Umetrics Suite Blog

A case for using predictive analytics to optimize and control bioprocesses

June 1, 2018

In bioprocessing today, a shift is happening that takes the ability to monitor, optimize and control processes to the next level. Whereas in the past manufacturers aspired to measure data in order to find out why a bioprocess action happened (using descriptive and diagnostic analytics), today we are able to use predictive analytics to determine what will happen in a bioprocess based on specific process data measured in real-time. This migration “up the food chain” to a higher level of data analytics requires automation, ongoing process monitoring and the ability to make adjustments in real-time.

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Injection molding no longer a black art: How to increase volume while reducing defects

February 26, 2018

For manufacturing companies, process control is essential— even for those producing low-cost items such as small plastic parts. That’s because even when units are small and inexpensive, the cost of defects becomes exponentially higher when they reach the next manufacturing step at another plant.

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What-If tool helps you identify and predict parameters that affect quality

December 7, 2017

In manufacturing and other industries that have complex processes, knowing which variables have the most impact on quality and at what point, or knowing which combination of variables to change in order to improve your process, can have a huge impact on the overall quality or profitability of your manufacturing process. But without making expensive and time-consuming changes in the physical processes in order to test all possible scenarios, how can you identify and predict the variables that have the most significant impact on your outputs?

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How to predict the future and optimize your production process

November 30, 2017

Using real-time data analytics monitoring has become the accepted way to monitor processes in several industries. The goal is to detect and diagnose issues as they happen, which is a great leap forward compared to traditional analysis conducted in retrospect. This has been highlighted in a previous blog post.

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Creating a design of experiments study to predict formula robustness

November 9, 2017

Using a Quality by Design (QbD) approach for DOE supports ICH Q8 compliance

In pharmaceutical development, manufacturers must be able to demonstrate product robustness and deliver the intended quality of the product within allowable ranges for the claimed shelf-life period. Both international and country specific regulatory agencies, such as the FDA, pay close attention to these claims.

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