Industry 4.0 implementation barriers in automotive manufacturing industry: Interpretive structural modelling approach

Industry 4.0 manufacturing practices are the trends of automation and data exchange, which involve heavy investment to adopt the latest modern technologies for improving the manufacturing process in terms of productivity, efficiency, flexibility, and profitability. In this context, the current study focuses on the key implementation barriers of Industry 4.0 in the automotive industry. An interpretive structural model of the barriers to implement Industry 4.0 in the automotive industry has been proposed to create a hierarchical order of key barriers, find the relationships among them, and create a graphical model of the system. Based on the review of available literature and discussion with experts in the automotive field, thirteen barriers have been identified to frame the model. Further, out of these thirteen, two barriers have been found to be dependent, another two as driving barriers, the remaining nine as linkage barriers, and none as autonomous barriers. Based on the developed model, ‘Great Risk of Obsolescence’ has been found to be the top-level dependent barrier and geographical risk to be the lowest-level independent barrier. A clear comprehension of the interactions between the key barriers can help in deciding priorities and managing the same to have higher efficacy and efficiency in implementing Industry 4.0. Overall, we aim to identify Industry 4.0 barriers in the automotive industry and prioritize them during the implementation of Industry 4.0. The structured model, so designed and developed, is expected to facilitate the understanding of the interdependence of the barriers of the Industry 4.0 manufacturing system amid its implementation.

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Publication Details

Journal
Concurrent Engineering
Published
2024-09-27
DOI
https://doi.org/10.1177/1063293x241287687
Citations
2
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
0.70
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article

Industry 4.0 implementation barriers in automotive manufacturing industry: Interpretive structural modelling approach

Avinash Ravi Raja, Sudesh Singh, Amit Kumar, Vineet Kumar et al.
2 citations
Concurrent Engineering
Digital Transformation in Industry
0.70
article

Industry 4.0 implementation barriers in automotive manufacturing industry: Interpretive structural modelling approach

Avinash Ravi Raja, Sudesh Singh, Amit Kumar, Vineet Kumar, Radhe Shyam Ojha
article en
2 citations

Abstract

Industry 4.0 manufacturing practices are the trends of automation and data exchange, which involve heavy investment to adopt the latest modern technologies for improving the manufacturing process in terms of productivity, efficiency, flexibility, and profitability. In this context, the current study focuses on the key implementation barriers of Industry 4.0 in the automotive industry. An interpretive structural model of the barriers to implement Industry 4.0 in the automotive industry has been proposed to create a hierarchical order of key barriers, find the relationships among them, and create a graphical model of the system. Based on the review of available literature and discussion with experts in the automotive field, thirteen barriers have been identified to frame the model. Further, out of these thirteen, two barriers have been found to be dependent, another two as driving barriers, the remaining nine as linkage barriers, and none as autonomous barriers. Based on the developed model, ‘Great Risk of Obsolescence’ has been found to be the top-level dependent barrier and geographical risk to be the lowest-level independent barrier. A clear comprehension of the interactions between the key barriers can help in deciding priorities and managing the same to have higher efficacy and efficiency in implementing Industry 4.0. Overall, we aim to identify Industry 4.0 barriers in the automotive industry and prioritize them during the implementation of Industry 4.0. The structured model, so designed and developed, is expected to facilitate the understanding of the interdependence of the barriers of the Industry 4.0 manufacturing system amid its implementation.

Concurrent EngineeringVol. 32(1-4)
Indian Institute of Information Technology Design and Manufacturing Jabalpur (IN), Sharda University (IN), Tsinghua University (CN)
Openalex Percentile: Top 26%
Digital Transformation in Industry
0.70
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