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Machine vision is now a well-established tool on theproduction line for making critical dimensionalmeasurements as part of the quality control process in both

high volume and low volume manufacturing, and provides a realreturn on investment. Quantifiable measurements that can beobtained from an image include distances, angles, centre ofmass, area and circular fit, to name but a few. Industrial visionmeasurements can also be directly linked into statistical processcontrol (SPC) methods to improve product quality, reducewastage, improve productivity and streamline the process.

The speed and accuracy of current industrial vision systemsmeans that in many applications 100% inspection can be carriedout, and each and every product or component can bemeasured. By feeding these data into the SPC system, not only

can trends be identified earlier, but random and sudden defectscan also be identified, which is not possible using more traditionalsampling methods for SPC data acquisition. The challenge forusing industrial vision in micro manufacturing is being able tomake measurements at the required scale in a production lineenvironment. As with any measurement system, the key factors ofaccuracy, precision and repeatability are of vital importance inmachine vision systems.

Accuracy is an indication of how close the actual measurement isto true value. Precision is the number of digits to which themeasurement can be read. Repeatability shows the closeness ofa number of repeated measurements. This is illustrated in Figure1, where it can be seen that a group of measurements could havepoor accuracy and poor repeatability, or good repeatability but

INDUSTRIAL VISION AND MICRO MANUFACTURING

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MAIN IMAGE: Figure 4. Effects on an image of varying the angle of incidentillumination, courtesy of STEMMER IMAGING.

Don Braggins, UK Industrial Vision Association

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poor accuracy, or good accuracy butpoor repeatability, as well as thedesired combination of goodaccuracy and good repeatability.Precision is generally limited by therepeatability and accuracycharacteristics.

Factors affecting accuracy andrepeatability in machine visionA number of factors affect accuracyand repeatability in machine visionsystems, including the camera, optics,illumination, object positioning andmeasurement algorithms.Fundamental imaging parameters arefield of view, working distance,resolution, depth of field and sensorsize (Figure 2). Measurements areonly as good as the information thatcan be extracted from the image, andimage quality is dependent onresolution, contrast, depth of field,perspective and distortion. Resolutionis the amount of object detailreproduced by the imaging systemand contrast is the difference betweenthe object and background greyscalevalues. Machine vision measuringsystems specify accuracy andrepeatability in terms of physical units,such as microns, provided that theimage field-of-view (the dimensions ofthe area seen by the camera) and thenumber of elements in the camera’simage sensor are known and fixed.This calibration procedure defines themeasurement dimension for eachindividual pixel in the camera sensorand is dependent not only on thenumber of pixels in the sensor, but onthe quality of the lens used as well.

For micro manufacturing applications,even with optimised lens/sensorcombinations, the measurementdimension of the individual pixel may

still be too large for the measurementsrequired, however, measurementalgorithms which use interpolation andfitting techniques to allowmeasurements to be made to afraction of a pixel can be used toimprove the measurement range.There is a wide choice of sensorresolutions available allowing the mostappropriate choice for the dimensionsbeing measured, however the lensesused in the optical system are also ofcritical importance. A perfect lenswould fully reproduce an image froman object with absolutely nodegradation. However sharpness,contrast, illumination, spectraltransmission and distortion all affectthe ability of a lens to reproduce animage. A lens can only resolve somuch detail in terms of spatialfrequency — the finer the image detailpassing through the lens, the harder itis for the lens to reproduce a goodimage; the image becomes lessdistinguishable.

Another consideration is theperformance of the lens across theentire field of view. For some lenses,the resolution capability deterioratesthe further away from the centre axis,which is an important consideration ifthe resolution is required across theentire image or alternatively meansthat the object must be accuratelypositioned in the centre of the field ofview. Depending on the size of theobject and the distance to thecamera, there may also be issues withdepth of field or off-axis distortion.

Telecentric imagingA telecentric lens is a compound lensused in machine vision systems toeliminate dimensional and geometricvariations of images within a range of

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Figure 1. Measurement accuracy and repeatability,courtesy of STEMMER IMAGING.

Figure 2. Fundamental Imaging parameters, courtesy of National Instruments.

Figure 3. Telecentric imaging, courtesy of STEMMER IMAGING.

