Literatura científica selecionada sobre o tema "Usinage – Qualité – Contrôle"
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Artigos de revistas sobre o assunto "Usinage – Qualité – Contrôle"
Scherrer, Simon C., Christoph Frei, Mischa Croci-Maspoli, Deborah van Geijtenbeek, Claudine Hotz e Christof Appenzeller. "Operational quality control of daily precipitation using spatio-climatological plausibility testing". Meteorologische Zeitschrift 20, n.º 4 (1 de agosto de 2011): 397–407. http://dx.doi.org/10.1127/0941-2948/2011/0236.
Texto completo da fonteMohammadha Hussaini, M., e R. Anita. "Power Quality Analysis in Wind Power Generation Using Sliding Mode Control". International Journal of Engineering and Technology 2, n.º 5 (2010): 481–85. http://dx.doi.org/10.7763/ijet.2010.v2.168.
Texto completo da fonteDakić, Pavle, Jelena Savić e Vladimir Todorović. "MENADŽMENT KONTROLE KVALITETA SOFTVERA UPOTREBOM BLACK-BOX TESTIRANJA NA POSTOJEĆEM WEBSHOP-U TRINITISHOP". FBIM Transactions 9, n.º 1 (15 de abril de 2021): 28–38. http://dx.doi.org/10.12709/fbim.09.09.01.03.
Texto completo da fonteHernández-Hierro, J. M., I. González-Martín, V. Villaescusa-García, F. López-González, C. Oiz-Jiménez, I. A. Lobos-Ortega e B. Gordillo. "Control of quality and silo storage of sunflower seeds using near infrared technology". Grasas y Aceites 64, n.º 1 (4 de fevereiro de 2013): 30–35. http://dx.doi.org/10.3989/gya.096312.
Texto completo da fonteWahyuni, Ayu Endah. "Analysis of Quality Control of Instant Mie Products Using C-Chart Methods (PT XYZ)". International Journal of Psychosocial Rehabilitation 24, n.º 2 (13 de fevereiro de 2020): 2804–7. http://dx.doi.org/10.37200/ijpr/v24i2/pr200577.
Texto completo da fonteM. Jamal Rashid, Kawa, e Sherzad Arif Hama. "Using the Quality Control to Determine the Factors of Failure Operation in Cement Sector". Journal of Zankoy Sulaimani - Part A 23, n.º 1 (20 de junho de 2021): 101–12. http://dx.doi.org/10.17656/jzs.10845.
Texto completo da fonte許文菁, 許文菁, 許郁笙 Wen-Chin Hsu, 尤琬筑 Yu-Sheng Hsu, 施心筑 Wan-Chu Yu e 王雅玲 Hsin-Chiu Shih. "運用品管手法改善藥師在職教育課程的辦理成效". 醫療品質雜誌 16, n.º 1 (janeiro de 2022): 056–62. http://dx.doi.org/10.53106/199457952022011601009.
Texto completo da fontePrasad, D. Babu Rajendra, A. D. Kulkarni e T. Ananthapadmanabha. "Operation and Control of the Distributed Energy Resources to Improve the Power Quality in Electrical Distribution System Using Hbmo -Ann - A Novel Control Algorithm". Indian Journal Of Science And Technology 15, n.º 42 (12 de novembro de 2022): 2204–18. http://dx.doi.org/10.17485/ijst/v15i42.2439.
Texto completo da fonteLü Xinrui, 吕新蕊, 刘婷婷 Liu Tingting, 廖文和 Liao Wenhe, 韦辉亮 Wei Huiliang, 杨涛 Yang Tao e 蒋立异 Jiang Liyi. "高强铝合金7075激光粉末床熔融凝固裂纹的消除与质量控制". Chinese Journal of Lasers 49, n.º 14 (2022): 1402209. http://dx.doi.org/10.3788/cjl202249.1402209.
Texto completo da fonteObukhov, P. S., I. V. Manuilov e V. S. Kreinin. "ANALYSIS OF THE EFFECTIVENESS OF THE IMPLEMENTATION OF AUTOMATED QUALITY CONTROL SYSTEMS FOR SHOE PRODUCTS USING MOBILE APPLICATIONS". European Journal of Natural History, n.º 3 2023 (2023): 28–34. http://dx.doi.org/10.17513/ejnh.34346.
Texto completo da fonteTeses / dissertações sobre o assunto "Usinage – Qualité – Contrôle"
Bajic, Eddy. "Intégration du contrôle qualité en production automatisée : application à un îlot automatisé de fabrication de pièces mécaniques". Nancy 1, 1988. http://www.theses.fr/1988NAN10015.
