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The pace of technical innovation, development, and adoption is continuing to accelerate. New emerging technologies are disrupting industries and approaches to test and measurement. And new technologies are being developed more quickly than ever before.

Last year the cellular industry began to roll out 5G networks and phones to the global market, and we are ramping up the deployment of 5G mmWave. This network's full deployment will realize many of the promises presented for 5G years ago. However, in the midst of this, researchers and technologists worldwide are already starting to map out what 6G could look like.

It's no secret that industry leaders are racing to be first to market with their products. But if they don't take the time to ensure quality and reliability, they will encounter issues down the road that could be detrimental to their business. Many semiconductor companies feel this tension creating economic and organizational challenges. They can start addressing these challenges by testing more and expanding test into design, characterization, and production test phases. But this means finding a balance between cost and development time. But what if we can imagine product performance and reliability data being captured early and often? What if we were able to capture product use data, identify common failure modes, and use that to influence measurements done during product characterization? That vision is within reach!

"We are seeing a trend among semiconductor companies of modernizing their labs and changing their approach to validation and characterization"

We are seeing a trend among semiconductor companies of modernizing their labs and changing their approach to validation and characterization. Currently, data is collected and needs to be compared across all stages of development and production. Electronic Design Automation tools capture data about device behavior in the simulation and modeling step. Test equipment captures data during device characterization and validation as well as production test. To ensure that devices perform as designed, data from the design step need to be compared to data captured during characterization. This then needs to be compared to production test data. The comparison and validation from all of these steps can push out the product release, and if issues are found too late in production, more iterations are needed.

Leading semiconductor organizations lean on a couple key best practices to help mitigate the time and cost associated with more testing. The first is standardization of hardware and software across all stages of the product development workflow. This speeds up the process of sharing and comparing data and increases engineering efficiency. The second, and possibly the most critical, best practice for the modern lab is incorporating automation. Moving from manually configuring tests to an automated approach saves time and maintains consistency between tests. Our customers see anywhere from a 5-10x increase in speed from automation.

NI’s vision is to accelerate semiconductor product development with software. Through our investments in partnerships with companies like Soliton, Mathworks and Maxlinear and our continued focus on providing software-connected Validation and Production test solutions, we aim to reduce time to market and cost of test for semiconductor companies. Our acquisition of Optimal + gives us access to key artificial intelligence technologies to apply to our data analytics tools. We believe these investments will enable predictive test, increased production, and improved time to market. The pace of innovation shows no sign of slowing; we believe that we can help companies keep up by allowing engineers to seamlessly transition from one phase of product development to the next through a software-connected approach.