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different distances from the lens and across the whole field ofview, by collimating the light entering the lens. Telecentric lenseshave the same magnification at all distances. An object-spacetelecentric lens creates images of the same size for objects at anydistance and has constant angle of view across the entire field ofview. An object that is too close or too far from the lens may stillbe out of focus, but the resulting blurred image will be the samesize as the correctly-focused image would be.

This makes them ideal for metrology applications, especially inthe automotive and electronics industries, for high accuracymeasurement of parts with complicated three-dimensionalshapes. Figure 3 shows an image of a thick drilled block using aconventional lens and telecentric lens. The conventional lensshows the walls of the holes, making measurement of thediameters difficult. With the telecentric lens, the walls are not seenand the diameters can readily be measured.

Off-axis imagingIn many applications it is not possible to position the imagingsystem so that it is mounted perpendicular to the object beingmeasured. If the imaging system has to be mounted off-axis, thendistortion and foreshortening effects can result and these must becorrected in order to ensure accurate measurements.

IlluminationMachine vision illumination controls how the object appears to thecamera. Adequate illumination can often make the differencebetween a system that works reliably and one that does not. Afterall, if the appropriate image is not presented to the camera formeasurement, considerations of accuracy and repeatabilitybecome largely irrelevant. At the most basic level, there must be‘enough’ light so that the camera can acquire a good image.Beyond this, it is almost always necessary to use the orientation,

geometry or colour of light to highlight relevant details or minimisethe appearance of unhelpful parts of the image, such as glare.

Probably the most important factor that governs how the imageappears is the angle at which the light falls on the object (Figure4). For example, light approaching an object from a low angle willtend to create highlights on raised edges. Choosing theappropriate wavelength of illumination can play a major role inrevealing or masking specific features on the object, while the‘quality’ of the light describes whether the light is diffuse or not.Lighting control is also important. For example, the light can bestrobed or pulsed, the intensity can be raised or lowered or, in amore complex set-up, different lighting scenarios can bepreprogrammed using a lighting controller.

SpeedAnother important factor to be considered is that of speed. Onceall of the dimensional measurement criteria have been met, thesystem needs to be able to make the measurements at theappropriate speed for the production line. In addition to the abilityto acquire and process the images at the appropriate rate, it alsomeans that the imaging system needs to be interfaced into theproduction line, with camera triggers linked into product deliverysystem, and if necessary into a reject mechanism to allow ‘out ofspec’ components to be removed.

Real world measurementsThree practical examples of the use of industrial vision systems inmicro manufacturing applications are illustrated here. The first isthe use of a vision system in the manufacture of solar cells.ECKELMANN AG, located in Wiesbaden, Germany, hasdeveloped a vision system based on line scan cameras for laseredge detection as part of the edge isolation process in solar cellmanufacture (Figure 5). It was designed for the ASYS Group

Figure 5. Inspection of solar cellmanufacture, courtesy ofSTEMMER IMAGING.

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(Dornstadt, Germany), a leading manufacturer of handlingsystems, process machines and special machines for theelectronic and solar industries, and is fully integrated to providefeedback control to the production process. Edge isolationprovides electrical separation between the active front side of asolar cell and the rear side. A laser cuts a small groove along thecell edges, the depth of the groove depending on the cell doping.The difficulty lies in positioning the groove as close as possible tothe outer contour of the cell in order to maximise the activesurface and thus the efficiency. The edge isolation control systemfeatures a line scan camera with 4096 pixels, optics andcustomised LED illumination supplied by STEMMER IMAGING.

The image processing system measures the outer contours of thecell and feeds them back to the control system of the laserequipped with a deflection mirror to provide an active feedbacksystem. If the edge damage is within tolerance levels the laser willignore it and proceed with the cutting process. Image acquisitionand analysis take place in just 800 ms and the resolution of thesystem makes it possible to ensure that the distance to the edgeduring laser cutting is below 100 µm. The calibration andqualification of the laser and camera have been automated so thesystem can easily be commissioned or recalibrated aftermaintenance work.

The second application uses vision to help with handlingcomponents in the micro assembly and testing industry. Sincethese components are tiny, almost weightless, and highlysensitive to electrostatic charge, inspecting and sorting themready for assembly can be a painstaking task. Vision has beenincorporated into a system that combines the functions offeeding, orientation and inspection of parts. IMS (Almelo, TheNetherlands) develops and builds high-tech productionequipment for the high-precision, electronics and medicalindustry. Working together with the University of Twente(Enschede, The Netherlands) and Bosch Rexroth (Lorh am Main,Germany), they developed the Vision Inspection Feeding System

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(ProVIS), a multi-purpose, modular system for the supply andrecognition, inspection, handling and placing of parts.Recognition and inspection, ProVIS (Figure 6) uses two separatecameras, one for recognition, and another for inspection.

