spc-training for cq

1CENTRAL QUALITY TRAINING

STATISTICAL PROCESS CONTROL (SPC)

PRESENTED BY:-

RANISH BERA


Objectives

• Acquaintance with basics of SPC

• Evaluation of “Process Capability”

• Read and Understand “Control Charts”

• Which “Control Chart” to use

• Implement SPC in your area


Contents

• Back To School

• Normal Distribution

• Variable and Attribute Data

• Basics of SPC

• Variability

• Common and Special Causes of variation

• Types of Variation in Processes

• Process Capability

• What is Process Capability?

• How to evaluate Process Capability?

• Control Charts

• Which control chart to use?

• X-MR Chart

• Other charts and their usage

• Continuous Improvement through SPC

• Local and Systemic improvement


Back to School

• Normal Distribution

• No two products, be it anything, are exactly identical, e.g. Diameter of Shaft, Height of Men of particular age group, Time to process an invoice etc. – All normal Occurrences or Naturally Occurring Phenomena

• There must be “VARIATION” in parts or products or occurrences

• Normal Distribution approximates many natural phenomena and thus is aptly called “NORMAL”

• Many “OTHER DISTRIBUTIONS” approach or tend to be “NORMAL DISTRIBUTION”for large observations or data


Back to School

Normal Distribution


Back to School

Normal Distribution & Standard Deviation


Back to School

• Variable and Attribute Data

• Attribute Data: Any data measurements that are not quantified on an infinitely divisible numeric scale. Attribute data can only be classified not quantified. Includes items like counts, proportions, ratios, or percentage of a characteristics, (i.e. sex, loan forms, department attendance, etc.) that have measurements like pass or fail, leak or no leak, small, medium, or large, go or no go tests

• Variable Data: Any data measurements that are quantified on an infinitely divisible numeric scale. Variable data can be quantified. Includes items like lengths, diameters, temperatures, electrical measurements, or hours, (i.e. blue print specifications, electrical specifications, etc.) that have measurements like 2.34, 2.55, etc

• Variable Data can be converted to Attribute Data, but not vise-versa using go-no go gauge or a rating system.


Basics of SPC

Variability


Basics of SPC

• Variability

• No two things are exactly alike

• Not only thoughts but also appearance of people differ, even if they are twins

• Temperature changes continuously

• Products we manufacture change continuously


Basics of SPC

• Common Causes of Variation

• Common cause of variation refer to many sources of variation within a process that has a stable and repeatable distribution over time

• When only common causes are present and are not changing, the process is said to be in Statistical Control

• If only common causes are present and do not change, the output of the process is predictable


Basics of SPC

• Special Causes of Variation

• Refer to any factor causing variation that are not always acting on the process

• Lead to sudden change in nature

• If special causes are present, they will affect the process output in an unpredictable way

• Process output will not be stable over time


Basics of SPC

• How processes can differ?

• Location

• Spread

• Shape


Basics of SPC

• Location – Mean (A measure of Central Tendency) Denoted as µ

• Mean is equal to sum of all values divided by total number of observations or data

• Spread – Standard Deviation Denoted as σ

• The root mean square of deviations from mean

• Shape – Whether the data is skewed. A histogram is pictorial representation of distribution of data

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Process Capability


Process Capability

• Process capability is defined as the capability of a process to meet its purpose as managed by an organization's management and process definition structures

• Hence process capability consists of two parts:-

• Measure of variability of output of the process

• Comparison of the variability with the specification of the product output

• Process capability has meaning when the process is in statistical control

• This means that the process must vary because of common causes of variation and not special causes of variation

• A batch of data needs to be obtained from the measured output of the process. The more data that is included the more precise the result, however an estimate

can be achieved with minimum 25 data points. 30 data points is recommended.


Process Capability

• Process Capability is measured by an index called Process Capability Index, Denoted as Cpk

• The formulas for finding the indices are as follows:-

Index Description

Estimates what the process is capable of

producing if the process mean were to be

centered between the specification limits.

Assumes process output is approximately

normally distributed.

