Auswahl der wissenschaftlichen Literatur zum Thema „Testing Machine Company“
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Zeitschriftenartikel zum Thema "Testing Machine Company"
Sibarani, Prince, Tanika D. Sofianti und Aditya Tirta Pratama. „Improving the Overall Equipment Effectiveness (OEE) of Drum Testing Machine in Laboratory of Tire Manufacturing Using FMEA and PFMEA“. Proceedings of The Conference on Management and Engineering in Industry 3, Nr. 3 (04.08.2021): 56–61. http://dx.doi.org/10.33555/cmei.v3i3.84.
Der volle Inhalt der QuelleC. M. Nalayani, Thanga Akilan .V, Hariharan .S, SaranArulnathan und Venkatanathan .S. „Placement Analysis for Students using Machine Learning“. September 2023 5, Nr. 3 (September 2023): 223–37. http://dx.doi.org/10.36548/jitdw.2023.3.001.
Der volle Inhalt der QuelleMustika, Nadya Intan, Bagus Nenda und Dona Ramadhan. „Machine Learning Algorithms in Fraud Detection: Case Study on Retail Consumer Financing Company“. Asia Pacific Fraud Journal 6, Nr. 2 (30.12.2021): 213. http://dx.doi.org/10.21532/apfjournal.v6i2.216.
Der volle Inhalt der QuellePorter, S. J., J. P. Chadwick, M. G. Owen und S. J. Page. „Evaluation of seven ultrasonic machines for estimating carcase composition in live bulls“. Proceedings of the British Society of Animal Production (1972) 1988 (März 1988): 46. http://dx.doi.org/10.1017/s0308229600016846.
Der volle Inhalt der QuelleCamille Merlin S. Tan und Lawrence Y. Materum. „Cleanroom Dashboard System for Time-Reduction Checking of Disk Tester Availability“. Journal of Advanced Research in Applied Sciences and Engineering Technology 43, Nr. 2 (17.04.2024): 237–57. http://dx.doi.org/10.37934/araset.43.2.237257.
Der volle Inhalt der QuelleSutrisno, Niantoro, Rizka Faradila, Rizka Faradila, Edison P. Sirait und Edison P. Sirait. „PENGARUH KAPASITAS MESIN DAN JUMLAH PERSEDIAAN BAHAN BAKU TERHADAP VOLUME PRODUKSI“. Jurnal Akuntansi dan Bisnis 10, Nr. 01 (25.06.2024): 15. http://dx.doi.org/10.47686/jab.v10i01.680.
Der volle Inhalt der QuelleQu, Ju Bao, und Shu Juan Wang. „Intelligent Quality Control System Based on Machine Vision of Multi-Line“. Applied Mechanics and Materials 513-517 (Februar 2014): 1192–96. http://dx.doi.org/10.4028/www.scientific.net/amm.513-517.1192.
Der volle Inhalt der QuelleSiti Nur Syamimi Mat Zain, Nor Azuana Ramli und Rose Adzreen Adnan. „CUSTOMER SENTIMENT ANALYSIS THROUGH SOCIAL MEDIA FEEDBACK: A CASE STUDY ON TELECOMMUNICATION COMPANY“. International Journal of Humanities Technology and Civilization 7, Nr. 2 (14.12.2022): 54–61. http://dx.doi.org/10.15282/ijhtc.v7i2.8739.
Der volle Inhalt der QuelleSrisattayakul, Parinya, Charnnarong Saikaew, Anurat Wisitsoraat und Naphatara Intanon. „Influence of MoN Sputtering Coating on Wear Resistance of a Fishing Net-Weaving Machine Component“. Advanced Materials Research 1016 (August 2014): 80–84. http://dx.doi.org/10.4028/www.scientific.net/amr.1016.80.
Der volle Inhalt der QuelleWeick, S., M. Grosse und M. Steinbrueck. „The INCHAMEL facility – a new device for in-situ neutron investigations under defined temperatures with applicable mechanical load“. Journal of Physics: Conference Series 2605, Nr. 1 (01.09.2023): 012035. http://dx.doi.org/10.1088/1742-6596/2605/1/012035.
