Detecting dings and dents on specular car body surfaces based on optical flow

[EN] This paper introduces a new approach to detect defects cataloged as dings and dents on car body surfaces, which is currently one of the most important issues facing quality control in the automotive industry. Using well-known optical flow algorithms and the deflectometry principle, the method proposed in this work is able to detect all kind of anomalies on specular surfaces. Hence, our method consists of two main steps: first, in the pre-processing step, light patterns projected on the body surface sweep uniformly the area of inspection, whilst a new image fusion law, based on optical flow, is used to obtain a resulting fused image holding the information of all variations suffered by the projected patterns during the sweeping process, indicating the presence of anomalies; second, a new post-processing step is proposed that avoids the need of using pre-computed reference backgrounds in order to differentiate defects from other body features such as style-lines. To that end, the image background of the resulting fused image is estimated in the first place through a method based on blurring the image according to the direction of each pixel. Afterwards, the estimated image background is used in a new subtraction law through which defects are well differentiated from other surface deformations, allowing the detection of defects in the entire illuminated area. In addition, since our approach, together with the system used, computes defects in less than 15 s, it satisfies the assembly plants time requirements. Experimental results presented in this paper are obtained from the industrial automatic quality control system QEyeTunnel employed in the production line at the Mercedes-Benz factory in Vitoria, Spain. A complete analysis of the algorithm performance will be shown here, together with several tests proving the robustness and reliability of our proposal.This work is supported by VALi+d (APOSTD/2016/044) and PROMETEO (PROMETEOII/2014/044) Programs, both from Conselleria d'Educacio, Generalitat Valenciana.Arnal-Benedicto, L.; Solanes Galbis, JE.; Molina, J.; Tornero Montserrat, J. (2017). Detecting dings and dents on specular car body surfaces based on optical flow. Journal of Manufacturing Systems. 45:306-321. https://doi.org/10.1016/j.jmsy.2017.07.006S3063214

On the detection of defects on specular car body surfaces

[EN] The automatic detection of small defects (of up to 0.2 mm in diameter) on car body surfaces following the painting process is currently one of the greatest issues facing quality control in the automotive industry. Although several systems have been developed during the last decade to provide a solution to this problem, these, to the best of our knowledge, have been focused solely on flat surfaces and have been unable to inspect other parts of the surfaces, namely style lines, edges and corners as well as deep concavities. This paper introduces a novel approach using deflectometry- and vision-based technologies in order to overcome this problem and ensure that the whole area is inspected. Moreover, since our approach, together with the system used, computes defects in less than 15 s, it satisfies cycle time production requirements (usually of around 30 s per car). Hence, a two-step algorithm is presented here: in the first step, a new pre-processing step (image fusion algorithm) is introduced to enhance the contrast between pixels with a low level of intensity (indicating the presence of defects) and those with a high level of intensity (indicating the absence of defects); for the second step, we present a novel post-processing step with an image background extraction approach based on a local directional blurring method and a modified image contrast enhancement, which enables detection of defects in the entire illuminated area. In addition, the post-processing step is processed several times using a multi-level structure, with computed image backgrounds of different resolution. In doing so, it is possible to detect larger defects, given that each level identifies defects of different sizes. Experimental results presented in this paper are obtained from the industrial automatic quality control system QEyeTunnel employed in the production line at the Mercedes-Benz factory in Vitoria, Spain. A complete analysis of the algorithm performance will be shown here, together with several tests proving the robustness and reliability of our proposal.This work is supported by VALi+d (APOSTD/2016/044) and PROMETEO (PROMETEOII/2014/044) Programs, both from Conselleria d'Educacio, Generalitat Valenciana.Molina, J.; Solanes Galbis, JE.; Arnal-Benedicto, L.; Tornero Montserrat, J. (2017). On the detection of defects on specular car body surfaces. Robotics and Computer-Integrated Manufacturing. 48:263-278. https://doi.org/10.1016/j.rcim.2017.04.009S2632784

Camera 3D positioning mixed reality-based interface to improve worker safety, ergonomics and productivity

[EN] This research develops a new mixed reality-based worker interface for industrial camera 3D positioning, which is intuitive and easy to manage, in order to enhance the worker safety, ergonomics and productivity. An experimental prototype to be used in the car body quality control is developed in the paper. The benefits and drawbacks of the proposed interface are discussed along the paper and sustained through several usability tests conducted with users familiar and not-familiar with mixed reality devices. Furthermore, the feasibility of the proposed approach is demonstrated by tests made in an industrial environment with skilled workers from Alfatec Sistemas company.This work was supported in part by the Spanish Government under the Project DPI2017-87656-C2-1-R.Muñoz García, A.; Martí Testón, A.; Mahiques, X.; Gracia Calandin, LI.; Solanes Galbis, JE.; Tornero Montserrat, J. (2020). Camera 3D positioning mixed reality-based interface to improve worker safety, ergonomics and productivity. CIRP Journal of Manufacturing Science and Technology (Online). 28:24-37. https://doi.org/10.1016/j.cirpj.2020.01.004S24372

Technology applications

A summary of NASA Technology Utilization programs for the period of 1 December 1971 through 31 May 1972 is presented. An abbreviated description of the overall Technology Utilization Applications Program is provided as a background for the specific applications examples. Subjects discussed are in the broad headings of: (1) cancer, (2) cardiovascular disease, (2) medical instrumentation, (4) urinary system disorders, (5) rehabilitation medicine, (6) air and water pollution, (7) housing and urban construction, (8) fire safety, (9) law enforcement and criminalistics, (10) transportation, and (11) mine safety

AI for in-line vehicle sequence controlling: development and evaluation of an adaptive machine learning artifact to predict sequence deviations in a mixed-model production line

