With the digital transformation of the maintenance function with emerging technology such as machine learning, Smart Maintenance will contribute to increased plant capacity as well as reduced maintenance costs. Profit Loss Indicator (PLI) has been tested for preventive maintenance combined with anomaly detection. Yet, it remains to include PLI into Smart Maintenance processes to ensure standardized application. PLI will also contribute towards sustainability in terms of improved production performance through reduced waste and time losses. This will also contribute to an improved working environment. The aim of this article is therefore to develop a smart maintenance process for PLI. This article demonstrates the main processes of smart maintenance that are harmonized with EN 17007 and sustainability. In addition to PLI, a hybrid approach for anomaly deployment as well as a dynamic FMECA (failure mode, effect and criticality analysis) are included in Smart Maintenance. Also, the result is partly tested where PLI is calculated for a Norwegian use-case. It is concluded that more elements for the smart maintenance processes must be further modelled and tested with industrial use-cases.