What is 'time-series analysis' in SAP MFG-DM-MI-PQM - Predictive Quality Management?

time-series analysis - Overview

• Component: MFG-DM-MI-PQM

• Component Name: Predictive Quality Management

• Description: A sub function of descriptive analytics. Time-series analysis helps to analyze the patterns of machine or process parameter data that is collected at different time stamps.

time-series analysis - Details

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  Key Concepts: 
  Time-series analysis is a statistical method used to analyze data points collected over a period of time. It is used to identify trends, patterns, and correlations in the data. In the context of SAP's Predictive Quality Management (PQM) component, time-series analysis is used to identify patterns in quality data that can be used to predict future quality issues. 
  
  How to use it: 
  Time-series analysis can be used to identify trends in quality data over time. This can be done by plotting the data points on a graph and looking for patterns or correlations. Once these patterns are identified, they can be used to predict future quality issues. 
  
  Tips & Tricks: 
  When using time-series analysis, it is important to consider the context of the data. For example, if the data points are collected over a period of time that includes seasonal changes, it is important to take this into account when analyzing the data. Additionally, it is important to consider any external factors that may have an effect on the data points. 
  
  Related Information: 
  Time-series analysis is closely related to other statistical methods such as regression analysis and correlation analysis. Additionally, it can be used in conjunction with machine learning algorithms such as neural networks and support vector machines to further improve predictions.