Customers in the manufacturing sector, especially in the automotive industry, have a high demand for individualized products at price levels comparable to traditional mass production. The contrary objectives of providing a variety of products and operating at minimum costs have introduced a high degree of production planning and control mechanisms based on a stable order sequence for mixed-model assembly lines. A major threat to this development is sequence scrambling, triggered by both operational and product-related root causes. Despite the introduction of just-in-time and fixed production times, the problem of sequence scrambling remains partially unresolved in the automotive industry. Negative downstream effects range from disruptions in the just-in-sequence supply chain to a stop of the production process. A precise prediction of sequence deviations at an early stage allows the introduction of counteractions to stabilize the sequence before disorder emerges. While procedural causes are widely addressed in research, the work at hand requires a different perspective involving a product-related view. Built on unique data from a real-world global automotive manufacturer, a supervised classification model is trained and evaluated. This includes all the necessary steps to design, implement, and assess an AI artifact, as well as data gathering, preprocessing, algorithm selection, and evaluation. To ensure long-term prediction stability, we include a continuous learning module to counter data drifts. We show that up to 50% of the major deviations can be predicted in advance. However, we do not consider any process-related information, such as machine conditions and shift plans, but solely focus on the exploitation of product features like body type, powertrain, color, and special equipment

Mechatronics applied to scale model decoration

The European toy industry is very heavily dependent on manual labour and therefore vulnerable to Far Eastern competitors, who have the advantage of lower labour costs. Automation is Europe's best hope of beating off this oriental challenge. The aim of the project described within this thesis is to investigate the replacement of a traditionally manual series of operations by flexible automation to provide the basis for higher productivity and a greater degree of responsiveness to product change, leading to Just In Time Manufacture with reduced Work In Progress, while still retaining the high quality traditionally associated with the product. This thesis presents one of the first working attempts to this end, represented by a proof-of­concept cell designed and commissioned for investigating the many problems and possibilities associated with the decoration of scale models of cars and trains. The cell was designed using the Mechatronics approach which means that the various mechanical, electrical and electronic and computing possibilities have been taken into account from the start of the design stage. The proof-of-concept cell consists of five stations which provide the necessary means of loading the models in the cell, identifying the models and their orientation, decorating the models, inspecting the decorated models and finally palletising them for assembly. The industrial partners for the project were Hornby Hobbies Limited, J-L Automation and Staubli Unimation. Because this project centres around the present decoration operations at Hornby Hobbies Limited, which is heavily dependant on pad printing, an overview of pad printing is included. This will give the reader a background to the problems faced during the project. Before describing the proof-of-concept cell and its hardware and software components, the present factory based method and the constraints put on the project by Hornby Hobbies Limited are explained so that the reasons for choices within the cell will be more readily understood. A brief history of Scalextric is also included so that the reader may also understand some of the historical problems associated with the product. The result of this mechatronic approach are two fold: a) the efficiency of the cell is improved because the individual parts are working at optimal efficiency b) the cell has a greater degree of flexibility because of the re-programming facilities embedded in each of its component parts. This Mechatronic investigation has led to new concepts for pad printing and assembly operations and these are described in detail in the conclusions

Applications of aerospace technology in the public sector

Current activities of the program to accelerate specific applications of space related technology in major public sector problem areas are summarized for the period 1 June 1971 through 30 November 1971. An overview of NASA technology, technology applications, and supporting activities are presented. Specific technology applications in biomedicine are reported including cancer detection, treatment and research; cardiovascular diseases, diagnosis, and treatment; medical instrumentation; kidney function disorders, treatment, and research; and rehabilitation medicine

New advances in vehicular technology and automotive engineering

An automobile was seen as a simple accessory of luxury in the early years of the past century. Therefore, it was an expensive asset which none of the common citizen could afford. It was necessary to pass a long period and waiting for Henry Ford to establish the first plants with the series fabrication. This new industrial paradigm makes easy to the common American to acquire an automobile, either for running away or for working purposes. Since that date, the automotive research grown exponentially to the levels observed in the actuality. Now, the automobiles are indispensable goods; saying with other words, the automobile is a first necessity article in a wide number of aspects of living: for workers to allow them to move from their homes into their workplaces, for transportation of students, for allowing the domestic women in their home tasks, for ambulances to carry people with decease to the hospitals, for transportation of materials, and so on, the list don’t ends. The new goal pursued by the automotive industry is to provide electric vehicles at low cost and with high reliability. This commitment is justified by the oil’s peak extraction on 50s of this century and also by the necessity to reduce the emissions of CO2 to the atmosphere, as well as to reduce the needs of this even more valuable natural resource. In order to achieve this task and to improve the regular cars based on oil, the automotive industry is even more concerned on doing applied research on technology and on fundamental research of new materials. The most important idea to retain from the previous introduction is to clarify the minds of the potential readers for the direct and indirect penetration of the vehicles and the vehicular industry in the today’s life. In this sequence of ideas, this book tries not only to fill a gap by presenting fresh subjects related to the vehicular technology and to the automotive engineering but to provide guidelines for future research. This book account with valuable contributions from worldwide experts of automotive’s field. The amount and type of contributions were judiciously selected to cover a broad range of research. The reader can found the most recent and cutting-edge sources of information divided in four major groups: electronics (power, communications, optics, batteries, alternators and sensors), mechanics (suspension control, torque converters, deformation analysis, structural monitoring), materials (nanotechnology, nanocomposites, lubrificants, biodegradable, composites, structural monitoring) and manufacturing (supply chains). We are sure that you will enjoy this book and will profit with the technical and scientific contents. To finish, we are thankful to all of those who contributed to this book and who made it possible.info:eu-repo/semantics/publishedVersio