Analysis of the Impact of Predictive Maintenance Based on IoT and Digital Twin on Production Efficiency in the Textile Industry in West Java

This study examines the impact of IoT-based predictive maintenance and digital twin technology on production efficiency in the textile industry in West Java. Employing a quantitative research design, data were collected from 120 respondents using a structured questionnaire with a 5-point Likert scale. Structural Equation Modeling - Partial Least Squares (SEM-PLS) was used for data analysis. The findings reveal that IoT-based predictive maintenance and digital twin technology positively and significantly influence production efficiency. Furthermore, the combined application of these technologies demonstrates the strongest impact, highlighting their synergistic benefits. This study underscores the potential of Industry 4.0 technologies to enhance operational performance in the textile sector and provides actionable insights for industry stakeholders.

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Publication Details

Journal
West Science Social and Humanities Studies
Published
2025-03-28
DOI
https://doi.org/10.58812/wsshs.v3i03.1795
Primary Topic
Digital Transformation in Industry
Type
article
Field-Weighted Citation Impact
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article

Analysis of the Impact of Predictive Maintenance Based on IoT and Digital Twin on Production Efficiency in the Textile Industry in West Java

Rully Fildansyah, Salwa Aulia Novitasari, Sopyan Sopyan
West Science Social and Humanities Studies
Digital Transformation in Industry
article

Analysis of the Impact of Predictive Maintenance Based on IoT and Digital Twin on Production Efficiency in the Textile Industry in West Java

Rully Fildansyah, Salwa Aulia Novitasari, Sopyan Sopyan
article en

Abstract

This study examines the impact of IoT-based predictive maintenance and digital twin technology on production efficiency in the textile industry in West Java. Employing a quantitative research design, data were collected from 120 respondents using a structured questionnaire with a 5-point Likert scale. Structural Equation Modeling - Partial Least Squares (SEM-PLS) was used for data analysis. The findings reveal that IoT-based predictive maintenance and digital twin technology positively and significantly influence production efficiency. Furthermore, the combined application of these technologies demonstrates the strongest impact, highlighting their synergistic benefits. This study underscores the potential of Industry 4.0 technologies to enhance operational performance in the textile sector and provides actionable insights for industry stakeholders.

West Science Social and Humanities StudiesVol. 3(03)
Universitas Wijaya Putra (ID), Universitas Patria Artha (ID)
Openalex Percentile: Top 91%
Digital Transformation in Industry
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