As researchers, you may encounter roadblocks in your experiments:
How do I interpret results and find the optimal process window?
What are the simulated variations that impact the process window?
Can I still meet specifications with X amount of variations?
Design of experiments (DOE) and prediction profilers are valuable tools in statistical analysis and serve different purposes. DOE is used for designing and conducting experiments to understand and optimize processes or systems, while prediction profilers are used to analyze predictive models and understand how input variables influence predicted outcomes.
Researchers, scientists and engineers may choose profilers as the next stage after design of experiments for their efficiency, ease of interpretation, flexibility, interactivity, and integration with modeling tools. Profilers provide intuitive graphical representations, enabling quick interpretation and real-time exploration of complex relationships between variables, ultimately streamlining the analytical workflow and facilitating informed decision making.
In the semiconductor industry, prediction profilers help optimize processes, improve yield, and enhance product performance. Researchers and process engineers use them to analyze the relationship between process parameters and key metrics like yield and device performance, enabling them to identify optimal settings, detect critical parameters affecting defects, optimize designs, assess reliability, and guide materials development.
In the pharmaceutical industry, prediction profilers analyze relationships between factors such as chemical structures, formulation parameters, and clinical outcomes. They help prioritize drug candidates, optimize processes, design efficient trials, and assess safety. This accelerates drug development and ensures efficacy and safety.
In food manufacturing, scientists use prediction profilers to optimize processes, improve product quality, and ensure safety. They analyze relationships between ingredients, processing conditions, and product characteristics to enhance taste, texture, and shelf-life while minimizing costs and food safety risks.
Discover the enhanced features of JMP 18 profilers in this on-demand webinar:
Prediction Profiler: includes overlaid interactions, smoother curves, improved constraint specifications.
Design Space Profiler: provides an easier method for synergizing your Prediction Profiler with Monte Carlo simulation.