QUALITY CONTROL & QUALITY ASSURANCE:INSPECTION, Control Chart

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Production and Operations Management MGT613

Lesson 27

QUALITY CONTROL & QUALITY ASSURANCE

Quality Control or QC as it is popularly referred as "is concerned with quality of conformance of a

process". The prime purpose of QC is to assure that the processes are performing in an acceptable

manner. Organizations accomplish QC by monitoring process outputs using statistical techniques. The

practical and pragmatic QC based Operations Strategy for a service or manufacturing organization

would focus on the principle of quality in design.

Learning Objectives

Introduction to Quality Control and Assurance

Phases of Quality Control

Elements of Control Process

How control charts are used to monitor a process and the concepts that underlie their use.

Use and interpret control charts.

Use of run tests to check for non randomness in process output.

Phases of Quality Assurance

Phases of Quality Assurance

Inspection

Quality built

Inspection and

Before / after

into the

Corrective action

production

process

during production

Pro

Continuous

Acceptance

ces

improvement

sampling

The most

The least

progressive

INSPECTION

Inspection is an important strategy, in its simplest form, is any method or device or tactics used to

minimize defects in products or services being offered to the customers. As Operations Manager we

should be able to identify the following four questions while considering Inspection process.

1. How Much/How Often

2. Where/When

3. Centralized vs. On-site

4. Whether to inspect Variables or Attributes.

An important thing to remember is that No inspection is necessary for low value, high volume products

like common items like common pins, erasers or pencils while automated inspection is necessary for

high value items. Automated inspection may be necessary for even high value, low volume items as

well. The word volume here refers to quantity.

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Production and Operations Management MGT613

Input

Transformatio

Output

Acceptance

Process

sampling

control

INSPECTION COSTS FOR HOW MUCH/HOW OFTEN

The graph on the next page shows the relationship between amount of inspection required and

costs incurred in carrying out such inspection.

1. With increase in Inspection activities the cost of undetected defectives decreases.

2. With increase in inspection activities the cost of inspection increases.

We need to observe for Total cost function curve which shows high costs at no inspection and gradually

comes down and reaches a minimum value at the optimal amount of inspection and then start increases.

Optimal

Amount of Inspection

Inspection Costs for How Much/How Often

1. Where to Inspect in the Process

2. Raw materials and purchased parts ( DO not purchase poor quality products)

3. Finished products ( Poor products returned by customers can also lead to additional shipping

costs)

4. Before a costly operation ( Do not waste Resources of Man, Material and Machine)

5. Before an irreversible process ( Pottery, Ceramics, Tiles, PC chips, glass filaments)

6. Before a covering process ( Before painting, plating and assembly)

EXAMPLES OF INSPECTION POINTS IN SERVICE INDUSTRY

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We cannot have same inspection points for the service industry, infact we need to pay attention to the

type of industry or business in which a service organization competes. Please refer to the table on the

next page and note the difference in characteristics and location of inspection points.

Type of

Inspection

Characteristics

business

points

Fast Food

Cashier

Accuracy

Counter area Appearance, productivity

Eating area

Cleanliness

Building

Appearance

Kitchen

Health regulations

Safe, well lighted

Hotel/motel Parking lot

Accuracy, timeliness

Accounting

Appearance, safety

Building

Waiting times

Main desk

Supermarket Cashiers

Accuracy, courtesy

Deliveries

Quality, quantity

CENTRALIZED VS ONSITE INSPECTION

1. Inspection of Ships, Nuclear Plants, Petroleum Refinery, Chemical Plant equipments for cracks,

brittle fracture etc both external and internal inspection.

2. Lab tests include blood tests, material testing

QUALITY CONTROL IN TERMS OF STATISTICAL PROCESS CONTROL:

We now focus on the idea of Quality Control in terms of Statistical Process Control, for this we need to

define

Statistical Process Control: Statistical evaluation of the output of a process during production

Quality of Conformance: A product or service conforms to specifications

Which Characteristics can be controlled: Only those characteristics which can be counted or

measured.

Main Task of QC: is to distinguish random from non random variability, because non random

variability indicates that the process is out of control

Control Chart

Control Chart: A time ordered plot representative sample statistics obtained from an on going

process (e.g. sample means)

Purpose: to monitor process output to see if it is random

Upper and lower control limits define the range of acceptable variation

CONTROL CHART & STATISTICAL PROCESS CONTROL

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Production and Operations Management MGT613

Out of

Abnormal variation

contro

due to assignable

Mea

Normal

variation

Abnormal variation

due to assignable

10 11 12 13 14 15

Sample

Statistical Process Control

The essence of statistical process control is to assure that the output of a process is random so

that future output will be random.

Statistical Process Control

The Control Process consists of the following important stages.

1. Define

2. Measure

3. Compare

4. Evaluate

5. Correct

6. Monitor results

Variations and Control

·Random variation: Natural variations in the output of a process, created by countless minor factors

Also called COMMON/ CHANCE. INHERENT and part of the process. E.g. Difference between old

and new machines.

·Assignable variation: A variation whose source can be identified

SAMPLING DISTRIBUTION

The variability of a sample statistic can be described by its SAMPLING DISTRIBUTION. The goal of

sampling is to determine whether non random /assignable/ correctable sources of variation are present in

the output of the process. E.g. Soft drinks bottle are never 250 ML. slight differences among the mean.

