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Measuring techniques suitable for verification and repairing of industrial components: A comparison among optical systems
G Model CIRPJ 525 No. of Pages 10
CIRP Journal of Manufacturing Science and Technology xxx (2019) xxx–xxx
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CIRP Journal of Manufacturing Science and Technology journal homepage: www.elsevier.com/locate/cirpj
Measuring techniques suitable for verification and repairing of industrial components: A comparison among optical systems M.G. Guerraa , F. Lavecchiaa , G. Maggipintob , L.M. Galantuccia,* , G.A. Longoc a b c
Dipartimento di Meccanica Matematica e Management, Politecnico di Bari, via E. Orabona 4, 70125 Bari, Italy Apulia Development Centre for Additive Repair, Politecnico di Bari, via Amendola 132, 70126 Bari, Italy GE Avio srl – Apulia Repair Development Centre, via Amendola 132, 70126 Bari, Italy
A R T I C L E I N F O
A B S T R A C T
Article history: Available online xxx
On-machine verification is increasingly demanded in modern industry, due to the simultaneous necessity of high quality product and reduced time for production and verification. At the time being, contact probe systems are considered the most reliable ones, but they have many drawbacks, especially when they are used to measure free form surfaces in scanning mode. Optical techniques have the great advantage to acquire large amounts of points in very short time, and they can be used for several applications: from dimensional verification of manufactured products to the inspection of very expensive damaged parts for repairing processes in the aerospace industry. Although, they are affected by many kinds of error and they are very sensitive to the reflectivity or translucency of the sample. In this paper, a comparison between optical techniques potentially suitable to be implemented in onmachine dimensional verification is reported. The comparison involved two laser scanners, one structured light scanner and a photogrammetry-based scanner. The comparison was conducted through a free form reference object realized by the NPL Institute, with 150 150 40 mm3 of total volume. © 2019
Keywords: Optical scanners 3D-Image processing Freeform artefacts Measurements Uncertainty assessment Reverse engineering Additive repairing
Introduction The recent tendency in the manufacturing field is moving towards on-machine measurement techniques, which would, contemporary, lead to the reduction of production defects and to the minimization of the resources needed. Non-contact techniques are ever more used due to their good compromise between time needed and resolution, for both inprocess measurements (the process is not stopped and the measuring process is carried out simultaneously) and on-machine measurements (the part is still placed on the machine tool, but the machining process is stopped) [1]. Those kinds of instruments allow not only to detect defects but also to identify the root cause of the fault, through the full 3D comparison between the acquired point clouds and the CAD model. In this context, car manufacturers moved their attention from off-line to in-line measurement in order to collect process data rather than product data, which allows them to extend quality control and process optimizing strategies [2]. Another very important tendency of the manufacturers, strongly encouraged by the development of metal additive
* Corresponding author at: Politecnico di Bari, viale Japigia 182, 70126 Bari, Italy. E-mail address: [email protected] (L.M. Galantucci).
techniques, is the repairing of damaged parts. Much attention, indeed, is paid to the life cycle of the products, and it is preferable to repair damaged parts when it is difficult or expensive to produce them, both from an economic and environmental point of view. The existing researches have demonstrated that reverse engineering is quite promising for the remanufacturing of worn mechanical components/parts, achieving much time efficiency and reducing manual labour: a quick and accurate acquisition of the damaged areas of the worn part is attainable and thereby facilitates remanufacturing operations necessary to bring the parts back to like-new conditions. The worn products/components, which arrive in the remanufacturing facility exhibit highly uncontrolled variabilities in parts’ quality conditions, as well as, the complexities in parts’ shapes, dimensions and structures. The current manual repair to restore its original shape is time and labour intensive, and also produces inconsistent quality. Automation of such recovery processes for worn parts is of significant importance to overcome the intrinsic problems arising from part-to-part geometry variations and to achieve high efficiency when meeting the stringent quality requirements [3]. The repair of worn parts is of great interest for aerospace industries to extend the life cycle of aerospace parts [4]. A Life Cycle Assessment (LCA) on the energy and environmental impacts showed that laser direct deposition is most beneficial with relatively small defects. When the repair volume is 10% (1.56 kg)
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there is at least a 45% carbon footprint improvement and a 36% savings in total energy over replacing with a new blade [5]. The additive repairing process, which is, undoubtedly, one of the most interesting solutions, is the set of additive technologies that allow to repair parts by adding material selectively in the damaged areas. For these technologies, it is of paramount importance to acquire the 3D dimensions of the damaged area, in order to compare it with the original model, to define the deposition paths of the material where it is necessary and, finally, to check the success of deposition process. In Ref. [5] Wilson et al. demonstrated the effectiveness of laser direct deposition in remanufacturing and its ability to adapt to a wide range of part defects, in particular they succeeded in repairing defective voids in two turbine airfoils based on a new semi-automated geometric algorithm. A 3D digitized mesh of the defective part and a surface reconstruction algorithm was applied to define part geometry. The geometric models of the defective part are amenable to a “virtual repair” process, which further enhances the quality of the actual repair. The repaired blade matched the geometry of the original blade with mean accuracy of 0.030 mm. In Ref. [6] Xue et al. investigated the feasibility of repairing fretting damaged RR501K fuel injectors using laser cladding of L605 alloy powder. In Ref. [7] Herali c et al. developed and integrated with the robot control system a 3D scanning system for automatic in-process control of the deposition. Based on the scanned repair model with different defects, a reverse engineering (RE)-based geometry reconstruction method was proposed and developed in Ref. [4] for the nominal geometry reconstruction of a worn blade. They presented a geometry analysis of worn blades to show the geometrical difference between a curved blade and a straight blade and the cross-section difference of a curved blade at different height. Nominal repair models should be reconstructed for the precise refurbishment of curved blades [4]. A 3D digitization system is used to acquire a worn part’s geometry in the format of polygonal mesh. Then identification and positioning of the part’s damaged area can be achieved by comparing the nominal CAD model with the 3D model of the defective part surface [3]. Noncontact techniques, and particularly optical measuring techniques, are suitable for this kind of applications, because they have the unique capability of acquiring the 3D model of the entire damaged area in far shorter time than CMMs. The surface geometry of the worn part can be scanned and digitized into a set of point clouds by using various 3D optical devices [8]. In Refs. [3,4,8] a GOM ATOS II400 non-contact optical measurement system was used to acquire 3D data from the part surface. The National Research Council Canada (NRC) developed a laser scanner based in-line measurement system that was used to measure damaged RR501K nozzle air cap surface. The system consisted of a laser displacement sensor