Estimates process capability for

specifications that consist of a lower limit

only (for example, strength). Assumes

process output is approximately normally

distributed.

Estimates process capability for

specifications that consist of an upper

limit only (for example, concentration).



Estimates what the process is capable of

producing, considering that the process

mean may not be centered between the

specification limits. (If the process mean

is not centered, overestimates process

capability.) if the process mean

falls outside of the specification limits.




Process Capability

Process Capability and Rejection


Process Capability

Centered Process and

Off-Centered Process


Process CapabilityCentered Process and

Off-Centered Process


Process Capability

Six Sigma Process


Process Capability

• One can use Microsoft excel to conveniently calculate Capability

Capability

Calculation


Control Chart

Which Control Charts to Use?


Control Chart


Control Chart

• X-R Chart

• Preparatory Steps

• Data Collection

• Define Trial Control Limits

• Validate Control Limits

• Process Capability Study

• On Going Control

• Improvement


Control Chart

• Preparatory Steps

• Establish an environment suitable for action

• Define the process

• Determine characteristics to be charted

• Define the measurement system

• Minimize unnecessary variation


Control Chart

• Data Collection

• Select size frequency and number of subgroups

• Record raw data in control chart

• Calculate average (X) and Range ( R ) of each subgroup

• Select Scales for Control Chart

• Plot Averages and Ranges on Control Chart


Control Chart

• Define Trial Control Limit

• Calculate Average Range ( R ) and Process Mean (X)

• Calculate the Trial Control Limits

• Else calculate using Microsoft Excel

• Draw Lines for the Averages and the Control Limits on the Charts


Control Chart

• Validation of Control Chart

• Discard all subgroup showing out of control situation (Starting from R Chart)

• Re-calculate control limits, plot and analyze for any out of control situation

• Again discard if any out of control situation is found again

• Continue the cycle until all plot indicate a control situation

• Repeat the same exercise with average chart

• If more than 50% data are required to be discarded, reject all data and recollect data


Control Chart

• Process Capability Study

• Perform Process Capability Study and calculate Cp, Cpk

• Process Performance (Pp) and Process Performance Index(Ppk)


Control Chart

• On-Going Control – Rules for Interpreting Control

Charts

• Rule 1

• Process is out of control if any data point falls outside the 3-sigma limit from centerline

• Implies that the process is grossly out of control


Control Chart


Charts

• Rule 2

• Process is out of control if 7 or more points are on the same side of the centerline

• Implies existence of Bias

7


Control Chart


Charts

• Rule 3

• Process is out of control if 6 consecutive points are continuously increasing or decreasing

• Implies existence of a trend


Control Chart


Charts

• Rule 4

• Process is out of control if 14 or more consecutive points are alternatively increasing and decreasing

• Implies that the variation is not random


Control Chart


Charts

• Rule 5

• Process is out of control if 2 out of 3 points in a row are more than 2 standard deviation from the mean in the same direction

• Variation is not following normal distribution, implying non-random behaviour


Control Chart


Charts

• Rule 6

• Process is out of control if 4 out of 5 points are more than 1 standard deviation from the mean in the same direction



Control Chart


Charts

• Rule 7

• Process is out of control if 15 points in a row are within 1 standard deviation from the mean



Control Chart


Charts

• Rule 8

• Process is out of control if there are 8 points in a row such that no point lies within 1 standard deviation from mean and the points are in both sides of mean or centerline



Control Chart

• Other Control Charts

• Variable Control Chart

� I-MR Chart

� X-S Chart

• Attribute Control Chart

� p - Chart

� np-Chart

� u – Chart

� c- Chart


Continuous Improvement

• SPC provides the mean to match the voice of customer with the voice of Process


Continuous Improvement

• LOCAL ACTIONS AND ACTIONS ON THE SYSTEM

• Local Actions

� Are usually required to eliminate special causes of variation

� Can usually be taken by people close to the process

• Actions on the System

� Are usually required to reduce the variation due to common causes

� Almost always require management action for correction


Thank You for Your Patience and Attention

spc-training for cq

Documents

assumes process

estimates

normal distribution

statistical

control situation

process capability

process output

specification