SAMPLING DISTRIBUTION

Sampling

distribution

Process

distribution

Mean

NORMAL DISTRIBUTION

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σ = Standard deviation

-3σ

-2σ

+2σ

+3σ

Mean

95.44%

99.74%

CONTROL LIMITS

Sampling

distribution

Process

distribution

Mean

Lower

Upper

contro

CONTROL CHARTS

A control chart is a time ordered plot of sample statistics.

It is used to distinguish between random variability and non random variability.

The basis of control chart is sample distribution which essentially describes random variability.

Theoretically any value is possible as the distribution extends to infinity.

99.7% of all values will be within + 3 standard deviations

Control Charts

We draw a line at + 3 and call it control chart limits and observe any value beyond this to be out

of limits.

Control Chart limits are the dividing lines between random deviations and mean of the

distribution and non random deviations and mean of the distribution.

The limits that separate random variations from non random variations is known as UCL and

LCL.

A sample statistic that falls between UCL and LCL suggests ( does not proves) randomness and a value

outside suggests ( does not proves) no randomness.

SPC Errors

Type I error: Concluding a process is not in control when it actually is or concluding that no

randomness is present when it is only randomness that is present.

Type II error: Concluding a process is in control when it is not that no randomness is not present

when it is present.

Type I Error

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Production and Operations Management MGT613

α/

Mean

α = Probabilit

OBSERVATIONS FROM SAMPLE DISTRIBUTION

UCL

LCL

Sample number

Control Charts for Variables

Mean control charts

Used to monitor the central tendency of a process.

X bar charts

Range control charts

Used to monitor the process dispersion

R charts

MEAN AND RANGE CHARTS

(process mean is

shiftingupward)

Sampling

Distribution

UCL

Detects shift

UCL

R-chart

Does not detect shift

x-Chart

Sampling

Distribution

(process variability is increasing)

UCL

Does not

x-Chart

reveal increase

UCL

R-chart

Reveals increase

CONTROL CHART FOR ATTRIBUTES

p-Chart - Control chart used to monitor the proportion of defectives in a process

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Production and Operations Management MGT613

c-Chart - Control chart used to monitor the number of defects per unit

Use of p-Charts

When observations can be placed into two categories.

Good or bad

Pass or fail

Operate or don't operate

When the data consists of multiple samples of several observations each

Use of c-Charts

Use only when the number of occurrences per unit of measure can be counted; non-occurrences

cannot be counted.

Scratches, chips, dents, or errors per item

Cracks or faults per unit of distance

Breaks or Tears per unit of area

Bacteria or pollutants per unit of volume

Calls, complaints, failures per unit of time

Use of Control Charts

At what point in the process to use control charts

What size samples to take

What type of control chart to use

1. Variables

2. Attributes

RUN TESTS

Run test a test for randomness

Any sort of pattern in the data would suggest a non-random process

All points are within the control limits - the process may not be random

Nonrandom Patterns in Control charts

Trend

Cycles

Bias

Mean shift

Too much dispersion

Counting Runs

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Counting Above/Below Median Runs

B A

Counting Up/Down Runs

U D U U

Underlining each runs helps in counting

IN case of Ups and Down the first value does not receives either a U or D because nothing precedes it.

PROCESS CAPABILITY

Tolerances or specifications is the range of acceptable values established by engineering design

or customer requirements

Process variability: is the natural variability in a process

Process capability: is the process variability relative to specification

Process Capability is thus more importantly related to our discussion of Quality Control and Quality

Assurance and we will take up three cases in detail to understand this important concept.

1. In Case A we observe that process specifications and output are matched.

2. In Case B process variability is well within the process specification and output.

3. In Case C, we need to check whether a process is capable of meeting specifications and not just

use a control chart.

Lower

Upper

Specificatio

A. Process variability

matches specifications

Lower

Upper

Specificatio

B. Process variability

Lower

Upper

well within specifications Specificatio Specificatio

Process Capability

Case C, A manager in case C can take the following steps.

1. Redesign the process to obtain the desired output.

2. Use an alternative process to obtain the desired output.

3. Retain the current process but attempt to eliminate output using 100 percent inspection

4. Examine the specifications to see if they are necessary or can be relaxed

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Production and Operations Management MGT613

Process Variability is the key factor in Process Capability. It is measured in terms of process standard

deviation. Process capability is considered to be + 3 Standard Deviations from the process mean. E.g.

An insurance company provides a service of registering a new membership ( filling of form) in 10 mins,

acceptable range of variation around the time is + 1 minute, the process has a standard deviation of

0.5min.It would not be capable because + 3 SDs would be + 1.5 Mins, exceeding the specification of +

1 minute.

Process Capability Ratio

Specification width

Process capability ratio, Cp =

Process width

Upper specification lower specification

Cp=

6σ

3 SIGMA AND 6 SIGMA QUALITY

Upper

Lower

specification

1350 ppm

1.7 ppm

Process

mean

+/- 3 Sigma

+/- 6 Sigma

Improving Process Capability

1. Simplify

2. Standardize

3. Mistake-proof ( Poka Yoke)

4. Upgrade equipment

5. Automate

Taguchi Loss Function

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Production and Operations Management MGT613

Traditional

cost

Cost

Taguchi

cost

Lowe

Uppe

Target

Limitations of Capability Indexes

1. Process may not be stable

2. Process output may not be normally distributed

3. Process not centered but Cp is used

OPERATIONS STRATEGY WRT Q/C

It is neither necessary nor desirable to use Control charts for every production process.

Some processes are highly stable and do not require Control Charts.

Managers should use Control Charts on processes that go out of control.

Use control Charts for new processes till they obtain stable results.

Judicious use of SPC will ensure detection of departures from randomness in a process.

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