Asset criticality plays a significant role in asset maintenance, for example, capital improvement, investment decision, maintenance tasks planning and scheduling, etc. Existing techniques to develop the conventional asset criticality are either based on asset prioritization or theoretical probability of failures and consequences highly dependent on individual opinions. Also, the static nature of the asset criticality hinders its purpose for facilities with aging equipment. This abstract introduces a smart asset criticality (SAC), which eliminates bias and subjectivity of individual opinions by utilizing real-time asset data managed by computerized maintenance management system (CMMS). Use of real time data improves equipment risk management, represents accurate equipment health status and elevates situational awareness of facilities equipment. This in return allows better incorporation of operational and asset risk factors leading to continuous quality data feeding into CMMS and dynamic iteration of SAC. This work involved a rigorous review of historical background of asset maintenance and its progression through industrial revolutions summarizing the literary works on asset criticality as the priori to develop the proposed SAC. The dynamic nature was tested and validated for its real-time implementation using data at Great Lakes Water Authority in Detroit, Michigan. The implementation results showed that the SAC provided a more realistic view of overall assets condition leading to a more efficient maintenance tasks management. It is concluded that in the Maintenance 5.0 manufacturing, smart asset criticality (SAC) is superior to conventional asset criticality in maintaining physical assets across industries.