Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)

<Previous Article In Volume
Next Article In Volume>

A Review of Six Sigma Approach to Enhance Performance in Manufacturing Industries

Authors
Ravindra L. Karwande1, *, Santosh P. Bhosle1, Prashant M. Ambad1
1Department of Mechanical Engineering, Maharashtra Institute of Technology, Aurangabad, India
*Corresponding author. Email: ravindrakarwande@yahoo.com
Corresponding Author
Ravindra L. Karwande
Available Online 1 May 2023.
DOI
10.2991/978-94-6463-136-4_56How to use a DOI?
Keywords
Six Sigma; Operational performance; DMAIC; TQM; DFSS; Lean Six Sigma
Abstract

From the last few decades, Six Sigma has played a vital role in global corporate as a top agenda in order to optimize cost and improve productivity, to generate maximum business benefit and competitive advantage by continually reducing defects in the organization. The paper summarizes a brief introduction to the Six Sigma methodologies in order to establish a basis of definition, methodology, advancement and scope for modernization of industry in terms of six sigma development. Article lightened the techniques of six sigma such as DMAIC, DFSS and Lean sigma with vast areas covered with advantages and benefits in the state of manufacturing and management organization to establish compact bonds of technology for further scope. Six Sigma techniques elaborated here, itself proves to be the best technique for present to future with the need of Artificial Intelligence and Information Technology: a new era of six sigma ahead for fast growing industries for more accurate and most efficient techniques for zero tolerance in order to achieve sustainable development goals worldwide.

Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Download article (PDF)

<Previous Article In Volume
Next Article In Volume>
Volume Title
Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
Series
Advances in Computer Science Research
Publication Date
1 May 2023
ISBN
978-94-6463-136-4
ISSN
2352-538X
DOI
10.2991/978-94-6463-136-4_56How to use a DOI?
Copyright
© 2023 The Author(s)
Open Access
Open Access This chapter is licensed under the terms of the Creative Commons Attribution-NonCommercial 4.0 International License (http://creativecommons.org/licenses/by-nc/4.0/), which permits any noncommercial use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license and indicate if changes were made.

Cite this article

risenwbib
TY  - CONF
AU  - Ravindra L. Karwande
AU  - Santosh P. Bhosle
AU  - Prashant M. Ambad
PY  - 2023
DA  - 2023/05/01
TI  - A Review of Six Sigma Approach to Enhance Performance in Manufacturing Industries
BT  - Proceedings of the International Conference on Applications of Machine Intelligence and Data Analytics (ICAMIDA 2022)
PB  - Atlantis Press
SP  - 654
EP  - 663
SN  - 2352-538X
UR  - https://doi.org/10.2991/978-94-6463-136-4_56
DO  - 10.2991/978-94-6463-136-4_56
ID  - Karwande2023
ER  -