The Race to Accelerate Your Lab

Digital transformation is more than a buzzword, especially these days. The truth remains: If you’re not already working toward the latest technologies, you’re behind. Test and product development has a faster pace—and has more volatile conditions—than ever before. Companies need to constantly work to keep up with, and outperform, their competitors. This leads to a rapidly evolving rate of innovation that creates shorter, more aggressive market schedules. All the while, the measurements themselves grow in complexity. Products need increased test coverage on more complex designs.

So, how can we deal with this pressure cooker of demands?

We’re past the point of holding back and clinging to the familiar. It’s time to put our foot on the gas pedal and drive full speed towards innovation!

The Race as We Know It Today

It can feel safer, and certainly more comfortable, to stick to processes and technologies you’ve been successfully using for years. After all, the phrase “If it ain't broke, don’t fix it,” may be all too familiar. But in today’s marketplace, you must keep up with the pace of innovation. If you aren’t seamlessly testing new technologies, you’re falling behind on the intricate measurements needed to test products that have become more complicated across the board.

Ten years ago, when characterizing a 4G RF front-end module, engineers probably had fewer than 75 test cases. Today’s 5G front-end modules have 600 test cases. Each has a different combination of radio band, carrier bandwidth, and waveform type. Shifting from 4G to 5G presents the clear need for greater test coverage with more complex measurements. For 5G mmWave devices, the incorporation of antenna-in-package technology eliminated physical connections to access the mmWave signal. As a result, many 5G mmWave devices require over-the-air (OTA) testing, a completely new test methodology. What’s more, major “5G Advanced” enhancements like the increased coexistence between networks (that is, Wi-Fi and non-terrestrial) and evolved duplexing may result in twice as much design complexity growth compared to 5G devices today.

With such an increase in product complexity, it feels appropriate to allow engineers more time to analyze the additional intricate measurements. But that’s not the reality we live in. Teams are being asked to do more with less, and product schedules don’t typically allow for increases in validation or characterization times. Timelines remain the same as before—and in many cases, they are even tighter. The solution to this issue isn’t more time or more engineers, but rather optimizing performance. Shorter market windows along with the need to test devices more extensively require engineers to streamline their processes and find opportunities to increase productivity.

Powering Your Engines

The need to enhance productivity is only going to grow, and elevating the tools in your lab is the answer. Any inefficiencies—even the smallest ones—can significantly impact release dates. Streamlining the engineering workflow has become more important than ever. The challenge is setting up teams for success. To keep up, they need to be well-oiled machines with no room for bottlenecks. That’s where we look for software-connected solutions to help in three main areas.

• Eliminate siloed data that creates repeated work and wasted time.
• Remove time-consuming manual workarounds by connecting tools.
• Embrace automation to save time and steps in the process.

From the substantial amount of setup time required by nonautomated environments to the highly manual nature of correlating inconsistent data, seemingly minor inefficiencies can prevent companies from delivering products to market quickly. However, even small adjustments can generate significant impacts that help teams reach aggressive market schedules. Agile organizations that proactively address inefficiencies in their workflows today will be strong market players tomorrow.

Data Is the Gasoline

When you hear about the need to innovate your lab, you might make a huge leap to radical processes and futuristic technologies. While those things are certainly part of the conversation, a lot of digital improvements you can make deal with something you already have a lot of—data.

Each step in the development process generates a great deal of data, but managing and developing the right strategy for your data throughout the design process can be difficult. This is where there is opportunity to turn to a modern “pit crew” for help. A common software framework can source consistent data, while a product analytics solution can generate actionable insights. Regardless of what solutions you employ, the important part is taking advantage of all the deeper product insights you can gain by connecting data gathered during various stages of development. The information from this data can improve productivity and accelerate product development. Data management and analytics tools are increasingly critical as product complexity escalates with each generation.

Revving Up Your Lab

While it might be tempting to go from 0 to 100, accelerating innovation begins with small steps. What seems like simple changes can—and will—add up. Plus, taking things slowly at first will allow your team to adjust to new processes and tools. What is important is taking the first steps.

Best practices would suggest tackling automation as a first step. While that’s not wrong, often the main cause of duplication is the lack of collaboration and communication across teams. Teams can get stuck in the status quo of disconnected systems that make collaboration difficult. It’s easy to get used to bottlenecks, but it doesn’t have to be that way. Sharing both test software and test methodologies across sites can save a substantial amount of development and validation time.

Companies that adopt a common software framework ultimately reduce engineering costs and shorten design schedules. This approach helps streamline validation workflows by increasing code reuse, expanding measurement coverage, and using measurement data better. The result is a faster development cycle to achieve business objectives.

Steps to Address:

• Take a critical look at your test systems to identify bottlenecks and see where collaboration struggles.
• Review manual systems and look for areas to automate.
• Migrate from a highly manual environment to automate and sequence individual character tests.
• Develop a common test management and automation framework that is scalable with modular, reusable tests that can be shared worldwide.

A customer that took these steps to standardize for this level of commonality saw the following results:

Getting in the Race

Your track to a future-proofed validation lab will be an evolving journey with many different pathways. Whether you’re taking your first steps to identify bottlenecks or deep into connected data analysis, every lab can become the next center of operational excellence in its organization.

Learn more about how validation lab innovations can increase your performance.