Der volle Inhalt der QuelleDissertationen zum Thema "Testing Machine Company"
Olivier, Louis Petrus. „Psychomotor ability and learning potential as predictors of driver and machine operator performance in a road construction company“. Diss., 2015. http://hdl.handle.net/10500/19687.
Der volle Inhalt der QuelleIndustrial and Organisational Psychology
M.A. (Industrial and Organisational Psychology)
Buchteile zum Thema "Testing Machine Company"
Abaei, Golnoush, und Ali Selamat. „Important Issues in Software Fault Prediction“. In Advances in Systems Analysis, Software Engineering, and High Performance Computing, 510–39. IGI Global, 2014. http://dx.doi.org/10.4018/978-1-4666-6026-7.ch023.
Der volle Inhalt der Quelle„Front Matter“. In Pendulum Impact Machines: Procedures and Specimens for Verification, FM1—FM10. ASTM International100 Barr Harbor Drive, PO Box C700, West Conshohocken, PA 19428-2959, 1995. http://dx.doi.org/10.1520/stp14652s.
Der volle Inhalt der QuelleAnand, Mansimar, Irtibat Shaukat, Harnoor Kaler, Jai Narula und Prashant Singh Rana. „Hybrid Model for the Customer Churn Prediction“. In SCRS Proceedings of International Conference of Undergraduate Students, 85–94. Soft Computing Research Society, 2023. http://dx.doi.org/10.52458/978-81-95502-01-1-9.
Der volle Inhalt der QuelleKanatani, Kenichi. „Statistical Analysis of Geometric Computation, 2“. In Geometric Computation for Machine Vision, 318–63. Oxford University PressOxford, 1993. http://dx.doi.org/10.1093/oso/9780198563853.003.0010.
Der volle Inhalt der QuelleZhang, Xiang. „Financial Data Anomaly Recognition Model Based on Improved Support Vector Machine“. In Advances in Transdisciplinary Engineering. IOS Press, 2024. http://dx.doi.org/10.3233/atde231272.
Der volle Inhalt der QuelleIwata, Kazunori, Toyoshiro Nakashima, Yoshiyuki Anan und Naohiro Ishii. „Machine Learning Classification to Effort Estimation for Embedded Software Development Projects“. In Research Anthology on Agile Software, Software Development, and Testing, 1652–65. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-3702-5.ch078.
Der volle Inhalt der QuellePai, Srinivasa P., und Nagabhushana T. N. „Tool Condition Monitoring Using Artificial Neural Network Models“. In Handbook of Research on Emerging Trends and Applications of Machine Learning, 550–76. IGI Global, 2020. http://dx.doi.org/10.4018/978-1-5225-9643-1.ch026.
Der volle Inhalt der QuellePai, Srinivasa P., und Nagabhushana T. N. „Tool Condition Monitoring Using Artificial Neural Network Models“. In Research Anthology on Artificial Neural Network Applications, 400–426. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-2408-7.ch019.
Der volle Inhalt der QuelleDeo, Ravinesh C., Sujan Ghimire, Nathan J. Downs und Nawin Raj. „Optimization of Windspeed Prediction Using an Artificial Neural Network Compared With a Genetic Programming Model“. In Research Anthology on Multi-Industry Uses of Genetic Programming and Algorithms, 116–47. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-8048-6.ch007.
Der volle Inhalt der QuelleDeo, Ravinesh C., Sujan Ghimire, Nathan J. Downs und Nawin Raj. „Optimization of Windspeed Prediction Using an Artificial Neural Network Compared With a Genetic Programming Model“. In Advances in Computational Intelligence and Robotics, 328–59. IGI Global, 2018. http://dx.doi.org/10.4018/978-1-5225-4766-2.ch015.
