Computer Aided Inspection

( 1 ) Introduction Inspection or testing is an act of checking materials, parts, components or products at various stages of manufacturing detecting poor quality manufactured products for taking corrective action. Inspection is performed before, during and after manufacturing to ensure that the quality of the product is consistent with the accepted design standard. The design standards are defined by the product designer, and for mechanical components they relate to factors such as dimension, surface finish and appearance. The objective of any inspection process is either to take actual measurements of the values of the specified product characteristics or to check whether specific characteristics meet design standards. When inspection and testing is carried out manually, the sample size is often small compared to size of the population. In high production runs, this size may be very small which may result in slipping of defective parts. In principle, the only way to achieve 100% good quality is to use 100% inspection using which only good quality parts will pass through the inspection procedure. But when this is done manually, the problem of expenses involved and error associated with the procedure is of major concern. Automation of inspection offers an opportunity to overcome these problems. Automated inspection

procedures are carried out by sensors that are controlled by computers.

( 2 ) Computer Aided Inspection Computer Aided Inspection (CAI) is a new technology that enables one to develop a comparison of a physical part to a 3D CAD model. This process is faster, more complete, and more accurate than using a Coordinate Measuring Machine (CMM) or other more traditional methods. An automatic inspection method and apparatus using structured light and machine vision camera is used to inspect an object in conjunction with the geometric model of the object. Camera images of the object are analyzed by computer to produce the location of points on the object's surfaces in three dimensions. Point-cloud data is taken from a laser scanner or other 3-D scanning device. During a setup phase before object inspection, the points are analyzed with respect to the geometric model of the object. The software provides a graphical comparison of the manufactured part compared to the CAD model. Many points are eliminated to reduce data-taking and analysis time to a minimum and prevent extraneous reflections from producing errors. When similar objects are subsequently inspected, points from each surface of interest are spatially averaged to give high accuracy measurements of object dimensions. The inspection device uses several multiplexed sensors, each composed of a camera and a structured light source, to measure all sides of the object in a single pass. Computers are used in many ways in inspection planning and execution also.

( 2.1 ) Computer controlled inspection equipment Coordinate Measuring Machine (CMM) is a 3-dimensional measuring device that uses a contact probe to detect the surface of the object. The

probe is generally a highly sensitive pressure sensing device that is triggered by any contact with a surface. The linear distances moved along the 3 axes are recorded, thus providing the x, y and z coordinates of the point. CMMs are classified as either vertical or horizontal, according to the orientation of the probe with respect to the measuring table.

Figure 36.1 Coordinate Measuring Machine (CMM)

( 2.2 ) Computer aided inspection setup planning Computer-Aided Inspection Planning (CAIP) is the integration bridge

between CAD/CAM and Computer Aided Inspection (CAI). A CAIP system for On-Machine Measurement (OMM) is proposed to inspect the complicated mechanical parts efficiently during machining or after machining. The inspection planning consists of Global Inspection Planning (GIP) and Local Inspection Planning (LIP). In the GIP, the system creates the optimal inspection sequence of features in a given part by analyzing the various feature information. Feature groups are formed for effective planning, and special feature groups are determined for sequencing. The integrated process and inspection plan is generated based on the series of heuristic rules developed. The integrated inspection planning is able to determine optimum manufacturing sequence for inspection and machining processes. Finally, the results are simulated and analyzed to verify the effectiveness of the proposed CAIP.

( 2.3 ) Computational metrology Computational metrology deals with fitting and filtering discrete geometric data that are obtained by measurements made on the parts. Some basic facts about manufacturing and measurement are best captured using following two axioms. • Axiom of manufacturing imprecision: All manufacturing processes are inherently imprecise and produce parts that vary. • Axiom of measurement uncertainty: No measurement can be absolutely accurate and with every measurement there is some finite uncertainty about the measured attribute or measured value. Fitting:- Fitting is the task of associating ideal geometric forms to nonideal forms (such as, for example, discrete set of points sampled on a manufactured surface). Normally, Fitting is done for the following reasons: • Datum establishment: Datum is a reference geometric object of ideal form established on one or more non-ideal geometric forms of a manufactured part. Datums are used for relative positioning of geometric objects in parts and assemblies of parts. • Deviation assessment: It is often important to determine how far

a manufactured surface deviates from its intended ideal geometric form which can be quantified by fitting. Fitting problems are broadly divided into two categories on the basis of the objective function which is to be optimized. First one is Least squares fitting, which has the objective to find an ideal geometric object (a smooth curve or surface) to minimize the sum of squared deviations of data points from desired object. Second on is Chebyshev fitting, which has the objective to minimize the maximum deviation. Filtering - Filtering is the task of obtaining scale-dependent information from measured data. At a more mundane level, filtering can be used to remove noise and other unwanted information from the measured data. In the context of engineering metrology, engineers are interested in use of filtering mainly for the two applications. • Surface roughness: Many engineering functions depend on roughness or smoothness of a surface on the piece. Designers define bounds on certain roughness parameters to ensure functionality of parts. These small-scale variations are subtracted from the surface measurement data before form and other deviations are assessed. • Manufacturing process diagnosis: Manufacturing processes leave tool marks on surfaces. By measuring surfaces at fine scale, it is possible to detect tool erosion and its effect on the surface quality.

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The computational scheme used for filtering is one of convolution. Two types of convolutions are in use; Convolution of functions: Filtering is often implemented as discrete convolution of functions. In the most popular version, the measured data is convolved with the Gaussian function. It has a smoothing effect on the surface data. Convolution of sets: Morphological filters are implemented using Minkowski sums. These can be regarded as convolutions where the input set is convolved with a circular or flat structuring

element.

( 2.4 ) Computer aided part localization and Shape Matching Many a times in inspection process comparison of shapes of two geometric entities is done. Shape matching can be used for comparison of shapes of two geometric entities. For example comparison of shapes between designed model and molded part. Shape localization is done with the help of transformations. Transformations can be translation and rotations. Shape matching can be broadly classified as • Curve-Curve Matching • Surface-Surface Matching • Solid-Solid Matching • Matching curve, surface or solid with point data set

Figure 36.2: Shape Localization and matching of two curves

Shape matching is used for many applications like character recognition, object recognition, medical imaging, etc. The same concept can be extended in the inspection of mechanical parts. In shape matching, the manufactured part is located with respect to designed part and error is measured. In character reorganization, characters are fitted with smooth curves and then matched with predefined templates.

Figure 36.3: Shape matching

( 3 ) Benefits of CAI • The CAI process saves both time and money. • The computer software processes data from a 3-D point cloud from a laser scanner, eliminating the need for slower and more time-consuming CMM measurements. • Inspecting with CMMs requires that designers create a 2-D drawing in addition to the 3-D CAD model of a part. The drawing is used to inspect the part at specific locations to verify that it matches the design. Point-cloud data is taken from a laser scanner or other 3-D scanning device. The software provides a graphical comparison of the manufactured part compared to the CAD model. • By producing point clouds of the entire part, measurement of the part can be done everywhere and not be limited to the specific locations on a drawing.