SKU: 12807673605

Makita DLX 2278 Y1J Akku Kombo Kit + DHP 484 Schlagbohrschrauber 54 Nm + DHR 171 Bohrhammer 1,2 J + 1x Akku 1,5 Ah + Makpac - ohne Ladegerät

$163.27 $181.41
Save 10%
No.2 Bestseller on 2pierres.com >

Pay in installments of $45.35 with ShopPay, AfterPay and Klarna

Shipping Estimate
USA
  • USA
  • CAN

Ships within 48 hours · Estimated delivery Jul 24 - Jul 29

Promo Codes Available:

For Your Every Summer RSVP, with Code: SUMMER15

Description

Makita DLX 2278 Y1J Akku Kombo Kit + DHP 484 Schlagbohrschrauber 54 Nm + DHR 171 Bohrhammer 1,2 J + 1x Akku 1,5 Ah + Makpac - ohne LadegerätLieferumfang: 1x Makita DHP 484 Z Akku Schlagbohrschrauber 1x Makita DHR 171 Z Akku Bohrhammer 1x Makita BL 1815 N Akku 18 V 1,5 Ah 1x Makita Makpac Koffer 1x Universaleinlage ohne Ladegert Produktbeschreibung: Der Makita DHP 484 ist ein hochleistungsfhiger Akku Schlagbohrschrauber, der sich ideal fr vielseitige Schraub und Bohrarbeiten eignet. Ausgestattet mit einem brstenlosen 18 V Motor und einem robusten 2 Gang Vollmetall Planetengetriebe, bietet

Lieferumfang:

- 1x Makita DHP 484 Z Akku Schlagbohrschrauber
- 1x Makita DHR 171 Z Akku Bohrhammer
- 1x Makita BL 1815 N Akku 18 V 1,5 Ah
- 1x Makita Makpac Koffer
- 1x Universaleinlage
- ohne Ladegerät

Produktbeschreibung:

Der Makita DHP 484 ist ein hochleistungsfähiger Akku-Schlagbohrschrauber, der sich ideal für vielseitige Schraub- und Bohrarbeiten eignet. Ausgestattet mit einem bürstenlosen 18 V Motor und einem robusten 2-Gang-Vollmetall-Planetengetriebe, bietet dieses Werkzeug eine beeindruckende Flexibilität für unterschiedliche Anwendungen. Das Gerät verfügt über ein Schlagwerk, das sich je nach Bedarf abschalten lässt und ein maximales Drehmoment von 54 Nm erreicht, welches in 21 Stufen plus einer Bohrstufe einstellbar ist. Besonders praktisch sind die kompakte Bauweise mit einer Gehäuselänge von nur 182 mm und das wartungsfreie, langlebige bürstenlose Motor-Design. Für Arbeiten in schlecht beleuchteten Bereichen ist der Schlagbohrschrauber mit einem leuchtstarken LED-Licht ausgestattet, das sogar eine Nachglimmfunktion hat. Die Sicherheit wird durch einen Tiefentladeschutz erhöht, der das Gerät automatisch abschaltet, wenn der Akku fast leer ist. Das Schnellspannbohrfutter ermöglicht schnelle Wechsel zwischen Schrauben und Bohren, während die einfache Einhand-Umstellung des Rechts-/Linkslaufs den Bedienkomfort erhöht.

