[Screenshot from 2022-07-07 12-20-23.png|https://di-plast.sis.cs.uos.de/attach/Exploratory%20Pattern%20Analytics/Screenshot%20from%202022-07-07%2012-20-23.png|500px] 


__%%( color: #003399; font-size: 18px; )Type of tool:/%__ e.g. web application or desktop application

__%%( color: #003399; font-size: 18px; )Required skills: /%__

- Process/material knowledge: e.g. knowledge of material properties

- Digitalization knowledge: e.g. no programming

__%%( color: #003399; font-size: 18px; )Short description of the tool: /%__

- Detailed description: Link to the guideline:

__%%( color: #003399; font-size: 18px; )Disclaimer:/%__

(Disclaimer Text)

__%%( color: #003399; font-size: 18px; )How to use/download/access it:/%__

e.g. got the the gitup [[link], copythe code into [[XY] and start using

__%%( color: #003399; font-size: 18px; )Use case/problem:/%__ Selecting material (recyclate) for specificproduct requirements

__%%( color: #003399; font-size: 18px; )Description of the problem the tools solves:/%__

[[General] + [[Tool-specific]

 

__%%( color: #003399; font-size: 18px; )Contact person of the tool: /%__Stefan Bloemheuvel

__%%( color: #003399; font-size: 18px; )Related tools:/%__

- Analyse and Visualize your process data with data analytics -> [Data Analytics]

- Get guidance to set up a working data infrastucture -> [Data Infrastructure Wiki]

- Find the right sensor to survey your process -> [Sensor Tool]

- Improve internal information and material flow -> [VSM]

- Match material requirements with material properties -> [Matrix]

 

! Tool Description

An important step in data analysis is data exploration, to achieve a betterunderstanding of the data. The Exploratory Pattern Analytics (EPA)tool works on prepared/preprocessed tabular data. It providesexplanatory patterns, i.e., simple rules between some parameters(e.g., temperature, pressure) that are predictive for a certaintarget parameter (e.g., scrap rate). This provides important insightsenhancing data understanding.For example, it could be used to better understand why certain known outliers occurin process data.

 

! Guidelines

Before you get started, take a look at the [guidelines|Paper mill EPA tool example updated.odt] and make yourself familiar with how to use the tool.

! Getting Started

The tool is available through the Data Analytics tool interface at: [https://github.com/cslab-hub/Data_Analytics_DIPLAST/tree/epa]. The python interface for programmers is available at: [https://github.com/cslab-hub/sd4py].