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This page was created on 07-Jun-2022 18:08 by Jonas Umgelter

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At line 1 changed one line
__General text on use of data an analyzing data__
!!%%(color: #003399; font-size: 24px;) Making use of your process data
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-> link to [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.
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-> link to [Data Validation]
At line 7 changed one line
-> link to [Exploratory Pattern Analytics]
!!%%(color: #003399; font-size: 24px;) You are not sure if your current process data is ready to use?
Having high quality data has an enormous potential in improving the data flows within the processes of your company, and is vital in analyzing your data and interpret the results. Therefore, the data quality needs to be checked.
At line 11 added 16 lines
\\%%(color: #F1717F)The [Data Validation] Tool can help you with that!
!!%%(color: #003399; font-size: 24px;) Your process data is valid but product with recyclate shows faults?
Due to instable processes caused by temperature, pressure or other changes in the
process, the quality outcome of extrusion or recycling machines can be lower
than expected. With help of the Process Quality Analytics tool, errors in the
data found during processing certain materials can be spotted automatically.
Such errors can be hard for the naked eye to spot.
\\%%(color: #F1717F)The [Data Analytics Tool |Data Analytics] can help you with that!
!!%%(color: #003399; font-size: 24px;) Do you want to understande and predict faults from process data?
Despite leading to a loss of output, and therefore being potentially very costly to the business, faults are still common in many production processes. Analysing process data to identify simple rules (patterns) between some parameters that are predictive for a certain target parameter can help you prevent faults before they occure.
\\%%(color: #F1717F)The [Exploratory Pattern Analytics] can help you with that!