Reflecting the advanced trends in global scientific research, the NIWeek 2019 EIA Awards are announced | Free report download

PXI also performs well in the semiconductor field. In the semiconductor manufacturing process, it is very important to conduct accurate wafer-level parameter testing to discover process-related problems in the early stages, and it can also optimize the R&D process, reduce costs, and shorten manufacturing time. IME created a highly parallel, PXI-based wafer-level parameter measurement system by using multiple PXIe-4135 SMUs in a SMU-per-pin parallel architecture. The development team uses LabVIEW to easily synchronize and control PXI instruments, probe stations, and automatic wafer loaders, and simultaneously record, analyze, and mark measurement data.

Let's continue with the award-winning projects in the semiconductor field. Samsung used multiple PXI-5172 oscilloscopes, an FPGA co-processing module, and a high-capacity RAID array to build a highly parallel measurement system that can independently trigger and synchronously measure the response of 120 PMIC outputs. What does this mean? Using a highly parallel and highly automated PXI test system, Samsung collected test results in three days, 10 times faster than the previous solution!

The increasing complexity of automotive electronic components has brought great challenges to testing. By making full use of the NI platform, Mazda, together with the MAC system, built a semi-physical (HIL) system consisting of PXI products, FPGA modules, and LabVIEW. The team integrated additional elements such as noise simulators, GPS simulators, and speech synthesis to integrate a complete automated processing system. I believe that the more complex automotive electronic devices will be, the simpler it will be with the NI test platform.

Volvo Cars uses a PXI Express 8-core controller running VeriStand software to conduct real-time testing with off-the-shelf IPG CarMaker hardware and vector devices to achieve configurable data acquisition and recording, test sequencing, and simulation model integration. This breakthrough will reduce the cost of expensive physical field testing, while saving more time for innovation and greatly shortening the development time of simulators.

Imagine what it would be like for a paralyzed or mobility-impaired person to climb Ras Dashan (Ethiopia's highest peak) in person? A team of student developers at the University of Southampton has made this fantasy a reality. The team uses CompactRIO as the main control unit for the manual wheel, monitoring solar power generation and battery management, while also controlling the motor in a closed loop, which will allow even those with mobility impairments to embark on an unprecedented mountaineering adventure! The good news is that in 2020, the team will also launch another new outdoor wheelchair specifically for Gobi Desert expeditions.

When taking medicine, have you ever thought that one day the medicine itself can be a doctor and diagnose yourself? Recently, researchers combined a series of NI hardware (including PXI Express, CompactRIO, myRIO and FlexRIO) to make this imagination a reality. This is an inhalable ultrasonic endoscopic capsule, Sonopill, which uses advanced microelectronic sensors to perform advanced health diagnosis when it passes through the patient's gastrointestinal tract. It is worth mentioning that researchers are using the NI platform to move from preclinical measurements to human testing and eventually into clinical use, where it will bring good news to millions of patients with gastrointestinal diseases.

I believe that no one likes blue screens and computer viruses... In fact, this is also true in the medical field. In IoT medical devices, malicious cyber attacks such as insulin pumps, brain stimulators, and pacemakers often cause irreparable damage to the safety and privacy of patients.

By using NI programmable hardware and the LabVIEW FPGA module, Hiller Measurements quickly built a neural network-based multi-layer perception model for real-time medical device security. Moreover, this FPGA-optimized neural network can maximize security accuracy by operating on 10 different inputs (such as age, BMI, and blood pressure). They achieved an incredible 98.1% accuracy rate in distinguishing between reliable and malicious communications. In addition to the chat field, the project is also moving into other hot information-physical system applications, such as driverless cars.

I believe that you must have been frequently bombarded with 5G and IoT technology applications in recent years, but in fact, while 5G is realizing large-scale IoT devices, power supply is a thorny issue. By integrating LabVIEW into a power beacon, using a USRP-2920 software-defined radio device as an RF signal source and VirtualBench All-in-One fully integrated instrument, the LRWE long-distance power transmission project provides a new way to wirelessly charge built-in batteries from a long distance. Compared with traditional battery replacement methods, this solution will greatly save time, complexity and cost.