and a measuring controller. The system had a maximum absolute error of about 0.09 mm as compare to CAD model (including sample dimension error, sensor error, measuring noise, motion system error, fixture dimension error, etc.) and had a repeatability (maximum deviation) of within about 0.06 mm [6]. A laser scanner was utilized in Ref. [7]. Resolution of the scanner in the z-axis was specified to 10 mm, and a 35 mm wide laser line gave a spatial resolution of 140 mm along the y-axis. Optical instruments are then preferable but, differently from Contact Measuring Machines (CMM), they are not fully traceable, especially in presence of freeform surfaces, which ever more characterize the aerospace, automotive and medical industries [9]. There are intrinsic characteristics coming from the equipment, such as camera resolution, depth of field, or errors due to external sources, like the ambient light [10,11] or the surface roughness and colours [12] affecting the results. The currently available standards for optical scanning systems, point based, area-based or multiview systems, are grouped in the VDI/VDE 2634 [13], which consists of two parts, involve the use of basic geometries, such as spheres, planes and cones to determine errors in forms and dimensions. Many efforts to design a specific and standardized procedure to test these kinds of instruments for real industrial cases are currently ongoing and, at the time being, they produced the conception of physical standards in order to evaluate the capability of the 3D imaging systems in more challenging conditions [14–16]. Moreover, triangulation-based systems, such as laser scanners and structured light scanners, require reference artefacts having cooperative optical surface characteristics, such as colour compatibility with the light source, and diffusely reflecting surfaces (Lambertian reflectance). The NPL Institute developed a free formcalibrated object [17], which is a challenge for an optical based scanner due to the reflective surface (aluminium) and due to the shape complexity, which better represent the complexity of the industrial reality. Research background 3D optical scanning systems have been widely used and compared between each other [18–21]. The comparison reported in this paper involved a laser line scanner (LLS) with a calibrated rotary stage, a structured light scanner (SLS), a photogrammetric scanning system with rotary table (PSSRT) and a portable measuring arm with laser line scanner (LSA). Laser scanners, in their several forms, through the well-known triangulation principle, are commonly used for machined surfaces inspection and with higher productivity. Because of their advantages, including the non-contact approach, fast speed, and
Fig. 1. NPL freeform artefact-main features.
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high precision, the laser scanning method has been obtaining increasingly extensive applications [22]. Laser line scanners are often used in combination with contact probe CMMs [23,24] in order to exploit the different advantages that each of these sensors has. However, point cloud registration still represents a criticality and leads to a registration error, which cumulatively affects the final bias [25]. Photogrammetry-based measurement derives 3D coordinates from images and tracking of cameras is not necessary, as camera positions and orientations are independently determined [26]. Thus, for industrial application and on-machine verification it is possible to use several cameras in different fixed or flexible positions or, one camera mounted on a motorized structure, or integrated into a robotic machine tool. Recently, a photogrammetry-based scanner was integrated in a robotic system for on machine verification purpose and a complete analysis of the main systematic error sources was carried out [27]. Structured light scanners are also implemented [28,29] and several studies were conducted with the aim to characterize this technology [30–32]. In Ref. [33] a practical procedure for qualifying a scanner based on structured blue light for geometrical and dimensional tolerances verification through a calibrated featurebased gauge was presented. Materials and methods In the present paper, a comparison between optical techniques through the use of a free-form calibrated object, designed by the NPL, is reported (Fig. 1). The NPL freeform artefact features both concave and convex forms of various sizes and it was produced with highly reflective material, 6082-T6 — Aluminium Dural, with the aim to identify the weaknesses of optical-based systems [17]. The surface roughness is very low: Rz considered in the uncertainty evaluation is 0.6 mm, further below the resolution of the majority of industrial opticalbased systems. The artefact includes also four ceramic spheres (in Fig. 1 they are indicated as Sphere 1–4) mainly used for defining the reference system. In Table 1, the calibrated values of spheres diameters, spheres distances and the cone diameter and angle are reported. The comparison involves a laser line scanner (LLS), a structured light scanner (SLS), a photogrammetric scanning system with rotary table (PSSRT) and a laser scanning arm (LSA), see Fig. 2. Table 1 Calibrated values of spheres diameters, spheres distances and cone angle and diameter. Spheres diameter
Calibrated value [mm]
Sphere 1 Sphere 2 Sphere 3 Sphere 4 Sphere 5 Sphere 6 Sphere 7 Cone diameter (z = 0)
9.997 9.998 9.999 9.996 85.071 64.918 19.993 19.214
Cone angle
Calibrated value [deg]
Angle
59.995
Spheres distances Sphere Sphere Sphere Sphere Sphere Sphere Sphere
1–2 2–3 3– 4 1–4 5–6 6–7 5–7
Calibrated value [mm] 149.935 150.091 149.999 150.004 89.564 54.224 70.237
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The laser line scanner (LLS) is a Vivid910/vi910 with a teleobjective lens mounted and a resolution of 0.4 mm, combined with a motorized and controlled rotary stage. The focusing distance used was 1100 mm, which allowed the survey of the entire object. The tilt angle of the scanner was 60 due to the presence of the deep cone and the number of projections was 18, one every 20 of rotary stage. The acquisition and the point clouds registration were completely automatic and they were conducted through the supplied software which manages and synchronizes the scanner and the rotary table (ISEL-RFII) movements. Afterwards, the registration was optimized by the application of the ICP (Iterative Closest Points) embedded in the mesh modelling software Geomagic. This scanner is affected by the registration errors, since a multi-view scan was needed for the acquisition of the object. The point clouds retrieved for the LLS was composed of about 2,000,000 points. The structured light scanner is an ATOS Core MV200, characterized by a working volume of 200 150 150 mm3 and by a resolution of 0.08 mm, see Fig. 2. The sensor was tilted of 45 , and scan step was set to 30 , which means the acquisition of the object from 12 points of views. The ATOS Core exploits the triple scan measuring principle with two cameras and a projector unit in the middle. It is a more compact solution with respect to the rest of the ATOS scanner series. During the scanning process, precise fringe patterns are projected onto the surface of the object and acquired by two cameras. This is a multi-view system and the registration of different scans is made possible by using specific targets, minimizing the registration error. The acquisition phase was semi-automatic with the manual rotary table. The reconstruction was done entirely using the GOM Scan Software. The point clouds retrieved for the SLS was composed by about 1,000,000 points. The PSSRT is a scanner already implemented and used for measurement in close and micro range [34–37]. It is a motorized and controlled scanning system with a great flexibility and working volumes ranging from a very small volume 18 18 10 mm3 to bigger ones, like approximately150 150 40 mm3. The