6 sigma tool overview traducido

8/10/2019 6 Sigma Tool Overview Traducido

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WHY Provides clear understanding of the

execution (baseline). Illustrates what is happening versus

what should be happening. Captures critical organizational

knowledge. Facilitates identification of problemareas.

Stimulates ideas for businessprocess reengineering.

Facilitates identifying locations fordata gathering (processmeasurement).

WHAT

A process map is a graphical means ofdepicting the steps or activities whichconstitute a process. It is a fundamentalplanning tool for identifying customers.Process Maps are also called flow charts.

HOW Use the right people. Include people who

work in the process. Start with Post-It notes; rarely is a sessioncompleted without reworking the map.Enough time needs to be allotted. ProcessMaps take longer than is expected.

Use the common charting symbols.

Mapa del Proceso

When to use:In im plementa t ion p lanning, reassesscr i t ica l needs / s teps f rom other workgrou ps / funct ion s in l ieu of com mercia lagreement changes as appropr ia te , news teps mus t be comm unica ted anddocumented .

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Activities An action that is oneof several sequentialsteps in thecompletion of abusiness process

Roles Funcionales A position assigned or assumed toaccomplish an activity or sub-activity

Diagrama RACI Definicin de Roles yResponsabilidades en un Proyecto (Matriz usada para identiificarrelaciones entre dos o ms comjuntos de informacin)

R = Responsable; A = Accountable; C = Consultado; I = Informado

R C A I

R C A

I

C

C I

R A

I R C A

R C A I

R C A I

I

R C

A

A position assigned or assumed to accomplish anactivity or sub-activity

Activities

An action thatis one ofseveralsequential

steps in thecompletion ofthe project

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Grfica de Pareto

WHY This technique is based on the

Pareto principle (80/20), whichstates that 80% of our problemcan be explained by just 20% ofthe causes.

The Pareto chart makes clearwhich "vital few" problems(causes) should be addressedfirst.

WHAT A bar chart in which the bars are arranged in

descending order, with the largest to the left.Each bar represents a problem (cause). Thechart displays the relative contribution of eachcause to the total problem.

HOW List all elements of interest. Measure the elements, using the same unit of

measurement for each element. Order the elements according to their

measure, not their classification. Create a cumulative distribution for the

number of items and elements measured andmake a bar and line graph.

Work on the most important elements first. Continue for several iterations if data is

available or can be measured.

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Diagrama Causa y Efecto(Espina de Pescado)

WHY Sort and relate the factors

affecting a process while littlequantifiable data is available.

Discussion guide to assist indetermining root causes. To determine the real cause to

the problem versus a symptom. To identify a team's level of

understanding.

WHAT Represents the relationship between an effect(problem) and its potential causes.

HOW Name the problem. Decide the major categories for causes.

Major causes may include: data and

information systems, dollars, environment,hardware, materials, measurements, method,people, training, etc.

Brainstorm for more detailed causes. Ask"why" each major cause happens at least 5times.

Eliminate causes that do not apply. Discuss the causes and decide which are

most important. Work on most important root causes. Perform another iteration for root causes, if

necessary.

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Tabla 1: Categoras sugeridas

Industrias deManufactura (Las 6 Ms)

MachinesMethods

MaterialsMeasurementsMother Nature(Environment)

Manpower(People)

Etapas de Proceso (por ejemplo )

Determine Customers Advertise Product

Incent PurchaseSell ProductShip ProductProvide Upgrade

Industrias deServicio (Las 4Ps)

Policies

ProceduresPeoplePlant/Technology

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Multivoto

WHY Improve the teams' ability or allow

each member to express strength of

opinion through voting withoutrisking judgment by group. To narrow down a list of alternatives

(to the one or two most important) .

