This page (revision-11) was last changed on 13-Jun-2022 15:02 by Jonas Umgelter

This page was created on 21-Mar-2022 11:10 by Leonid

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Version Date Modified Size Author Changes ... Change note
11 13-Jun-2022 15:02 2 KB Jonas Umgelter to previous
10 07-Jun-2022 19:24 2 KB Jonas Umgelter to previous | to last
9 07-Jun-2022 19:23 2 KB Jonas Umgelter to previous | to last
8 07-Jun-2022 18:11 1 KB Jonas Umgelter to previous | to last
7 07-Jun-2022 18:08 2 KB Jonas Umgelter to previous | to last
6 07-Jun-2022 18:03 2 KB Jonas Umgelter to previous | to last
5 07-Jun-2022 17:58 2 KB Jonas Umgelter to previous | to last
4 07-Jun-2022 17:57 2 KB Jonas Umgelter to previous | to last
3 07-Jun-2022 17:41 2 KB Jonas Umgelter to previous | to last
2 07-Jun-2022 17:26 2 KB Jonas Umgelter to previous | to last
1 21-Mar-2022 11:10 82 bytes Leonid to last

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Getting Started...nobody

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At line 6 changed one line
Go to [Finding the right recyclate] ”
Go to [Finding the right recyclate]
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__Digitalizing tons of material data sheet to use
them in tools like the matrix tool is too much work for you?__
__Digitalizing tons of material data sheet to use them in tools like the matrix tool is too much work for you?__
At line 13 changed one line
Go to [Digitalize material data sheet] ”
Go to [Digitalize material data sheet]
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The processing of recyclates requires process consistency and sufficient data to
prove quality for data sheets and acceptance test certificates. If these characteristic
values are not or not sufficiently available supports we can help you with our
solutions. (Data Infrastructure Wiki and Sensoring Tool)
The processing of recyclates requires process consistency and sufficient data to prove quality for data sheets and acceptance test certificates. If these characteristic values are not or not sufficiently available supports we can help you with our solutions.
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Collecting process data is not enough, a qualified evaluation and interpretation of the data enables you to better understand the data you collect and draw more informed conclusions. An additional improvement in data analysis can be achieved by visualization ...this is where our solutions support you. (Data Analytics, Data validation, EPA)
Collecting process data is not enough, a qualified evaluation and interpretation of the data enables you to better understand the data you collect and draw more informed conclusions. An additional improvement in data analysis can be achieved by visualization ...this is where our solutions support you.
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Go to [Using and Analyzing data]
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Go to [Using/Analyzing data|https://di-plast.sis.cs.uos.de/Using/Analyzing_data#_-%3E_] ”
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Go to [Gathering data|https://di-plast.sis.cs.uos.de/Gathering_data#_-%3E_] ”
Go to [Data Gathering]