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Manufacturing excellence through SPC and Seven Quality Tools


Focus Areas

  • Fundamentals of Statistics
    • Measures of central tendency and spread
    • Types of frequency distributions
    • Evaluation of discrete data and grouped data (through example)
    • Concepts of probability
    • Statistical decision making
    • Acceptance sampling (sampling plans)
  • Objectives and benefits of SPC
  • Understanding of common and special causes
  • PDCA / 8D Approach for problem solving
  • Basic 7 QC Tools
    • Check sheet
    • Stratification
    • Brainstorming and Pareto chart
    • Cause and Effect diagram
    • Graphs and control charts
    • Histograms
    • Scatter diagrams
  • Machine and process capability
  • Application of control charts for Variables & attributes
  • Analysis of control charts
    • Exercises/Case study on statistical decision making
    • Exercises/Case study on control charts for variables & attributes
    • Exercises/Case study on process capability
  • Basics of MSA & its application with example
  • Case studies from Industry for effective problem solving by using QC tools

Background

Variation in any manufacturing process is inevitable but needs to be controlled. If external or assignable causes of variations are excluded, the natural causes are restricted to a combination of variations due to machines, tools, methods, materials and people who work at the workplace. Statistical Process Control (SPC) is a technique to enable measurement and analysis of the variations at the workplace and try and control the same at optimum levels. While SPC techniques involve extensive use of various types of control charts, an understanding of all the basic seven quality tools helps in a better understanding and implementation of SPC as well as Problem solving.

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