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.
How Multivariate Data Analysis Can Separate the Players from the Gorillas
We have more data than ever before coming at us from many sources – both in our personal lives as well as business. Data is everywhere: from the production flow of a manufacturing floor to the sales results in a grocery store to the number of shares a page gets on Facebook. How do you sort it all out in a way that makes sense? Which data should you worry about and which should you ignore?
Whether you work in engineering, R&D, or a science lab, understanding the basics of experimental design can help you achieve more statistically optimal results from your experiments or improve your output quality.
“The first rule of any technology used in a business is that automation applied to an efficient operation will magnify the efficiency. The second is that automation applied to an inefficient operation will magnify the inefficiency.” — Bill Gates
Producing and distributing raw materials and foodstuffs with a low profit margin is a challenging business. One major supplier has made significant gains through applying multivariate data analysis (MVDA) to their manufacturing processes and logistics.
The key to process manufacturing success is a mixture of knowledge and experience supported by mastery of data. A presentation I recently attended put this into sharp focus. A major paper manufacturer was faced with the challenge of maintaining paper smoothness during production. They approached this problem in a way that gave them enormous insight into their process, the ability to control it in real time, and ultimately lead to cost savings and maintained quality. There were also a few added benefits, including the ability to spot, diagnose and solve problems in real time.
Attending IFPAC 2017? Come to booth #407 to see how augmented reality and data analytics work hand-in-hand. Using Microsoft Hololens technology, Sartorius Stedim Data Analytics is making groundbreaking innovation which we will showcase and demo at IFPAC 2017. Get a personal demo, and see, among other interesting use cases, how multidimensional design spaces can be visualized as a hologram using augmented reality.