Power production systems are made up of assets that support material handling and production of electricity. As these assets deteriorate, it may be difficult to deliver the expected quality of service, and to meet regulatory requirements and sustainable development goals (Lutchman, 2018).

Moreover, Covid 19 has accelerated both manufacturing and service industries to go digital (Biard & Nour, 2021), increasing demand for both electrical power and production systems reliability. This challenge imposes an increase in the focus on efficiency of physical asset management and has prompted power production Industries to look for innovative solutions that yield maximum value for physical asset management functions. The arrival of asset management 4.0 concepts enables the exploitation of big data to improve and manage system reliability (Longhitano, et al., 2021).

Furthermore, asset performance depends on various factors like quality of maintenance and operating environmental factors, such that even two identical assets will seldom obey their estimated mean time to failure (Longhitano, et al., 2021). Considering this, a data driven approach is necessary as it spot deviations in time and maintenance is done when required, increasing its effectiveness (Jasiulewicz-Kaczmarek, et al., 2020).

The present research aims to develop a data driven asset management framework that is enhanced by Industry 4.0 technologies to execute the key functions of asset management in the operation, maintenance, and management phase of the physical asset’s life cycle, and effectively integrate the environmental, social, and economic aspects into physical asset management related activities to improve system performance and extend its service life.

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Ms. Tsitsi Mashupeka