Texto completo da fonteChouhad, Hassan. "Towards online metrology for proactive quality control in smart manufacturing". Thesis, Paris, HESAM, 2022. http://www.theses.fr/2022HESAE021.
Texto completo da fonteIn the traditional manufacturing industry, metrology is an essential element in sanctioning quality at the end of the production line. The innovation brought by concept of smart manufacturing leads to a repositioning of metrology to be proactive at the heart of production by performing the so-called first-time-right manufacturing of parts. The goal of this thesis is therefore to propose a methodological approach for the development of a proactive system, enhanced by AI models, to control the conformity of a product to a specification during machining and to characterize its defects. For this purpose, a first study on the surface aspect was carried out by collecting high-resolution images of coated and cut copper wires that may present defects. The images, taken by a computer vision system based on chromatic confocal imaging, were used to generate different artificial intelligence models. These models can perform segmentation and classification of observed defects. When comparing the accuracy and processing time of the AI models, transfer learning using the mobile-net model showed better performance. To extend the study of surface quality assessment, surface profile measurements on machine tools were performed using non-contact chromatic confocal sensors. Two approaches were performed: i) milling aluminum without tool wear signature, and ii) milling titanium with tool wear signature. In both cutting configurations, machining parameters, surface roughness profiles, and cutting forces were measured to build a dataset for training the prediction models by machine learning. The results showed that the XGboost model presented the best prediction performance and for both scenarios i) and ii). By considering the cutting time in titanium milling, the autoregressive integrated moving average time series prediction model was applied to track the evolution of roughness with tool wear
Mawissi, Kwamivi. "Modèles de représentation et de définition d'outillages de forme complexe : application à le génération automatique de processus d'usinage". Cachan, Ecole normale supérieure, 1995. http://www.theses.fr/1995DENS0001.
Texto completo da fonteMotta, Mariane Prado. "Contribution à l’étude de systèmes de surveillance de l'usinage basés sur des méthodes d‘apprentissage machine et des mesures de vibrations, efforts et température de coupe". Electronic Thesis or Diss., Université de Lorraine, 2022. http://www.theses.fr/2022LORR0296.
Texto completo da fonteMachining is an economically important manufacturing process that relies on the use of a sharpened cutting tool to mechanically cut and remove material from a part to achieve a desired geometry. Given the ever-increasing demands for quality, product variability and cost reduction, tool condition and workpiece quality monitoring systems based on artificial intelligence (AI) techniques are a potential solution are a potential solution for a more reliable and economical manufacturing processes. Recent developments in the field of AI, have shown great potential to transform the manufacturing domain with advanced tools dedicated to data analysis and modeling. In particular, supervised machine learning (ML) algorithms are a powerful tool for modeling complex relationships between input and output variables based on a dataset containing examples, i.e., input-output pairs. Nevertheless, one of the main drawbacks of these modeling techniques is that a large amount of data, usually obtained through experiments (often long and expensive to perform), is required to train accurate and reliable models. This fact limits the applicability of these types of models in an industrial context. Considering this context, this study aims to contribute to the identification of methodologies for the development of ML models dedicated to machining monitoring within industrial conditions, in which time and resources for the realization of experiments are often limited. For this purpose, it is considered in this study that, although experiments can be onerous, in the industry it is common that, before starting large scale machining productions with a new tool or material, setup experiments are performed to determine the most appropriate cutting parameters to perform that production. Given this need (or recommendation), it will be investigated in this thesis, the predictive performances that can be achieved if data, obtained from these tuning experiments, are used to generate predictive models for machining monitoring. More precisely, setting experiments from the standardized methodology Couple Tool-Material protocol (NF E 66-520) are considered. In an effort to obtain good predictive performance with a limited amount of experimental data, sensors for measuring cutting forces, temperature and vibrations are chosen as instrumentation for the monitoring system to be developed, given its close relationship with the kinematics of the machining process. In this matter, special attention is given to the feature engineering step. That is, the process of transforming the available raw data, for example, the signals recorded by the sensors, into features, i.e., information, that more accurately represent the problem underlying the predictive model. Finally, since in the industry the changes in cutting tool reference can occur quite often, it will also be investigated whether the models developed for a given target tool can be applied to other slightly different tools (variations on nose radius, substrate and coating) and whether, for the training of ML models, the use of larger databases, but containing observations related not only to the target tool but also to other tools slightly different from it, will be more advantageous, compared to the use of a smaller database specific to the target tool
Dutilh, Vincent. "Maîtrise de l'intégrité de surface par la surveillance d'usinage sur les pièces critiques en superalliage de turbomoteurs aéronautiques". Phd thesis, Toulouse, INPT, 2011. http://oatao.univ-toulouse.fr/15642/1/Dutilh.pdf.
