaded articles. The bibliometric information related to the most-cited and productive authors, countries, sources, and universities was extracted. Lotka’s and Bradford’s law applicability to authors and sources, respectively, have been demonstrated. The interconnections between the authors, their respective countries and universities were represented with the help of three-field plot. The trend topics, keywords, and thematic evolution form the basis of a review of the cited work. The critical issues related to AM for achieving Industry 4.0 were reviewed. The insight of the case studies powering industry 4.0 was also presented. The challenges and limitations of AM’s implementation with respect to Industry 4.0 were highlighted. The conclusions were drawn out, and future scope was pointed out.

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Abbreviations

AFP:

Automatic fiber placement

AM:

Additive manufacturing

ANN:

Artificial neural networks

AR:

Augmented reality

ASTM:

American Society for Testing and Materials

ATP:

Automatic tape placement

BJ:

Binder jetting

BJP:

Binder jetting 3D printing

BMD:

Bound metal deposition

BPNN:

Back-propagation neural networks

CaaS:

Control as a service

CAD:

Computer aided design

CLIP:

Continuous liquid interface production

CNC:

Computer numerical controller

CNN:

Convolution neural network

CPPS:

Cyber-physical production system

CPS:

Cyber-physical systems

DDP:

Daylight polymer printing

DED:

Direct energy deposition

DLP:

Digital light processing

DM:

Digital manufacturing

DMLS:

Direct metal laser sintering

DOD:

Drop on demand

DOI:

Digital object identifier

EBM:

Electron beam melting

FDM:

Fused deposition modelling

FFF:

Fused filament fabrication

FPY:

First publication year

GRNN:

Generalised regression neural networks

HAM:

Hybrid additive manufacturing

IoT:

Internet of Things

IIoT:

Industrial Internet of Things

KBE:

Knowledge-based engineering

LBPF:

Laser powder bed fusion

LENS:

Laser engineered net shaping

LOM:

Laminated object manufacturing

MJ:

Material jetting

MJF:

Multi jet fusion

ML:

Machine learning

NP:

Number of publications

NPJ:

Nanoparticle jetting

SLA:

Stereolithography

SLM:

Selective laser melting

SLS:

Selective laser sintering

SM:

Subtractive manufacturing

STL:

Standard tessellation language

TC:

Total citations

UAM:

Ultrasonic additive manufacturing

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Acknowledgements

We are thankful to India's science and engineering research board (SERB), India, for funding the current study.

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The work was supported by the Science and Engineering Research Board (SERB). Grant no. (CRG/2019/001320).

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  1. Mechanical Engineering Department, BITS Pilani, Pilani Campus, Pilani, Rajasthan, 333031, India

    Rishi Parvanda & Prateek Kala

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Correspondence to Prateek Kala.

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Parvanda, R., Kala, P. Trends, opportunities, and challenges in the integration of the additive manufacturing with Industry 4.0. Prog Addit Manuf 8, 587–614 (2023). https://doi.org/10.1007/s40964-022-00351-1

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