WHAT

A method for selecting or narrowing a set of alternatives.Can be used to prioritize a list.HOW List all alternatives and count them ( i.e. , N# of

alternatives). Give each member N/3 votes (or whatever # seems

reasonable given the number of alternatives) . Have each member cast his / her votes given these

guidelines: The member can cast all, some, or none of his

votes for any alternative. When all votes (the sum) are cast, the member is

done. Rank order the alternatives based on the number of

votes received.

Repeat the process until desired result is accomplished.

ISSUE A IIII

ISSUE B III

ISSUE C IIII

ISSUE D II

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Hoja de Verificacin

WHY To present data in a way that clearly

communicates the answer. To help analyze the data to

determine the factual answers to thequestion.

To generate information from data. To collect the data and facts relating

to the question.

WHAT A simple recording form that has been

designed to readily interpret results from theform itself. A well-designed form does morethan simply provide a record of the data itallows simultaneous analysis trends in thedata.

HOW

Formulate good questions that relate tospecific information needs of the project. Use appropriate data analysis tools ( e.g. ,

Pareto, histogram). Define comprehensive data collection points. Understand data collectors and their

environment.

Design data collection form (keep it simple). Train data collectors including purpose of

study Audit the collection process.

Problem

1 2 3 Total A II II I 5

B II I II 5

C IIII II IIII 10

Total 8 5 7 20

Month

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WHY To visually represent data. To monitor a process to see

whether the long range average

is changing. To focus attention on truly vital

changes in the process. To identify meaningful trends or

shifts in the average.

WHAT The simplest possible display of trends

within written observation points over aspecified periods of time.

HOW Identify the measurement to be made.

Decide on the time interval of themeasurements. Select the scale to be used. Plot points on the order in which they

occur and connect with straight lines. Analyze the data looking for non

random events. It is expected that weshould find an equal number of pointsfalling above and below the average.

Measure

Time

Carta de Corrida

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Diagrama de Scatter

WHY To determine relationships between

two sets of data. For example,whether work backlog affects theerror rate of computer data entry.

Data relationships can be non-mathematically evaluated by using ascatter diagram.

WHAT A graphical method of plotting two

parameters to determine if there is arelationship between the two. This tool issometimes called a cross plot or scatter plot.

HOW Collect data that are suspected to be related. The data pairs are plotted on X-Y axis as a

scatter diagram. Each axis is used for one of the two sets of

data being compared. The Y axis is usually reserved for the

characteristic we would like to predict, e.g. ,the error rate. The X axis is used for the variable which

makes the prediction, e.g. , work backlog.

Variable 2

Variable 1

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Carta de Control

WHY Monitor and control a process. At a glance, can determine

whether process is in control. To know when to adjust a

process. To know the difference between

assignable and chance variation. To determine process capability. To predict from the pattern of

variability the percentage of

occurrences that fall outsideexpected values.

WHAT The application of statistical techniques for

measuring and analyzing the variation of aprocess. The diagnosis of the SPC graphsallow one to analyze problems and improvethe process.

HOW

Decisions on the objectives of the charts. Choice of variable or attribute charts. Select subgroup size and frequency of data

collection. Calculate average, standard deviation,

control limits and plot the charts. Draw preliminary conclusions from the

charts. Indication of control or lack of control.Relationship between what process is doingand what its supposed to do.

Take action suggested by the charts.

#

Reading over Time

LCL

X

UCL

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Diagrama de Afinidad

WHY When breakthrough is needed

to help organize. To help develop central

theme. Facts on a problem are not

well organized. Breakthrough in traditional

thinking is needed.

WHAT A tool for organizing facts, opinions and

issues into natural grouping as an aid todiagnose a complex problem. Theinputs are listed on cards which are

then rearranged until useful groups areidentified.HOW Assemble the right team. Clearly state the problem to be

addressed.

Brainstorm ideas on cards. Clearly display cards on wall as ideas

are generated. Sort cards into related groups. Create header cards. Draw the completed diagram.

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Diagrama de Inter relacin

WHY

Allows identification ofpotential root causes whenlittle data exist

WHAT A tool to assist in classification of Cause and Affectrelationships that exist among potential root causes.