Der volle Inhalt der QuelleKonferenzberichte zum Thema "Testing Machine Company"
Abbas, Raafat, Aaron Simon, Doug Dunbar, Rodrigo Serrano, Andrew Creegan und Ernie Prochaska. „Automatic Driller Optimization Application Using Machine Learning and Artificial Intelligence Drives Consistent Performance in an Operator’s West Texas Drilling Program“. In SPE Annual Technical Conference and Exhibition. SPE, 2023. http://dx.doi.org/10.2118/215087-ms.
Der volle Inhalt der QuelleValdiero, Antonio C., Ronei O. Ziech, Mauricio S. Pinto, Ivan J. Mantovani und Luiz A. Rasia. „Development and Construction of an Instrumentalized Workbench With a Hydraulic Motor for Farm Machine Testing“. In 9th FPNI Ph.D. Symposium on Fluid Power. American Society of Mechanical Engineers, 2016. http://dx.doi.org/10.1115/fpni2016-1552.
Der volle Inhalt der QuelleGerchman, Mark Craig. „The Single Point Diamond Turning (SPDT) Of Optical Surfaces For Visible Wavelength Applications“. In Optical Fabrication and Testing. Washington, D.C.: Optica Publishing Group, 1990. http://dx.doi.org/10.1364/oft.1990.jtuc3.
Der volle Inhalt der QuelleAl Radhi, Mohammed, Fernando Angel Bermudez, Wael Al Madhoun, Khaled Al Blooshi, Noor Nasser Al Nahhas und Mohammed Nazeih Shono. „Unlocking the Potential of Electrical Submersible Pumps: the Successful Testing and Deployment of a Real-Time Artificially Intelligent System, for Failure Prediction, Run Life Extension, and Production Optimization“. In SPE Symposium: Artificial Intelligence - Towards a Resilient and Efficient Energy Industry. SPE, 2021. http://dx.doi.org/10.2118/208647-ms.
Der volle Inhalt der QuelleBermudez, Fernando, Noor Al Nahhas, Hafsa Yazdani, Michael LeTan und Mohammed Shono. „Unlocking the Potential of Electrical Submersible Pumps: The Successful Testing and Deployment of a Real-Time Artificially Intelligent System, for Failure Prediction, Run Life Extension, and Production Optimization“. In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207839-ms.
Der volle Inhalt der QuelleMiller, Richard J., und Reginald D. Conner. „Field Validation Testing of New HEAT™ Steam Turbine“. In ASME 2006 Power Conference. ASMEDC, 2006. http://dx.doi.org/10.1115/power2006-88202.
Der volle Inhalt der QuelleBlack, J. T. „Lean Manufacturing Cell Design“. In ASME 1996 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 1996. http://dx.doi.org/10.1115/imece1996-0773.
Der volle Inhalt der QuelleKasim, Fadzlin Hasani, Nurul Nadhira Idris, Saeed Majidaie, Budi Priyatna Kantaatmadja, Numair Ahmed Siddiqui, Akhmal Sidek und Nur Aqilah Nabila Yahaya. „The Utilization of Machine Learning Method to Predict Hydrocarbon Flow Rate for a Better Reservoir Potential Evaluation“. In International Petroleum Technology Conference. IPTC, 2022. http://dx.doi.org/10.2523/iptc-22025-ms.
Der volle Inhalt der QuelleLiao, Leo, und Ang Li. „An Intelligent System to Automate the Inquery in Logistics Industry using AI and Machine Learning“. In 8th International Conference on Natural Language Processing (NATP 2022). Academy and Industry Research Collaboration Center (AIRCC), 2022. http://dx.doi.org/10.5121/csit.2022.120109.
Der volle Inhalt der QuelleAnderson, Joel, Nathan Switzner, Jeffrey Kornuta und Peter Veloo. „Incorporating Measurement Uncertainty Into Machine Learning-Based Grade Predictions“. In 2022 14th International Pipeline Conference. American Society of Mechanical Engineers, 2022. http://dx.doi.org/10.1115/ipc2022-87347.
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