Advanced 3D scan data analysis for performant reengineering maintenance processes

Abstract

Overhaul processes of long-living, cost-intensive machines and facilities are time-consuming tasks. They aim either at full recovery of the original product condition through repair or spare part exchange or at modernization for performance enhancement. However, decision for an overhaul should be carefully considered, because realization may be difficult und time-critical. Every overhaul process is unique and based on a thoroughly diagnosis of product condition. This makes it a risky and hard to plan project. In this context speed of overhaul operation is essential for avoiding costs due to machine down times. Obsolescence of components and modernization goals demand for an efficient reengineering to design geometric models for production. Modern 3D scanning technologies deliver 3D models of actual product geometry and allow deviation and tolerance analyses in case of available reference models. However, optical limitations and difficult part disassembly make 3D digitization still a laborious task and is additionally followed by a high effort in data post-processing. This paper depicts a new approach to facilitate reengineering processes through advanced methods in 3D scan data analysis of non-disassembled products. Implementations allow parts identification in 3D assembly scans through shape recognition and database search for provision of needed CAD1 data.