The Matrox Imaging Library software development kit performs allthe product recognition and inspection tasks. To use the system,a technician calibrates the ProVIS with a part that is withintolerance to create what’s known as the Golden Template. Thenthe camera takes pictures of the parts on the inspection stage.Finally, specific processing modules analyse the parts. First theGeometric Model Finder (GMF) module locates the parts in theimage, so the Metrology module can measure the features ofeach part. The results, both good and bad parts, are displayed onthe monitor. Parts that pass inspection can be used for assembly;parts that cannot be recognised are most likely lying on theirsides or too close to another part, so they are re-fed into thesystem by a vibratory tray. If the inspection shows a part to be outof tolerance, the system tags it; if the system is feeding parts forassembly, the non-conforming parts will be kept out of theassembly step.

The system can also be programmed to find surface defects. TheMetrology module figures prominently in the solution, and is usedfor finding dimensions and checking tolerances, complexoperations that are processing-intensive. With the appropriateoptical system the measurement results are accurate to +/- 0.01 mm. Without appropriate lighting, the camera is unableto produce usable images.

The ProVIS features a dome with blue light above the tray wherethe products are fed to the system. The inspection of the parts’dimensions, the fundamental task of the system, is backlit. Theright combination of illumination and zoom lenses provides theaccuracy needed for such tiny parts. As with most assemblyapplications time is important, and all the visual inspections anddata processing has to be completed within the allowed cycle

Figure 6. ProVIS inspection system, courtesy of Matrox Imaging.

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time, typically 1 to 5 seconds, depending onthe complexity of the inspection operation.

The final application also makes use ofanother machine vision capability — that ofoptical character recognition to ensure that thecorrect batch number is marked on a product.At Micro Crystal in Switzerland, a smartcamera from Cognex is used to inspect thepackaging of ceramic surface-mounteddevices (SMDs) which contain the quartzoscillator used in watches and mobile phones.A smart camera is one in which the imageprocessing is carried out within the cameraitself, rather than transferring the image to aPC for processing.

These SMDs are sold on rolls of polyester tapein quantities up to 16,000. SMD packages canbe as small as 2 x 1.2 mm. The company hasbeen using an Optical Tape End-Controller onthis production line. Similar to a film-cuttingtable, the roll of uninspected SMD tape isguided over a worktable where the smartcamera performs an automatic opticalinspection (Figure 7).

The inspection process checks the followingcriteria:

• That there is an SMD in the package.• That the position of the SMD is correct.• That the batch number is present on the

ceramic housing of the SMD and that it can be read perfectly.

The image processing is achieved usingpattern-matching technology which locatesobjects reliably even if they are of differentsizes, differently aligned, if their appearance ispoor or even if they are partly covered. Byanalysing the geometrical information, it is ableto determine the position of the object clearly.LED lighting is used to give the optimumillumination to ensure reliable detection of thelaser marked batch numbers, even thoughthey are not always sharply contoured.

According to the packaging specifications ofMicro Crystal, the gold contact surfaces of theceramic housing must always be on the sidefacing away from the camera, and so theyshould be invisible to the vision system. If thesmart camera detects fluctuations inbrightness triggered by the gold areas on thegrey ceramic surface, the Optical Tape End-Controller sounds the alarm. The faulty sectionis then moved to a pre-determined processingpoint and removed by hand.

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About the UKIVAThe UKIVA is a SpecialInterest Group of the PPMA(Processing & PackagingMachinery Association), andits prime objective ispromoting the use of visionby manufacturing industry.The Association’s membersare involved in the supply ofvision systems andcomponents for use in awide range of industrialimaging applications. Thanks are due to UKIVAmembers Cognex UK(www.cognex.co.uk), MatroxImaging (www.matrox.com),National Instruments(www.ni.com) andSTEMMER IMAGING(www.stemmer-imaging.co.uk) for theircontributions to this article.www.ukiva.org

Figure 7.Inspection of SMDs, courtesy of Cognex UK.

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