SPC Fundamentals

Prerequisites:

Interest and willingness to learn the concepts of Statistical Process Control.

Workload:

16 hours, divided into 2 days.

Training Objective

To enable quality and production professionals to understand and apply the concepts and methodologies of Statistical Process Control (SPC). The course covers everything from the origins of SPC to the practical application of its tools, enabling participants to identify and control variations in processes with a view to continuous quality improvement.

Target audience

Professionals in the area of quality control, production and managers who wish to learn and implement Statistical Process Control practices to optimize the quality of products and services.

Program Content

  • Introduction to Statistical Process Control
    • What is SPC and who needs it.
    • The origin of Statistical Process Control.
  • Process Variation
    • Causes of poor quality.
    • Random (natural) causes and special (assignable) causes.
    • How to identify the type of cause and the effects of the interference.
  • Populations and Samples
    • Sampling, rational subgroups, randomness and distortions.
    • The W’s and 2 H’s of sampling and strategies with case studies.
  • Descriptive Measures and Distributions
    • Calculation and interpretation of mean, median and standard deviation.
    • Study of the normal distribution and distributions for attributes.
  • Process Capacity and Performance
    • Capacity Index Analysis: Cp, Cpk, Cpm.
    • Analysis of Performance Indices: Pp, Ppk, Ppm.
  • Control Charts for Variables
    • Fundamentals of Shewhart charts.
    • Configuration and interpretation of control charts.
    • Differentiating between processes under control and out of control.
    • Application of control limits, specification limits and alarm rules.
  • Control Charts for Attributes
    • P chart (percentage of defective) and NP chart.
    • C Chart and U Chart (defect count).
  • Effective SPC implementation
    • Practical exercises and application examples.
    • How to avoid SPC implementation failures and steps to success.

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