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1988
In this paper, we will review some visual inspection problems that were presented to our laboratory by a con- sortium of Belgian industrial companies. These problems were selected to serve as a test vehicle for a software pack- age, called LILY (Leuven Image processing Library), that was developed for the consortium by our laboratory. There- fore, this paper consists of
1988
In this paper, we will review some visual inspection problems that were presented to our laboratory by a consortium of Belgian industrial companies. These problems were selected to serve as a test vehicle for a software package, called LILY (Leuven Image processing Library), that was developed for the consortium by our laboratory. Therefore, this paper consists of several parts : first, an overview of the LILY software package will be given; then, three case studies carried out with the package will be detailed. The case studies are very different in nature, so that a variety of algorithms will be dealt with. The first case study is about defect inspection in unexposed radiographic film. In this case, image data is presented as a continuous stream of lines of pixels. In the study, convolution techniques, curve fitting methods and Fourier analysis were applied. The second case studv treats the inspection of textured textiles and is thus essentially a texture inspection problem. Here,...
IEEE Transactions on Automation Science and Engineering, 2000
Ergonomics, 1973
This paper present optimal preventive maintenance strategy for efficient operation of boilers. Efficient operation of Boiler can be achieved from an optimal preventive maintenance strategy. It would be especially beneficial for those plants that rely on breakdown or run-to-failure maintenance. There are many advantages for having an optimal preventive maintenance strategy. The advantages apply to every kind and size of plant. The law of preventive maintenance strategy is that the higher the value of plant assets and equipment per square foot of plant, the greater will be the return on a preventive maintenance strategy.
Visual Inspection is the single most frequently-used aircraft inspection technique, but is still error-prone. This project follows previous reports on fluorescent penetrant inspection (FPI) and borescope inspection in deriving good practices to increase the reliability of NDI processes through generation of good practices based on analysis of the human role in the inspection system. Inspection in aviation is mainly visual, comprising 80% of all inspection by some estimates, and accounting for over 60% of AD notices in a 2000 study. It is usually more rapid than other NDI techniques, and has considerable flexibility. Although it is usually defined with reference to the eyes and visible spectrum, in fact Visual Inspection includes most other non-machine-enhanced methods, such as feel or even sound. It is perhaps best characterized as using the inspectors’ senses with only simple job aids such as magnifying loupes or mirrors. As such, Visual Inspection forms a vital part of many other NDI techniques where the inspector must visually assess an image of the area inspected, e.g. in FPI or radiography. An important characteristic of Visual Inspection is its flexibility, for example in being able to inspect at different intensities from walk-around to detailed inspection. From a variety of industries, including aviation, we know that when the reliability of visual inspection is measured, it is less than perfect. Visual inspectors, like other NDI inspectors, make errors of both missing a defect and calling a non-defect (misses and false alarms respectively).
Procedia CIRP, 2015
Visual inspection is a task regularly seen in manufacturing applications and is still primarily carried out by human operators. This study explored the use of job aids (anything used to assist the operator with the task, such as lists, check sheets or pictures) to assist with visual inspection within a manufacturing facility that inspects used parts. Job aids in the form of inspection manuals were used regularly during the inspection process, and how accurately they were followed was dependent on a number of factors such as size of part, experience of the operator, and accuracy of the inspection manuals. If the job aids were well structured, well written and accessible, then the inspectors were seen to follow them, however for certain jobs inspectors were seen to change the inspection order making inspection more efficient. The findings of the study suggest that prior experience can help in designing efficient, easy to use job aids and that a collaborative approach to design as well as using pictorial examples for comparison purposes would improve the inspection process.
In recent years, the opening of worldwide markets to many products has forced manufacturing companies to compete on a global basis. This high level of competition amongst manufacturers has led to rapid developments in the areas of computer integrated manufacturing, flexible manufacturing, agile manufacturing, and intelligent manufacturing. These developments have in turn generated a need for intelligent sensing and decision making systems capable of automatically performing many tasks traditionally executed by human beings. Visual inspection is one such task, and there is a need for effective automated visual inspection systems in today's competitive manufacturing environments. The following will discuss the advantages of implementing an intelligent visual inspection system based on natural human vision. Results from current models will also be presented,
Series in Machine Perception and Artificial Intelligence, 2000
Despite the obvious needs of applications, texture analysis is a rare method in automated visual inspection outside textile industry. Most textures in the real world are non-uniform, the inspection speed requirements extreme and very difficult to satisfy at a reasonable cost using textbook methods. Furthermore, the costs of retraining the systems tend to exceed any acceptable level. This paper gives a brief overview of the problem space of applying texture analysis for industrial inspection, presenting some solutions proposed and their prerequisites.
Computing Research Repository, 2008
This paper draws a proposal of a set of parameters and methods for accuracy evaluation of visual inspection systems. The case of a monochrome board is treated, but practically all conclusions and methods may be extended for colour acquisition. Basically, the proposed parameters are grouped in five sets as follows:Internal noise;Video ADC cuantisation parameters;Analogue processing section parameters;Dominant frequencies;Synchronisation (lock-in) accuracy. On basis of this set of parameters was developed a software environment, in conjunction with a test signal generator that allows the "test" images. The paper also presents conclusions of evaluation for two types of video acquisition boards
Mechanical Engineering Research, 2011
Industrial inspection is one of the crucial tasks to ensure quality conformance of products. The inspection tasks can be done by using several methods like non-scaled go/not go gauging, measuring instruments, or advanced non-touching tools. In this research visual inspection using a developed optical system is conducted. One of the aims of this research is to design an on line visual inspection system that is capable to test geometrical quality characteristics of 2-D machined products. The design process includes developing an economical optical system to acquire inspected product's images. Image processing tools are utilized to deal with the product image; and extract features of its geometrical characteristics. A neural network-based methodology is developed and applied to decide whether the product conforms to pre-specified tolerances. The results of the developed methodology are compared to some statistics based visual approaches from the literature. The results show the goodness of the system as an automated visual inspection system and prove its superior performance with respect to other methods.
