A Systematic Review of Additive Manufacturing Solutions Using Machine Learning, Internet of Things, Big Data, Digital Twins and Blockchain Technologies: A Technological Perspective Towards Sustainability

IF 9.7 2区工程技术 Q1 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS

Archives of Computational Methods in Engineering Pub Date : 2024-04-28 DOI:10.1007/s11831-024-10116-4

Ruby Pant, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Lovi Raj Gupta, Amit Kumar Thakur

{"title":"A Systematic Review of Additive Manufacturing Solutions Using Machine Learning, Internet of Things, Big Data, Digital Twins and Blockchain Technologies: A Technological Perspective Towards Sustainability","authors":"Ruby Pant, Rajesh Singh, Anita Gehlot, Shaik Vaseem Akram, Lovi Raj Gupta, Amit Kumar Thakur","doi":"10.1007/s11831-024-10116-4","DOIUrl":null,"url":null,"abstract":"<div><p>New manufacturing expertise, along with user expectations for gradually modified products and facilities, is creating changes in manufacturing scale and distribution. Standardization is essential for every industrial manufactured sector that delivers goods to consumers. Digital manufacturing (DM) is a vital component in the scheduling of all knowledge-based manufacturing. Additive Manufacturing (AM) is recognized as a useful technique in the area of sustainable development goals (SDGs). Modern Development techniques are inspected as a tool for the practices that are being adopted. Additive Manufacturing (AM) was introduced as an advanced technology that includes a new era of complicated machinery and operating systems. Cloud manufacturing framework makes it much easier to gain access to a variety of AM resources while investing as little as possible. This paper contributes an overview of used technologies advancement in the era of Additive manufacturing such as IoT, Big Data, ML, Digital twins, and Blockchain, and their contribution to Industry 4.0 for better and effective design, development, and production while at the same time providing a richer and ethical environment.</p><h3>Graphical Abstract</h3>\n<div><figure><div><div><picture><source><img></source></picture></div></div></figure></div></div>","PeriodicalId":55473,"journal":{"name":"Archives of Computational Methods in Engineering","volume":"31 8","pages":"4601 - 4616"},"PeriodicalIF":9.7000,"publicationDate":"2024-04-28","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Archives of Computational Methods in Engineering","FirstCategoryId":"5","ListUrlMain":"https://link.springer.com/article/10.1007/s11831-024-10116-4","RegionNum":2,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}

引用次数: 0

Abstract

New manufacturing expertise, along with user expectations for gradually modified products and facilities, is creating changes in manufacturing scale and distribution. Standardization is essential for every industrial manufactured sector that delivers goods to consumers. Digital manufacturing (DM) is a vital component in the scheduling of all knowledge-based manufacturing. Additive Manufacturing (AM) is recognized as a useful technique in the area of sustainable development goals (SDGs). Modern Development techniques are inspected as a tool for the practices that are being adopted. Additive Manufacturing (AM) was introduced as an advanced technology that includes a new era of complicated machinery and operating systems. Cloud manufacturing framework makes it much easier to gain access to a variety of AM resources while investing as little as possible. This paper contributes an overview of used technologies advancement in the era of Additive manufacturing such as IoT, Big Data, ML, Digital twins, and Blockchain, and their contribution to Industry 4.0 for better and effective design, development, and production while at the same time providing a richer and ethical environment.

Graphical Abstract

Abstract Image

查看原文本刊更多论文

使用机器学习、物联网、大数据、数字双胞胎和区块链技术的增材制造解决方案系统综述：实现可持续发展的技术视角

新的制造技术以及用户对逐步改进产品和设施的期望，正在改变制造规模和分配方式。标准化对每一个向消费者提供产品的工业制造部门都至关重要。数字化制造（DM）是所有知识型制造的重要组成部分。增材制造（AM）被认为是可持续发展目标（SDGs）领域的一项有用技术。现代发展技术被视为正在采用的实践工具。快速成型制造（AM）是一项先进技术，它将复杂的机械和操作系统带入了一个新时代。云制造框架使人们更容易获得各种增材制造资源，同时投资尽可能少。本文概述了物联网、大数据、ML、数字双胞胎和区块链等增材制造时代的先进技术，以及这些技术对工业 4.0 的贡献，以便更好、更有效地进行设计、开发和生产，同时提供更丰富、更符合道德规范的环境。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

求助全文

约1分钟内获得全文求助全文

来源期刊

Archives of Computational Methods in Engineering 工程技术-工程：综合

CiteScore

19.80

自引率

4.10%

发文量

153

审稿时长

>12 weeks

期刊介绍： Archives of Computational Methods in Engineering Aim and Scope: Archives of Computational Methods in Engineering serves as an active forum for disseminating research and advanced practices in computational engineering, particularly focusing on mechanics and related fields. The journal emphasizes extended state-of-the-art reviews in selected areas, a unique feature of its publication. Review Format: Reviews published in the journal offer: A survey of current literature Critical exposition of topics in their full complexity By organizing the information in this manner, readers can quickly grasp the focus, coverage, and unique features of the Archives of Computational Methods in Engineering.