qm-statistical control charts

8/14/2019 QM-Statistical Control Charts

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Statistical Control Charts Basic Concepts

Mean Chart

Range Chart C Chart

P Chart

NP Chart


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Basic Concepts Control Charts form an integral part of

production process.

Samples taken continuously on aregular basis and data analysedstatistically which will give a valuedinformation.


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Advantages Anticipating trouble during production

in the form of deterioration in qualityof materials, properties or processcharacteristics and predicting well intime so that the causes can beidentified and remedial or corrective

action taken in time. Reduction in rejection rates thereby

enhancing production.

Reducing cost of inspection.


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Advantages Narrowing down the specifications,

thus enabling higher quality ofproduction without increasing cost of

production. Allowing efficient use of materials. Reducing cost of production and

affecting large savings. Providing sound & scientific altering

for specification for high productivityand better economy.

Fool proof method for past & presentperformance.


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Mean Chart Control limits are shown by two limits,one upper, and other lower, indicatingthat the distribution of points should

not occur out side these two limits. If the tendency for the points to go outof the upper or lower limits persiststhere would be a problem of arisingand the process going out of control.

The control limits are called warninglimits and the other action limits.


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Mean Chart If the points are dispersed within

warning limits, the process is said tobe stable and under control.

If the points cross both limits, it showsreal danger, warranting immediateaction by stopping the process to

prevent any damage.


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Range Chart Range Charts are a set of control

charts for variables data (data that isboth quantitative and continuous inmeasurement, such as a measureddimension or time)

The Range chart monitors the

variation between observations in thesubgroup over time.


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Range Chart Used when you can rationally collectmeasurements in groups (subgroups)of between two and ten observations.

The charts' x-axis are time based, sothat the charts show a history of theprocess. It is necessary to have datathat is time-ordered; that is, entered in

the sequence from which it wasgenerated


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C Chart


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C Chart The final product is still useful but are

with numbered defects. For example: steel sheets, wood

furniture etc


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P Chart In this chart, we plot the percent ofdefectives (per batch, per day, permachine, etc.) as in the C chart.

The control limits in this chart are notbased on the distribution of rareevents but rather on the binomialdistribution (of proportions).

Is mostly applicable to situationswhere the occurrence of defectives isnot rare (e.g., we expect the percentof defectives to be more than 5% of

the total number of units produced).


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NP Chart Is used to determine if the rate of

nonconforming product is stable,

and will detect when a deviationfrom stability has occurred.

There should only be an Upper

Control Limit (UCL), and not aLower Control Limit (LCL) sincerates of nonconforming productoutside the LCL is actually a goodthin .


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NP Chart There is a difference between a "PChart" and an "Np Chart". A P chart isone that shows the fraction defective

(p), whereas the Np chart shows theNUMBER of defectives (Np). They are practically the same thing

with the exception that an Np chart isused when the size of the subgroup

(N) is constant, and a P chart is usedwhen it is NOT constant.


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NP Chart STEP #1 - Collect the data recordingthe number inspected (N) and thenumber of defective products (Np).

Divide the data into subgroups.Usually, the data is grouped by date orby lot numbers. The subgroup size (N)should be over 50, and it is stronglyrecommended you stick with the

constant sample size of 100 forsubgroups. STEP #2 - Record the number of

defectives on a chart or spreadsheet,along with the subgroup size.

STEP #3 - Record the number of

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