Geometric dimensioning, tolerancing and inspection

In this paper, a framework based on Augmented Reality (AR) and a mobile device is proposed for monitoring mechanical components during fatigue tests. This solution enables the user to move around and to inspect the component through AR from different points of view. In addition, the framework proposes a solution to estimate in real time the crack growth and to visualize it directly onto the component. A user application is developed according to the proposed framework and it is used for case studies of fatigue test for adhesively bonded joints.

Product lifecycle management (PLM) is increasingly important for organizations acting in dynamic and competitive markets since PLM can improve decision-making and reduce costs by taking advantage of the efficiencies and effectiveness coming from improved market intelligence and collaboration of partners. In the last years, academics as well as practitioners and consultants have developed a wide range of maturity models for the purpose of measuring and describing certain aspects of PLM "maturity". The PLM maturity models permit to assess the relative position of companies on their road to complete PLM implementation. However, it is a tough job for the company to select the most appropriate PLM maturity model, as each maturity model has different attributes. Since, to our knowledge, no benchmarking for PLM maturity models exists to date, the rising number of maturity models implicates problems with respect to retrievability and reusability. With the aim to enhance the time consuming and exhausting search and selection process of appropriate assessment models, a benchmarking framework for PLM maturity models is presented in this paper. © 2013 Springer-Verlag London.

Keywords: Capability maturity model (CMM) , Maturity models , Product lifecycle management (PLM)

In the last few years the need for methodologies capable of performing an automated geometric inspection has increased. These methodologies often use 3D high-resolution optical digitisers to acquire points from the surface of the object to be inspected. It is expected that, in the near future, geometric inspection will be requiring more and more the use of these instruments. At present geometric inspection is not profiting from all the opportunities attainable by 3D high-resolution optical scanners or from the numerous tools which can be used for processing the point cloud acquired from the inspected product. For some years now, these authors have been working on a new methodology for automatic tolerance inspection working from a 3D model acquired by optical digitisers. In this paper all the information recognisable in a scanned object is organised into a new data structure, called Recognised Geometric Model (RGM). The final aim is to define a representation of the inspected object for the automatic evaluation of the non-idealities pertaining to the form, orientation and location of the non-ideal features of the acquired object. The key concept of the proposed approach is the capability to recognise some intrinsic nominal properties of the acquired model. These properties are assumed as references to evaluate the non-idealities of the inspected object. With this approach the references of geometric inspection are searched for in the inspected object independently of a tolerance specification and of the availability of a 3D nominal representation. The high-level geometric information within RGM depends on the rules used for its identification. The capability to recognise specific categories of nominal references offers the possibility of introducing new tolerances to be specified. The proposed approach has been implemented in original software by means of which a specific test case has been analysed. © 2012 Springer-Verlag France.

Keywords: Automated inspection , ISO tolerancing , Three-dimensional metrology

The present paper proposes a novel general approach to automatically calculate the variational parameters for planar or cylindrical features for a given set of tolerance specifications, according to ANSI or ISO Standards. Variational parameters correspond to those directions along/around which variation, in terms of small translation and rotation, may propagate for a given feature with tolerance specifications. A graph representation of these tolerance specifications is adopted and it is used along with screw theory and Davies's laws to automatically calculate the variational parameters, and then the net variational space of each toleranced feature, by capturing nominal geometries directly from a CAD environment (SolidWorks). From screw theory, twist matrices, able to capture the motion properties of any kinematic joint in mechanical assemblies, are here adopted at part level and collected for every feature-to-datum relationship. Davies's laws are then recalled to put those matrices together to calculate the variational parameters. In this way, both single-datum and multi-datum tolerance specifications can be handled. The proposed approach for the automatic calculation of variational parameters could be successfully implemented in a more general expert system for designing mechanical assemblies where an added-value interaction could allow user to detect relationships between geometric features. In this way, the leading of activities aimed to tolerance analysis could be accomplished both during the preliminary design stages and throughout the manufacturing and reviewing sessions. © 2012 Springer-Verlag France.

