All manufacturing industries need good control and good overview of their production processes. As already discussed in a previous blog post [https://blog.umetrics.com/improve-production-processes-with-multivariate-data-analytics-tool-for-real-time-monitoring], SIMCA-online enables you to apply advanced multivariate data analytics in real time to monitor your production processes, for example to make sure that your production process is behaving as it should or that the quality is what it should be.
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?
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.
In a previous blog post we discussed how SIMCA-online can help you make complex data simple and ensure that you get maximum value from your data.
In this blog post we will introduce a number of benefits of the newly released versions of SIMCA 15 and SIMCA-online 15. To mention just a few things, you get a much improved ability to model and control complete processes, including processes with a very high complexity. You also get a much better connection between SIMCA and SIMCA-online so that information can flow in both ways.
An important environmental issue that has come into focus is the increasing number of chemicals that we are exposed to in our everyday life. Chemicals are found in products ranging from cars and furniture to clothing and skincare, and are also by-products from combustion. The CAS REGISTRYSM, an international standard for chemical information, currently contains more than 134 million unique organic and inorganic chemical substances and more than 67 million sequences.
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.
Using advanced data analytics models in real time opens up a whole new world of possibilities for improving your production processes. Not only does real-time process monitoring provide a level of confidence in your process performance, it can also help improve the overall quality of your production output.
If data analytics were easy, everyone would do it, right? Well, what if were easy enough for anyone to do it? Can you image what sort insights you might glean from the vast pools of data your company collects about your manufacturing processes, sales or production outputs?
If all of your data stays hidden in the depths of some process control computer or in Excel spreadsheets on the manufacturing floor manager’s desk, are they doing anyone any good?
Analyzing batch process data is a lot like juggling. You have multiple sets of data from different sources and in order to turn them into a meaningful presentation, you need a method of handling them to make sure they are all in the right place at the right time.
When to apply OPLS-DA vs PCA for metabolomics and other omics data analysis
Do you know when to use OPLS-DA and when to use PCA/SIMCA data analysis techniques? Find out how to uncover the differences in your data with these classification and discriminant analysis methods.