Texto completo da fonteRemenaric, Hajak Mateja. "Study of ribonucleoprotein particle biogenesis and quality control by a novel technique using bacterial Rho factor as a tool". Thesis, Orléans, 2016. http://www.theses.fr/2016ORLE2013/document.
Texto completo da fonteIn eukaryotes, the genetic information is transcribed into messenger RNA which undergoes various processing and assembly events prior to its export from the nucleus. These transcript modifications are performed by numerous protein factors recruited to the nascent transcript, thus making a messenger ribonucleoprotein particle (mRNP). mRNP biogenesis is tightly interconnected with both transcription and quality control to ensure efficiency and accuracy in production of mature mRNPs. Recent findings suggest that members of THO-Sub2 complex might be crucial factors in coupling transcription, mRNP biogenesis and export. In our group, we have implemented an innovative assay to study mRNP biogenesis and quality control, based on the expression of the bacterial factor Rho in Saccharomyces cerevisiae. Rho interferes with proper mRNP assembly and generates aberrant transcripts degraded by the nuclear degradation machinery. In this study, we use Rho experimental system to expand our findings on Rrp6 and exosome involvement in quality control degradation of transcripts, as well as to better characterize the role and function of THO-Sub2 complex in the process of mRNP biogenesis. Obtained results reveal an interesting difference in behavior of THO complex members upon Rho action and disclose their dependence on binding to the RNA, which could not be observed by other experimental techniques. This substantiates the expected potential of Rho-based experimental system in the study of protein factors involved in mRNP biogenesis and quality control
Cassady, Charles Richard. "Statistical quality control techniques using multilevel discrete product quality measures". Diss., This resource online, 1996. http://scholar.lib.vt.edu/theses/available/etd-06062008-151120/.
Texto completo da fonteGosselin, Ryan. "ON-LINE QUALITY CONTROL IN POLYMER PROCESSING USING HYPERSPECTRAL IMAGING". Thesis, Université Laval, 2010. http://www.theses.ulaval.ca/2010/26629/26629.pdf.
Texto completo da fonteThe use of plastic composite materials has been increasing in recent years in order to reduce the amount of material used and/or use more economic materials, all of which without compromising the properties. The impressive adaptability of these composite materials comes from the fact that the manufacturer can choose the raw materials, the proportion in which they are blended as well as the processing conditions. However, these materials tend to suffer from heterogeneous compositions and structures, which lead to mechanical weaknesses. Product quality is generally measured in the laboratory, using destructive tests often requiring extensive sample preparation. On-line quality control would allow near-immediate feedback on the operating conditions and may be transferrable to an industrial production context. The proposed research consists of developing an on-line quality control tool adaptable to plastic materials of all types. A number of infrared and ultrasound probes presently exist for on-line composition estimation, but only provide single-point values at each acquisition. These methods are therefore less adapted for identifying the spatial distribution of a sample’s surface characteristics (e.g. homogeneity, orientation, dispersion). In order to achieve this objective, a hyperspectral imaging system is proposed. Using this tool, it is possible to scan the surface of a sample and obtain a hyperspectral image, that is to say an image in which each pixel captures the light intensity at hundreds of wavelengths. Chemometrics methods can then be applied to this image in order to extract the relevant spatial and spectral features. Finally, multivariate regression methods are used to build a model between these features and the properties of the sample. This mathematical model forms the backbone of an on-line quality assessment tool used to predict and optimize the operating conditions under which the samples are processed.
Binny, Diana. "Radiotherapy quality assurance using statistical process control". Thesis, Queensland University of Technology, 2019. https://eprints.qut.edu.au/130738/1/Diana_Binny_Thesis.pdf.
Texto completo da fonteFaust, Justin E. "Increase efficiency using the six sigma methodologies". Online version, 2009. http://www.uwstout.edu/lib/thesis/2009/2009faustj.pdf.
Texto completo da fonteLivros sobre o assunto "Usinage – Qualité – Contrôle"
Price, Frank. Right everytime: Using the Deming approach. Aldershot: Gower, 1990.
Encontre o texto completo da fontePrice, Frank. Right every time: Using the Deming approach. New York: M. Dekker, 1990.
Encontre o texto completo da fontePrice, Frank. Right every time: Using the Deming approach. Aldershot: Gower, 1993.
Encontre o texto completo da fonteBhote, Keki R. World class quality: Using design of experiments to make it happen. New York, NY: Amacom, 1991.
Encontre o texto completo da fonteStapenhurst, Tim. Mastering statistical process control: A handbook for performance improvement using cases. Amsterdam: Elsevier Butterworth-Heinemann, 2005.
