The recent advances in Smart Manufacturing open opportunities in Maintenance and Management of its assets through new support strategies. This trend allows the collection of machine operation data in the shop floor, in order to interact with cyberspace computers through a communication network, therefore enabling the Cyber Physical System concept (CPS). Furthermore, the rapid advances of Information and Communications Technology (ICT) provide means to analyze Big Data, more quickly, autonomously, ubiquitously and in real time, offering information that assist in more efficient decision making in manufacturing processes. Nowadays, Prognostic and Health Management (PHM) leverages researches in the new generation of manufacturing. For this, an architecture called 5Cs, that directs the PHM implementation in CPS context is being adopted with expressive results, which allows the application of several math and/or Artificial Intelligence techniques to estimate the assets' remaining useful life. In particular, the use of Experts Systems and semantic information modeling can make it possible to represent knowledge found in the scientific literature and consolidated standards about the subject. This paper uses methodology of ontology development 101, which guides management, development and documenting of a formal taxonomy of failure prognostics. For model creation and evaluation, the Protégé suite is used, for it allows future researches to interact with the model, such as monitoring techniques and failure diagnostics in order to simulate real cases of mechanical components. This way, new possibilities for cyberspace oriented application development for industrial machine health management are revealed.