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Measure : SPCMeasure : SPC

Dedy SugiartoDedy Sugiarto

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Statistical Process Control ≈ Statistical Process Control ≈

Variation or Variation or VariabilityVariability

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No two units of productNo two units of product produced by a produced by a manufacturing process manufacturing process are identicalare identical..

Some variation is inevitableSome variation is inevitable. Simple . Simple case: make signature two times!case: make signature two times!

StatisticsStatistics is the science of analyzing data is the science of analyzing data and drawing conclusions, taking and drawing conclusions, taking variationvariation in the data into account. in the data into account.

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What is Variation?What is Variation?

Less Variation Less Variation ==

Higher QualityHigher Quality

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http://www.asq.org

SPCSPC = The application of statistical = The application of statistical techniques to control a process, reducing techniques to control a process, reducing variation so that performance remains variation so that performance remains within boundaries, or specification limits. within boundaries, or specification limits.

SQCSQC = The application of statistical = The application of statistical techniques to control quality; includes techniques to control quality; includes acceptance sampling (inspection of a acceptance sampling (inspection of a sample from a lot to decide whether to sample from a lot to decide whether to accept that lot) as well as SPC. accept that lot) as well as SPC.

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The seven major tools are

HistogramHistogram Control ChartControl Chart Flow Chart (With Microsoft Visio)Flow Chart (With Microsoft Visio) Check Sheet (With Microsoft Excel)Check Sheet (With Microsoft Excel) Scatter DiagramScatter Diagram Pareto DiagramPareto Diagram Cause-and-Effect DiagramCause-and-Effect Diagram

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Seven Tools of Quality Seven Tools of Quality ImprovementImprovement

Histogram - Histogram - A graphic summary of variation in a set of data. A graphic summary of variation in a set of data. The pictorial nature of the histogram lets people see The pictorial nature of the histogram lets people see patterns that are difficult to detect in a simple table of patterns that are difficult to detect in a simple table of numbers. numbers.

Control chart - Control chart - A chart with upper and lower control limits A chart with upper and lower control limits on which values of some statistical measure for a series on which values of some statistical measure for a series of samples or subgroups are plotted. The chart of samples or subgroups are plotted. The chart frequently shows a central line to help detect a trend of frequently shows a central line to help detect a trend of plotted values toward either control limit. plotted values toward either control limit.

Flowchart/process mapFlowchart/process map - Graphical tools for process - Graphical tools for process understanding. A flowchart creates a graphical understanding. A flowchart creates a graphical representation of the steps in a process. A process map representation of the steps in a process. A process map adds lists of inputs and outputs for each step. adds lists of inputs and outputs for each step.

Check sheetCheck sheet - A simple data-recording device. The check - A simple data-recording device. The check sheet is custom-designed by the user, which allows him sheet is custom-designed by the user, which allows him or her to interpret the results easily. or her to interpret the results easily.

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Seven Tools of Quality ImprovementSeven Tools of Quality Improvement

Scatter diagrams - Scatter diagrams - A graphical technique to analyze the relationship A graphical technique to analyze the relationship between two variables. Two sets of data are plotted on a graph, between two variables. Two sets of data are plotted on a graph, with the y-axis being used for the variable to be predicted and with the y-axis being used for the variable to be predicted and the x-axis being used for the variable to make the prediction. The the x-axis being used for the variable to make the prediction. The graph will show possible relationships among variables: those graph will show possible relationships among variables: those who know most about the variables must evaluate whether they who know most about the variables must evaluate whether they are actually related or only appear to be related. are actually related or only appear to be related.

Pareto chartPareto chart - A graphical tool for ranking causes from most - A graphical tool for ranking causes from most significant to least significant. It is based on the Pareto principle, significant to least significant. It is based on the Pareto principle, which was first defined by J. M. Juran in 1950. The principle, which was first defined by J. M. Juran in 1950. The principle, named after nineteenth-century economist Vilfredo Pareto, named after nineteenth-century economist Vilfredo Pareto, suggests that most effects come from relatively few causes; that suggests that most effects come from relatively few causes; that is, 80% of the effects come from 20% of the possible causesis, 80% of the effects come from 20% of the possible causes

Cause-effect diagramCause-effect diagram - A tool for analyzing process dispersion. It is - A tool for analyzing process dispersion. It is also referred to as the "Ishikawa diagram," because Kaoru also referred to as the "Ishikawa diagram," because Kaoru Ishikawa developed it, and the "fishbone diagram," because the Ishikawa developed it, and the "fishbone diagram," because the complete diagram resembles a fish skeleton. The diagram complete diagram resembles a fish skeleton. The diagram illustrates the main causes and subcauses leading to an effect illustrates the main causes and subcauses leading to an effect (symptom). (symptom).

. .

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Types of variationTypes of variation

Common Causes of variaton

Special Causes of variaton

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Special CausesSpecial Causes Common CausesCommon Causes

* Change in raw material* Change in raw material * Badly maintained machines* Badly maintained machines

* Change in machine setting* Change in machine setting * Poor lighting* Poor lighting

* Broken tool or die or pattern* Broken tool or die or pattern * Poor workstation layout* Poor workstation layout

* Failure to clean equipment* Failure to clean equipment * Poor instructions* Poor instructions

* Equipment malfunction* Equipment malfunction * Poor supervision* Poor supervision

* Keying in incorrect data* Keying in incorrect data * Materials and equipment no suited * Materials and equipment no suited to the requirementsto the requirements

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Examining VariationExamining Variation

Common CausesCommon Causes

The cause of variations in a The cause of variations in a stable process is called a stable process is called a

Common CauseCommon Cause..

