Main Training Program

STATISTICAL PROCESS CONTROL

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INTRODUCTION FOR STATISTICAL PROCESS CONTROL

SPC or statistical process control is a statistically-based family of tools used to monitor, control, and improve processes, has become an important business strategy for many organizations; manufacturers, distributors, transportation companies, financial services organizations; health care providers, and government agencies. Quality is a competitive advantage. A business that can delight customers by improving and controlling quality can dominate its competitors. SPC is a technical method for achieving success in quality control and improvement.

 

COURSE OBJECTIVES

At the end of the course participants will be able to understand and know:

  • What is Statistical Process Control
  • Understands the advantages of SPC
  • Knows the statistical background
  • Is able to calculate control limits and capability indices
  • Understanding of problem-solving methods and prevention-based quality assurance
  • Understanding variability
  • Use of check sheets, cause and effect diagrams, and flow charts
  • Selection, construction and interpretation of various control charts
  • Interpretation of SPC results
  • Construction and interpretation of histograms, Pareto charts, run charts, and scatter diagrams

 

COURSE CONTENT

Module 1: What is SPC

  • What is Statistical Process and Control
  • Benefits of SPC
  • Customer view
  • History of Quality Methods
  • What is Process Capability
  • Stability vs Capability
  • Area of SPC usage
  • Continuous Improvement

Module 2: Basic Tools of Problem Solving

  • Pareto Analysis
  • Flow Charts
  • Cause and Effect Analysis
  • Data Collection
  • Check sheets
  • Scatter Diagrams
  • Histograms
  • Run Charts
  • Control Charts

Module 3: Understanding Variation

  • Introduction to Variation
  • Measuring Variation
  • Patterns of Variation
  • Measures of Variation
  • Normal Curve
  • Process Stability

Module 4: Statistical background

  • Definition of symbols
  • Sample, Model and population
  • Normal or Gaussian Distribution
  • Central limit theorem
  • The normal Probability Paper
  • Probability paper – Idea
  • Simulation of distribution
  • Practical session on selected process for data collection

Module 5: Constructing Control Chart

  • What are Control Charts
  • What a Control Chart Looks Like
  • Interpreting Control Charts
  • Types of Control Charts
  • Using Variable Control Charts
  • Using Attribute Control Charts
  • Selecting Control Charts
  • Determining Control Limits
  • Constructing Control Charts
  • Charts Calculation tool
  • Situation of Cp and Cpk
  • Calculation of Cp and Cpk
  • Target and reasons for low Cpk
  • Parameter’s classification

Module 6: Monitoring and Improvement With SPC

  • Process control
  • Set up control limits
  • Interpreting Control Chart
  • Reduce Variation
  • Shifting Means
  • SPC Principles
  • Control limit calculation
  • Practical session on select process for improvement

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