A Machine Learning–Assisted Evaluation of Industry 4.0 Maturity and Sustainability in Manufacturing Enterprises
Keywords:
Industry 4.0; Sustainability; Smart Manufacturing; Cyber-Physical Systems, (CPSs); Big Data Analytics; Indian ManufacturingAbstract
The increasing digitalization of manufacturing systems through Industry 4.0 (I4.0) technologies has transformed global industrial operations by integrating cyber-physical systems (CPSs), the Internet of Things (IoT), robotics, additive manufacturing, and big data analytics. Despite widespread recognition of their potential, the sustainability and practical implementation of these technologies remain challenging, particularly within developing economies such as India. This study aims to evaluate the sustainability and maturity of Industry 4.0 enabling technologies in Indian manufacturing industries. A comprehensive mixed-method approach was adopted, combining literature review, expert interviews, and a structured questionnaire survey conducted across 16 manufacturing industries, including heavy engineering, metallurgical, textile, food processing, and chemical sectors. Findings reveal that smart sensors and robotic systems exhibit the highest adoption rates, while big data analytics and CPSs remain at the early implementation stage. The maturity–importance matrix indicates that sustainability in Industry 4.0 enhances both economic performance and social stability. Results demonstrate a positive correlation between sustainability and business profitability, supported by a rise in job creation and workforce skill levels as industries advance toward higher digital maturity. The research establishes that sustainable Industry 4.0 integration contributes to technological advancement, economic growth, and workforce transformation, offering an evidence-based roadmap for smart manufacturing implementation in developing economies.
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