working volume strictly depends on the optical configuration chosen and, according to the latter, the resolution of the system varies. The optical configuration chosen in this work is the one able to allow the acquisition of the NPL of 150 150 40 mm3. Thus, a Canon Eos 760D with a Canon EF 50 mm 1:1:8 II lens was used with the objective focused at its minimum distance, consequently, the ground resolution was 0.0223 mm/pixel. Three tilt angle values were chosen, one low value (30 ) which allowed the reconstruction of the more vertical sides of the object and two higher values (40 and 55 ), which allowed the reconstruction of all the features, both concave and convex. The rotary stage chosen was 8 and, consequently, the total number of images was 135. The image processing step was conducted with Agisoft Photoscan v 1.0.4 and the internal parameters for correcting camera distortion were computed by the software itself on the same images using a target-less internal calibration. The scale factor was computed through the distance between two spheres (Sph n5 and n6) and the photogrammetric models were scaled with the GOM Inspect software. The number of points acquired was about 2,000,000. The laser scanning arm (LSA) is an Hexagon ROMER Absolute Arm with integrated laser line scanner, characterized by an arm length equal to 2000 mm and laser line resolution of 0.043 mm. The main advantages of using this scanner are the portability, the flexibility and the good measurement accuracy. It is normally used in industry, in particular in the aerospace and automotive sectors and it is used in the Apulia Repair Development Centre, located at Politecnico di Bari, for the acquisition of damaged parts as input for the subsequent
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Fig. 2. Image showing the four described systems, according to the explained strategies. C is the sensor tilt angle for the LLS, SLS and PSSRT.
additive repairing processes. The laser arm is guided by the operator for the acquisition of the points. He regulates the distance from the object and the sensor tilting movements according to the geometry, while the laser power is automatically modulated with respect to the specific surface properties. The scanning strategy followed for the acquisition of the NPL consisted of 5 5 parallel scans in two orthogonal directions and at different distances from the object in order to go into deep areas, such as the cone, or generally the cavities of the object, as well as to acquire the convex shape of the sphere 6 and the torus. The complexity of the strategy in this case is due to the complexity of the object geometry. Each scan is fused with the others through an automatic point cloud registration conducted by software PC-DMIS, which is supplied together with the scanner. This kind of technology is affected by the registration error, as the
Laser line scanner (LLS). The number of acquired points was about 2,000,000. For each instrument involved in the comparison, three repetitions were carried out and analysed. Results are shown in the next section. Moreover, the artefact surface was not sprayed or coated with an opaque texture, with the aim to analyse the limits of those optical scanning systems. Results The analysis of the scanners outputs was conducted with the GOM inspect software [38], for the feature extraction and their dimensional verification and with Cloud Compare [39] for the 3D comparisons respect to the reference point cloud. Both features
Fig. 3. Spheres 5–7 diameter measured with each instrument [mm]. Error bars represent the expanded uncertainty (Eq. (1)).
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dimensions and point cloud data, adopted as reference, were the ones certified by the NPL Institute. Feature analysis Feature analysis was conducted with GOM Inspect software. The features fitting was conducted through the least squares process selecting the all points mode for the feature computation. Both bidirectional (sphere diameters) and unidirectional (distances between spheres) lengths were investigated and results are reported. The expanded uncertainty [mm] associated with each feature was computed according to the PUMA method [40] and comprised the following components:
Uncertainty of calibration — uc Uncertainty due to the measuring process — up Uncertainty due to temperature variation — ub Uncertainty due to the variability of error of the fitted form — uw
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi U ¼ K u2c þ u2p þ u2b þ u2w
ð1Þ
Where, k, the coverage factor is set to 2 for a 95% of confidence interval. In Fig. 3, spheres diameters were reported for each instrument involved in the comparison. Each dot is accompanied by an error bar, which represents the expanded uncertainty computed according to Eq. (1). Green dots represent the reference values (certified) of spheres diameters. Results obtained put in evidence that LLS system presented the highest errors and uncertainties. LSA registered also high errors but still in the same order of magnitude of the PSSRT system. The best result was obtained with the SLS system, both for errors and uncertainties (cents of millimetres). Moreover, PSSRT registered the best result for the sphere 7, which was the most complicated feature due to its location on the artefact. Same results were obtained for the cone measurement, with good performances of PSSRT, SLS and LSA. The cone was characterized by a diameter, in particular the one corresponding to the intersection with z = 0 plane and by the angle. Results are showed in Fig. 4. Finally, unidirectional lengths in the form of spheres distances were analysed, see Fig. 5. Results confirmed good performances of
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SLS and PSSRT characterized by errors comprised in the interval between 0.01–0.1 mm. In particular, for both instruments, distances involving the sphere 7, due to its location in the most reflective area of the object, were characterized by errors in the order of 0.1 mm, while the distance between Sphere 5 and 6 was characterized by errors in the order of 0.01 mm. Distances involving the sphere number 7 were the worst for the rest of the scanners too, especially for the LLS, with errors in the order of 0.45 mm. The SLS and the LLS were also capable of acquiring the ceramic spheres, while PSSRT had some problems due to homogeneous texture of ceramic material and LSA was not capable of acquiring ceramic spheres without changing the scanning parameters, such as exposure with respect to the value used for scanning the aluminium part. Results obtained highlighted a great difference between LLS and SLS (Fig. 6), with the latter well overlapped with the reference data. Errors obtained with the SLS are in the order of 0.01 mm, while errors obtained with LLS are in the order of several tenths of millimetre. 3D comparisons The output of the optical scanning systems in the form of point clouds were compared with respect to the point cloud reported in the certified data from the NPL. The reference point cloud consists of about 16,000 points acquired with a traceable CMM placed at NPL Institute. Cloud Compare software was used for the point cloud-point cloud comparisons, where, after a preliminary point cloud registration between reference and test, errors were evaluated as distances between homologous points belonging, respectively, to the reference and to the test point cloud. 3D comparisons and their results are reported in Figs. 7–10.. Results are presented in the form of frequency plots in order to highlight the error distribution of the compared points. The frequency plots show the distribution of the errors registered respect to the reference point cloud. Frequency is shown on the y axis, in terms of number of points comprised in a specific interval of error, which is reported on x axis. Three repetitions were examined and data overlapped on the same graph. As representative data, three parameters were chosen: the total range of error and the ranges of error containing the 95% and the 50% of points involved in the comparison.