A common cause is a natural cause of A common cause is a natural cause of variation in the system.variation in the system.

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Examining VariationExamining VariationStable ProcessStable Process

Normal distribution at all timesNormal distribution at all times

Prediction

Time

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Examining VariationExamining Variation

Thic

kness

Activity: Comparing stable processesActivity: Comparing stable processes

Which process has better quality?Which process has better quality?

1501401301201101009080706050

1501401301201101009080706050

Thic

kness

Sequence0 5 10 15 20 25

Sequence0 5 10 15 20 25

AA BB

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Reducing VariationReducing Variation

Centering at TargetCentering at Target

Reducing Common Cause VariationReducing Common Cause Variation

Improving a Stable ProcessImproving a Stable Process

Two strategies for improving a stable processTwo strategies for improving a stable process

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Reducing VariationReducing VariationCentering at TargetCentering at Target

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ickn

ess

200180160140120100806040200

Time

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Reducing VariationReducing VariationReducing Common Cause VariationReducing Common Cause Variation

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ickn

ess

200180160140120100806040200

Time

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Reducing VariationReducing Variation

Structured problem solvingStructured problem solving Planned experimentsPlanned experiments

Reducing Variation in a Stable Reducing Variation in a Stable ProcessProcess

Make Permanent ChangesMake Permanent Changes

Changes are based on the scientific Changes are based on the scientific approachapproach

Examples: new equipment, equipment upgrade, new procedure, new machine

settings, better raw material

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Examining VariationExamining Variation

Special CausesSpecial Causes

Anything that causes variations that Anything that causes variations that are not part of the stable process are not part of the stable process

is called a is called a special causespecial cause, , assignable causeassignable cause, or , or unnatural unnatural

causecause..

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Examining VariationExamining VariationUnstable ProcessUnstable Process

Any process that is not stable is called an Any process that is not stable is called an unstableunstable or or out-of-controlout-of-control process. process.

Prediction

Time

??

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Reducing VariationReducing Variation

Do not Do not ignore special causes.ignore special causes. DoDo quickly detect special cause quickly detect special cause

variations.variations. DoDo stop production until the process stop production until the process

is fixed. (Reactive)is fixed. (Reactive) DoDo identify and permanently identify and permanently

eliminate special causes. (Preventive)eliminate special causes. (Preventive)

Reducing Variation in an Reducing Variation in an Unstable ProcessUnstable Process

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Reducing VariationReducing Variation

DetectDetect the special cause variation. the special cause variation. IdentifyIdentify the special cause. the special cause. FixFix the process the process

• Remove the special cause, orRemove the special cause, or• Compensate for the special cause.Compensate for the special cause.

PreventPrevent the special cause from the special cause from occurring againoccurring again

Improving an Unstable ProcessImproving an Unstable Process

Four Step ProcessFour Step Process

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Reducing VariationReducing VariationImproving an Unstable ProcessImproving an Unstable Process

ReactiveReactive200180160140120100806040200

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Time

Detect HereNot Here

Detect Here

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Detecting VariationDetecting Variation

How can we decide if variation is the How can we decide if variation is the result of common or special cause? result of common or special cause?

By using control chart By using control chart

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Control ChartControl Chart(The Concept)(The Concept)

Process that Process that not in a state of statistical control not in a state of statistical control will will showshow excessive variations and exhibit excessive variations and exhibit variations that change with time.variations that change with time.

Process in a state of statistical control is called Process in a state of statistical control is called statistically stablestatistically stable..

Control chartControl chart is used is used to detectto detect whether a whether a process is statistically stable.process is statistically stable.

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Control ChartControl Chart(Assumption on the Statistic)(Assumption on the Statistic)

It is It is independentindependent, i.e. value is not influenced by , i.e. value is not influenced by its past value and will not affect future values.its past value and will not affect future values.

It is It is normally distributednormally distributed, i.e. the data has a , i.e. the data has a normal probability density function.normal probability density function.

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Control ChartControl Chart(Types of Chart)(Types of Chart)

Different charts is used depending on the Different charts is used depending on the nature of the charted datanature of the charted data..

For For continuouscontinuous ( (variablesvariables) ) datadata::– Shewhart sample Shewhart sample meanmean and and rangerange charts. charts.

– Shewhart sample Shewhart sample meanmean and and standard deviation standard deviation charts.charts.

– Shewhart Shewhart samplesample and and moving rangemoving range charts. charts.

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Control ChartControl Chart(Types of Chart)(Types of Chart)

For For discretediscrete ( (attributesattributes) ) datadata::– Sample proportion defective chart.Sample proportion defective chart.

– Sample number of defectives.Sample number of defectives.

– Sample number of defects.Sample number of defects.

– Sample number of defects per unit.Sample number of defects per unit.

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Control Chart SelectionControl Chart Selection

Quality Characteristicvariable attribute

n>1?

n>=10 or computer?

x and MRno

yes

x and s

x and Rno

yes

defective defect

constant sample size?

p-chart withvariable samplesize

no

p ornp

yes constantsampling unit?

c u

yes no

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Interpreting x-bar charts : one Interpreting x-bar charts : one point outside control limitpoint outside control limit

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Interpreting R charts : one point Interpreting R charts : one point outside control limitoutside control limit

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Interpreting x-bar and R charts : Interpreting x-bar and R charts : one point outside control limitone point outside control limit