ML63Q2537-NNNTBZWBY

ROHM Semiconductor
755-ML63Q2537NNNTBZW
ML63Q2537-NNNTBZWBY

Mfr.:

Description:
32-bit Microcontrollers - MCU Solist-AI, 32-bit Microcontroller (Arm Cortex-M0+)

Lifecycle:
New Product:
New from this manufacturer.
ECAD Model:
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In Stock: 937

Stock:
937 Can Dispatch Immediately
Factory Lead Time:
20 Weeks Estimated factory production time for quantities greater than shown.
Minimum: 1   Multiples: 1
Unit Price:
-,-- €
Ext. Price:
-,-- €
Est. Tariff:

Pricing (EUR)

Qty. Unit Price
Ext. Price
11,26 € 11,26 €
8,55 € 85,50 €
8,20 € 205,00 €
7,22 € 722,00 €
6,87 € 1.717,50 €
6,85 € 3.425,00 €
Full Reel (Order in multiples of 1000)
5,82 € 5.820,00 €

Product Attribute Attribute Value Select Attribute
ROHM Semiconductor
Product Category: 32-bit Microcontrollers - MCU
ML63Q2500
SMD/SMT
TQFP-48
ARM Cortex-M0+
256 kB
16 kB
32 bit
12 bit
32.768 kHz
34 I/O
2.3 V
5.5 V
- 40 C
+ 105 C
Reel
Cut Tape
Brand: ROHM Semiconductor
Data RAM Type: RAM
Interface Type: I2C
Moisture Sensitive: Yes
Number of ADC Channels: 12 Channel
Number of Timers/Counters: 1 x 16 bit
Product: 32-bit Microcontrollers
Product Type: 32-bit Microcontrollers - MCU
Program Memory Type: Flash
Factory Pack Quantity: 1000
Subcategory: Microcontrollers - MCU
Tradename: Solist-AI
Watchdog Timers: Watchdog Timer
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TARIC:
8542319000
USHTS:
8542310025
ECCN:
3A991.a.2

ML63Q2500 AI-Equipped Microcontrollers

ROHM Semiconductor ML63Q2500 AI-Equipped Microcontrollers (MCUs) provide a network-independent solution for early anomaly detection before equipment failure. This contributes to more stable and efficient system operations by decreasing maintenance costs and the risk of line stoppages. These devices adopt a simple three-layer neural network algorithm to implement ROHM's proprietary on-device AI solution, Solist-AI™. This feature allows the MCUs to independently perform AI learning and inference without cloud or network connectivity. The modules integrate a 32-bit Arm® Cortex®-M0+ processor, ROHM's proprietary AI accelerator AxlCORE-ODL, and a variety of peripheral circuits. The ML63Q2500 MCUs permit real-time operational status monitoring while avoiding network latency issues and security risks. With a low 40mW power consumption during AI processing, the series is ideal for anomaly detection and predictive maintenance in industrial applications.