The intense use of Additive Manufacturing technologies, especially Selective Laser Melting (SLM), to produce complex functional components by several sectors of the industry evidenced that current machines are not able to ensure the product quality. The results are affected by failures occurred in manufacturing processes caused, for instance, by the controller software. Such failures influence either the time to manufacture a component or its final quality. Current system validation methodologies are not adapted to SLM machines and, therefore, they are not effective. Within this context, this dissertation focused on the development of a methodology to evaluate process failures originated by the software of SLM machines in order to measure the machine quality. For this purpose, a process map for the machine was described, Key Performance Indicators were designed, and the Conformance Timed Automata Effect Analysis (ConTEA) testing methodology was developed. By using ConTEA, models with functioning scenarios are created, the tests can be generated and applied to the SLM machine software, failures can be tracked and the machine quality can be assessed.

Selective Laser Melting (SLM) is the most attractive Additive Manufacturing technology to companies because it manufactures metallic functional and lightweight workpieces. However, current SLM machines do not ensure the product quality due to their low reliability. In order to assess a SLM machine quality, the Conformance Timed Automata Effect Analysis testing methodology was developed and an innovative systematic evaluation can be performed.