Semiconductor process engineers would love to develop successful process recipes without the guesswork of repeated wafer testing. Unfortunately, developing a successful process can’t be done without ...

Accurate and predictive process modeling, in combination with virtual metrology enables the characterization of any feature on any given structure, is becoming a key requirement in advanced technology ...

PSE’s gPROMS is a unified equation-oriented process modeling environment for applications across the plant, from complex catalytic reaction and separation to wastewater treatment and utilities.

In biopharmaceutical manufacturing the interactions between cells, nutrients, and reagents in culture determine product quality. The big challenge for process developers is modeling these complex ...

Process orchestration can give organizations visibility into the performance of all of their processes, so they can take steps to continuously improve them.

Gaussian process (GP) models are widely used to approximate time consuming deterministic computer codes, which are often models of physical systems based on partial differential equations (PDEs).

Join this information gathering session exploring the challenges and opportunities for physical, process-based modeling approaches that enable attribution science. This session will focus on large- ...

For process improvement practitioners, Monte Carlo simulation is an important tool and method to reduce risk and facilitate those decisions grounded on data and evaluation. Mark Sidote is a Principal ...