MEMXPRO Launches Durable 3D TLC Industrial SSDs with 10K P/E Cycles and 4‑Year Warranty

MEMXPRO announced the launch of a new industrial 3D TLC SSD family at Embedded World 2019, featuring the PT30 (with DRAM) and ET30 (without DRAM) models. Both drives are built on SMI controllers and Micron’s proprietary B17A 3D TLC flash, engineered for 10,000 program/erase cycles and backed by a four‑year warranty.

The event also highlighted MEMXPRO’s high‑speed U.2 PCIe and M.2 2280 PCIe PT33 series, which incorporate the same rugged 3D TLC NAND and support capacities up to 4 TB. These SSDs are paired with wide‑temperature DDR4‑2666 MHz DRAM modules, delivering reliable performance across industrial temperature ranges.

Designed for the AIoT market, the new NVMe PCIe PT33 and SATA 3 PT30/ET30 SSDs combine Micron’s 10,000‑cycle endurance with enhanced data‑protection features. The result is improved endurance, retention, and overall durability—making them ideal for embedded systems, industrial machinery, and edge computing platforms that must operate reliably in harsh environments.

As flash density rises, high‑capacity SSDs are becoming standard in industrial data workflows. MEMXPRO’s E231 line extends this trend, offering 2.5‑inch SSDs up to 4 TB, mSATA and Half‑Slim variants up to 1 TB, and CF cards up to 256 GB. All models meet JEDEC standards, feature MLC flash with 3,000 P/E cycles, and include industrial‑grade temperature ICs for extended reliability.

In line with industry momentum, MEMXPRO’s DDR4‑2666 modules meet JEDEC specifications and operate at a low 1.2 V, ensuring energy efficiency and thermal stability. With a wide temperature range of –40 °C to +85 °C, these modules are suited for extreme‑climate applications where performance consistency is critical.

MEMXPRO’s mSMART 4.0 software, available free for download, offers intuitive device monitoring and predictive analytics. By integrating with enterprise databases, the tool logs SSD health data, alerts operators to impending failures, and reduces maintenance costs through data‑driven decision making.