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Description
YAR207-106-2F SKFTechnische Basisdaten Hersteller: SKF Synonym: 56207. 106 Abdichtung: Abdichtung: und Schleuderscheibe an beiden Seiten Auendurchmesser: 72 mm Berechnungsfaktor: f0: 14 ueres Breitenma: 42,900 mm Einlagering: RIS 207 A Ermdungsgrenzbelastung: 0. 655 kN Gewicht: 442 Gramm Grenzdrehzahl1): 5 300 r min Herstellungsland: Italien Stellschraube: G2: 5 16 24 UNF Zolltarifnummer: 8482 1090 Erweiterte technische Daten ueres Breitenmae:(D) mm 72,00 ueres
Technische Basisdaten
| Hersteller: SKF |
| Synonym: 56207.106 |
| Abdichtung: Abdichtung: und Schleuderscheibe an beiden Seiten |
| Außendurchmesser: 72 mm |
| Berechnungsfaktor: f0: 14 |
| Äußeres Breitenmaß: 42,900 mm |
| Einlagering: RIS 207 A |
| Ermüdungsgrenzbelastung: 0.655 kN |
| Gewicht: 442 Gramm |
| Grenzdrehzahl1): 5 300 r/min |
| Herstellungsland: Italien |
| Stellschraube: G2: 5/16-24 UNF |
| Zolltarifnummer: 8482 1090 |
Erweiterte technische Daten
| Äußeres Breitenmaße:(D) mm 72,00 |
| Äußeres Breitenmaße:(B) mm 42,90 |
| Einzelgewicht in (kg): 0.46 |
| Innenmaße:(d) mm 34,93 |
| Spezialbehandlung: Keine Spezialbehandlung |
| 72 mm Außendurchmesser |
| Art der Abdichtung: Contact, standard |
| Außendurchmesser 72 mm |
| Beschichtung Ohne |
| Äußeres Breitenmaß, gesamt 42.9 mm |
| Dynamische Tragzahl 25.5 kN |
| Dynamische Tragzahl: 25.5 kN |
| Einlagering Ohne |
| Einzelgewicht 0.435 kg |
| Grenzdrehzahl 5 300 r/min |
| Nachschmierfunktion Für |
| Schmierstoff: Fett |
| Statische Tragzahl 15.3 kN |
| Statische Tragzahl: 15.3 kN |
| UNSPSC-Code 31171536 |
| eClass-Code 23-05-08-02 |
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4.5 ★★★★★
Based on 15 reviews
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Product Reviews
★★★★★ 5
A good book for Cyber Professionals
Format: Paperback
A very good book, I absolutely love how it gives security professionals much needed AI security insights.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on January 16, 2026
★★★★★ 5
In-depth and highly technical!
Format: Paperback
"Adversarial AI Attacks, Mitigations, and Defense Strategies" by John Sotiropoulos is a must-have resource for cybersecurity professionals navigating the complexities of AI security.
This book is an incredibly in-depth guide that tackles the intricate details of defending AI systems from adversarial attacks. It’s highly technical, making it an excellent choice for those with a solid background in cybersecurity, machine learning, and system administration. Sotiropoulos doesn’t shy away from the details, providing comprehensive code examples, system admin settings, and scripts that are invaluable for practical implementation.
One of the standout aspects of this book is its coverage of both predictive and generative AI. This dual focus ensures that readers are well-equipped to handle security challenges across different AI applications. Whether you're dealing with machine learning models in a predictive context or exploring the relatively newer field of generative AI, this book has you covered.
If you’re looking for a technical, hands-on approach to securing AI systems, this book is an essential addition to your library.
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Reviewed in the United States on August 12, 2024
★★★★★ 4
Good and thorough!
Format: Paperback
I was amazed to see a thick book arriving in the package and spent quite some time reading this. The book is so hands-on. I build agentic systems at work and going through these concepts felt good. My only complaint is that the code snippets are not up to date for which I had to edit my code several times.
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Reviewed in the United States on May 9, 2026
★★★★★ 5
Amazing book
Format: Paperback
Excelent product
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Reviewed in the United States on November 4, 2025
★★★★★ 5
solid read with walk through
Format: Paperback
There is limited material on this topic and I am about 4 chapters in and I have enjoyed the walkthrough on setting up a lab as the background... will update as I continue through the book.
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Reviewed in the United States on October 18, 2024