Axis 6 Sigma

Six Sigma

En un comienzo.. . •

La historia de Six Sigma comienza en Motorola. La compañía recibía muchas quejas de sus clientes que decían que, aunque les gustaba hacer negocios con Motorola, querían un nivel de servicio más elevado en lo referente a entregas, finalización de pedidos, exactitud en los datos de las transacciones, etc.

•

Como consecuencia de esto, la compañía lanzó en 1987 un programa de control de calidad a largo plazo llamado “programa de calidad Six Sigma”. El propósito de este programa era mejorar la satisfacción del cliente, reduciendo al mínimo o eliminando los defectos y variaciones en los productos y procesos.

•

¿Porque Six Sigma? El nombre se escogió para reflejar el objetivo principal del programa de calidad, es decir, medir el numero de defectos y variaciones y reducirlo. El “programa de calidad Six Sigma” tuvo un éxito enorme. Otras grandes empresas como Ford, Caterpillar y General Electric lo han implementado.

Pero….

que es Six Sigma?

Es una metodologia que se enfoca en la mejora de procesos satisfaccion del cliente y resultados financieros La meta de todo proceso Six Sigma es: -minimizar la variacion -centrar el proceso, de tal manera que el centro del valor alcanzado se encuentre al menos a 6 desviaciones estandar de lo que se considera no aceptable (o el limite superior e inferior de la especificacion).

Proceso Six Sigma Six Sigma

Limite inferio r 99.9996% del producto de acuerdo a especificacion

6σ 5σ

4 σ

3σ

Limite superio r

Centro del proceso

2 σ

σ

σ

2 σ

3σ

4 σ

5σ 6σ

Que es Sigma (σ)?

Sigma es un simbolo que representa el grado de variacion de un proceso. En estadistica representa la desviacion estandar, que por definicion es la medida en la cual los numeros se encuentran dispersos con relacion a su promedio. Se representa con la ecuacion:

σ = Σ ( X-Xn )2 n-1

N= numero de muestras X= promedio

Significado practico de 6S 99% Correcto (4σ) Servicio Postal 20,000 articulos perdidos cada hora

99.99966% Correcto (6σ) 7 articulos perdidos por hora

Aerolineas 2 aterrizajes forzosos diarios

1 aterrizaje forzoso cada 5 años

Medicos 200,000 prescripciones erroneas al año

68 prescripciones erroneas al año

Que sig nifi ca 6 Si gma e n la vid a diaria ?

P Asesoria Recetas PM’ Cuentas en restaurantes 1000000 legal medicas s100000 Procesamiento de nomi 10000

σ

%non1000 defective 100

2 3 4 5 6

10 69.1% 93.32% 1 99.379% 1 99.9767% 99.99966%

2

3

4

Manejo de equipaje Mejor en su Segurid Clase ad en Aerolin 5 6 7 6σ eas

Sigma Level

Pero…que es Six Sigma? Es una metodologia, es decir, una forma de desarrollar un proyecto basada en el trabajo en equipo.

Los equipos Six Sigma deben: • Tener un problema especifico • Tener un objetivo o meta establecido • Ser multi-funcionales • Tener un lider (green-black belt) • Tener sesiones periodicas programadas

Miembros de un equipo Six Sigma Extended Team

Core Team Six Sigma Project

Master Black Belt

Belt Sponsor

En que consiste la metodologia 6S?

D M AI C

DEFINIR MEDIR

ANALIZAR MEJORAR CONTROLAR

Herramientas Six Sigma Medicion: Mapeo de Proceso Matriz Causa-Efecto Analisis del Sistema de Medicion

Analisis: Estudio de Capacidad Multi-vari Analisis Estadistico Mejora: Diseno de Experimentos Diseno a prueba de error Control: Plan de Control

Project Tracker

Project Start Date = Charter signed by belt Develop Charter Review 6 Project Approved & Sigma & other Schedule on Database Database

Project hopper and Sponsor role Project Hopper

Define

“Y” Identified

Draft Charter

10/7/03 10/07/03

Process Map

C&E Matrix or FTA

30 day MBB check-in

Preliminary FMEA or FTA

11/10/03

11/17/03

12/01/03

10/8/03

10/10/03

10/07/03

10/08/03

MBB Review

MSA

Measure 10/27/03

Initial Capability Study

Multi-Vari

Analyze

MBB Revie w

Contract Approval

12/15/033

Legend

12/15/03

Actual completion date Completion check

M/D/Y 12/26/03

One Factor or Multiple Factor Testing (DOE)

