A Conceptual Framework Towards the Realization of In situ Monitoring and Control of End-to-End Additive Manufacturing Process

Author:

Karadgi Sachin1,M. Bhovi Prabhakar23,Patil Arun Y.2,Ramaiah Keshavamurthy4,Venkateswarlu K.5,Langdon Terence G.6

Affiliation:

1. Department of Automation & Robotics, KLE Technological University, Hubballi, 580031, Karnataka, India

2. School of Mechanical Engineering, KLE Technological University, Hubballi, 580031, Karnataka, India

3. B.V.B. College of Engineering and Technology, Mechanical Engineering, KLE Technological University, Hubballi, 580031, Karnataka, India

4. Department of Mechanical Engineering, Dayananda Sagar College of Engineering and Technology, Bengaluru, 560078, Karnataka, India

5. Materials Research Group, CSIR-National Aerospace Laboratories (CSIR-NAL), Bengaluru, Karnataka, India

6. Materials Research Group, School of Engineering Sciences, University of Southampton, Southampton, SO17 1BJ, United Kingdom

Abstract

Abstract: Additive Manufacturing (AM) is considered one of the key technologies for realizing Industry 4.0. There are numerous stages in the end-to-end AM process, including component design, material design, build, and so on. An enormous amount of data is generated along the end-to-end AM process that can be acquired from the 3D printer in real-time, micro-characterization studies, and process plan details, among others. For instance, these data can be employed to predict the printed components’ quality and, at the same time, proactively adapt the 3D printer parameters to achieve better quality. This end-to-end AM process can be mapped onto the digital thread. The current article elaborates on a conceptual framework to acquire the data from various sources associated with the end-to-end AM process and realize monitoring and control of the end-to-end AM process, leading to an intelligent AM process.

Publisher

Bentham Science Publishers Ltd.

Subject

Building and Construction

Reference51 articles.

1. Kagermann H.; Wahlster W.; Helbig J.; Recommendations for Implementing the Strategic Initiative INDUSTRIE 40, Tech 2013

2. Lu Y.; Morris K.; Frechette S.; Current Standards Landscape for Smart Manufacturing Systems 2016,8107

3. Leiva C.; Three Functional Dimensions Converge on Smart Manufacturing, Tech Rep Whitepaper 59 2018

4. ISO/TC 184/SC 4 Secretary, ISO 10303 Part 1 – Overview and fundamental principles, Standard, International Organization for Standardization (ISO) 1994

5. Hannah M.; James M.; Johnson S.; Leiva C.; Michel A.; Noller D.; Riddick F.; Riley D.; Wallace E.; Brad Williams, Smart Manufacturing – The Landscape Explained, Tech rep 2016

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3