Improve process monitoring, understanding and control with Unscrambler® X Process Pulse II. It enables powerful multivariate models developed with The Unscrambler® X to be used to monitor at-line, on-line and in-line processes.
Unscrambler® X Process Pulse II has been developed with the goal of delivering a solution for advanced process monitoring and control, while at the same time being user-friendly. With a non-complex set up procedure, the software supports configurable dashboards, intuitive plots, and alarms to alert potential issues.
The software offers early event detection and immediate identification of out-of-limit variables for real-time process control, giving users the possibility to remedy potential failures before they occur. It includes advanced quality predictions and drilldown plots to investigate the variables contributing to deviations, making Unscrambler® X Process Pulse II a powerful tool for improving process understanding. Unscrambler® X Process Pulse II also includes powerful multivariate prediction and classification methods, and outlier diagnostics such as Hotelling T2, Q residuals and Y predicted with deviations. A variety of file formats from scientific instruments and process equipment are supported, and data can easily be exported to be presented in third party solutions.
Designed to work with small and mid-size processes, Unscrambler® X Process Pulse II can also be scaled up and connected seamlessly into existing control systems.
Unscrambler® X Process Pulse II can be utilized in many different parts and levels of the organization, and provides users with a tool to solve a variety of challenges.
Data analysts often face challenges with the data they want to analyze. The data can be in different formats, coming from different systems, or it can be a mix of historical and live data and contain a large number of variables. Unscrambler® X Process Pulse II handles all of these challenges, and translates the data into what is actually happening in the production process. Unscrambler® X Process Pulse II helps to improve product knowledge and understanding by identifying patterns and relations between the data, and grouping the data.
In many organizations access to specialized data analysts is limited and the data owner, e.g. an engineer, has to carry out the daily data analysis. Unscrambler® X Process Pulse II’s ease of use makes this situation viable.
Unscrambler® X Process Pulse II provides all the tools required for data driven manufacturing and continuous improvement as shown in Figure 2.
The starting point for data driven manufacturing is data (see the upper right corner of the figure). The data can come from a historian documenting earlier process runs, or alternatively generated by experimental design for product transfer or development purposes. The data can be reviewed and analyzed in The Unscrambler® X and models can be developed describing any interesting relationships between the different variables. Subsequently the models are transferred into the Unscrambler® X Process Pulse II system.
The software can be connected directly to the data sources generating data such as spectrometers etc or to third party systems holding data, e.g. MES (manufacturing execution systems). In both cases the data is read into Unscrambler® X Process Pulse II where any linked models are executed. The results from the models and the raw data are then presented to the user via screens or sent externally to third party systems for further handling or use. In parallel all information is stored in the Unscrambler® X Process Pulse II historian. Users can generate standard reports or their own reports based on the data in the historian. These reports form the basis for quality assurance or planning of process changes. And of course, as the process is running new data is stored in the database which can again be used to develop new models or refine existing models starting a new turn of the continuous improvement wheel.
Improve process performance with this easy to use, affordable multivariate process monitoring software.
Significant cost reduction: Minimize the need to discard faulty end-product, reduce waste/scrap and avoid costly process delays by detecting outliers and drifts during the process.
Improved quality control: Reduce variability in products and get a better view of the health of a process by identifying issues that may lead to poor quality product.
Faster time to market: Increased process understanding can reduce the time to market for new products, and enable fast tech transfer, site-to-site transfer and scale up.
Better process understanding: Benefit from powerful multivariate models, rather than traditional (univariate) statistics used by most SPC systems, which do not show interactions between variables.
Low cost to buy and run: The solution is affordable for even the smallest process environments and requires minimal training and implementation, keeping the Total Cost of Ownership low.
Fast return on investment: Improve yields, produce more consistent product, minimize failures and improve overall performance through continuous process improvement.