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The recent explosion in consumer electronics technology is amazing. Today, over one third of Americans own a smartphone. However, as the complexity and functionality of these devices grow exponentially (as promised by Moore’s law), so too does the cost of testing them. Finding ways to minimize the cost of test can be a challenge, but one way is to test more with less.
Fortunately, Moore’s law works in our favor as well—while gadgets have gotten more complex, test equipment has grown smarter. For example, the PXI platform, by taking a software-defined approach to test, gives the next generation of testers greater flexibility, functionality, and performance at a smaller size and lower cost. By taking advantage of software-defined instrumentation, test engineers can translate advancements in PC technology (such as faster processors with multiple cores) into tangible improvements on test performance.
With the built-in parallel testing capabilities of NI TestStand, you can test multiple devices in parallel and easily increase the overall performance of your test system. Efficiently testing multiple devices simultaneously on each test system lowers the number of test systems you need. This reduces not only the up-front capital cost of the test equipment but also the space and power requirements.
An Example: Testing Smartphones
Assume that you are testing smartphones and running three different tests on each: (1) a power consumption test that uses a programmable source measure unit (SMU), (2) a GSM test that uses an RF vector signal generator (VSG), and (3) an audio quality test that uses a dynamic signal analyzer (DSA). Pretend that each of these tests takes one unit of time to execute.
Figure 1. The NI PXIe-1075 is an example of a PXI automated test system with a VSG, SMU, DSA, and the required switches.
On a typical test system that tests one phone at a time sequentially, you would test phones at a rate of one device under test (DUT) every three units of time. Testing three phones would take nine (3 x 3 = 9) units of time.
The sequential test example in Figure 2 shows that each test instrument is left unused for six of nine time units. That’s a 66 percent downtime per instrument! Imagine how much more efficient your test system could be if you use this downtime to start testing the next phone. This is precisely what you can do with parallel testing.
Figure 2. Testing three phones sequentially takes nine units of time whereas testing three phones with autoscheduling takes only three units of time and optimizes instrumentation use.
Parallel Testing: Increase Instrument Utilization
An easy way to increase your instrument usage and test your devices more efficiently is to test multiple devices in parallel (that is, simultaneously) using the same set of instruments. The National Instruments automated test platform provides all the tools, both hardware and software, that you need.
From a hardware perspective, a switch helps you connect your test instruments, such as the DSA and SMU, to multiple DUTs and switch between connections programmatically. For instance, you can control which smartphone is connected to the DSA at any given time. NI offers a variety of PXI-based switches (including RF switches) with a variety of topologies to meet just about any application need.
From a software perspective, NI TestStand, the ready-to-run test management software provides built-in process models (execution configurations) for parallel testing so you can easily migrate to testing multiple devices in parallel with minimal changes to your existing test code. NI TestStand is thread-safe, and features standard synchronization constructs like locks, semaphores, and more. In addition, NI TestStand integrates with NI Switch Executive to give you the ability to graphically configure your switch routes.
Now modify the previous example so that your test fixture accommodates three smartphones simultaneously. By adding switching to your test system, and turning on parallel testing in NI TestStand, you can now test these three phones in parallel (as shown in the parallel test example in Figure 2).
You are now testing the three phones in five units of time, reducing test time by 44 percent. In addition, each instrument is idle for only two units of time, meaning that instrument downtime is reduced from 66 percent to 40 percent. The waterfall or pipelining effect is due to the fact that each instrument can test only one smartphone at a time and that the tests are statically configured to run in a particular sequence (power followed by GSM and then audio).
Autoscheduled Parallel Testing: Intelligent Test Sequencing
You can further optimize your test system by taking advantage of autoscheduling, a feature in NI TestStand that automatically reorders tests during execution based on which instruments are free. The tests that are allowed to be reordered are set by you, the developer, so that you can still force certain tests or actions to run in a specific order (this is important for setup and cleanup processes).
Because NI TestStand can intelligently reorder the tests, you can eliminate the pipelining effect seen earlier. You can now test all three phones in just three units of time—the same amount of time it took to test a single phone earlier. You’ve effectively reduced your test time by 66 percent, and you’re making the most of your instruments by cutting instrument downtime to zero.
The bottom line is that by taking advantage of the advanced parallel testing capabilities of NI’s software-defined automated test platform, you can use one set of instruments (that is, one test station) to test multiple devices in parallel. This in turn means you can test the same number of phones with fewer test stations, thereby drastically reducing the capital cost of test equipment without sacrificing test throughput.
Jervin Justin is a product marketing manager for automated test software at National Instruments. When he’s not creating NI TestStand demos, he actively supports Texas A&M University’s football team.
Download and execute a software-only demonstration of parallel testing and autoscheduling.
This article first appeared in the Q1 2012 issue of Instrumentation Newsletter.
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