Fig. 4. Cone dimensions (angle and diameter).
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Fig. 5. Spheres distances and corresponding uncertainty [mm].
Fig. 6. Ceramic Spheres (1–4) results: diameters and distances.
Fig. 7. (SLS) Frequency plot.
Discussion Results obtained and reported in the previous section highlighted the good performance of the SLS and PSSRT in 3D comparisons, with a percentage of points in the range of deviation
comprised between 0.01 of respectively 85% and 70% for SLS and PSSRT, see Fig. 11. Differently, the two laser scanners presented almost 30% of points in that range of deviation. 3D comparisons as coloured deviation maps are reported in Fig. 12. It is of great importance to analyse where deviations are
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Fig. 8. PSSRT frequency plot.
Fig. 9. LSA frequency plot.
Fig. 10. LLS frequency plot.
located on the object to try to determine the fault cause. In particular, the SLS map resulted to be uniformly green (0.02 mm) except for the cone where the reflectivity of the material was worse (no coating was applied). The coloured maps obtained from the PSSRT and LLS showed higher deviation in correspondence of the most reflecting parts, the torus contour, the cone and the spheres
junctions, however the performance registered by PSSRT is far better than LLS. Finally, in features analysis, LSA registered results in line with results obtained with SLS and PSSRT systems, while in 3D comparison, they were worse and only the 20% of points were characterized by errors within the interval 0.01 mm. This is mainly due to the registration between different scans necessary to
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Table 2. “Quality” of the results obtained were described by the average value of the relative errors registered for each kind of feature (spheres, cone, distances between spheres) and the average value of the relative uncertainties. Both values are expressed in percentage and computed according to the Eqs. (2)–(3). n P
Relative Average Error ½% ¼
i
Abs Errori Measured Dimensioni
n
100
ð2Þ
*Spheres Diameters/Spheres Distances/Cone Diameter/Cone Angle n P
Relative Average Uncertainty ½% ¼ Fig. 11. Percentage error distribution of each instrument.
obtain the entire model. It is possible to notice this effect from the coloured map and, in particular, the red points, which are coming from the overlapped regions. With the aim to summarize the results obtained so far, data about time needed and “quality” obtained were collected in
i
Exp Uncertaintyi Measured Dimensioni
n
100
ð3Þ
*Spheres Diameters/Spheres Distances/Cone Diameter/Cone Angle Where i represents the number of the feature (e.g. Sphere n5–7, or Spheres Distances Sph5–6, Sph5–7, Sph6–7). Regarding the time required to obtain the complete model, SLS registered the minimum time, for both, acquisition and data processing, even if the scanning strategy involved the manual
Fig. 12. 3D coloured maps showing point deviations. The coloured scale is expressed in mm. Table 2 Table showing overall results in terms of time required, relative errors and relative uncertainties.
SLS PSSRT LSA LLS
Acquisition time [min]
Processing time [min]
Post processing time [min]
Relative error on spheres ø — average value [%] relative uncertainty [%]
Relative error on distances — average value [%] relative uncertainty [%]
Relative error on cone ø — average value [%] relative uncertainty [%]
Relative error on cone angle — average value [%] relative uncertainty [%]
25 15 120 10
20 180 0 20
0 0 60 60
0.21 0.22 0.61 0.15 0.47 0.41 2.99 1.41
0.07 0.02 0.18 0.03 0.3 0.09 0.57 0.19
0.37 0.24 1.54 0.16 1.77 0.52 3.37 1.63
2.27 0.64 0.13 0.26 0.62 1.03 9.05 4.52
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movement of the rotary table. Moreover, there was no necessity for post-processing operations and mesh repairing. SLS registered also the best results in terms of errors in the 3D comparisons, as well as, in the feature analysis, with relative uncertainties of 0.1% for the spheres and 0.01% for unidirectional distances. PSSRT system registered errors comprised between cents up to few tenths of millimetres with a low relative uncertainty in the order of 0.1% for the spheres and the cone (diameter and angle) and 0.01% for distances. The main drawback was the time required for image processing, while at the end of the meshing process no other post-processing operation was required. Errors and uncertainties registered for LSA were higher and the time, to ultimate the acquisition and post-processing procedure was the highest, but errors are still in the same order of magnitude (except for the 3D comparisons, as reported above). LLS system presented the worst results in terms of errors and uncertainty. It is interesting to highlight that the LSA scanning time for single feature is much lower, in the order of 5 min and for the additive repairing applications, it is not necessary to scan the whole object. Conclusion In the present work, four optical scanning systems, potentially suitable for on-machine verification of industrial components and acquisition of damaged parts for repairing processes, were investigated. The investigation was carried out through a calibrated artefact with a free-form surface made of aluminium without the use of any coating. Results put in evidence the good performance of the structured light scanner (SLS) and of the photogrammetry-based scanner (PSSRT), with deviation in the 3D comparison mostly comprised in the range 0.01 mm and uncertainty in the order of about 0.2% for spheres and cone diameters and of 0.01% for unidirectional spheres distances. Among the other techniques, photogrammetry-based system showed promising results, considering the higher sensitivity to the object texture and reflectivity if compared with the structured light scanner. LLS resulted to be the worst optical instrument for these experimental conditions, while LSA was characterized by the highest registration problems, which did not affect particularly the single feature reconstruction and are mostly appreciable in the 3D comparison, in correspondence of the overlapped scans. To conclude, optical instruments still suffer from some limitations due to materials and surface characteristics such as surface finishing and colours. However, there are many reasons making them preferable respect to contact instruments. Based on the present experience, it is clear that the visible texture of the measured object plays a fundamental role for the performance of a 3D optical scanner and it strongly depends on the measuring principle adopted (laser, structured light, photogrammetry). Due to the increase of the materials available in the main industrial sectors, such as in the aerospace and automotive sectors, future works will be addressed for better understanding the effect due to optical interactions affecting these scanners when they are used to measure different materials and colours. Acknowledgements Operation co-financed by the European Fund for Regional Development Apulia POR Apulia 2014–2020 “Investing in your future” ASSE I – Specific Objective 1 – Action 1.1 (R & S) The authors wish to thank also GOM Italia s.r.l. for the great availability of the staff and the instrument ATOS Core MV200 to carry out the measures related to this work.