SPIE Proceedings, 2003
A key problem in using automatic visual surface inspection in industry is training and tuning the systems to perform in a desired manner. This may take from minutes up to a year after installation, and can be a major cost. Based on our experiences the training issues need to be taken into account from the very beginning of system design. In this presentation we consider approaches for visual surface inspection and system training. We advocate using a nonsupervised learning based visual training method.
Industrial Engineering Journal
With current era of the Automobile industry, the product is manually or visually checked by using check list there is difficulty in inspection due to dependence on human skills and lack of ergonomic applications which cause fatigue. Inspection is one of the primary segments of the industrial parts production process. Machine vision is a present day strategy to inspect produced parts and it is a subcategory of engineering machinery, dealing with issues of information technology, optics, mechanics and industrial automation. Machine vision systems are used increasingly to solve problems of industrial inspection. This paper introduces an automatic vision based defect inspection or detection and dimensional measurement. The system identifies defects (Part Miss, Part Location, Welding Defects and grinding defects etc.) which usually occur in an assembly Structure component. The image processing technique used for Defect detection and algorithms developed for defect detection and linear dimension measurement. Various types of sensors were interfaced with the vision hardware and the part handling mechanism, to complete the total automated vision based inspection system. This system is an accurate, repeatable, fast and cheap solution for industries. This image processing technique is finished utilizing MATLAB programming. This work presents a strategy which decreases the manual work.
2008
This paper is aimed to present an intelligent Visual Inspection System which compared to human, can operate untiringly and provide consistent quality and accuracy of the inspected products. The system can detect defects that are too subtle for an unaided human and can operate with higher speeds than human eye. The scheme is concerning the development of an automated visual inspection based on CMOS web-camera in a production line simulation. The main objectives are to develop intelligent visual inspection system and image processing algorithm to perform measurement of part parameter. In this research, the systems are divided into hardware and software framework. The result shows that dimensions of part can be obtained by calculating the pixel value.
Machine Vision and Applications, 2000
The continuing development of machine vision is initiating a change from human to machine vision for inspection purposes. This paper concentrates on a general analysis graph within a systematic automated visual inspection concept that speeds up the development of such systems by increasing the flexibility. The detection of primitives is separated from the model-based analysis process. Together with an object-specific description, the analysis graph is instantiated to perform the inspection. The analysis graph can be seen as a "recipe" for solving industrial applications, stating which kind of decisions have to be made at which stage.
IEEE Transactions on Systems, Man, and Cybernetics, 1992
Abstruct-The problem of determining if a given twodimensional (2-D) automated visual inspection system using binary images is capable of inspecting a specified part to the design specifications is addressed. This is accomplished by modeling the error inherent in the visual inspection system. The error defines a process capability zone that is compared to the part design specifications.
Pattern Recognition, 1985
We present the design criteria and the basic structure of GYPSY, a software laboratory for visual inspection and recognition in industrial automation tasks.
Mathematical and Computer Modelling, 1994
The demand to minimize the number of defects along with the increasing availability of computerized vision systems has made the on-line inspection of all production parts a feasible option in modern manufacturing systems. Vision systems enable noncontact, and thus, nondestructive measurements. An image of the production part is electronically obtained and stored in digital form in a computer. In most cases, the image is then processed to identify the local edges of the object. At a higher image processing level, information on local edges is used to obtain the boundaries of the object. Measurements on the computationally obtained boundary can then be performed mathematically, allowing tests to verify the shape and dimensions of the production part. It is the purpose of this paper to investigate and present methods for the determination of shapes and the use of this information for on-line quality inspection.
2013
In manufacturing industry, machine vision is very important nowadays. Computer vision has been developed widely in manufacturing for accurate automated inspection. A model of automated inspection system is presented in this conceptual paper. Image processing is used for inspection of part. It is assumed that the part after going through many previous operations comes to inspection system where the weight of the part as well as geometry made on that part is detected and later decided whether it is to be accepted or rejected with the help of image processing technique. Using MATLAB software a program is developed and pattern or geometry is detected.
2006
Automated visual inspection is defined as a quality control task that determines automatically if a product, or test object, deviates from a given set of specifications using visual data. In the last 25 years, many research directions in this field have been exploited, some very different principles have been adopted and a wide variety of algorithms have been appeared in the literature. However, automated visual inspection systems still suffer from i) detection accuracy, because there is a fundamental trade off between false alarms and miss detections; and ii) strong bottleneck derived from mechanical speed and from high computational cost. For this reasons, automated visual inspection remains an open question. In this sense, Automated Multiple View Inspection, a robust method that uses redundant views of the test object to perform the inspection task, is opening up new possibilities in inspection field by taking into account the useful information about the correspondence between the different views. This strategy is very robust because in first step it identifies potential defects in each view and in second step it finds correspondences between potential defects, and only those that are matched in different views are detected as real defects. In this paper, we review the advances done in this field giving an overview of the multiple view methodology and showing experimental results obtained on real data.
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