Correlating in-situ process monitoring data with the reduction in load bearing capacity of selective laser melted Ti–6Al–4V porous biomaterials

Selective Laser Melting allows for the creation of intricate porous structures, that possess favourable biological properties. These structures are known as porous biomaterials. The focus of this paper is to evaluate the use of an in-line photodiode based process monitoring system, for the monitoring of the operational behaviour of the laser, and to correlate this with the resultant parts mechanical performance. In this study the production scale Renishaw 500M was used to produce porous structures, using Ti–6Al–4V feedstock powder. During the process, a co-axial process monitoring system was utilised to generate data relating to both the meltpool and the operational behaviour of the laser. An advanced scanning technique was used to produce the structures, whereby the laser parameters determine the strut dimensions. In this study, the laser input energy was reduced by 33%, 66% and 100%, at specific layers within the structures. Computer Tomography and Scanning Electron Microscopy was utilised to characterise the affected struts within the structures, while quasi-static compression testing was used to determine the structure's mechanical properties. It was demonstrated that as the level of input energy decreased and the number of affected layers increased, a corresponding decrease in the load bearing capacity of the structures occurred. With the structures experiencing a significant loss in strength also exhibiting a change in the failure mode during compression testing. Data generated during the processing of such structures was compared to the data generated during the processing of control structures, with the difference between the two been calculated on a layer-by-layer basis. A clear correlation was demonstrated between the total level of deviation between the two signal sets and a reduction in the load bearing capacity of the structures. This indicates that by comparing build data to a benchmark data set, valuable information relating to the structural integrity of the porous structures can be obtained.