HOWDraw the boxes in a circular Pattern. List the potentialroot causes in the boxes. Choose any idea as a startingpoint, Is there a relationship between the boxes. Useonly one way arrows, always draw the arrow to the

stronger direction influence. Repeat the question for theremaining boxes. No relationship is acceptable. Tallythe number of outgoing and incoming arrows for eachbox..

A high number of outgoing arrows indicate root cause.

A high number of incoming arrows indicates an item isan affect.

Focus on root causes.

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A prueba de Error(Poka-Yoke)

WHY

To prevent defects/rework in abusiness process.

WHAT Creative tools/devices/procedures that

mistake -proof a business process. HOW Define defect. Determine cause of defect. Utilize

Brainstorming/Benchmarking/BestPractices to develop a technique tomistake -proof the process.

Implement technique.

????

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Matriz Causa-Efecto

WHY To determine what key process

steps / variables should be thesource of focus for performanceimprovement to best meet customerrequirements.

WHAT A cause and effect matrix is a simplified QFD

(quality function deployment) matrix thatgives focus to the Steps / inputs that aremost likely to affect process output based onCCRs.

HOW List key process steps and / or inputs against

outputs in a matrix format. Give outputs ratings relative to customer

importance Determine correlation between all inputs to

all output variables as follows: 0 = no correlation 1 = remote correlation

3 = moderate correlation 9 = strong correlation Cross multiply and develop input variable

totals. Focus on the variable with the highest

scores.

1 2 3 4 5 6 7 8

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Anlisis de Modo y Efectos de Falla(FMEA)

WHY Methodology that facilitates

process improvement. Identifies and eliminates concerns

early in the development of aprocess or design.

Improve internal and externalcustomer satisfaction.

WHAT Failure Modes & Effects Analysis is a

methodology to evaluate failure modes andeffects in designs and in processes. Theapproach is very similar to the basic PDPCmethod.

HOW

Team identify potential failure modes for designfunctions or process requirements.

They assign severity to the effect of this failuremode.

They assign frequency of occurrence to thepotential cause of failure and likelihood ofdetection.

Team calculates a risk priority number bymultiplying severity times frequency ofoccurrence times likelihood of detection.

Team uses ranking to focus processimprovement.

Likeliness of Failure: 1-10 with 10 representing most likely Detectability of Failure: 1-10 with 10 representing most difficult Severity of Failure: 1-10 with 10 representing most severeRisk Priority = (Likeliness of Failure) X (Detectability of Failure) X

(Severity of Failure)

FailureMode Specific Cause Effect of Failure Likelinessof Failure Detectabilityof Failure Severity of Failure RiskPriorityGas will notshut off

Spring brokepreventing valvefrom closing

Explosion resulting inproperty damageand/or serious injury

3 5 10 150

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Herramientas avanzadas

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WHY To transform data into information

WHAT A statistical discovery software used by

Dow Black Belts to explore data anddiscover patterns

HOW JMP is controlled largely through point

and click ,mouse manipulation and aimsto present a graph with every statistic,very similar to Excel spread sheets.

JMP

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Error de Medicin / Gage R&R

WHY Organizations often overlook

the measurement system as thesource of error resulting inmaking capable processesappear unsatisfactory orunsatisfactory processesappear capable.

Gage R&R measures the quality

of the measurement system.

WHAT A Gage R&R study is conducted to

understand the repeatability andreproducibility of your measurementsystems.

HOW Prepare for Gage R&R study. Conduct Gage R&R study. When R&R divided by the specification

yields: Under 10% Acceptable gage. 10% to 30% May be acceptable. Over 30% Gage is unacceptable and

should be corrected or replaced.

Gage R&R

Repeatability Reproducibility

Measurement Error

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Cp & Cpk (Capacidad del Proceso)

WHY A process is said to be in

control if no special causes ofvariation exist.

