Ch-7 (Statistical Process Control).ppt

7-1 Excel Books Total Quality Management Text and Cases G Nagalingappa, Manjunath V S

Copyright © 2010, G Nagalingappa, Manjunath V S

Statistical Process ControlCH-7

CChapterhapterCChapterhapter

77 Statistical Process

Control




Introduction

Statistical process control (SPC) involves using statistical techniques to

measure and analyze the variation in processes.

SPC is used to monitor the consistency of processes used to

manufacture a product as designed.

There are seven basic statistical tools which are very widely used for

identifying and solving quality-related problems.




Seven Statistical Tools of Quality

1. Pareto chart

2. Process flow diagrams

3. Cause-effect diagrams

4. Check sheets

5. Histograms

6. Control chart

7. Scatter diagrams




Pareto Diagram

Purpose

The purpose of the

Pareto chart is to

prioritize problems.

500

400

300

200

100

0

Dollars Percent

100

80

Salaries Equipment Transport Phone/Fax Suppliers

Charges, First Quarter

Pareto Chart

A Typical Pareto Diagram




• A Pareto chart is a series of vertical bars lined up in a descending order form high to low to reflect frequency, importance, or impact.

• Pareto charts quickly draw everyone’s attention to the most important factor-providing an at-a-glance snapshot of priorities.

• It is graphical overview of process problems in making order of the most frequent, down to the least frequent, in descending order from left to right.




When to use Pareto chart• Is used when the process you are investigating

products data that are broken down into categories and can count the number of times each category occurs.

• Pareto chart can be helpful, “ early on to identify which problem should be studied, later to narrow down which causes of the problem to address first.




Cont….

Process Flow Diagram or Flow Process Chart

Purpose

Flow charts provide a visual illustration of the sequence of operations

required to complete a task.

Flow charts

Flow charting is the first step we take in understanding a process.

Construction of the flow chart (General guidelines)

1. Involving the right people in making the flow chart.

2. Flow charts usually require more time to construct than expected.




3.Asking questions is the key to the flow charting process.

• What is the first thing that happen?.

• what is the next thing that happen?

• Where does the outputs of this operation go?

• Where does the inputs to the process come from?

• how does the inputs get to the process?

• Is their anything else that must be done at this point?




Cont….

Symbols used

Beginning and

Ending steps

Activity

Description

Decision

Box

To show the direction of flow

from one activity to the next.




Steps in drawing flowchart• Identify the start & end of the process.

• Observe the entire process form start to end.

• Define the steps in the process.

• Construct a draft of flowchart to represent the process.

• Review the draft flowchart with the people involved in the process.

• Improve the flowchart based on this review.

• Verify the flowchart against the actual process.

• Date the flowchart for future reference.




Start ReceiveDocument

Enter number ofCopies in Log

StartCopying

RestartCopying

Machine-operatedProperly

Call forPick-up

EndCorrectFault

Yes

No

A Typical Flow Chart




Cont….

Cause and Effect Diagram

Cause-effect diagram is a tool for analyzing and illustrating a process by

showing the main causes and sub causes leading to an effect (symptom).

One method used is the “5M”

Machinery, Manpower, Method, Material, Maintenance

In non-manufacturing organization “4P”

People, Plant (the equipment used), Policies, Procedures.




Cont….

MaterialMachine/

PlantMeasurement/

Policies

QualityProblem

Men/People

Methods/Procedures

Generic cause-effect diagram




Methods

Mixing

Speed

Pre-cure Period

Machines

Molding

Trimming

Stamping

EdgeFlawsBase Specs

Color Matl.

Materials

Base Variation

Supervision

Training

Morale

Operators

Casue and Effect diagram for Edge Flaws




Why should we use a Cause & Effect Diagram

• Is tool that is useful for identifying & organizing the known or possible causes of quality, or the lack of it.

• The structure provided by the diagram helps team members think systematic way.




Benefits of Cause & Effect Diagram

• It encourages the root causes of problem or quality characteristic using a structured approach.