Improve 3/5/04

Control Plan

1/20/04

1/20/04

1/21/04

M/D/Y

Planned completion date MBB Revie w

Project Close Date = Quality Champion Sign-off

3/5/04

Control plan hand off Training

Final Capability Study

Process Owner Sign-off

Final Project Presentation & Report

MBB Review & Approvals

Control 3/25/04

4/5/04

4/5/04

4/2/04

4/9/04

4/14/04

Grados de Six Sigma • Yellow Belt • Green Belt • Black Belt • Master Black Belt

Como certificarte? • Existen companias dedicadas a la certificacion de Belts. • Para todos los grados, la certificacion incluye una parte teorica y una practica • Generalmente la parte teorica incluye de 2 a 4 semanas de entrenamiento. • La parte practica es cubierta con la implementacion de un proyecto Six Sigma

Leoni Wiring Systems Inventory Reduction

Definicion del Problema

Raw Material Inventory Project Objective: Benefits:

Project Team:

Schedule:

Reduce raw material inventory level from 100 days in supply to 40 days supply without affecting on time delivery. -reduced investment -reduced material handling cost -reduced material storage cost -increased floor space availability for new business -decreased manpower required to manage inventory -reduced risk of obsolete and excess material -total savings of $240k Belt: Haydee Garcia Sponsors: Jay Meridew CFO MBB: James Blomenberg Mick Holland COO Core Team: Logistics Manager: Abelardo Aragonez Warehouse Supervisor: Moises Ibarra Procurement Supervisor: Brenda Carranza Finance Manager: Cynthia Armenta Measure: 12/17/03 Analyze: 01/23/04 Customer Service Supervisor: Eduardo Quijada Improve: 03/08/04 Control: 04/27/04 Closeout: 05/21/04

Medicion

Measure Phase

System Mother Nature

I nventory Management

50k High Level Process Step

Process Inputs

8

10

Outputs (Y’s) 9

9

9

252

Static Data

9

9

9

252

Plan Production, Procure Material, Receive Material, Process Demand

Training

9

9

9

252

Run MRP

Raw Matl Inventory Accuracy

9

9

9

252

People

9

9

9

252

Purchasing Agreements

9

9

9

252

9

9

9

252

Process Demand

Cust. Demand (Firmed Orders/Forecast)

9

9

3

192

Process Demand

Supplemental Forecast

9

9

3

192

Vindiola (3rd party provider)

9

9

3

192

Procure Material, Receive Material, Process Demand, Plan Production

Raw Material Type

People On Time Raw Analysis Material Material I nventory Visual (MRP) Raw Material Management Top 5 KPIV’s: Quantity System Mother Nature 10Maps KPIV carried Process All X’sRaw 37 inputs On Time 1. Supplemental Forecast to FMEA Top 5 KPIV’s: Analysis C&E Matrix M 1st “Hit List” 10 inputs Material Screened List 5 inputs FMEA/Multi-Vari Procure Material

Receive Material, Process Demand, Plan Production, Procure Material

8

10

Type of material

10

Raw material quantity

1. 2. 3. 4. 5.

Procedures

On time raw material

Rating of Importance to Customer Receive Material

Process Step

Process Inputs

Process Demand

EDI system

9

9

9

252

Plan Production, Run MRP, Process Demand,

Static Data

9

9

9

252

Plan Production, Procure Material, Receive Material, Process Demand

Training

9

9

9

252

Raw Matl Inventory Accuracy

9

9

9

252

9

9

252

9

9

252

9

9

252

9

3

192

9

3

192

9

3

192

Run MRP

2. 3. 4. 5.

