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SIX SIGMA (PART 2)
Manuel Rincón, M.Sc. October 15th, 2004

DMAIC Process

Develop Charter and Business Case Map Existing Process Collect Voice of the Customer Specify Controls / Requirements

Control

Define

Improve Analyze

Measure

Measure Controls / Requirements Determine Process Stability Determine Process Capability Calculate Baseline Sigma Refine Problem Statement

SIXSIGMA

DMAIC: Measure

Measure the performance of the Core Business Process involved. Develop a data collection plan & operational definitions for the process. Collect data from many sources to determine types of defects and metrics. Compare to customer survey results to determine shortfall.

SIX SIGMA

DMAIC: Measure
Cycle Time Data (T6
600 500 400

out

-T2 in)
80 70 60 50Min: 48 Days Max: 506 Days

Average Time per Step
Negotiation

Days

Days

Sample Size: 17

300 200 100 0

40

SOW
30 20 10 0

Other Party Approval RA Draft Dow Approval Review Distributed

Avg.= 153 Days

T1

T2

T3

T4 out

T5

T6

T7

Cycle Time for 1st Draft Prepared (T2
70 60 50

-T2 in)
Fact

Min: 0 (same) Day Max: 68 Days Sample Size: 26

Days

4030 20 10 0

There is no standard mechanism for recording cycle time

Avg.= 20 Other Party’s Agm RA Template

Performed by Team

Partially Negotiated

DAS Agm

SIX SIGMA

DMAIC Process

Develop Charter and Business Case Map Existing Process Collect Voice of the Customer Specify Controls / Requirements

Control

Define

Improve Analyze

Measure

Measure Controls /Requirements Determine Process Stability Determine Process Capability Calculate Baseline Sigma Refine Problem Statement

Identify Root Causes Quantify Root Causes Verify Root Causes

SIX SIGMA

DMAIC: Analyze

Analyze the data collected and process map to determine root causes of defects and opportunities for improvement. Identify gaps between current performance and goal performance Prioritizeopportunities to improve. Identify sources of variation.

SIX SIGMA

DMAIC: Analyze

Control Charts

Pareto Charts

Scatter plots

Data collection

Histograms

Stratification

Ishikawa Diagrams

SIX SIGMA

… cambiemos a Español…

SIX SIGMA

Ejemplo (Control de fracciones disconformidades)
Se envasa petróleo refinado (Mezcla Mexicana) en barriles de 200 litros. Estosenvases los produce una máquina formando un tubo a partir de una pieza de hierro y aplicando luego un fondo metálico. Al inspeccionar un barril puede determinarse al llenarlo si goteará por la junta lateral o la del fondo. Tal bote disconforme tiene un sellado inadecuado en la junta lateral o del fondo. Para establecer el sistema de control se seleccionaron 30 muestras de n=50 barriles cada mediahora durante un período de tres turnos. Se desea elaborar un diagrama de control preliminar para ver si el proceso estaba bajo control cuando se obtuvieron esos datos.

Número de muestra Número de disconformidades 1 12 2 15 3 8 4 10 5 4 6 7 7 16 8 9 9 14 10 10 11 5 12 6 13 17 14 12 15 22 16 8 17 10 18 5 19 13 20 11 21 20 22 18 23 24 24 15 25 9 26 12 27 7 28 13 29 9 30 6

SIX SIGMA

Ejemplo(Control de fracciones disconformidades)
Número de muestra Número de disconformidades 1 12 2 15 3 8 4 10 5 4 6 7 7 16 8 9 9 14 10 10 11 5 12 6 13 17 14 12 15 22 16 8 17 10 18 5 19 13 20 11 21 20 22 18 23 24 24 15 25 9 26 12 27 7 28 13 29 9 30 6 347 Fracción disconforme 0.24 0.3 0.16 0.2 0.08 0.14 0.32 0.18 0.28 0.2 0.1 0.12 0.34 0.24 0.44 0.16 0.2 0.1 0.26 0.22 0.4 0.36 0.48 0.3 0.18 0.24 0.14 0.260.18 0.12 0.2313

p =-

SIX SIGMA

Fórmulas para definir Límites de Control

Límite Superior de Control (LSC) =

p

+

3

√ √

p(1-p) n

Límite Inferior de Control (LIC) =

p

-

3

p(1-p) n

SIX SIGMA

Ejemplo (Control de fracciones disconformidades)
Diagrama de Control (Disconformidades)
0.5

0.45

0.4 Fracción disconforme muestral

0.35

0.3...
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