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Contents lists available at ScienceDirect
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Measuring techniques suitable for verification and repairing of industrial components: A comparison among optical systems M.G. Guerraa , F. Lavecchiaa , G. Maggipintob , L.M. Galantuccia,* , G.A. Longoc a b c
Dipartimento di Meccanica Matematica e Management, Politecnico di Bari, via E. Orabona 4, 70125 Bari, Italy Apulia Development Centre for Additive Repair, Politecnico di Bari, via Amendola 132, 70126 Bari, Italy GE Avio srl – Apulia Repair Development Centre, via Amendola 132, 70126 Bari, Italy
A R T I C L E I N F O
A B S T R A C T
Article history: Available online xxx
On-machine verification is increasingly demanded in modern industry, due to the simultaneous necessity of high quality product and reduced time for production and verification. At the time being, contact probe systems are considered the most reliable ones, but they have many drawbacks, especially when they are used to measure free form surfaces in scanning mode. Optical techniques have the great advantage to acquire large amounts of points in very short time, and they can be used for several applications: from dimensional verification of manufactured products to the inspection of very expensive damaged parts for repairing processes in the aerospace industry. Although, they are affected by many kinds of error and they are very sensitive to the reflectivity or translucency of the sample. In this paper, a comparison between optical techniques potentially suitable to be implemented in onmachine dimensional verification is reported. The comparison involved two laser scanners, one structured light scanner and a photogrammetry-based scanner. The comparison was conducted through a free form reference object realized by the NPL Institute, with 150 150 40 mm3 of total volume. © 2019
Keywords: Optical scanners 3D-Image processing Freeform artefacts Measurements Uncertainty assessment Reverse engineering Additive repairing
Introduction The recent tendency in the manufacturing field is moving towards on-machine measurement techniques, which would, contemporary, lead to the reduction of production defects and to the minimization of the resources needed. Non-contact techniques are ever more used due to their good compromise between time needed and resolution, for both inprocess measurements (the process is not stopped and the measuring process is carried out simultaneously) and on-machine measurements (the part is still placed on the machine tool, but the machining process is stopped) [1]. Those kinds of instruments allow not only to detect defects but also to identify the root cause of the fault, through the full 3D comparison between the acquired point clouds and the CAD model. In this context, car manufacturers moved their attention from off-line to in-line measurement in order to collect process data rather than product data, which allows them to extend quality control and process optimizing strategies [2]. Another very important tendency of the manufacturers, strongly encouraged by the development of metal additive
* Corresponding author at: Politecnico di Bari, viale Japigia 182, 70126 Bari, Italy. E-mail address: [email protected] (L.M. Galantucci).
techniques, is the repairing of damaged parts. Much attention, indeed, is paid to the life cycle of the products, and it is preferable to repair damaged parts when it is difficult or expensive to produce them, both from an economic and environmental point of view. The existing researches have demonstrated that reverse engineering is quite promising for the remanufacturing of worn mechanical components/parts, achieving much time efficiency and reducing manual labour: a quick and accurate acquisition of the damaged areas of the worn part is attainable and thereby facilitates remanufacturing operations necessary to bring the parts back to like-new conditions. The worn products/components, which arrive in the remanufacturing facility exhibit highly uncontrolled variabilities in parts’ quality conditions, as well as, the complexities in parts’ shapes, dimensions and structures. The current manual repair to restore its original shape is time and labour intensive, and also produces inconsistent quality. Automation of such recovery processes for worn parts is of significant importance to overcome the intrinsic problems arising from part-to-part geometry variations and to achieve high efficiency when meeting the stringent quality requirements [3]. The repair of worn parts is of great interest for aerospace industries to extend the life cycle of aerospace parts [4]. A Life Cycle Assessment (LCA) on the energy and environmental impacts showed that laser direct deposition is most beneficial with relatively small defects. When the repair volume is 10% (1.56 kg)
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there is at least a 45% carbon footprint improvement and a 36% savings in total energy over replacing with a new blade [5]. The additive repairing process, which is, undoubtedly, one of the most interesting solutions, is the set of additive technologies that allow to repair parts by adding material selectively in the damaged areas. For these technologies, it is of paramount importance to acquire the 3D dimensions of the damaged area, in order to compare it with the original model, to define the deposition paths of the material where it is necessary and, finally, to check the success of deposition process. In Ref. [5] Wilson et al. demonstrated the effectiveness of laser direct deposition in remanufacturing and its ability to adapt to a wide range of part defects, in particular they succeeded in repairing defective voids in two turbine airfoils based on a new semi-automated geometric algorithm. A 3D digitized mesh of the defective part and a surface reconstruction algorithm was applied to define part geometry. The geometric models of the defective part are amenable to a “virtual repair” process, which further enhances the quality of the actual repair. The repaired blade matched the geometry of the original blade with mean accuracy of 0.030 mm. In Ref. [6] Xue et al. investigated the feasibility of repairing fretting damaged RR501K fuel injectors using laser cladding of L605 alloy powder. In Ref. [7] Herali c et al. developed and integrated with the robot control system a 3D scanning system for automatic in-process control of the deposition. Based on the scanned repair model with different defects, a reverse engineering (RE)-based geometry reconstruction method was proposed and developed in Ref. [4] for the nominal geometry reconstruction of a worn blade. They presented a geometry analysis of worn blades to show the geometrical difference between a curved blade and a straight blade and the cross-section difference of a curved blade at different height. Nominal repair models should be reconstructed for the precise refurbishment of curved blades [4]. A 3D digitization system is used to acquire a worn part’s geometry in the format of polygonal mesh. Then identification and positioning of the part’s damaged area can be achieved by comparing the nominal CAD model with the 3D model of the defective part surface [3]. Noncontact techniques, and particularly optical measuring techniques, are suitable for this kind of applications, because they have the unique capability of acquiring the 3D model of the entire damaged area in far shorter time than CMMs. The surface geometry of the worn part can be scanned and digitized into a set of point clouds by using various 3D optical devices [8]. In Refs. [3,4,8] a GOM ATOS II400 non-contact optical measurement system was used to acquire 3D data from the part surface. The National Research Council Canada (NRC) developed a laser scanner based in-line measurement system that was used to measure damaged RR501K nozzle air cap surface. The system consisted of a laser displacement sensor