Der Makita DHR 171 Akku-Bohrhammer zeichnet sich durch sein kompaktes Design dank des bürstenlosen Motors aus, das sowohl zum Bohren als auch zum Hammerbohren geeignet ist. Dieses Gerät ist besonders praktisch, da es mit einer vibrationsarmen Konstruktion von Gehäuse und Handgriff sowie einer SDS-PLUS Aufnahme ausgestattet ist. Mit einer Einzelschlagstärke von bis zu 1,2 Joule ermöglicht der Bohrhammer effektive Bohrungen in Beton bis zu einem Durchmesser von 17 mm. Die kompakte und kurze Bauform macht den Bohrhammer besonders handlich. Für kontinuierliche Leistung sorgt die Konstantelektronik, während eine leuchtstarke LED mit Nachglimmfunktion für optimale Sicht beim Arbeiten sorgt. Sicherheitsmerkmale wie integrierte Temperaturüberwachung, Überlastschutz und Tiefenentladeschutz gewährleisten eine lange Lebensdauer des Geräts und schützen vor Schäden durch Überbeanspruchung oder zu tiefe Entladung des Akkus. Zusätzlich verfügt das Gerät über eine elektronisch regelbare Drehzahl und schaltet sich automatisch ab, sobald der Akku fast leer ist, um eine Tiefenentladung zu verhindern.

Technische Daten:

- Hersteller: Makita
- Herstellerbezeichnung: DLX 2278

DHP484:

- Spannung: 18 V
- Drehmoment weich: 30 Nm
- Drehmoment hart: 54 Nm
- Leerlaufdrehzahl 1. Gang: 0-500 min-1
- Leerlaufdrehzahl 2. Gang: 0-2000 min-1
- Leerlaufschlagzahl 1. Gang: 0-7500 min-1
- Leerlaufschlagzahl 2. Gang: 0-30000 min-1
- Bohrleistung in Holz: 38 mm
- Bohrleistung in Stahl: 13 mm
- Bohrleistung in Mauerwerk: 13 mm
- Bohrfutterspannweite: 1,5 - 13 mm
- Maße (LxBxH): 189x79x244 mm
- Gewicht ohne Akku: 1,6 kg
- Schalldruckpegel (Lpa): 88 dB(A)
- Schallleistungspegel (Lwa): 99 dB(A)
- K-Wert Geräusch: 3 dB(A)
- Vibration Bohren Metall: 2,5 m/s^2
- K-Wert Vibration: 1,5 m/s^2

DHR171:

- Spannung: 18 V 
- Einschlagenergie: 1,20 Joule
- Werkzeugaufnahme: SDS plus
- Motorart: bürstenlos 
- Max. Leerlaufdrehzahl: 0-680 UpM 
- Max. Schlagzahl: 4.800 1/min 
- Bohrdurchmesser Beton: Ø 17 mm 
- Bohrdurchmesser Holz: Ø 13 mm 
- Bohrdurchmesser Stahl: Ø 10 mm
- Gewicht ohne Akku: 1700 g
- Schalldruckpegel: 86 dB(A)
- Schallleistungspegel: 97 dB(A)
- Messunsicherheit (K): 3 dB (A)


Bei gewerblicher Nutzung beachten Sie bitte die Bauvorschriften!

Shipping Notes
  • Free Standard Shipping on $100+ Orders to the USA.
  • Except Preorder products are shipped in 48 hours.
  • Delivery to the USA:
  1. Standard Shipping : 3-10 business days
  • If time is of the essence, please consider selecting expedited delivery for faster service.
Exchange/Return Notes
  • We offer a 30-day return/exchange service after receiving.
  • Final sale items are not eligible for returns or exchanges.
  • To process your return/exchange, please contact us at [email protected]
  • Please click here for more details>>> Return & Exchange Policy
SKU: 12807673605