• It encourages group participation & utilizes group knowledge of the process.

• They use an orderly, easy-to-read format to diagram cause-and-effect relationships.

• It indicates possible causes of variations.

• It increases knowledge of the process by helping everyone to learn more about the factors at work and how they relate.

• It identifies areas where data should be collected for further study.




Cont….

Check Sheets

Check sheet is a simple data-recording device.

Check sheets and simple surveys are effective methods, easy to

design, and fun to implement either as an individual or a team.




Check sheets have the following main functions:

1. Production process distribution checks: where distribution lies.

2. Defective item checks: to determine what kind of defects exist in the

process.

3. Defective location checks: to determine where the column defects on

part are located.

4. Defective cause checks: type of defect and thus validate the cause.

5. Check-up confirmation checks : final phase assembly to check the

finished product or work.




Check sheets have the following main functions:

1. creates easy to understand data.

2. Builds with each observation a clear picture of the facts.

3.Forces agreement on the definition of each condition or event of interest.

4.Makes patterns in the data become obvious quickly.

Defect type Insufficient solder

Cold solder Solder bridge

Blow holes Excessive solder

Frequency Xxxx Xxxxx Xxxx Xxx Xxx

Total 4 5 4 3 3




Cont….

Histogram

It is used to determine the spread or variation of a set of data points in a

graphical form.

The histogram will graphically show:

1. The center of the data.

2. The spread of the data.

3. Any data skew ness (slant, bias or run at an angle).

4. The presence of outliers (product outside the specification range).

5. The presence of multiple modes (or peaks) within the data.




Cont….

299.4 299.6 299.8 300 300.2

20

16

12

8

4

0

Histogram

Co

un

ts

Michelso.Dat

A Typical Histogram




20

10

71 77 83 90 97 104 111

No# of Samples = 50

Histogram




Cont….

Statistical Fundamentals

Statistics is defined as the science that deals with:

1. The collection

2. Tabulation

3. Analysis

4. Interpretation

5. Presentation of quantitative data.




Measures of Central tendency

• Mean

• Median

• Mode

• GM

• HM




Dispersion

• SD

• MD

• QD

• CV




Normal curve

Freq

uenc

y

60

50

40

30

20

10

0

Thickness of output in mm

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16

Normal Curve is a smooth symmetrical bell shaped curve as shown below.

CTQ

Normal Distribution Curve




Introduction to Control Charts

Purpose

To ensure that the process is in control and to monitor process variation on a

continuous basis.

Statistical Process Control

The development and use of statistics and statistical theories about

distributions and how they vary has become the cornerstone of process

improvement.

Common and Special Cause Variation

Variation in a process can be caused by, or related to, two types of causes.

1. Common or system causes

2. Special or local causes




• Special causes are problems that arise in a periodic fashion.

• Unpredictable & can be dealt with at the machine or operator level.

• Operator error, broken tools, machine setting drift.




• Common causes are problems in the system itself.

• They are always present & affect the output of the process.

• Poor training, inappropriate production methods, poor work station.




• Shewart chart:

• Statistically based control chart is a device to be used.

• At the point of operation

• By the operator of that process

• To assess the current situation

• By taking sample & plotting sample result.




Steps in control charts

• Identify quality characteristics of product or process that affects fitness for use.

• Design the sampling plan & decide method of its measurement.

• Take samples at different intervals & plot statistics of the sample measurements on the control chart

• Take corrective action : when a signal for significant change in process.




Elements in control charts:

• Upper control limits

• Upper warning line

• Lower control limits

• Lower warning line

• Plotting of sample statistics

• Line connecting the plotted statistics.




Control charts




Variable Control Charts

These charts are used for variable data that is for quality characteristics

which can be measured.

Basic Steps for Control Charts

Elements of Typical Control Chart

Out of Control Process

Interpretation of the X-bar and Range Charts

Factors for Control Chart Limits




Cont….

Control Charts for Attributes

1. Many quality characteristics cannot be conveniently represented

numerically.