Encontre o texto completo da fontePrice, Frank. Right first time: Using quality control for profit. Aldershot: Wildwood House, 1986.
Encontre o texto completo da fonteSolow, Lawrence. What works for GE may not work for you: Using human systems dynamics to build a culture of process improvement. New York: Productivity Press, 2010.
Encontre o texto completo da fonteSolow, Lawrence. What works for GE may not work for you: Using human systems dynamics to build a culture of process improvement. New York: Productivity Press, 2010.
Encontre o texto completo da fonteR, Bhote Keki. World class quality: Using design of experiments to make it happen. 2a ed. New York, NY: American Management Association, 2000.
Encontre o texto completo da fonteAft, Lawrence S. Quality improvement using statistical process control. San Diego: Harcourt Brace Jovanovich, 1988.
Encontre o texto completo da fonteCapítulos de livros sobre o assunto "Usinage – Qualité – Contrôle"
Okello, Gabriel Otieno. "Statistical Quality Control". In Simplified Business Statistics Using SPSS, 405–50. Boca Raton: Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003292654-21.
Texto completo da fonteSantos-Fernández, Edgar. "Multivariate Control Charts". In Multivariate Statistical Quality Control Using R, 17–61. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5453-3_2.
Texto completo da fonteSantos-Fernández, Edgar. "A Small Introduction". In Multivariate Statistical Quality Control Using R, 1–15. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5453-3_1.
Texto completo da fonteSantos-Fernández, Edgar. "Multivariate Process Capability Indices (MPCI)". In Multivariate Statistical Quality Control Using R, 63–85. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5453-3_3.
Texto completo da fonteSantos-Fernández, Edgar. "Tools of Support to MSQC". In Multivariate Statistical Quality Control Using R, 87–106. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5453-3_4.
Texto completo da fonteSantos-Fernández, Edgar. "Study Cases". In Multivariate Statistical Quality Control Using R, 107–19. New York, NY: Springer New York, 2012. http://dx.doi.org/10.1007/978-1-4614-5453-3_5.
Texto completo da fonteMousa, Wail A., e Abdullatif A. Al-Shuhail. "Quality Control of Real Seismic Data". In Processing of Seismic Reflection Data Using MATLAB™, 15–21. Cham: Springer International Publishing, 2011. http://dx.doi.org/10.1007/978-3-031-02534-1_3.
Texto completo da fonteElsayed, E. A., M. Gultekin e J. H. Byun. "Shift Detections of Process Mean using Regression and Cross-Correlation Analyses". In Optimization in Quality Control, 279–300. Boston, MA: Springer US, 1997. http://dx.doi.org/10.1007/978-1-4615-6151-4_11.
Texto completo da fonteGhosh, Arindam, e Gerard Ledwich. "Realization and Control of DSTATCOM". In Power Quality Enhancement Using Custom Power Devices, 287–331. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1153-3_8.
Texto completo da fonteGhosh, Arindam, e Gerard Ledwich. "Structure and Control of Power Converters". In Power Quality Enhancement Using Custom Power Devices, 137–214. Boston, MA: Springer US, 2002. http://dx.doi.org/10.1007/978-1-4615-1153-3_5.
Texto completo da fonteTrabalhos de conferências sobre o assunto "Usinage – Qualité – Contrôle"
Wan, au, au Marjanovic e au Lennox. "Trajectory tracking of batch product quality using intermittent measurements and moving window estimation". In 2012 UKACC International Conference on Control (CONTROL). IEEE, 2012. http://dx.doi.org/10.1109/control.2012.6334640.
Texto completo da fonteHillman, Tomos, e Vincent Lizzi. "Self-generating quality control". In Declarative Amsterdam. Amsterdam: John Benjamins, 2020. http://dx.doi.org/10.1075/da.2020.hillman-lizzy.quality-control.
Texto completo da fonteResonnek, Verena, e Volker Schöppner. "Self-optimizing barrel temperature setting control of single screw extruders for improving the melt quality". In MATERIALS CHARACTERIZATION USING X-RAYS AND RELATED TECHNIQUES. Author(s), 2019. http://dx.doi.org/10.1063/1.5088268.
Texto completo da fonteTairi, Hamid, Tadeusz Sliwa, Yvon Voisin, Alain Diou e L. Radouane. "Visual servo control using orthinormal polynomial". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.515087.
Texto completo da fonteDenis, Florence, e Atilla M. Baskurt. "Directional structures detection using steerable pyramid". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.515161.
