What is 'data stratification and analytics' in SAP MFG-DM-MI-PQM - Predictive Quality Management?

data stratification and analytics - Overview

• Component: MFG-DM-MI-PQM

• Component Name: Predictive Quality Management

• Description: A functionality to analyze the impact of man, machine, material, and method on the product quality and manufacturing performance.

data stratification and analytics - Details

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  Key Concepts: 
  Data stratification and analytics is a process used in Predictive Quality Management (PQM) of SAP Manufacturing Data Management (MFG-DM-MI). It involves the analysis of data to identify patterns and trends, and then using this information to create a stratified data set. This data set can then be used to make predictions about future quality issues. 
  
  How to use it: 
  Data stratification and analytics can be used to identify potential quality issues before they occur. This process involves collecting data from various sources, such as production logs, customer feedback, and supplier information. The data is then analyzed to identify patterns and trends. Once these patterns are identified, the data is stratified into different categories based on the identified patterns. Finally, predictive models are created using the stratified data set to make predictions about future quality issues. 
  
  Tips & Tricks: 
  When using data stratification and analytics for Predictive Quality Management, it is important to ensure that the data collected is accurate and up-to-date. Additionally, it is important to use a variety of sources when collecting data in order to get a comprehensive view of the situation. Finally, it is important to regularly review the predictive models created in order to ensure that they are still accurate and up-to-date. 
  
  Related Information: 
  Data stratification and analytics is an important part of Predictive Quality Management in SAP Manufacturing