Sustainable Lean Six Sigma project selection in manufacturing environments using best-worst method-Reference-Cited by-同舟云学术

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Sustainable Lean Six Sigma project selection in manufacturing environments using best-worst method

Published:2022-11-10 Issue:7-8 Volume:34 Page:990-1014
ISSN:1478-3363
Container-title:Total Quality Management & Business Excellence
language:en
Short-container-title:Total Quality Management & Business Excellence

Author:

Swarnakar Vikas¹^ORCID,Singh A. R.²^ORCID,Antony Jiju¹^ORCID,Tiwari Anil Kr²^ORCID,Garza-Reyes Jose Arturo³^ORCID

Affiliation:

1. Department of Industrial and Systems Engineering, Khalifa University, Abu Dhabi, UAE

2. Department of Mechanical Engineering, National Institute of Technology, Raipur, India

3. Centre for Supply Chain Improvement, The University of Derby, Derby, UK

Publisher

Informa UK Limited

Subject

General Business, Management and Accounting

Link

https://www.tandfonline.com/doi/pdf/10.1080/14783363.2022.2139675

Reference49 articles.

1. A novel and practical conceptual framework to support Lean Six Sigma deployment in manufacturing SMEs

2. Best–worst method for robot selection

3. Lean Six Sigma in policing services: case examples, lessons learnt and directions for future research

4. Lean Six Sigma Project Selection and Prioritisation

Cited by 8 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. A data-driven decision-making approach for evaluating the projects according to resilience, circular economy and industry 4.0 dimension;Engineering Applications of Artificial Intelligence;2024-08

2. Evaluation of sustainable manufacturing performance – A case illustration with multistakeholder perspective;Journal of Cleaner Production;2024-06

3. Six sigma project generation and selection: an action research study;International Journal of Lean Six Sigma;2024-03-22

4. Select a winning Lean Six Sigma 4.0 project: Best Worst Method based decision making approach;Total Quality Management & Business Excellence;2024-03-18

5. Sustainable Project Choice: Integrating Must-Be Kano and Fuzzy Logic for Optimal Project Selection;2024

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