A measure of process capabilitycan provide insight into issuesof mean shift of the process orexcessive variability. Theseinsights can be used to improveprocess capability.

WHAT Process capability/performance studies

assess a process relative to specificationcriteria.

Cp is the capability index that is defined asthe tolerance width divided by the processcapability, irrespective of process centering.

Cpk is the capability index that accounts forprocess centering.

HOW Create a control chart. Calculate standard deviation. Calculate C p:

Cp = (USL-LSL)/6s

Calculate C pk: Cpk = min[(USL-m)/3s,(m-LSL)/3s]

x

LSL USL

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WHAT- Sigma is;

A measure of goodness The higher the Sigma level, the lower the defect

rate. How precise the process is at any given time True potential of the process technology to meet the

given performance specifications

What the process can do if everything is controlled Only random variation/background noise present

HOW Use the Z transformThe Z measurement scale has no units

Allows comparison of Zs when units not same Any measurement (X) can be transformed into a ZUse Dow Sigma Calculator Excel spreadsheetWith one process capability measure can calculateothersDow Sigma Calculator.xls

)

Capability Measure AssumptionsCp Normal

Centered

Cpk

Z Values

Normal

DPO

DPMO

Percent Out of Spec

1 Defect Per # of OpportunitiesSigma value

None

Sigma como medida de Capacidad deProceso

Why

Sigma indicates how often defectsare likely to occur .Sigma is a dimension less number andtherefore allows comparison of variouswork processes, products and services

of varying complexity on a similarbasis!

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A: Current PositionWhere at Now?

Business Strategy/Direction/NeedsScope - Products/Services w/ Quantity/DollarsGeneral Background (Include major Barriers - Contract constraints, etc.)Risk/Reward Quadrant AnalysisOther Matrix Analysis as appropriate (Supplier Base, Market Share/Leverage, etc.)

B: Opportunity Analysis/Scenario DevelopmentWhy Should We Do It?

AssumptionsOptions

Obstacles/Barriers Internal - Organizational & Capital CostsRegulatoryMarketSelection & Justification

C: Objective PositionWhat Want to Achieve?

Value Proposition: Cost savings (VAP), Risk reduction, etc.Supplier & Methodology ChangesTime PeriodCan show Directional Change (Arrow) in Matrix from Current PositionCan include Matrix of Market Share/Leverage from Current Position

D: Negotiation PlanWho Does What, When to Deliver the Value?

Roles & Responsibilities - Team DefinitionTactical Plan (Negotiation, Communications, Processes, etc.)

E: Implementation PlanWho Does What, When to Deliver the Value?

Roles & Responsibilities - Team DefinitionTactical Plan (Negotiation, Communications, Processes, etc.)

What is current Sigma?

Calculating Sigma - Defect, Unit and Opportunity (LeGrange research)

Area: Bulk Marine Freight Costsbetween the U.S. and EuropeCustomer Quote: Leverage

combined Dow / UCC volumeScope: shipments between USarea and EuropeCTQ description: Cost per MT CTQ Measure: Dow oldagreement price vs Leveragedagreement priceCTQ Specification: Avg.$3.00 per ton cost reductionDefect: Cost above Six SigmaTarget cost reduction Unit: = $Opportunity: 1.89093E-05 of $

Sigma Calculations by Using Regression

X Axis Y Axis2 Q 2002 cost

per MTDPMO

(long-term)Z (long-term)

Six Sigma level Performance 30.6 6.00 3.4 4.50Baseline level Performance 33.6 2.50 158655.3 1.00

New Performance level 31 3.53 21157.0 2.03

Sigma = 3.53 and a long-term DPMO of 21,157.0defect = 1.89093E-05

SIGMA

0.0

20000.0

40000.0

60000.0

80000.0

100000.0

120000.0

140000.0

160000.0

180000.0

30 30.5 31 31.5 32 32.5 33 33.5 34

2 Q 2002 cost per MT

D P M O ( l o n g - t

e r m

)

DPMO (long-term) = 52883.9529853113 2 Q 2002 cost per MT + -16182 .