Keywords: CAD automation , Graph representation , Mechanical networks , Screw theory , Tolerance analysis , Variational parameters

In the variational modeling of assemblies it is important to define the location of a part both in absolute terms and with respect to the position/orientation of other assembled parts. The present paper proposes a programming optimization approach to solve this problem. The algorithm, by using the heuristic Nelder-Mead technique - combined with a penalty function - simulates and solves sequential assembly strategies to find the optimal geometric configuration of a rigid part with variational features satisfying all the assembly constraints in the given sequence. The algorithm best aligns mating features avoiding, at the same time, feature-to-feature interferences, and automatically calculating the amount of movement the part being assembled must obey to satisfy assembly constraints, at that state of the assembly process. Thus, different assembly sequences can be simulated also including variational features. © 2013 The Authors.

Keywords: Assembly simulation , Constrained optimization , Rigid assemblies , Sequential constraint solver , Tolerance analysis

In this paper a procedure based on a statistical approach to manufacturing for the analysis of tolerance chains is reported. In particular, the proposed approach can be summarised into two main steps. First, each single technological operation (for example, the drilling of a hole) is simulated by extracting, from a statistical distribution typical of the machine tool, the parameters characteristic of the manufacturing procedure. Then, a simulation is performed, to verify if the real features of the part can simultaneously fit the virtual gage. This method of acceptance/rejection of a part is according to the ISO/ASME standards and is representative of the real functional requirements of the part. © (2013) Trans Tech Publications, Switzerland.

Keywords: Manufacturing , Statistical , Tolerancing

We present an overview of methods and applications of automatic characterization of the appearance of materials through colour and texture analysis. We propose a taxonomy based on three classes of methods (spectral, spatial, and hybrid) and discuss their general advantages and disadvantages. For each class we present a set of methods that are computationally cheap and easy to implement and that was proved to be reliable in many applications. We put these methods in the context of typical industrial environments and provide examples of their application in the following tasks: surface grading, surface inspection, and content-based image retrieval. We emphasize the potential benefits that would come from a wide implementation of these methods, such as better product quality, new services, and higher customer satisfaction. © 2013 Elena González et al.

Automatic detection and assessment of dirt particles in pulp and paper plays a pivotal role in the papermaking industry. Traditional visual inspection by human operators is giving the way to machine vision, which provides many potential advantages in terms of speed, accuracy and repeatability. Such systems make use of image processing algorithms which aim at separating paper and pulp impurities from the background. The most common approach is based on image thresholding, which consists of determining a set of intensity values that split an image into one or more classes, each representing either the background (i.e.: An area with no defects) or an area with some types of contraries. In this paper we present a quantitative experimental evaluation of four image thresholding methods (i.e.: Otsu's, Kapur's, Kittler's and Yen's) for dirt analysis in paper. The results show that Kittler's method is the most stable and reliable for this task. © 2013 DIME UNIVERSITÀ DI GENOVA.

Keywords: Image thresholding , Machine vision , Paper , Quality assessment

In this paper we consider the problem of colour-based sorting hardwood parquet slabs into lots of similar visual appearance. As a basis for the development of an expert system to perform this task, we experimentally investigate and compare the performance of various colour descriptors (i.e.: soft descriptors, percentiles, marginal histograms and 3D histogram), and colour spaces (i.e.: RGB, HSV and CIE Lab). The results show that simple and compact colour descriptors, such as the mean of each colour channel, are as accurate as more complicated features. Likewise, we found no statistically significant difference in the accuracy attainable through the colour spaces considered in the paper. Our experiments also show that most methods are fast enough for real-time processing. The results suggest the use of simple statistical descriptors along with RGB data as the best practice to approach the problem. © 2012 Elsevier Ltd. All rights reserved.

