In chemical industries, corrosion poses significant risks to the assets, people, environment, and safety. The implemented robust RPMS framework detects pipeline leakage and corrosion on a real-time basis, thus enhancing industrial safety. The system proposes a proactive detection method that works on chemical industries’ historical and real-time datasets through various sensors like temperature, flow, total dissolved solid, etc., to analyze the immediate leakage point in the pipeline system. A secured environment using blockchain stores the data, and changes are notified to the users with the help of smart contracts. Data captured through sensors is used in blockchain for further analysis and detection of leakage and corrosion. The ML SVM algorithm is used to detect the life and stage of the corrosion-causing factor and leakage point helping user to solve these issues fast and efficiently. This paper provides realistic RPMS testing and validation in the chemical industry that has demonstrated acceptable performance.