There are cases where establishing the unit of measure or basis of adefect for a agreement negotiations / S.A.L.T. project is not always

straight forward and traditional defects cannot be measured.We use regression analysis to establish a Sigma for S.A.L.T. projects.

contact your MBB for assistance in calculating Sigma for your project below is example of Sigma by regression

Baseline

New Performance Level

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Simple Relationship Plots

WHY To provide visual insight into

relationship between KPIVs andKPOVs without requirement to modifythe process.

To develop relationship hypotheseswhich can then be tested statistically.

These graphical techniques aresimilarly used to validate statisticalmodels.

Ultimately, these visualizations offerinsight to direct and focusimprovement efforts.

WHAT Graphical representations of data which enable

relationship hypotheses to be developed. Somekey examples are Multi-Vari Charts, Box Plots,Marginal Plots, Main Effects Plots, and InteractionPlots.

HOW Collect data that are suspected to be related.

Input the data into the plotting feature of a statisticalanalysis program and plot the desired graphs. Analyze the plots for patterns and trends to

determine whether additional testing is required orwhether statistical conclusions seem supported bythe graphical analyses.

NOTE: Conc lus ions shou ld no t be d rawn f romgraphica l techniques . These techniquesprov ide c lues to sugg es t fur ther s ta ti s t ica ltes t ing to formula te f ina l conc lus ions to foc usimprovement .

.85

21 3

.90

.80

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Hypothesis Testing

WHY To utilize test statistics to make

statistically significant inferencesregarding unknown populationsfrom sample data.

To establish a decision rule toachieve an optimal balancebetween taking incorrect actionsas a result of the decision.

WHAT A technique to determine the decision-making

process for an experiment to help ensure thedecision made is statistically valid.

HOW Formulate the hypothesis. Consider whether

upper-tailed, lower-tailed, or two-sided tests arerequired, (Default = 2 sided). Define the nullhypothesis to depict the most significantscenario.

Select the test statistic, eg., population meanis different from value = t test, data is notnormally distributed = chi square / shapiro -wilke.

Establish the significance level and theacceptance and rejection regions for thedecision rule.

Collect the sample data and compute the valueof the test statistic.

Make the decision.

H o is true

H o is false

Reject H o Accept H o

Critical Value

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Analysis of Variance (ANOVA)WHY To determine whether differences exist among

two or more settings, treatments, or conditions.For example, differences between plantaverages.

Treatment similarities and differences can bemathematically evaluated using Analysis ofVariance.

WHAT A mathematical method of evaluating whether the

means of different treatments are the same. Theanalysis determines whether discrepanciesbetween treatment means are more than could bereasonable expected from variation within treatments.

HOW Collect data to compare the different treatments. Input the data into the ANOVA feature of a

statistical analysis program and generate the

ANOVA table. Validate the model by evaluating residual plots (allresiduals, each treatments residuals, residual timesequence, etc).

Utilize the F value to determine the statisticalsignificance level of the comparison.

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Linear Regression Analysis

WHY Explains how statistical modeling fits

into y = f(x)

To determine the relationships ofindependent variables (X) on adependent variable (Y). For example,whether sales are a function of price,promotions, and market factors.Significant relationships are useful forprediction

Cause and effect relationships can bemathematically evaluated usingregression analysis.

WHAT A mathematical method of developing an

equation of a line that best depicts therelationship between the dependent andindependent variables. The line is fitted so thesquared differences between the line and theplotted points are least .

HOW Collect data that are suspected to be related. Input the data into the regression analysis feature of

a statistical analysis program and plot the fittedline.

The R Squared value depicts the percent of thevariation in the data explained by the fittedequation.

Evaluate the T statistic for each dependent (X)variable to determine its statistical significant on Y.

High R Squared and T statistics are desired. In multivariable regression, play with the model by

adding and dropping X variables to achieve high RSquares and T statistics.

Y

X

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