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The work describes a concept application to aid a safety engineer to perform an audit of a production aircraft against safety driven installation requirements. The capability is achieved using the following steps: A) Image capture of a product and measurement of distances between datum points within the product with/without references to a planar surface B) A digital reconstruction of the fabricated product by using multiple captured images to reposition parts according to the actual model. C) The projection onto the 3D digital reconstruction of the safety related installation constraints, respecting the original intent of the constraints that are defined in the digital mock-up.

Safety is one of the most important aspects of which we are concerned with in the field of aerospace-systems development. There are a variety of safety assessment activities that are performed throughout a system's lifecycle. Multiple interrelated safety analysis artifacts are generated from the process. However, requirements and guidance for the synthesis and validation of the results of this analysis are insufficient and are not explicit. In traditional system development processes, certification coordination, safety assessment, requirements validation, and implementation verification are generally treated as supporting processes, which are concurrent and interactively dependent throughout the iterative development of a system. In SAE ARP4754A, these processes are stressed as integral processes with traceability between safety requirements and the dependencies between safety assessment activities highlighted as an important concern.

The work describes a concept application that aids a safety engineer to create a layup of equipment models by using an image scan of a schematic and a library of predefined standard component and their symbols. The approach uses image recognition techniques to identify the symbols within the scanned image of the schematic from a given library of symbols. Two recognition approaches are studied, one uses General Hough Transform; the other is based on pixel-level feature computation combining both structure and statistical features. The application allows the user to accept or edit the results of the recognition step and allows the user to define new components during the layup step. The tool then generates an output file that is compatible with a formal safety modeling tool. The identified symbols are associated to behavioral nodes from a model based safety tool.