MEANING & SIGNIFICANCE OF STATISTICAL PROCESS CONTROL

[SPC]

Presented by,JAYA VARATHAN B SANKARAN S SARAVANAN J THANGAVEL S

PRESENTATION OUTLINE• History Of SPC• Meaning &Significance Of SPC• SPC in TQM• SPC in Production• SPC Process• Variation-Natural&Assignable• Using sample in SPC• Control charts using SPC• Applying SPC to services• Advantages of SPC

HISTORY OF SPC

Foundation for Statistical Process Control was laid by Dr.Walter Shewart

In 1920s conducting research on methods to improve quality and lower costs .

Concept of control with regard to variation, and came up with Statistical Process Control Charts.

Today,SPC is used in both production & services all over the world.

MEANING OF SPCMethod for achieving quality control in

manufacturing processes.An optimisation philosophy concerned with

continuous process improvements, using a collection of (statistical) tools for – data and process analysis – making inferences about process behaviour – decision making

It Employs control charts to detect whether the process obeserved is under control or not.

SIGNIFICANCE OF SPC

Detecting error at inspection.More uniform quality of production.Reduces inspection costs.Reduces no of rejects and saves the cost of

material.Determining the capability of the

manufacturing process.Once the process is stable, provides process

capability analysis with comparison to product tolerance.

SPC IN TQM

SPC– Using PDSA CYCLE .– Tool for identifying problems

and make improvements.– Contributes to the TQM goal of continuous improvements.

Variation is inherent in every process. Natural or common causes. Special or assignable causes.

Four sources of variation - Process, materials, operators & miscellaneous [ includes heat,light,radiation and humidity].

Provides a statistical signal when assignable causes are present.

Detect & eliminate assignable causes of variation.

SPC IN PRODUCTIONSPC IN PRODUCTION

PROCESS IN SPC

Identify measurable atrributes of process

Identify defined process

Characterize natural variation of attributes

Is process controlled ?

Identify assignable causes

Track variation Removes assignable cause

YES

NO

NATURAL VARIATIONCommon causesInherent in a processCannot be eliminated Like difference in operator ,machine vibration,

minor variation in raw materials ...etc; Output measures follow a probability

distributionFor any distribution there is a measure of central

tendency and dispersionIf the distribution of outputs falls within

acceptable limits, the process is said “in control”

ASSIGNABLE VARIATION

Special causesLarger in magnitude and easily tracedCan be eliminated only through improvements

in the systemLike difference among machines,process,

materials, relationship with one another....etc; When assignable causes are present

Eliminate the bad causes

Incorporate the good causes

USING SAMPLES IN SPCUSING SAMPLES IN SPC

To measure the process, we take samples and analyze the sample statistics following these steps

(a) Samples of the product, say five boxes of cereal taken off the filling machine line, vary from each other in weight

Fre

qu

ency

Weight

#

## #

##

##

#

# # ## # ##

# # ## # ## # ##

Each of these represents one sample of five boxes of

cereal

CONTROL CHARTS USING SPCCONTROL CHARTS USING SPCControl charts, also known as Shewhart charts (after Walter A. Shewhart) or process-behavior charts, in statistical process control are tools used to determine if a manufacturing or business process is in a state of statistical control.

OBJECTIVES

Be able to explain how control charts relate to assigned dimension and tolerance

State what value you get from control chartsBe able to name several ways that control

charts indicate that a process is “out of control”

Normal Distribution Defined by two parameters:

mean and standard deviation

Reminder:

, R AND S CHART

Mean [avg] - Calculated by summing all of the observations and dividing by the number of observations.

Range - Measure of the spread of the data, calculated as highest value minus lowest value

SD -Measure of the spread of a set of data from its mean, abbreviated:

σ for a population , s for a sample

The standard deviation is the square root of the variance.

X

X

What does the control chart look like?X

- First we measure a number of parts as they come off the line. - For eg we might measure 4 parts per hour for 20 hours.Those 80 parts would give us an overall mean and standard deviation that would define the control chart.

µ

µ+3σ

µ-3σ

Time

Q - How do you know a process is “out of control”?

A – When the data aren’t “normal”

“Out of Control” cues include - Points outside of control limits (±3σ) - 8 consecutive points on one side of center line - 2 of 3 consecutive points outside the 2σ limits - 4 of 5 points outside the 1 σ limits - 7 consecutive points trending up or down

2.50±0.05

Example:

Suppose we specify a dimension and tolerance as shown.

X

µ+3σµ-3σ

2.552.45

Assigned Tolerances

Measured Variation

How does the control chart relate to the tolerances?

Defect Prevention

When you see signs that the process is “out of control” you can look for and fix the causes before you make bad parts.

The control chart can help you distinguish between “common cause” & “special cause” problems.

Nature of defect is different in servicesService defect is a failure to meet customer

requirementsMonitor times, customer satisfaction

Applying SPC to Service

Applying SPC to Service Hospitals

timeliness and quickness of care, staff responses to requests, accuracy of lab tests, cleanliness, courtesy, accuracy of paperwork, speed of admittance and checkouts

Grocery Stores waiting time to check out, frequency of out-of-stock items,

quality of food items, cleanliness, customer complaints, checkout register errors

Airlines flight delays, lost luggage and luggage handling, waiting time

at ticket counters and check-in, agent and flight attendant courtesy, accurate flight information, passenger cabin cleanliness and maintenance

ADVANTAGES OF SPC

Improving product quality Improving productivity Streamlining process Reducing wastage Reducing emissions Improving customer service, etc.