The Industrial Internet of Things (IIoT) is rapidly transforming the manufacturing industries by enhancing productivity and enabling real-time data monitoring and control, intelligent process control and digital connectivity across the systems. This work is focused on bibliometric analysis of the term “Industrial internet of Things” with emphasis on Manufacturing domain. This study further delves into casting and one of the special process Vertical Centrifugal Casting (VCC) used for manufacturing cylindrical and hollow cylindrical casting. Using comprehensive datasets extracted from two leading academic databases: Scopus® and Web of Science® for the period 2015–2025, a total of 25,628 non-duplicate records were analyzed using RStudio®. The analysis explores the various parameters such as publication trends, most cited countries, top contributing institutions, keyword co-occurrence networks, collaboration patterns, and author productivity metrics. The results indicate the exponential growth in the IIoT-related research in recent few years from the countries like China, India and USA. This research aligns with Digital Twins, Quality Prognosis, Predictive Maintenance, Smart Foundries and immersive technologies. In parallel, to support the bibliometric insights with a practical perspective, a prototype of IIoT integrated VCC setup was developed and demonstrated using embedded sensors, a NodeMCU microcontroller, and a custom mobile application for remote monitoring and control. This combination of bibliometric mapping and experimental implementation provides a holistic view of the current research landscape and technological direction of IIoT in advanced manufacturing, laying the foundation for future innovation in intelligent, data driven casting systems.