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Measurement Process Control Based on ISO-GUM and 3rd Edition of AIAG MSA-Manual

It is well known that "If you cannot measure, you cannot control." The role of measurement and significance of measurement quality in making correct decision about product and process performance is known to quality decision makers. All management system standards have mandated the control of measurement process in some form or the other.

We at QGS have experienced that Measurement Process is not understood as a process. Bits and pieces in form of "Measurement System Selection", "Measurement Uncertainity" (A requirement for all calibration and test laboratories) and , "Measurement System Analysis" have a synergy and should be understood as a comprehensive process.

The objective of this training is to equip the participants with in-sight view and total exposure to the concept , requirements and practices of

  • Measurement Process

  • Measurement System Selection

  • Measurement Uncertainity Evaluation and

  • Measurement System Analysis

     

Who should participate?

  • Techical Managers

  • Quality Managers

  • Production Managers

  • Engineers

  • Metrology / Standard room personnel

  • Quality Engineering (e.g. APQP Team)

  • Laboratory Personnel

  • Quality Management Consultant

  • Quality Control Executive

  • S.Q.C / S.P.C Team

 

What will Participants learn:

  • Understanding Measurement Process - Statistical properties of measurement system, Effect of measurement process on measurement decisions and SWIPE

  • Measurement Strategy & Planning - Measurement life cycle and Selection of measurement system

  • Measurement Process & PDCA

  • Basic statistics in MSA

    1. Variation due to common Variation due to common & & special cause

  •  

  • Location and width measurement process variations and their contribution to Manufacturing process variation

  • Evaluating Measurement System Uncertainty

    1. Definition

    2. Type of Measurement Uncertainity

    3. Standard Uncertainity

    4. Combined Uncertainity

    5. Expanded Uncertainity

    6. Uncertainity Evaluation

    7. Uncertainity Budget

  • MSA for simple measurement system, preconditions, interpretation of result and role of graphical analysis

    1. Bias Study

    2. Linearity Study

    3. Stability Study

    4. GRR - No. of Distinct Data Categories

     

  • Attribute Study -

    1. Risk Analysis Method

    2. Kappa Method

    3. Analytical Method

     

  • MSA for complex & non repeatable measurements

 
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