Statistical Process Control

GENERAL DESCRIPTION

This course includes e-Learning with audio description (EN)+ 1/2 day  discussion with trainer (RO/EN)

The SPC manual of AIAG defines the SPC as: the use of statistical techniques such as control graphs for the analysis of a process or exits from a process in order to take appropriate actions to maintain a state of statistical control and improve the capability of the process.

OBJECTIVES 

At the end of this Statistical Process Control course, participants will be able to:

  • Understand the SPC concepts relating to process variability and the identification and classification of the causes of process variation
  • Understand the concepts of data and its processing
  • Know the basic tools used in the analysis of process variation (histogram, operation diagram and Xmed-R and p control diagrams) as tools for keeping processes under control
  • Understand the concept of process capability

WHO SHOULD ATTEND

  • Management representatives
  • All persons (engineers, technicians, laboratory staff and operators) involved in the implementation of the SPC
  • Engineers and Process Improvers
  • Internal System Auditors (IATF 16949) and process and product auditors
  • Second party auditors
  • Anyone interested in knowing the SPC

 

PREREQUISITE

They are not required, although basic mathematical skills would be beneficial.

 

TRAINING AGENDA

  • Introduction and overview of the course
  • Process variation and data processing
  • What is variation?
  • Quality Loss Function
  • Vocabulary of statistics terms
  • What is data?
  • Graphical representation of data (histograms, operating diagrams)
  • Control charts
  • Examination of process variation – statistical characteristics for determining the location, scattering and shape
  • Control charts
  • Control charts for variables – control diagram  and R (construction and use)
  • Control charts for attributes – p control diagram (construction and use)
  • Process capability and machine capability
  • Capability indices – Cp, Cpk, Pp, Ppk, Cm, Cmk
  • Adjustments and rules arising from statistical analysis
  • Adjustment status check diagram

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Enrolled: 3 students
Lectures: 87

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