Keywords: Colour descriptors , Grading , Parquet , Sorting , Wood

In mechanical design, geometrical specifications and dimensional tolerances are commonly used to avoid final product malfunction and to allow for assembly integration. Geometric specification usage, in particular, has many manufacturing and durability implications, the feasibility of their measurement and verification, however, is often neglected and the influence of measurement uncertainty in their evaluation underestimated. Often geometrical specifications are defined without considering measurement uncertainties, or measurability at all: it is not uncommon to find approved specifications prescribing unverifiable geometry, or dimension tolerances that exceed state-of-art measurements. This article explores the case study of orthogonality between a circular hole and the plane on which it is drilled, evaluated using a Coordinate Measuring Machine. Such specification is defined, according to ISO 14253, as the angle between the plane normal and cylinder axis. Uncertainty of points coordinates obtained can, however small, play a key role in the final evaluation of orthogonality: if the specified tolerance is thigh enough it is also possible to have misalignment uncertainty higher than the tolerance itself. The authors propose the results of a mathematical and numerical model, meant to help the designer to define specification to assess the relationship between cylinder-plane misalignment measurability, CMM uncertainty and features dimensions. © 2013 EDP Sciences.

Keywords: Geometric specification , Measurability , Orthogonality , Tolerances verification , Uncertainty

The increasing integration between electronics and mechanical engineering brings to the industrial market very hi-tech sensors, often non-linear, capable of more than a single input and single output. A problem more and more relevant for sensors like these is calibration. Classic linear calibration procedures, when applied to this extremely engineered sensors, lead to poor accuracy and are generally not satisfactory. The case study is the calibration of a bi-dimensional laser based position sensor, in particular a positive sensitive detector, that is an optical position transducer based on series of photodiodes commonly used as multidimensional sensor. To perform the calibration a micrometric positioning table was used to test the whole photodiode active area in both directions. The sensor studied showed a very linear behaviour in the central region of the working range, and a limited nonlinearity closer to the range limits and was to be used to verify robot movement capabilities; to reduce uncertainty associated with nonlinearities, a set of nonstandard, non-linear, calibrations were performed, pointing out residual values in order to compare different algorithms. In a previous work, authors have already tested a linear model against an algorithm based on radial basis functions (RBF) and Nelder-Mead simplex method. Object of this paper is the definition of a procedure based on RBF and genetic algorithms for multi-dimensional interpolation of data cloud and a comparison between this updated procedure results and the ones of the previous studied algorithms. The reference model for calibration was a black box with two inputs, X and Y position of the laser spot, and two outputs, voltages Vx and Vy, while the calibration procedure was split in two separate layers, one for each output depending on both inputs. Given N data points in a M-dimensional environment and N values that represent the non linearity residual, purpose of the algorithm is to approximate a data cloud with a real function, that is represented as a sum of a polynomial (linear) part and L radial basis functions, each associated with a different center (node) and weighted by an appropriate coefficient, that the procedure also allow to assess. When no starting guess for nodes are given in input. nodes coordinates are the output of a non-linear optimizer based on a genetic algorithm, whose goal is to locally minimize the objective function. The algorithm stops itself whenever it reaches a certain tolerance level, a user- specified number of nodes or when the previous iteration has a better value of the objective function. This study has been performed for various RBF classes, and shows an increased accuracy, thus a better metrological behaviour, with respect to the standard linear (planar) calibration model traditionally used.

Keywords: Calibration , Genetic algorithm , Multi input , Radial basis function , Uncertainty

In order to avoid final product malfunction and to allow for assembly integration, geometric specifications and dimensional tolerances are commonly used in mechanical design. However the feasibility of geometric specification measurement and verification is often neglected and the influence of measurement uncertainty in geometric tolerances evaluation underestimated. The authors propose updated results of a mathematical and numerical model, based on Monte Carlo simulations, developed in order to define a measurability threshold of geometric tolerances in relation to measurement uncertainty and geometric parameters, such as feature dimensions, meant to help the designer to define measurable geometric specifications. Starting from EN ISO 14253-2:2011 and EN ISO 14253- 3:2011 standards, a perpendicularity tolerance between a cylindrical feature and a planar one has been simulated. A mathematical model has been defined for each feature, in order to assess both misalignment and its uncertainty when starting from the estimate of geometric entities obtained from point coordinates measured by a Coordinate Measurement Machine (CMM). Monte Carlo Analysis of these simulation underlined how geometric parameters, such as dimensions of the features involved, can act as magnifiers for measurement uncertainty when verifying a geometric specification: there could be cases where this magnification effect could lead to non-measurability of misalignment and non-verifiability of the geometrical specification requested.

