Developing a Delphi assisted total interpretive structural model (D-TISM) for adopting the Industry 4.0 technologies within Lean Six Sigma framework-Reference-Cited by-同舟云学术

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Developing a Delphi assisted total interpretive structural model (D-TISM) for adopting the Industry 4.0 technologies within Lean Six Sigma framework

Published:2023-08-29 Issue: Volume: Page:1-25
ISSN:0953-7287
Container-title:Production Planning & Control
language:en
Short-container-title:Production Planning & Control

Author:

K. E. K. Vimal¹,Rashmi Divya²,K. Sivakumar³^ORCID,Kandasmay Jayakrishna⁴^ORCID,K. P. Paranitharan⁵^ORCID,Venkataraman Balaji⁶

Affiliation:

1. Department of Production Engineering, National Institute of Technology Tiruchirappalli, India

2. LEAD Program, Wabtec Corporation, India

3. Centre for Logistics and Supply Chain Management, Loyola Institute of Business Administration, Loyola College Campus, Chennai, India

4. School of Mechanical Engineering, Vellore Institute of Technology, Vellore, India

5. Department of Industrial Engineering, TVS Sensing Solutions Private Limited, Madurai, India

6. TVS Sensing Solutions Private Limited, Madurai, India

Publisher

Informa UK Limited

Subject

Industrial and Manufacturing Engineering,Management Science and Operations Research,Strategy and Management,Computer Science Applications

Link

https://www.tandfonline.com/doi/pdf/10.1080/09537287.2023.2251014

Reference112 articles.

1. Organizational and managerial challenges in the path toward Industry 4.0

2. A systematic review of Lean Six Sigma for the manufacturing industry

3. The Role of Industry 4.0 Technologies in Mitigating Supply Chain Disruption: Empirical Evidence From the Australian Food Processing Industry

4. Industry 4.0 and Lean Six Sigma: Results from a Pilot Study

5. Industry 4.0

Cited by 2 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Leagile supply chains and sustainable business performance: application of total interpretive structural modelling;Production Planning & Control;2024-04-25

2. Machine Learning Aided Six Sigma: Perspective and Practical Implementation;IEEE Transactions on Engineering Management;2024

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