Discover Niche Categories That Outsell

Top-Converting Item to Boost Your Average Order

4.0 ★★★★★
Based on 21 reviews
Sort
Highest Rating
Newest First
Oldest First
Product Reviews
S
Verified Purchase
Shannon
New York, US
★★★★★ 5
The best DL/ML book I have ever seen!!
Format: Hardcover
Fantastic deep-learning book! The logic is very easy to follow, but the content is very thorough when it comes to explaining the theories behind it, making it perfect for beginners as well as math and CS students. The best DL/ML book I have ever seen!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on November 30, 2025
W
Verified Purchase
William P Ross
Phoenix, US
★★★★★ 5
Comprehensive Look At An Incredibly Complex Topic
Format: Hardcover
Deep Learning is an advanced book with great explanations and details. There is a heavy math focus with the book's beginning chapters detailing the necessary linear algebra and probability that one will need to understand deep learning. I liked that the author's chose to cover only the parts of these subjects which are relevant to deep learning. There are many interesting philosophical sections in the book as well. Just about when I was feeling overwhelmed with the complexity of the mathematics the authors take a step back and cover the foundations of deep learning such as borrowing concepts from human learning. There was an interesting dicussion about the early studies done on the vision of cat's and monkey's in the 1970s. The text covers the entire history of deep learning and the bibliography is hundreds of sources. It is clear this is the most comprehensive text available about deep learning. For anybody interested in this topic this book is a mandatory read. There are sections about machine learning as well, which makes sense because deep learning is a subset of machine learning. These sections focused on the machine learning concepts which are most relevant to deep learning. The book was well organized and divided into three parts which cover mathematics related to deep learning, typical deep learning techniques, and then more experiment learning techniques. Often the author's state when a technique works well or when it does not, and which types of data works best for the technique. Just a warning, the math in this book is highly complex. It requires a lot of work to go through this book, but the effort will be well rewarded.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on March 15, 2017
A
Verified Purchase
Adam
West Palm Beach, US
★★★★★ 4
Too Dry.
Format: Hardcover
This was a required textbook for my class in college. I think it was too dry. The book titled Deep Learning: From Curiosity To Mastery is much more approachable.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 22, 2026
A
Verified Purchase
Amazon Customer
Chelsea, US
★★★★★ 5
Comprehensive! The Bible of Deep Learning!
This book has by far surpassed my expectations! I have purchased many machine learning and deep neural network books in the past, but nothing has ever come close to this book! First of all, it is written by the fathers of Deep Learning, and is therefore an authority. Secondly, the book is broken into three parts: 1. A math overview and refresher. 2. Deep Learning applications and 3. Research in Deep Learning. I can't help but go through this book from front to back. It is a smooth read, and every sentence written is meaningful. These guys know their stuff! And after you read this book, YOU WILL ALSO know your stuff! If you feel daunted by the price, just remember, you get what you pay for! I'd say they could easily charge about $300+ for this book, but they are doing everyone a very kind favor by ONLY charging this reasonable amount. You get A LOT of bang for your buck with this purchase. I hesitated at first about buying this book because of the price, but I am soooooo happy that I did! Worth every penny! Look no further, get this book and start your Deep Learning journey!!
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on July 14, 2017
M
Verified Purchase
mackster
Waukegan, US
★★★★★ 1
A rushed, poorly written guide of how the "experts" can't really explain what Deep Learning is
Format: Hardcover
This book, in every sense of the word, is rushed. I think the authors wanted to establish themselves as leaders of this young-ish field, but does so by sacrificing quality. It also shows that Deep Learning theory has been there for a long time, known by another name called Neural Networks. The interesting algorithms are of MLP, Back Propagation and the classical neural networks. The optimization methods such as Adam are the ones that are new and interesting, and the only ones worthy of in this book. So, essentially, what you get from this book is use A for X, B for Y and C for Z type of dry, un-intuitive, badly written waste of paper. As for the structure of the book, it's like an example of how not to structure a book. It has some linear algebra, probability at the start (not good enough, and confuses more people and wastes paper). Goes on to prove other algorithms such as PCA (yeah, ok!). Then, talks about how this architecture works for this and that architecture. So, yeah, if you really want to try out deep learning, don't buy this book. Set up Tensorflow/pytorch/ other library, run the tutorials, find an architecture for the problem you are interested in and start tweaking that. You will have far more fun and would have saved your money. The praise that this book gets is beyond me. Did Musk even read this book? I doubt it.
WAS THIS REVIEW HELPFUL?YesReportShare
Reviewed in the United States on May 15, 2018

recommand products

Polyesterjacke Iconic
27.00
Condivo 22 Polo AH
29.50
Polyesterjacke Champ 2.0
27.00
Entrada 22 Track Jacket
30.50
LIGA Baselayer Tee LS
22.50