Keywords: Dimensional parameters , Geometric tolerances , Measurability threshold , Measurement uncertainty

In several manufacturing processes, the cutting of 2D parts from sheets is an important task. The arrangement of the parts in the sheets, supported by computers, is called nesting and is addressed to minimize the wasted material. In literature some approaches are proposed, based on genetic or heuristic algorithms which emphasize different characteristics, e. g. the time complexity or the wasted material. In shipbuilding the parts to be arranged have significantly different sizes, which are often difficult to pack in a fast way using the standard methods in literature. In this work an approach is proposed, able to arrange parts with very different dimensions, which is based on the identification of a suitable starting rotation that ensures a solution in a reasonable time. The main steps are: A) importation of the model files of the parts to be packed, b) identification of a preliminary orientation and sorting of the parts (starting position), c) optimization of the position of the parts, ensuring a minimum distance between them. For the starting rotation, three different orientations are considered: i) the original orientation, ii) the x axis coincident with the minimum inertia axis, iii) the x axis aligned with the maximum edge. The orientation is selected in order to obtain the minimum area of the bounding box. The implementaiton of the method has been investigated and the results show the advantages of the approach: reduction of waste material and time for performing the nesting. © Springer-Verlag London 2013.

Keywords: CAD/CAM , CAPP , Cutting-stock , Nesting , Packing , Shipbuilding

Purpose: The purpose of this study was to investigate the marginal precision of computer numeric control- milled frameworks fabricated of grade 4 commercially pure titanium or cobalt-chrome alloy through digital technology and to compare them with conventional cast frameworks. Material and Methods: A titanium cast of a mandibular arch with six implant analogs was used as a master. The master cast was measured with a coordinate measuring machine. Fifteen rigid anatomic frameworks were created on the master cast in cast gold alloy and milled in titanium or cobalt-chrome material. The fifteen anatomic frameworks were measured in the same manner as the master cast. While the milled frameworks were measured once, at the end of the milling process, the cast anatomic frameworks were measured twice: immediately after the casting and divesting procedures and again after a technical adaptation procedure. Each anatomic framework was weighed. To compare the measurements obtained from each group of frameworks, descriptive statistics were calculated and one-way analysis of variance was performed, with values considered statistically significant at P < .05. Results: The mean weight of the cast frameworks was 33.41 g, the cobalt-chrome frameworks weighed 18.12 g on average, and the titanium frameworks averaged 8.7 g. The mean values for three-dimensional deviation of the center point position for each group of frameworks were 261 µm (cast frameworks before adaptation), 49 µm (cast frameworks after adaptation), 26 µm (milled frameworks in cobalt-chrome), and 26 µm (milled frameworks in titanium). Conclusions: Within the limitations of this in vitro study, absolute passive fit cannot be achieved, regardless of material and fabrication technique. Anatomic milled frameworks fabricated in titanium or cobalt-chrome presented reduced center point deviation compared to cast frameworks. Titanium frameworks weighed less than cobalt-chrome and cast gold alloy frameworks. © 2013 by Quintessence Publishing Co Inc.

Keywords: Cobalt-chrome , Computer-aided design/computer-assisted manufacture , Dental implant , Edentulous jaw , Passive fit , Prosthesis framework , Titanium

Muon tomography has been recently proposed by a Los Alamos research group [1]. Some proponents of this abstract built and operated the first large volume prototype of muon tomography [2] and based on the results obtained participated to a request for European funding, that was granted in the Mu-Steel project [3]. The project started in July 2010 and finished at the end of 2012. The final goal of the project was the design of an inspection portal able to detect, using the cosmic rays, shielded radioactive sources hidden in scrap metal containers. Indeed in the last years it happened that such radioactive sources could pass undetected the entrance controls and, once melted, caused enormous damages to the steel mills, contaminating all the production line. The project studied and built a prototype for the muon detectors to be used in the portal, designed the structure and the configuration of the inspection portal and developed the needed tomographic reconstruction software. The results of the project will be presented and discussed. © 2013 IEEE.

