Linda Salma Angreani

• The existing Industry 4.0 maturity models (I4.0 MM) have mostly been built and tested in developed nations, making them less effective in developing countries with unique issues. Additionally, flexible updated models are needed to support the smooth integration of I4.0 adoption in rapid technological advancements and organizational matters. The research addresses the challenges by developing an adaptable I4.0 MM using approaches starting with structured literature reviews (SLRs), investigating the causal relationship and prioritization of I4.0 MMs key driving factors, aligning it with reputable reference architecture model (RAMs), and developing an ontology, named Ontomat 4.0, to facilitate interoperability of I4.0 MMs. The research's general findings highlight the core gaps in existing I4.0 MMs, the need to prioritize and the interdependence of the key driving factor in I4.0 transformation, the importance of strategically enhancing I4.0 adoption by aligning the key factor of I4.0 MMs with RAMs, and the necessity of a framework with an approach that can bridge the theoretical foundation of I4.0 MMs with practical application. The research concludes by describing contributions to the issues and challenges in the findings. However, while the research acknowledges the significant progress in its accomplishment, there are limitations to the study that need to be addressed in future research directions, including integrating sustainability metrics and increasingly essential factors, such as Customers, the potential integration of artificial intelligence (AI) within Ontomat 4.0, future exploration equipped with longitudinal studies, and the expansion of Ontomat 4.0 into a collaborative ecosystem where knowledge sharing and best practices can grow.