In life sciences manufacturing, some of the most valuable data remains trapped in spreadsheets, scattered across different systems or simply uncollected. This fragmentation creates blind spots around ...

Nagesh Nama, CEO, xLM. Nagesh Nama is a seasoned technology executive with over 30 years of experience in life sciences. My journey into industrial data operations (DataOps) began over two decades ago ...

If manufacturing is the world’s most data-rich sector, why do so many factories still lean on Post-it notes, color-coded paper, binders, and employee intuition? Manufacturers generate more data than ...

SE: What kind of product and financial data could people add to a manufacturing data analytics solution? Rathei: In the back end, our software has the capability to calculate the test recovery rate.

Enabling direct system coordination without centralized bottlenecks allows robots, conveyor systems and equipment to interpret data, make decisions and adapt together as an integrated manufacturing ...

Modern manufacturing operates in complex environments where traditional management approaches are no longer enough. This highlights the need for real-time, dynamic and self-adaptive management ...

Manufacturers everywhere feel they’re behind on mastering their use of operations data. The answer to that problem isn't collecting more data, it's tracking those data points that actually solve ...

For decades, we heard silicon was the only answer. However, while the world’s largest fabs were busy taping out silicon, the communities of engineers and scientists working on non-silicon technologies ...

The semiconductor industry stands at an inflection point. As Moore’s Law scaling becomes increasingly challenging and system complexity explodes through advanced packaging and chiplet-based ...

The basic machine for grinding a steel ball bearing has been the same since around 1900, but manufacturers have been steadily automating everything around it. Today, the process is driven by a ...