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How does big data influence smart manufacturing in the presence of preventive maintenance? A multi-analytical investigation
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DOI：10.1108/JMTM-08-2024-0454.png)
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Abstract
En 中文
PurposeSmart manufacturing (SM) capitalizes on big data analytics (BDA) advancements by enhancing current capabilities such as defect identification and enabling supporting capabilities such as preventive maintenance (PM). The previous literature fails to investigate the comprehensive associations between SM, BDA and PM. Therefore, this study aims to investigate the relationship among SM, BDA and PM.Design/methodology/approachThe present research implements a multi-analytical PLS-SEM-ANN approach to investigate the relationships among BDA, PM and SM.FindingsThis investigation indicates that BDA is an effective digital technology that positively affects the operations of SM and PM. Furthermore, the results suggest that PM has a positive influence on SM and that it also positively mediates the relationship between BDA and SM, where PM cannot be treated as an auxiliary practice and plays an important role in SM as a primary operation. Furthermore, implementing the BDA enhances the performance of SM and PM.Originality/valueThe role of PM in the context of BDA and SM has been ignored in past research, and this study offers novelty by examining this relationship.
Keywords:
PLS-SEM
Big data analytics
Smart manufacturing
Artificial neural network
Preventive maintenance
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