Abstract— Looking forward to integrating practically the industry 4.0 technologies, it is mandatory to deal with information unavailability problems to manage better the mining machines by maintenance KPIs. This close monitoring issue is more present in the maintenance information’s flow through all the organization management level. This research presents the predictive maintenance system PdMSys design using model-based system engineering according to the system life cycle management paradigm. The use of a modeling language such as SysML helped dissect all aspects to meet the mining industry stakeholders' needs and expectations regarding the PdMSys features. PdMSys is a transversal and customized system created for three users’ hierarchical levels. The system sources data from the field sensors, the machine's parameters, and other systems databases to enable first monitoring assets' health state and secondly effectively managing the maintenance KPIs across the ore mine. This paper discusses the ability of PdMSys to transform the company's traditional practices into digital and proactive. Additionally, the financial benefits of implementing PdMSys are also presented. Lastly, the authors address PdMSys resilience to handle scalability and interoperability. Keywords— Predictive maintenance, Industry 4.0, Key performance indicators management, Model based system engineering, System modeling language