How Industry 4.0 Components Can Enhance the Competitiveness of a Small Household Electrical Appliance Manufacturer in China?

In recent years, researchers have begun studying the relationship between Industry 4.0 and Lean Six Sigma. Initially, they focused on the impact of Industry 4.0 on Lean Manufacturing and later expanded their investigation to include Six Sigma after 2020. However, most studies have taken a holistic approach, which presents challenges for small and medium-sized manufacturers who may lack the necessary resources to upgrade their manufacturing and quality systems all at once to benefit from the competitive advantages offered by Industry 4.0.This article aims to address this research gap by adopting an “individual approach.” It focuses on examining the various components of Industry 4.0 and their potential interaction with the “Define” stage of the Six Sigma practice in this initial research paper. Specifically, this study explores how big data analysis (BDA) and Artificial Intelligence (AI), which are key components of Industry 4.0, can enhance the collection efficiency of the “Voice of Customer.” By gaining a better understanding of the “Voice of Customer” and improving the identification of relevant and significant improvement projects during the “Define Stage” of Six Sigma, enterprises can adopt Industry 4.0 components and reap the associated benefits of this individual integration.Furthermore, this paper also establishes future research directions, guiding subsequent research papers to investigate the interaction between different Industry 4.0 components and the “Measure,” “Analyze,” “Improve,” and “Control” stages of Six Sigma.

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Published
2024-12-15
DOI
https://doi.org/10.1109/ieem62345.2024.10857065
Primary Topic
Digital Transformation in Industry
Type
article
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article

How Industry 4.0 Components Can Enhance the Competitiveness of a Small Household Electrical Appliance Manufacturer in China?

Eric Cheung, Shu Lun Mak, Weizheng Tang
Digital Transformation in Industry
article

How Industry 4.0 Components Can Enhance the Competitiveness of a Small Household Electrical Appliance Manufacturer in China?

Eric Cheung, Shu Lun Mak, Weizheng Tang
article en

Abstract

In recent years, researchers have begun studying the relationship between Industry 4.0 and Lean Six Sigma. Initially, they focused on the impact of Industry 4.0 on Lean Manufacturing and later expanded their investigation to include Six Sigma after 2020. However, most studies have taken a holistic approach, which presents challenges for small and medium-sized manufacturers who may lack the necessary resources to upgrade their manufacturing and quality systems all at once to benefit from the competitive advantages offered by Industry 4.0.This article aims to address this research gap by adopting an “individual approach.” It focuses on examining the various components of Industry 4.0 and their potential interaction with the “Define” stage of the Six Sigma practice in this initial research paper. Specifically, this study explores how big data analysis (BDA) and Artificial Intelligence (AI), which are key components of Industry 4.0, can enhance the collection efficiency of the “Voice of Customer.” By gaining a better understanding of the “Voice of Customer” and improving the identification of relevant and significant improvement projects during the “Define Stage” of Six Sigma, enterprises can adopt Industry 4.0 components and reap the associated benefits of this individual integration.Furthermore, this paper also establishes future research directions, guiding subsequent research papers to investigate the interaction between different Industry 4.0 components and the “Measure,” “Analyze,” “Improve,” and “Control” stages of Six Sigma.

Vocational Training Council (HK)
Industry, innovation and infrastructure
Openalex Percentile: Top 61%
Digital Transformation in Industry
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How Industry 4.0 Components Can Enhance the Competitiveness of a Small Household Electrical Appliance Manufacturer in China? — Eric Cheung, Shu Lun Mak, et al. · (2024) | TGRS Research Map | TGRS