Statistical Process Control Overview

Background

• Statistical Process Control is the use of statistical techniques such as control charts to analyze a process or its output so as to take appropriate actions to achieve and maintain a state of statistical control and to improve the process capability.

Learning Objectives

• Learn proven questioning techniques for effective SPC implementation through developing an Operational Definition
• Demonstrate an understanding of the linkage between SPC and the larger scope of the core tools manuals (MSA, FMEA, APQP), along with the requirements of IATF 16949.
• Identify the sources of variation present and know how to categorize normal versus non-nor- mal
• Differentiate between prevention and detection and illustrate their impact on the Cost of Poor Quality (CoPQ)
• Learn about the different tools that support SPC implementation
• Identify the correct and applicable tools for both variable and attribute data
• List best practices regarding implementation and taking action on out-of-control conditions to aid in effective implementation
• Calculate and Interpret acceptance criteria for process capability indices like CpK and PpK
• Apply methods for implementing the principles of SPC to manufacturing processes
• Apply software to the calculation of Control Limits and incorporation of measurement studies process to the selected Process Controls
• Demystify SPC by learning to carry out all calculations and interpretations following the steps in the SPC reference manual

Who Should Attend

• Recommended for quality managers, quality team leaders, manufacturing managers and technicians, quality assurance and laboratory technicians and engineers, anyone involved in the implementation of IATF 16949:2016, individuals and cross functional teams interested in risk reduction and anyone who wants a better understanding of SPC.