Electronics and Textile Engineering: Inside Tatiana Krasik's Innovative Approach

How an RF engineer's unique perspective is transforming testing methodologies across industries

According to recent analysis from FPGA Insights, as telecommunications companies race to expand 5G infrastructure globally, efficient testing systems have become a critical bottleneck in production pipelines. The rapid deployment of these networks has introduced unprecedented complexities in testing due to factors like diverse frequency bands, massive Multiple-Input Multiple-Output (MIMO) technology, and stringent requirements for ultra-low latency. Addressing these challenges, Tatiana Krasik, an Automated Test Equipment (ATE) System Developer at Ceragon Networks, recently developed innovative automated testing methodologies that reduced Radio Frequency (RF) module testing time by 50%, which proved instrumental in the successful market launch of the company's flagship IP-50EX platform for 5G backhaul. The innovation comes at a critical time as manufacturing facilities struggle to keep pace with the technical demands of next-generation wireless equipment. Krasik is now preparing to publish two scientific papers that expand on her mathematical models for RF testing, potentially transforming quality control processes industry-wide. Her distinctive background - applying electronic engineering principles to textile manufacturing and telecommunications - highlights how cross-disciplinary approaches can break through technical barriers that specialists often find insurmountable.

From your perspective working directly with 5G equipment development, how do you see the current state of the global 5G rollout, and what do you think are the biggest challenges telecommunications companies are facing right now?

What I observe from the engineering side is that companies are essentially trying to solve two problems simultaneously: scaling up production while managing unprecedented technical complexity. The 5G rollout has created a perfect storm where demand is skyrocketing, but the equipment itself is far more sophisticated than previous generations. Companies are investing billions, as you mentioned, but they're discovering that traditional manufacturing and testing approaches simply don't scale to meet the current demand. From my experience at Ceragon, I see that the real challenge isn't just building the equipment – it's ensuring consistent quality at volume. Every base station deployment represents a significant investment, and equipment failures in the field are exponentially more expensive than catching issues during testing. The pressure to accelerate deployment timelines while maintaining reliability has forced the industry to fundamentally rethink how we approach quality assurance. I believe we're at an inflection point where companies that can solve the testing efficiency problem will have a significant competitive advantage in capturing market share during this critical deployment phase.

You mentioned upcoming publications about your mathematical models for RF testing. Can you explain for non-specialists why mathematical modelling matters in equipment testing?

Most people think of testing as a purely practical activity – connecting the equipment, running the test, and checking the results. But the reality is far more complex, especially with advanced telecommunications equipment. Mathematical modelling allows us to understand the underlying physics of our testing and identify patterns that wouldn't be obvious through trial and error. For example, we discovered through our models that certain calibration steps were mathematically redundant under specific conditions. This insight wasn't intuitive—it emerged from the equations. By creating mathematical representations of the entire testing process, we could simulate thousands of scenarios to identify precisely where efficiencies could be gained without compromising accuracy. These models also allow us to predict how testing parameters might change as technology evolves, which is crucial in an industry where today's innovation is tomorrow's standard feature. In my upcoming papers, I'm extending these models to account for more variables and potentially eliminate even more unnecessary steps in the testing process.

Your automated test systems for RF modules at Ceragon Networks, a leading global provider of wireless backhaul solutions, were critical to the commercial success of the IP-50EX platform. What makes your approach to testing different from conventional methodologies?

I developed a somewhat unusual perspective in the telecommunications industry at Ceragon Networks. My engineering approach combines rigorous mathematical modelling with automated test implementation, but what truly sets it apart is the systematic analysis of the entire testing workflow. Traditional RF testing procedures require frequent recalibration, significantly slowing production processes. By redesigning the testing methodology to eliminate this requirement, we reduced testing time by approximately 50% while improving measurement consistency across units. This wasn't just a technical improvement – it directly translated to faster market delivery for the IP-50EX platform, which is crucial in the competitive 5G equipment space.

Your doctoral dissertation on textile manufacturing processes was quite unique and resulted in multiple patents. We understand that devices developed from your research are now operating in textile companies across multiple countries. How did your electronic engineering background enable you to approach textile manufacturing from such an innovative angle?

The real breakthrough was applying electronic device expertise to textile manufacturing. I created a theoretical framework for real-time thread breakage detection during spinning – an approach that had never been studied using electronic devices before. My electronic engineering background allowed me to conceptualize how sensors and monitoring systems could be integrated into high-speed spinning processes to identify inconsistencies that were traditionally impossible to detect in real-time. The mathematical models I developed for this research proved surprisingly adaptable – the principles of analyzing rapid signal changes and detecting anomalies in textile fibers later influenced my approach to signal behavior analysis in telecommunications equipment. It was this cross-disciplinary thinking that shaped my methodology for tackling complex engineering challenges.

At Hermon Laboratories, one of Israel's leading testing and certification facilities, you conducted radio and EMC testing up to 200 GHz and worked with major international standards like FCC and ETSI. How did your experience at Hermon Laboratories with radio and EMC testing shape your approach to developing automated test systems?

My time at Hermon Labs was invaluable – it's where I developed a deep understanding of testing methodology itself. Working with radio tests up to 200 GHz and EMC testing gave me a comprehensive view of how electronic devices interact with their environment under various conditions. This experience was critical when I later developed automated testing systems at Ceragon. When you've personally conducted hundreds of tests manually, you gain insights into where the inefficiencies lie and which aspects of testing are most prone to human error. I could identify precisely which testing elements would benefit most from automation. Moreover, at Hermon, I became intimately familiar with FCC and ETSI standards, which later enabled me to design test systems that improved efficiency and ensured regulatory compliance – a critical factor in telecommunications.

With your extensive experience across textile manufacturing, telecommunications, and aerospace sectors, what emerging trends do you see in RF testing, and how are you preparing for the future?

We're moving toward fully integrated testing ecosystems with seamlessly connected verification stages. I'm currently working on two scientific papers exploring more theoretical aspects of my work in telecommunications, focusing on mathematical models that could underpin next-generation testing methodologies. The future will require not just automation but intelligent automation that can adapt to varying test conditions and requirements. AI integration is inevitable, with systems that can predict potential failure points before they occur and automatically adjust test parameters. I'm preparing for this shift by combining my experience in hardware-based test automation with software-defined testing approaches. What excites me most is the potential for these advances to reduce product development cycles dramatically. By creating more efficient testing methodologies, we can help bring critical communications infrastructure to market faster, ultimately expanding connectivity to underserved regions globally.