2. In such cases, each item inspected is classified as either conforming or

nonconforming to the specifications on that quality characteristic.

3. Quality characteristics of this type are called attributes.

4. Examples are nonfunctional semiconductor chips, warped connecting

rods, etc.

5. Our objectives for this section are to learn how to use control charts to

monitor discrete data.




Process Capability

Process capability is the long-term performance level of the process

after it has been brought under statistical control.

It is the ability of the combination of your 5 M's to produce a product

that will consistently meet the design requirements and the customer

expectation.

Men, machine, material, method, Money.




Process Capability • Inherent variability a quality characteristic that

the process is capable of maintaining, when in a state of statistical control under a given set of condition.

• Process capability = ± 3 SD= Total Spread of 6 SD




• Process capability is the repeatability and consistency of a manufacturing process relative to the customer requirements in terms of specification limits of a product parameter. This measure is used to objectively measure the degree to which your process is or is not meeting the requirements




• Capability indices can be used to compare the product/process matches and identify the poorest match (lowest capability).

• The poorest matches then can be targeted on a priority basis for improvement.




• The diagram on the left shows a series of sample distributions that fall inside of and outside of the specification limit.

• This is an example of an unstable, not capable process. The right side of the diagram shows all of the distributions falling within the specification limits.

• This is an example of a capable process.




• Process capability can be expressed with an index. Assuming that the mean of the process is centered on the target value, the process capability index Cp can be used.




• Cp is a simple process capability index that relates the allowable spread of the spec limits (spec range or the difference between the upper spec limit, USL, and the lower specification limit, LSL) to the measure of the actual, or natural, variation of the process, represented by 6 sigma, where sigma is the estimated process standard deviation.




• If the process is in statistical control, via "normal" SPC charts, and the process mean is centered on the target, then Cp can be calculated as follows:

• Cp = (USL - LSL) / 6 sigma

• Cp<1 means the process variation exceeds specification, and a significant number of defects are being made. This process will produce more than 2700 non-conforming PPM.




• Cp=1 means that the process is just meeting specifications. A minimum of 0.3% defects will be made and more if the process is not centered.

• Cp>1 means that the process variation is less than the specification, however, defects might be made if the process is not centered on the target value.




While Cp relates the spread of the process relative to the specification width, it does not address how well the process average, X, is centered to the target value. Cp is often referred to as process "potential".




• Cpk measures not only the process variation with respect to allowable specifications, it also considers the location of the process average.

• Cpk is taken as the smaller of either Cpl or Cpu

• Cpl = (X -LSL) / 3 sigma where X is the process mean

• Cpu = (USL - X ) / 3 sigma where X is the process mean




Factors influencing process capability

• Condition of machine /equipment

• Type of operation & operational conditions

• Raw materials

• Skill of operators

• Measurement method/instrument

• Inspector’s skill.




• Process Capability Studies are designed to see what the process is "capable" of doing under controlled conditions.

• The studies look at how capable the process is given ideal conditions over a short period of time (such as one hour to twenty-four hours.)

• The individual who is mainly responsible for a the process capability study is a Process Engineer.




• The Process Engineer must keep in mind the following two considerations when conducting the study.




n LA

RG

En SM ALL

x–BAR; s

x–BAR; R

n=1x CHART; MOVING RANGE

n CONSTANT

DEFECTIVEATTRIBUTE

VARIA

BLE

CONTROLCHART

n VAR IABLE

n VARIABLE

DEFECTS n CONSTANT c or u

p

p or np

Decision Tree




Cont….

Scatter Diagrams

The Scatter Diagram is another quality tool that can be used to show

the relationship between "paired data", and can provide more useful

information about a production process.

Scatter diagrams are graphical techniques to analyze the relationship

between two variables.




Constructing the Scatter Diagram

Step 1: Select the two items you wish to study.

Step 2: Collect the data.

Step 3: Draw the axis of the scatter diagram.

Step 4: Plot each set of paired data onto the graph.

Ch-7 (Statistical Process Control).ppt

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