Analysis of Indonesian Industry Readiness for the Adoption of Autonomous Manufacturing Systems in the Era of Industry 4.0

Gibran Al Rafid (Department of Industrial Engineering, Universitas Mercu Buana Jakarta, Indonesia)

Jurnal Mekintek : Jurnal Mekanikal, Energi, Industri, Dan Teknologi
Vol. 16 No. 2 (2025): October: Mechanical, Energy, Industrial and Technology

The rapid advancement of Industry 4.0 technologies has accelerated the transition from conventional manufacturing systems toward Autonomous Manufacturing Systems (AMS), which integrate Artificial Intelligence (AI), Industrial Internet of Things (IIoT), robotics, cyber-physical systems, digital twins, and big data analytics to enable intelligent, self-optimizing, and highly efficient production processes. Given the increasing importance of autonomous manufacturing for enhancing industrial competitiveness, this study aims to assess the readiness of Indonesian manufacturing industries to adopt Autonomous Manufacturing Systems. A mixed-methods approach was employed, combining quantitative and qualitative techniques. Data were collected through questionnaires, interviews, observations, and secondary sources involving respondents from the automotive, electronics, food and beverage, and textile sectors. The collected data were analyzed using descriptive statistics, readiness index calculations, gap analysis, Structural Equation Modeling (SEM), thematic analysis, and content analysis. The results indicate that the overall readiness level of Indonesian manufacturing industries is moderate. However, human resource readiness and cybersecurity readiness remain significant challenges due to shortages of specialized talent, limited AI-related competencies, insufficient workforce training, and varying levels of cybersecurity preparedness. The study also found substantial disparities between large enterprises and SMEs in terms of technology adoption and resource availability. The study concludes that while Indonesian manufacturing industries have established a foundation for autonomous manufacturing adoption, further improvements in workforce development, technology integration, cybersecurity infrastructure, and policy support are required. To accelerate the transition toward autonomous manufacturing, collaborative efforts among industry, government, and educational institutions are essential to strengthen technological capabilities, develop skilled human resources, and create a supportive innovation ecosystem.