and a measuring controller. The system had a maximum absolute error of about 0.09 mm as compare to CAD model (including sample dimension error, sensor error, measuring noise, motion system error, fixture dimension error, etc.) and had a repeatability (maximum deviation) of within about 0.06 mm [6]. A laser scanner was utilized in Ref. [7]. Resolution of the scanner in the z-axis was specified to 10 mm, and a 35 mm wide laser line gave a spatial resolution of 140 mm along the y-axis. Optical instruments are then preferable but, differently from Contact Measuring Machines (CMM), they are not fully traceable, especially in presence of freeform surfaces, which ever more characterize the aerospace, automotive and medical industries [9]. There are intrinsic characteristics coming from the equipment, such as camera resolution, depth of field, or errors due to external sources, like the ambient light [10,11] or the surface roughness and colours [12] affecting the results. The currently available standards for optical scanning systems, point based, area-based or multiview systems, are grouped in the VDI/VDE 2634 [13], which consists of two parts, involve the use of basic geometries, such as spheres, planes and cones to determine errors in forms and dimensions. Many efforts to design a specific and standardized procedure to test these kinds of instruments for real industrial cases are currently ongoing and, at the time being, they produced the conception of physical standards in order to evaluate the capability of the 3D imaging systems in more challenging conditions [14–16]. Moreover, triangulation-based systems, such as laser scanners and structured light scanners, require reference artefacts having cooperative optical surface characteristics, such as colour compatibility with the light source, and diffusely reflecting surfaces (Lambertian reflectance). The NPL Institute developed a free formcalibrated object [17], which is a challenge for an optical based scanner due to the reflective surface (aluminium) and due to the shape complexity, which better represent the complexity of the industrial reality. Research background 3D optical scanning systems have been widely used and compared between each other [18–21]. The comparison reported in this paper involved a laser line scanner (LLS) with a calibrated rotary stage, a structured light scanner (SLS), a photogrammetric scanning system with rotary table (PSSRT) and a portable measuring arm with laser line scanner (LSA). Laser scanners, in their several forms, through the well-known triangulation principle, are commonly used for machined surfaces inspection and with higher productivity. Because of their advantages, including the non-contact approach, fast speed, and
Fig. 1. NPL freeform artefact-main features.
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high precision, the laser scanning method has been obtaining increasingly extensive applications [22]. Laser line scanners are often used in combination with contact probe CMMs [23,24] in order to exploit the different advantages that each of these sensors has. However, point cloud registration still represents a criticality and leads to a registration error, which cumulatively affects the final bias [25]. Photogrammetry-based measurement derives 3D coordinates from images and tracking of cameras is not necessary, as camera positions and orientations are independently determined [26]. Thus, for industrial application and on-machine verification it is possible to use several cameras in different fixed or flexible positions or, one camera mounted on a motorized structure, or integrated into a robotic machine tool. Recently, a photogrammetry-based scanner was integrated in a robotic system for on machine verification purpose and a complete analysis of the main systematic error sources was carried out [27]. Structured light scanners are also implemented [28,29] and several studies were conducted with the aim to characterize this technology [30–32]. In Ref. [33] a practical procedure for qualifying a scanner based on structured blue light for geometrical and dimensional tolerances verification through a calibrated featurebased gauge was presented. Materials and methods In the present paper, a comparison between optical techniques through the use of a free-form calibrated object, designed by the NPL, is reported (Fig. 1). The NPL freeform artefact features both concave and convex forms of various sizes and it was produced with highly reflective material, 6082-T6 — Aluminium Dural, with the aim to identify the weaknesses of optical-based systems [17]. The surface roughness is very low: Rz considered in the uncertainty evaluation is 0.6 mm, further below the resolution of the majority of industrial opticalbased systems. The artefact includes also four ceramic spheres (in Fig. 1 they are indicated as Sphere 1–4) mainly used for defining the reference system. In Table 1, the calibrated values of spheres diameters, spheres distances and the cone diameter and angle are reported. The comparison involves a laser line scanner (LLS), a structured light scanner (SLS), a photogrammetric scanning system with rotary table (PSSRT) and a laser scanning arm (LSA), see Fig. 2. Table 1 Calibrated values of spheres diameters, spheres distances and cone angle and diameter. Spheres diameter
Calibrated value [mm]
Sphere 1 Sphere 2 Sphere 3 Sphere 4 Sphere 5 Sphere 6 Sphere 7 Cone diameter (z = 0)
9.997 9.998 9.999 9.996 85.071 64.918 19.993 19.214
Cone angle
Calibrated value [deg]
Angle
59.995
Spheres distances Sphere Sphere Sphere Sphere Sphere Sphere Sphere
1–2 2–3 3– 4 1–4 5–6 6–7 5–7
Calibrated value [mm] 149.935 150.091 149.999 150.004 89.564 54.224 70.237
3
The laser line scanner (LLS) is a Vivid910/vi910 with a teleobjective lens mounted and a resolution of 0.4 mm, combined with a motorized and controlled rotary stage. The focusing distance used was 1100 mm, which allowed the survey of the entire object. The tilt angle of the scanner was 60 due to the presence of the deep cone and the number of projections was 18, one every 20 of rotary stage. The acquisition and the point clouds registration were completely automatic and they were conducted through the supplied software which manages and synchronizes the scanner and the rotary table (ISEL-RFII) movements. Afterwards, the registration was optimized by the application of the ICP (Iterative Closest Points) embedded in the mesh modelling software Geomagic. This scanner is affected by the registration errors, since a multi-view scan was needed for the acquisition of the object. The point clouds retrieved for the LLS was composed of about 2,000,000 points. The structured light scanner is an ATOS Core MV200, characterized by a working volume of 200 150 150 mm3 and by a resolution of 0.08 mm, see Fig. 2. The sensor was tilted of 45 , and scan step was set to 30 , which means the acquisition of the object from 12 points of views. The ATOS Core exploits the triple scan measuring principle with two cameras and a projector unit in the middle. It is a more compact solution with respect to the rest of the ATOS scanner series. During the scanning process, precise fringe patterns are projected onto the surface of the object and acquired by two cameras. This is a multi-view system and the registration of different scans is made possible by using specific targets, minimizing the registration error. The acquisition phase was semi-automatic with the manual rotary table. The reconstruction was done entirely using the GOM Scan Software. The point clouds retrieved for the SLS was composed by about 1,000,000 points. The PSSRT is a scanner already implemented and used for measurement in close and micro range [34–37]. It is a motorized and controlled scanning system with a great flexibility and working volumes ranging from a very small volume 18 18 10 mm3 to bigger ones, like approximately150 150 40 mm3. The working volume strictly depends on the optical configuration chosen and, according to the latter, the resolution of the system varies. The optical configuration chosen in this work is the one able to allow the acquisition of the NPL of 150 150 40 mm3. Thus, a Canon Eos 760D with a Canon EF 50 mm 1:1:8 II lens was used with the objective focused at its minimum distance, consequently, the ground resolution was 0.0223 mm/pixel. Three tilt angle values were chosen, one low value (30 ) which allowed the reconstruction of the more vertical sides of the object and two higher values (40 and 55 ), which allowed the reconstruction of all the features, both concave and convex. The rotary stage chosen was 8 and, consequently, the total number of images was 135. The image processing step was conducted with Agisoft Photoscan v 1.0.4 and the internal parameters for correcting camera distortion were computed by the software itself on the same images using a target-less internal calibration. The scale factor was computed through the distance between two spheres (Sph n5 and n6) and the photogrammetric models were scaled with the GOM Inspect software. The number of points acquired was about 2,000,000. The laser scanning arm (LSA) is an Hexagon ROMER Absolute Arm with integrated laser line scanner, characterized by an arm length equal to 2000 mm and laser line resolution of 0.043 mm. The main advantages of using this scanner are the portability, the flexibility and the good measurement accuracy. It is normally used in industry, in particular in the aerospace and automotive sectors and it is used in the Apulia Repair Development Centre, located at Politecnico di Bari, for the acquisition of damaged parts as input for the subsequent
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Fig. 2. Image showing the four described systems, according to the explained strategies. C is the sensor tilt angle for the LLS, SLS and PSSRT.
