Course Content
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DAY 1 Understand the Methodology and Implementation of Advance Root Cause Analysis
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Introduction
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The pitfall of using One-Input-at-a-Time for root cause analysis
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What are interaction factors or inputs?
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Advance Root Cause Roadmap
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Deploying Analysis of Variance for Root Cause Analysis • One-way analysis of variance • Two-way analysis of variance
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Development of the data matrix for analysis • Breaking down total variance to variation of interest and variation due to error • Data analytic (statistics) to derive the root cause(s) and irreversible corrective actions. • Case studies
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DAY 2
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Deploying Factorial Experimentation for Root Cause Analysis • Experimentation with two factors • How to establish the experimental error for analysis for a two-factors experiment?
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Experimentation with four or more factors • Identification of problem • Brainstorming • Multi-voting • How to use to create an experimental matrix • Establishing the experiment error for analysis • Data analytic to establish the root cause(s) result from interacting factors and main factors Irreversible corrective action • Case studies
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