Total

Raw Material Inventory Accuracy A Found Critical X’s Controlling Critical X’s Static Data Training Break point= 560 Procedures Matrix Critical Input Variables

Procure Material, Receive Material, Process Demand, Plan

People Production Supplemental Forecast 3 inputs Design of Exp. Purchasing I 50K Agreements Material 2 inputs 9 RawProcure Material Inventory Accuracy Control Plans Receive Material, Process Demand, Plan Production, Procure C 9 Procedures Material Static Data 6 Inputs/ 3 Outputs Cust. Demand (Firmed 9 Orders/Forecast) Process Demand Training 5K Break point= 560 9 Supplemental Forecast Process Demand Procedures Vindiola (3 party 37 Inputs carried to C&E Receive Material

Total

EDI system

Process Demand

Plan Production, Run MRP, Process Demand,

Raw Material Quantity

10

Type of material

Inputs (X’s)

Raw Material Type

Rating of Importance to Customer

Raw material quantity

People Material Visual (MRP)

Outputs (Y’s)

On time raw material

50k High Level

Inputs (X’s)

9

rd

provider)

9

MSA results # of days = of inventory

$ in raw material $ in production

= raw material quantity X suppliers’ cost harness quantity X customer price 4 elements to check: – – – –

Raw material quantity Raw material price Harness quantity Harness price

94.09% 91.46% 95.00% 93.25%

Analisis

Analyze Phase I and MR Chart for DaysProd by MONTH Individual Value

Not normal data

Normality: P value= 0.004 Stability:

5 100 90 80 70 60 50 40 30 20

Subgroup

Moving Range

40

Process Capability Analysis for DaysProd

6

15

7

22

1 55656

9

Process Data USL

65.0000

Target

40.0000

Lower Bound Mean

Target

Mean=62.64 LCL=38.15

50 6

100

7

8

1

1

9 1

10

Overall

Sample N

156

StDev (Within)

6.6414

StDev (Overall)

10.2668

Potential (Within) Capability Cp * CPU CPL

-0.01 *

Cpk

-0.01

Cpm

* Overall Capability

Pp PPU

0

20

40

Observed Performance * -0.00

PPL

*

Ppk

-0.00

PPM < LB

0.00

60

80

Exp. "Within" Performance PPM < LB

100 Exp. "Overall" Performance

*

PPM < LB

*

PPM > USL

442307.69

PPM > USL

507181.36

PPM > USL

504645.67

PPM Total

442307.69

PPM Total

507181.36

PPM Total

504645.67

1

11

12

Stable data

UCL=30.09

LCL=0

Within

0.0000

10

150

R=9.209

USL

65.1196

12

6

0 LB

11

6666

0 5

10

UCL=87.13

62 1

30 20

8

We need to move the mean to the target value

After the Multi-Vari analysis, we found 3 inputs with big impact on our main output : 3. Training 4. Inventory Accuracy 5. Supplemental Forecast With these, we conducted a full factorial DOE, having the following results: Pareto Chart of the Standardized Effects (response is DAYS, Alpha = .10) A: SUPP B: INV C: TRAIN

A

Main Effects Plot (data means) for DAYS C

AL RM NO

AB

HI

HI

LO

HI

LO

54.0

51.5

0

1

2

3

4

5

6

DAYS

B

49.0

46.5

44.0 SUPP

INV

TRAIN

Mejora

Improvement Summary • Customer Service Department was transfered to Hermosillo plant in order to improve communication, offer a better service, and have a deeper understanding of the forecasted production. • Material Agreements were developed with customers in order to establish safety stock levels, MOQ, Standard pack size, etc. • A new method was implemented to improve stock accuracy by classifying and prioritizing raw material, and redesigning cyclecounting. • Special training material was developed to help personnel in logistics area do a better job and understand the business. • Continuous review and updating of ERP static data is taking place

Control

Control Plan Raw Material Inventory Reduction Control Plan

Process

Process Step

Inventory

Inventory

management Inventory

Output

N/A

management Inventory Days Process demand N/A

management Inventory

Inventory

management

management

Input

N/A

Process Specifications 40 days +/- 7 days

Capability /Date

Measurement Technique Report

1/21/2004 Supplemental 100% accuracy Forecast Training

MSA Result

Sample Size

95%

1/21/2004 actual demand HR employee file

required training

1/21/2004

Control Method

Reaction Plan

RM & WIP

MPS report vs

completion of

Sample Frequency daily

I-MR chart

Contact Logistics Manager

weekly

p-chart

Contact Logistics Manager

biannually

p-chart

Contact HR manager

100% 95% every employee 100%

fin