additive repairing processes. The laser arm is guided by the operator for the acquisition of the points. He regulates the distance from the object and the sensor tilting movements according to the geometry, while the laser power is automatically modulated with respect to the specific surface properties. The scanning strategy followed for the acquisition of the NPL consisted of 5 5 parallel scans in two orthogonal directions and at different distances from the object in order to go into deep areas, such as the cone, or generally the cavities of the object, as well as to acquire the convex shape of the sphere 6 and the torus. The complexity of the strategy in this case is due to the complexity of the object geometry. Each scan is fused with the others through an automatic point cloud registration conducted by software PC-DMIS, which is supplied together with the scanner. This kind of technology is affected by the registration error, as the
Laser line scanner (LLS). The number of acquired points was about 2,000,000. For each instrument involved in the comparison, three repetitions were carried out and analysed. Results are shown in the next section. Moreover, the artefact surface was not sprayed or coated with an opaque texture, with the aim to analyse the limits of those optical scanning systems. Results The analysis of the scanners outputs was conducted with the GOM inspect software [38], for the feature extraction and their dimensional verification and with Cloud Compare [39] for the 3D comparisons respect to the reference point cloud. Both features
Fig. 3. Spheres 5–7 diameter measured with each instrument [mm]. Error bars represent the expanded uncertainty (Eq. (1)).
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dimensions and point cloud data, adopted as reference, were the ones certified by the NPL Institute. Feature analysis Feature analysis was conducted with GOM Inspect software. The features fitting was conducted through the least squares process selecting the all points mode for the feature computation. Both bidirectional (sphere diameters) and unidirectional (distances between spheres) lengths were investigated and results are reported. The expanded uncertainty [mm] associated with each feature was computed according to the PUMA method [40] and comprised the following components:
Uncertainty of calibration — uc Uncertainty due to the measuring process — up Uncertainty due to temperature variation — ub Uncertainty due to the variability of error of the fitted form — uw
qffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffiffi U ¼ K u2c þ u2p þ u2b þ u2w
ð1Þ
Where, k, the coverage factor is set to 2 for a 95% of confidence interval. In Fig. 3, spheres diameters were reported for each instrument involved in the comparison. Each dot is accompanied by an error bar, which represents the expanded uncertainty computed according to Eq. (1). Green dots represent the reference values (certified) of spheres diameters. Results obtained put in evidence that LLS system presented the highest errors and uncertainties. LSA registered also high errors but still in the same order of magnitude of the PSSRT system. The best result was obtained with the SLS system, both for errors and uncertainties (cents of millimetres). Moreover, PSSRT registered the best result for the sphere 7, which was the most complicated feature due to its location on the artefact. Same results were obtained for the cone measurement, with good performances of PSSRT, SLS and LSA. The cone was characterized by a diameter, in particular the one corresponding to the intersection with z = 0 plane and by the angle. Results are showed in Fig. 4. Finally, unidirectional lengths in the form of spheres distances were analysed, see Fig. 5. Results confirmed good performances of
5
SLS and PSSRT characterized by errors comprised in the interval between 0.01–0.1 mm. In particular, for both instruments, distances involving the sphere 7, due to its location in the most reflective area of the object, were characterized by errors in the order of 0.1 mm, while the distance between Sphere 5 and 6 was characterized by errors in the order of 0.01 mm. Distances involving the sphere number 7 were the worst for the rest of the scanners too, especially for the LLS, with errors in the order of 0.45 mm. The SLS and the LLS were also capable of acquiring the ceramic spheres, while PSSRT had some problems due to homogeneous texture of ceramic material and LSA was not capable of acquiring ceramic spheres without changing the scanning parameters, such as exposure with respect to the value used for scanning the aluminium part. Results obtained highlighted a great difference between LLS and SLS (Fig. 6), with the latter well overlapped with the reference data. Errors obtained with the SLS are in the order of 0.01 mm, while errors obtained with LLS are in the order of several tenths of millimetre. 3D comparisons The output of the optical scanning systems in the form of point clouds were compared with respect to the point cloud reported in the certified data from the NPL. The reference point cloud consists of about 16,000 points acquired with a traceable CMM placed at NPL Institute. Cloud Compare software was used for the point cloud-point cloud comparisons, where, after a preliminary point cloud registration between reference and test, errors were evaluated as distances between homologous points belonging, respectively, to the reference and to the test point cloud. 3D comparisons and their results are reported in Figs. 7–10.. Results are presented in the form of frequency plots in order to highlight the error distribution of the compared points. The frequency plots show the distribution of the errors registered respect to the reference point cloud. Frequency is shown on the y axis, in terms of number of points comprised in a specific interval of error, which is reported on x axis. Three repetitions were examined and data overlapped on the same graph. As representative data, three parameters were chosen: the total range of error and the ranges of error containing the 95% and the 50% of points involved in the comparison.
