Gorka Kortaberria

Major aircraft manufacturers are expecting the commercial aircraft market to overcome the pre-COVID levels by 2025, which demands an increase in the production rate. However, aeronautical product assembly processes are still mainly manually performed with a low level of automation. Moreover, the current industry digitalization trend offers the possibility to develop faster, smarter and more flexible manufacturing processes, aiming at a higher production rate and product customization. Here, the integration of metrology within the manufacturing processes offers the possibility to supply reliable data to constantly adjust the assembly process parameters aiming at zero-defect, more digital and a higher level of automation manufacturing processes. In this context, this article introduces the virtual metrology as an assistant of the assembly process of the Advanced Rear-End fuselage component. It describes how the assembly process CADmodel is used by simulation tools to design, set up and perform the virtual commissioning of the new metrology-driven assembly methods, moving from a dedicated tooling approach to a more flexible and reconfigurable metrology-aided design. Preliminary results show that portable metrology solutions are fit-to-purpose even for hardly accessible geometries and fulfil the current accuracy demands. Moreover, the simulation environment ensures a user-friendly assembly process interaction providing further set-up time reduction.

Data-driven manufacturing in Industry 4.0 demands digital metrology not only to drive the in-process quality assurance of manufactured products but also to supply reliable data to constantly adjust the manufacturing process parameters for zero-defect manufacturing processes. Better quality, improved productivity, and increased flexibility of manufacturing processes are obtained by combining intelligent production systems and advanced information technologies where in-process metrology plays a significant role. While traditional coordinate measurement machines offer strengths in performance, accuracy, and precision, they are not the most appropriate in-process measurement solutions when fast, non-contact and fully automated metrology is needed. In this way, non-contact optical 3D metrology tackles these limitations and offers some additional key advantages to deploying fully integrated 3D metrology capability to collect reliable data for their use in intelligent decision-making. However, the full adoption of 3D optical metrology in the manufacturing process depends on the establishment of metrological traceability. Thus, this article presents a practical approach to the task-specific uncertainty assessment realisation of a dense point cloud data type of measurement. Finally, it introduces an experimental exercise in which data-driven 3D point cloud automatic data acquisition and evaluation are performed through a model-based definition measurement strategy.

In this research, a multi-view photogrammetric model was developed and tested in simulation in order to understand its capabilities for close-range photogrammetric applications. It was based on contour line detection and least squares geometrical fitting of a cylindrical geometry from multiple views. To feed and validate this model, synthetic data were created for several cylinders poses and camera network set-up. The simulation chain comprises three main stages: synthetic image creation, image data processing by means of shape-matching and cylinder pose estimation based on developed photogrammetric model. Beforehand, a priori data was theoretically established according to a common reference for both for intrinsic and extrinsic parameters of the cameras. The preliminary results highlight that the model is suitable for large scales and sensible to a priori known data as well as to image data quality. These results were compared against other validated geometrical methods to assure that the model is truthful. Preliminary results show that the accuracy of the model ranges between 1/1000 and 1/20000 for multiple poses and cylinder dimensions. Moreover the simulation procedure has been enhanced with a Montecarlo approach to estimate more realistic pose uncertainties considering possible imaging error sources.

Knowledge of machine tool behaviour is a key element to improve production, quality and availability as behaviour indicators represent or give an idea of the real state of the machine. Indeed, real conditions can be used to update simulation models’ parameters, detect or anticipate quality fault on workpiece, and to estimate damage state of machine components such as axis and spindle. Behaviour indicators extraction is based on the analysis of specific and known moves or actions of the machine tools. Two kinds of approaches to build these indicators are discussed in this chapter.

Product optimization for casting and post-casting manufacturing processes is becoming compulsory to compete in the current global manufacturing scenario. Casting design, simulation and verification tools are becoming crucial for eliminating oversized dimensions without affecting the casting component functionality. Thus, material and production costs decrease to maintain the foundry process profitable on the large-scale component supplier market. New measurement methods, such as dense matching techniques, rely on surface texture of casting parts to enable the 3D dense reconstruction of surface points without the need of an active light source as usually applied with 3D scanning optical sensors. This paper presents the accuracy evaluation of dense matching based approaches for casting part verification. It compares the accuracy obtained by dense matching technique with already certified and validated optical measuring methods. This uncertainty evaluation exercise considers both artificial targets and key natural points to quantify the possibilities and scope of each approximation. Obtained results, for both lab and workshop conditions, show that this image data processing procedure is fit for purpose to fulfill the required measurement tolerances for casting part manufacturing processes.

An engineering validation of a large optical telescope consists of executing major performing tests at the subsystem level to verify the overall engineering performance of the observatory. Thus, the relative pointing error verification of the telescope mount assembly subsystem is of special interest to guarantee the absolute pointing performance of the large synoptic survey telescope. This paper presents a new verification method for the relative pointing error assessment of the telescope mount assembly, based on laser tracker technology and several fiducial points fixed to the floor. Monte-Carlo-based simulation results show that the presented methodology is fit for purpose, even if floor movement occurs due to temperature variation during the measurement acquisition process. A further research about laser tracker technology integration into the telescope structure may suggest that such laser tracker technology could be permanently installed in the telescope in order to provide an active alignment system that aims to detect and correct possible misalignment between mirrors or to provide the required mirror positioning verification accuracy after maintenance activities. The obtained results show that two on-board laser tracker systems combined with eight measurement targets could result in measurement uncertainties that are better than 1 arcsec, which would provide a reliable built-in metrology tool for large telescopes.

Nowadays, errors during the manufacturing process of high value components are not acceptable in driving industries such as energy and transportation. Sectors such as aerospace, automotive, shipbuilding, nuclear power, large science facilities or wind power need complex and accurate components that demand close measurements and fast feedback into their manufacturing processes. New measuring technologies are already available in machine tools, including integrated touch probes and fast interface capabilities. They provide the possibility to measure the workpiece in-machine during or after its manufacture, maintaining the original setup of the workpiece and avoiding the manufacturing process from being interrupted to transport the workpiece to a measuring position. However, the traceability of the measurement process on a machine tool is not ensured yet and measurement data is still not fully reliable enough for process control or product validation. The scientific objective is to determine the uncertainty on a machine tool measurement and, therefore, convert it into a machine integrated traceable measuring process. For that purpose, an error budget should consider error sources such as the machine tools, components under measurement and the interactions between both of them. This paper reviews all those uncertainty sources, being mainly focused on those related to the machine tool, either on the process of geometric error assessment of the machine or on the technology employed to probe the measurand.

The main objective of this study is to present a new method to carry out measurements so as to improve the positioning verification step in the wind hub part dimensional validation process. This enhancement will speed up the measuring procedures for these types of parts. An industrial photogrammetry based system was applied to take advantage of its results, and new functions were added to existing capabilities. In addition to a new development based on photogrammetry modelling and image processing, a measuring procedure was defined based on optical and vision system considerations. A validation against a certified procedure by means of a laser-tracker has also been established obtaining deviations of ±0.125 μm/m.