Keywords: Cosmic rays , muons , radioactive sources , steel mills , tomography

In a previous paper (Di Angelo, L., Di Stefano, P. and Morabito, A., 2011. Automatic evaluation of form errors in high-density acquired surfaces. International Journal of Production Research, 49 (7), 2061-2082) we proposed an original methodology for the automation of the geometric inspection, starting from an acquired high-density surface. That approach performed a recognition process on the acquired data aiming at the identification of some intrinsic nominal references. An intrinsic nominal reference was detected when a geometric property was recognised to be common to a set of adjacent points in the 3D data set representing the acquired object. The recognition of these properties was carried out based on some rules. Starting from these concepts, a new specification language was defined, which is based on recognisable geometric entities. This paper expands the category of intrinsic nominal references to include new mutual intrinsic orientation, location and dimensional properties pertaining to 3D features. This approach involves the automatic construction of a geometric reference model for a scanned workpiece, called recognised geometric model (RGM). The domain of the representable entities within the RGM strictly depends on the rules used for the recognition of the intrinsic properties. In particular, this paper focuses on the rules for the recognition of the orientation and location properties between non-ideal features. When using the RGM, tolerances are specified according to the set of available and recognisable intrinsic nominal references. Based on the geometric product specification, the RGM data structure can be queried to capture some quantitative information concerning special intrinsic geometric parameters and/or non-idealities. © 2012 Copyright Taylor and Francis Group, LLC.

Keywords: automated inspection , ISO tolerancing , shape recognition , three dimensional metrology , triangular meshes

The detection of surface defects during periodic inspection is important because, usually, the stresses are higher at the surface, thus affecting the growth of the discontinuity. Surface defects can be detected using some traditional non-destructive testing methods, such as eddy current, dye penetrant, magnetic particle and ultrasonic. Some of these methods can be used only in static conditions; the others have limitations for the dynamic inspection. The recent progress in the field of non-contact ultrasonic sensors has led us to develop a simple system for the real-time inspection of moving bodies at a high speed. The paper presents the possibility of using, with the developed system, two methodologies, based on non-contact ultrasound, to detect surface defects on objects moving at 100 km/h, so that in service inspection is possible. A methodology, based on laser and air-coupled sensors, uses the advantages of laser-generated surface waves; the analysis is done on the reflected wave, created by the interaction of the surface wave with the defect. The inspected surface layer can be selected from the wavelength of the surface wave. The other methodology, based on air-coupled sensors, uses the disadvantages of the ultrasound transmission at the air/metal interface; the analysis is done on the diffraction of the wave reflected from the surface. The execution of the inspection is simple with both techniques. The experimental results indicate a good efficiency of the two methodologies proposed for the real-time detection of surface defects on objects moving at high speed.

This paper is about the development of an expert system for automatic classification of granite tiles through computer vision. We discuss issues and possible solutions related to image acquisition, robustness against noise factors, extraction of visual features and classification, with particular focus on the last two. In the experiments we compare the performance of different visual features and classifiers over a set of 12 granite classes. The results show that classification based on colour and texture is highly effective and outperforms previous methods based on textural features alone. As for the classifiers, Support Vector Machines show to be superior to the others, provided that the governing parameters are tuned properly. © 2012 Elsevier Ltd. All rights reserved.

Keywords: Classification , Colour , Grading , Granite , Texture

This article proposes a mathematical approach for the definition of a multiple input calibration diagram, based on a two step sequence, iteratively defining a set of radial basis functions and fitting its parameter to experimental data. Different radial basis functions have been evaluated and compared, focusing on Gaussian and multi-quadratic elements. The case studied used to test this method is the calibration of a bi-dimensional laser based position sensor believe that the method could be generalized and applicable to all transducers presenting multiple outputs, multiple inputs and localized non-linearities.

Keywords: Calibration , Multi input , Radial basis function , Uncertainty