Fig. 4. Cone dimensions (angle and diameter).
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Fig. 5. Spheres distances and corresponding uncertainty [mm].
Fig. 6. Ceramic Spheres (1–4) results: diameters and distances.
Fig. 7. (SLS) Frequency plot.
Discussion Results obtained and reported in the previous section highlighted the good performance of the SLS and PSSRT in 3D comparisons, with a percentage of points in the range of deviation
comprised between 0.01 of respectively 85% and 70% for SLS and PSSRT, see Fig. 11. Differently, the two laser scanners presented almost 30% of points in that range of deviation. 3D comparisons as coloured deviation maps are reported in Fig. 12. It is of great importance to analyse where deviations are
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Fig. 8. PSSRT frequency plot.
Fig. 9. LSA frequency plot.
Fig. 10. LLS frequency plot.
located on the object to try to determine the fault cause. In particular, the SLS map resulted to be uniformly green (0.02 mm) except for the cone where the reflectivity of the material was worse (no coating was applied). The coloured maps obtained from the PSSRT and LLS showed higher deviation in correspondence of the most reflecting parts, the torus contour, the cone and the spheres
junctions, however the performance registered by PSSRT is far better than LLS. Finally, in features analysis, LSA registered results in line with results obtained with SLS and PSSRT systems, while in 3D comparison, they were worse and only the 20% of points were characterized by errors within the interval 0.01 mm. This is mainly due to the registration between different scans necessary to
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Table 2. “Quality” of the results obtained were described by the average value of the relative errors registered for each kind of feature (spheres, cone, distances between spheres) and the average value of the relative uncertainties. Both values are expressed in percentage and computed according to the Eqs. (2)–(3). n P
Relative Average Error ½% ¼
i
Abs Errori Measured Dimensioni
n
100
ð2Þ
*Spheres Diameters/Spheres Distances/Cone Diameter/Cone Angle n P
Relative Average Uncertainty ½% ¼ Fig. 11. Percentage error distribution of each instrument.
obtain the entire model. It is possible to notice this effect from the coloured map and, in particular, the red points, which are coming from the overlapped regions. With the aim to summarize the results obtained so far, data about time needed and “quality” obtained were collected in
i
Exp Uncertaintyi Measured Dimensioni
n
100
ð3Þ
*Spheres Diameters/Spheres Distances/Cone Diameter/Cone Angle Where i represents the number of the feature (e.g. Sphere n5–7, or Spheres Distances Sph5–6, Sph5–7, Sph6–7). Regarding the time required to obtain the complete model, SLS registered the minimum time, for both, acquisition and data processing, even if the scanning strategy involved the manual
Fig. 12. 3D coloured maps showing point deviations. The coloured scale is expressed in mm. Table 2 Table showing overall results in terms of time required, relative errors and relative uncertainties.
SLS PSSRT LSA LLS
Acquisition time [min]
Processing time [min]
Post processing time [min]
Relative error on spheres ø — average value [%] relative uncertainty [%]
Relative error on distances — average value [%] relative uncertainty [%]
Relative error on cone ø — average value [%] relative uncertainty [%]
Relative error on cone angle — average value [%] relative uncertainty [%]
25 15 120 10
20 180 0 20
0 0 60 60
0.21 0.22 0.61 0.15 0.47 0.41 2.99 1.41
0.07 0.02 0.18 0.03 0.3 0.09 0.57 0.19
0.37 0.24 1.54 0.16 1.77 0.52 3.37 1.63
2.27 0.64 0.13 0.26 0.62 1.03 9.05 4.52
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movement of the rotary table. Moreover, there was no necessity for post-processing operations and mesh repairing. SLS registered also the best results in terms of errors in the 3D comparisons, as well as, in the feature analysis, with relative uncertainties of 0.1% for the spheres and 0.01% for unidirectional distances. PSSRT system registered errors comprised between cents up to few tenths of millimetres with a low relative uncertainty in the order of 0.1% for the spheres and the cone (diameter and angle) and 0.01% for distances. The main drawback was the time required for image processing, while at the end of the meshing process no other post-processing operation was required. Errors and uncertainties registered for LSA were higher and the time, to ultimate the acquisition and post-processing procedure was the highest, but errors are still in the same order of magnitude (except for the 3D comparisons, as reported above). LLS system presented the worst results in terms of errors and uncertainty. It is interesting to highlight that the LSA scanning time for single feature is much lower, in the order of 5 min and for the additive repairing applications, it is not necessary to scan the whole object. Conclusion In the present work, four optical scanning systems, potentially suitable for on-machine verification of industrial components and acquisition of damaged parts for repairing processes, were investigated. The investigation was carried out through a calibrated artefact with a free-form surface made of aluminium without the use of any coating. Results put in evidence the good performance of the structured light scanner (SLS) and of the photogrammetry-based scanner (PSSRT), with deviation in the 3D comparison mostly comprised in the range 0.01 mm and uncertainty in the order of about 0.2% for spheres and cone diameters and of 0.01% for unidirectional spheres distances. Among the other techniques, photogrammetry-based system showed promising results, considering the higher sensitivity to the object texture and reflectivity if compared with the structured light scanner. LLS resulted to be the worst optical instrument for these experimental conditions, while LSA was characterized by the highest registration problems, which did not affect particularly the single feature reconstruction and are mostly appreciable in the 3D comparison, in correspondence of the overlapped scans. To conclude, optical instruments still suffer from some limitations due to materials and surface characteristics such as surface finishing and colours. However, there are many reasons making them preferable respect to contact instruments. Based on the present experience, it is clear that the visible texture of the measured object plays a fundamental role for the performance of a 3D optical scanner and it strongly depends on the measuring principle adopted (laser, structured light, photogrammetry). Due to the increase of the materials available in the main industrial sectors, such as in the aerospace and automotive sectors, future works will be addressed for better understanding the effect due to optical interactions affecting these scanners when they are used to measure different materials and colours. Acknowledgements Operation co-financed by the European Fund for Regional Development Apulia POR Apulia 2014–2020 “Investing in your future” ASSE I – Specific Objective 1 – Action 1.1 (R & S) The authors wish to thank also GOM Italia s.r.l. for the great availability of the staff and the instrument ATOS Core MV200 to carry out the measures related to this work.
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