https://player.vimeo.com/video/670141220
Type of tool: e.g. web application or desktop application
Required skills:
- Process/material knowledge: e.g. knowledge of material properties
- Digitalization knowledge: Be able to install two well-known programming tools used by millions of people worldwide
Short description of the tool:
- Detailed description: Link to the guideline:
Disclaimer:
The tool is meant to guide users into starting our with using Data Analytics at their organization. But keep in mind that the analytics techniques displayed in this tool are 100% error-less. Always check if the results are in line with your expert knowledge of your processes.
How to use/download/access it:
Get the code from https://github.com/cslab-hub/DataAnalytics_Diplast
Use case/problem:
- Visualize process data
- Compare two runs (one without recyclate and one with) of making a product
- Explore patterns inside a dataset
Description of the problem the tools solves:
After validating your data with help of e.g., the data validation tool, we can begin analyzing to get further insights. The Data Analytics tool is an interactive dashboard that helps with interpreting the variables in your dataset with help of visuals. By providing your own data in the 'data' folder, several analytical options are at your disposal. For example, a correlation plot that gives insights into which variables are behaving similarly, or a PCA analysis that will help determining the most influential variables in your dataset.
Contact person of the tool: Jurgen van den Hoogen & Stefan Bloemheuvel
Related tools:
- Get guidance to set up a working data infrastucture -> Data Infrastructure Wiki
- Find the right sensor to survey your process -> Sensor Tool
- Validate your process data -> Data Validation
- Improve internal information and material flow -> VSM
- Match material requirements with material properties -> Matrix
Process Data Analytics:
In the current developments towards a smart industry (4.0), more and more data is collected concerning your operation processes. Insights in the data could contribute to improving these processes. After getting the data from your systems, and validating it with help of the Data Validation tool, the Process Data Analytics tools provides insights consisting of reports, visualizations and other analysis methods that describe the state of your processes and/or machinery. The process analytics tool consists of several data analytics modules that describe and analyse the underlying process data. In this tool, we strive to perform data science techniques such as classification, clustering and pattern mining accompanied by visualizations. Within the tool, we focus on the analyzing Time Series data.
The files for the tool can be downloaded at: https://github.com/cslab-hub/Data_Analytics_DIPLAST
