Design for verification

Increased competition in the aerospace market has placed additional demands on aerospace manufacturers to reduce costs, increase product flexibility and improve manufacturing efficiency. There is a knowledge gap within the sphere of digital to physical dimensional verification and on how to successfully achieve dimensional specifications within real-world assembly factories that are subject to varying environmental conditions. This paper describes a novel Design for Verification (DfV) framework to be used within low rate and high value and complexity manufacturing industries to aid in achieving high productivity in assembly via the effective dimensional verification of large volume structures, during final assembly. The 'Design for Verification' framework has been developed to enable engineers to design and plan the effective dimensional verification of large volume, complex structures in order to reduce failure rates and end-product costs, improve process integrity and efficiency, optimise metrology processes, decrease tooling redundancy and increase product quality and conformance to specification. The theoretical elements of the DfV methods are outlined, together with their testing using industrial case studies of representative complexity. The industrial tests have proven that by using the new Design for Verification methods alongside the traditional 'Design for X' toolbox, resulted in improved tolerance analysis and synthesis, optimized large volume metrology and assembly processes and more cost effective tool and jig design

Thermal compensation using the hybrid metrology approach compared to traditional scaling:DET 2016 Special Edition

Control of temperature in large-scale manufacturing environments is not always practical or economical, introducing thermal effects including variation in ambient refractive index and thermal expansion. Thermal expansion is one of the largest contributors to measurement uncertainty; however, temperature distributions are not widely measured. Uncertainties can also be introduced in scaling to standard temperature. For more complex temperature distributions with non-linear temperature gradients, uniform scaling is unrealistic. Deformations have been measured photogrammetrically in two thermally challenging scenarios with localised heating. Extended temperature measurement has been tested with finite element analysis to assess a compensation methodology for coordinate measurement. This has been compared to commonly used uniform scaling and has outperformed this with a highly simplified finite element analysis simulation in scaling a number of coordinates at once. This work highlighted the need for focus on reproducible temperature measurement for dimensional measurement in non-standard environments. </jats:p

Thermal Compensation of Photogrammetric Dimensional Measurements in Non-standard Anisothermal Environments

AbstractManufacturers are currently facing large volume metrology challenges driven by thermal effects such as variation in refractive index and thermal expansion. Thermal expansion is one of the largest contributors to measurement uncertainty and it can often be difficult to realise the standard 20° C temperature required. The current process for dimensional measurement requires that the temperature is measured at the instrument, and the entire measurement volume is scaled linearly by the same factor. Unfortunately, this assumes that temperatures are uniform all over the measurand, which is seldom the case particularly at large volume scales.Useful for deformation measurement, photogrammetry is increasingly employed in industry, which in some cases can exhibit uncertainties comparable with the industry standard laser tracker. By measuring temperature more broadly and combining this data with finite element analysis, it is possible to compensate each of these points in 3D space along the X, Y and Z axes. Actively creating challenging metrology conditions with highly localized temperature gradients, and maximum temperatures in excess of 45° C has allowed this approach to be tested. Results show that in many cases it is possible to make localized predictions of displacement within the range of photogrammetric measurement uncertainty