Texto completo da fonteNipas, Marte D., Mon Arjay F. Malbog, Jennalyn N. Mindoro, Rufo I. Marasigan e Jennifer B. Enriquez. "QualiOn: An Onion Quality Analyzer and Sorter Device using Random Forest Classifier". In 2022 IEEE 13th Control and System Graduate Research Colloquium (ICSGRC). IEEE, 2022. http://dx.doi.org/10.1109/icsgrc55096.2022.9845169.
Texto completo da fonteKang, Sangkyu, Joon-Ki Paik, Andreas Koschan, Besma R. Abidi e Mongi A. Abidi. "Real-time video tracking using PTZ cameras". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.514945.
Texto completo da fonteRamadoss, Balaji, Jin-Choon Ng, Andreas Koschan e Mongi A. Abidi. "Scene inspection using a robotic imaging system". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.515092.
Texto completo da fonteTurtinen, Markus, Matti Pietikaeinen, Olli Silven, Topi Maenpaa e Matti Niskanen. "Texture-based paper characterization using nonsupervised clustering". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.515125.
Texto completo da fonteTucker, Jr., Raymond W., Stephen W. Kercel e Venugopal K. Varma. "Characterization of gas pipeline flaws using wavelet analysis". In Quality Control by Artificial Vision, editado por Kenneth W. Tobin, Jr. e Fabrice Meriaudeau. SPIE, 2003. http://dx.doi.org/10.1117/12.515157.
Texto completo da fonteRelatórios de organizações sobre o assunto "Usinage – Qualité – Contrôle"
Lee, Jusang, John E. Haddock, Dario D. Batioja Alvarez e Reyhaneh Rahbar Rastegar. Quality Control and Quality Assurance of Asphalt Mixtures Using Laboratory Rutting and Cracking Tests. Purdue University, 2019. http://dx.doi.org/10.5703/10.5703/1288284317087.
Texto completo da fonteLee, Jusang, John E. Haddock, Dario D. Batioja Alvarez e Reyhaneh Rahbar Rastegar. Quality Control and Quality Assurance of Asphalt Mixtures Using Laboratory Rutting and Cracking Tests. Purdue University, 2019. http://dx.doi.org/10.5703/1288284317087.
Texto completo da fonteHibbert, Angela, Jue Lin e Begona Pérez Gómez. Automated tide gauge data quality control software and report. EuroSea, 2023. http://dx.doi.org/10.3289/eurosea_d5.7.
Texto completo da fonteAl-Qadi, Imad, José Rivera-Perez, Watheq Sayeh, Javier García Mainieri, Hadi Meidani, John Huang, Hasan Ozer e Adam Hand. Case Studies Using Quality Control for Performance and Pay for Performance Specifications: Field Observations. Illinois Center for Transportation, junho de 2020. http://dx.doi.org/10.36501/0197-9191/20-007.
Texto completo da fonteMcCarthy, James, e Tom McGrath. PR-312-12210-R01 CEPM Monitoring Plan for Two-Stoke Cycle Lean Burn Engines. Chantilly, Virginia: Pipeline Research Council International, Inc. (PRCI), março de 2019. http://dx.doi.org/10.55274/r0011564.
Texto completo da fonteLi, Xiaojun, Dingxin Cheng, Kun Zhang, Kanwar M. S. Jakhar e Uday V. Pericherla. Development of a Quality Control Method and Guidelines for Hot Mix Asphalt Using Recycled Concrete Aggregate. Mineta Transportation Institute, março de 2020. http://dx.doi.org/10.31979/mti.2020.1854.
Texto completo da fonteAl-Qadi, Imad, José Rivera-Perez, Javier García Mainieri e Watheq Sayeh. Illinois’ Experience Using Quality Control for Performance and Pay for Performance to Determine Pay for Hot-mix Asphalt. Illinois Center for Transportation, julho de 2021. http://dx.doi.org/10.36501/0197-9191/21-023.
Texto completo da fonteСавченко, Лариса Олексіївна. Characteristic of the future specialists professional preparation to the quality educational assessment. Педагогічна думка, 2015. http://dx.doi.org/10.31812/0564/365.
Texto completo da fonteHall, Candice, e Robert Jensen. Utilizing data from the NOAA National Data Buoy Center. Engineer Research and Development Center (U.S.), março de 2021. http://dx.doi.org/10.21079/11681/40059.
Texto completo da fonteAndrian, Leandro Gaston, Oscar Valencia, Jorge Hirs e Ivan Leonardo Urrea Rios. Fiscal Rules and Economic Cycles: Quality (Always) Matters. Inter-American Development Bank, janeiro de 2023. http://dx.doi.org/10.18235/0004570.
Texto completo da fonte